From b6863ae2bb6f8be26ce04af3564b0e456982241f Mon Sep 17 00:00:00 2001
From: liubai
Date: Tue, 20 Oct 2026 15:21:42 +0800
Subject: [PATCH 01/44] fix(asktool): keep card drafts across session switches
The AskTool card kept its question index and draft answers in component
state, so switching sessions unmounted the card and returning to the same
pending ask reset every answer. Store the draft by requestId instead and
let the card read and write that entry, dropping it when the ask is
resolved, dismissed, or removed.
Amends the asktool card spec's request-transition rule and adds
E2E-ASKTOOL-draft-survives-session-switch.
---
apps/desktop/src/components/AskToolCard.tsx | 78 +++++++++++--------
apps/desktop/src/lib/pending-asks.ts | 75 +++++++++++++++++-
apps/desktop/src/stores/app-state.ts | 8 +-
.../desktop/src/stores/slices/events-slice.ts | 18 ++++-
.../src/stores/slices/initial-state.ts | 1 +
.../src/stores/slices/interaction-slice.ts | 18 +++++
.../src/stores/slices/project-slice.ts | 3 +
.../src/stores/slices/session-slice.ts | 12 ++-
docs/adr/README.md | 1 +
.../asktool-draft-survives-session-switch.md | 50 ++++++++++++
docs/spec/04-ux/11-asktool-question-card.md | 18 +++--
docs/spec/06-delivery/04-e2e-test-plan.md | 15 ++++
scripts/e2e/asktool-card.tsx | 39 +++++++++-
13 files changed, 294 insertions(+), 42 deletions(-)
create mode 100644 docs/adr/asktool-draft-survives-session-switch.md
diff --git a/apps/desktop/src/components/AskToolCard.tsx b/apps/desktop/src/components/AskToolCard.tsx
index c1c1daa4e3..34c64efbac 100644
--- a/apps/desktop/src/components/AskToolCard.tsx
+++ b/apps/desktop/src/components/AskToolCard.tsx
@@ -3,38 +3,45 @@ import { useTranslation } from "react-i18next";
import {
askToolOptionDescription,
askToolOptionLabel,
- type AskToolQuestion,
} from "@pi-desktop/shared";
import { AskToolRichText } from "./AskToolRichText";
-import type { PendingAsk } from "../lib/pending-asks";
+import {
+ emptyAskDraft,
+ type AskDraft,
+ type AskDraftAnswer,
+ type PendingAsk,
+} from "../lib/pending-asks";
import { useAppStore } from "../stores/app-store";
import { Button } from "./ui";
-type DraftAnswer = {
- values: string[];
- customSelected: boolean;
- customText: string;
- skipped: boolean;
-};
+type DraftAnswer = AskDraftAnswer;
const CUSTOM_OPTION = "__asktool_custom__";
-function emptyDrafts(questions: AskToolQuestion[]): DraftAnswer[] {
- return questions.map(() => ({
- values: [],
- customSelected: false,
- customText: "",
- skipped: false,
- }));
-}
-
export function AskToolCard({ request, queued = 0 }: { request: PendingAsk; queued?: number }) {
const { t } = useTranslation();
const resolveAsk = useAppStore((state) => state.resolveAsk);
const showToast = useAppStore((state) => state.showToast);
- const [index, setIndex] = useState(0);
- const [drafts, setDrafts] = useState(() => emptyDrafts(request.questions));
+ const storedDraft = useAppStore((state) => state.askDrafts[request.requestId]);
+ const setAskDraft = useAppStore((state) => state.setAskDraft);
const [resolving, setResolving] = useState(false);
+ // The store owns the draft, so a session switch (which unmounts this card)
+ // cannot reset the answers. Read lazily rather than seeding during render.
+ const draft: AskDraft =
+ storedDraft && storedDraft.answers.length === request.questions.length
+ ? {
+ ...storedDraft,
+ index: Math.min(
+ Math.max(0, storedDraft.index),
+ request.questions.length - 1,
+ ),
+ }
+ : emptyAskDraft(request.questions);
+ const index = draft.index;
+ const drafts = draft.answers;
+ const updateDraft = (next: AskDraft) => setAskDraft(request.requestId, next);
+ const setIndex = (nextIndex: number) =>
+ updateDraft({ ...draft, index: nextIndex });
const current = request.questions[index];
const currentDraft = drafts[index];
@@ -54,14 +61,17 @@ export function AskToolCard({ request, queued = 0 }: { request: PendingAsk; queu
[drafts],
);
- const updateDraft = (update: (draft: DraftAnswer) => DraftAnswer) => {
- setDrafts((previous) =>
- previous.map((draft, draftIndex) => (draftIndex === index ? update(draft) : draft)),
- );
+ const updateCurrentDraft = (update: (answer: DraftAnswer) => DraftAnswer) => {
+ updateDraft({
+ ...draft,
+ answers: drafts.map((answer, draftIndex) =>
+ draftIndex === index ? update(answer) : answer,
+ ),
+ });
};
const selectOption = (option: string) => {
- updateDraft((draft) => {
+ updateCurrentDraft((draft) => {
if (option === CUSTOM_OPTION) {
return {
...draft,
@@ -113,18 +123,24 @@ export function AskToolCard({ request, queued = 0 }: { request: PendingAsk; queu
? { ...draft, skipped: true }
: draft,
);
- setDrafts(nextDrafts);
- if (index === request.questions.length - 1) void submit(nextDrafts);
- else setIndex((value) => value + 1);
+ if (index === request.questions.length - 1) {
+ updateDraft({ ...draft, answers: nextDrafts });
+ void submit(nextDrafts);
+ } else {
+ updateDraft({ ...draft, answers: nextDrafts, index: index + 1 });
+ }
};
const skip = () => {
const nextDrafts = drafts.map((draft, draftIndex) =>
draftIndex === index ? { ...draft, skipped: true, values: [], customSelected: false } : draft,
);
- setDrafts(nextDrafts);
- if (index === request.questions.length - 1) void submit(nextDrafts);
- else setIndex((value) => value + 1);
+ if (index === request.questions.length - 1) {
+ updateDraft({ ...draft, answers: nextDrafts });
+ void submit(nextDrafts);
+ } else {
+ updateDraft({ ...draft, answers: nextDrafts, index: index + 1 });
+ }
};
return (
@@ -223,7 +239,7 @@ export function AskToolCard({ request, queued = 0 }: { request: PendingAsk; queu
placeholder={t("askTool.customPlaceholder")}
aria-label={t("askTool.customOption")}
onChange={(event) =>
- updateDraft((draft) => ({ ...draft, customText: event.target.value, skipped: false }))
+ updateCurrentDraft((draft) => ({ ...draft, customText: event.target.value, skipped: false }))
}
autoFocus
/>
diff --git a/apps/desktop/src/lib/pending-asks.ts b/apps/desktop/src/lib/pending-asks.ts
index b7da1fda52..76b3066193 100644
--- a/apps/desktop/src/lib/pending-asks.ts
+++ b/apps/desktop/src/lib/pending-asks.ts
@@ -1,4 +1,4 @@
-import type { AskToolRequest } from "@pi-desktop/shared";
+import type { AskToolQuestion, AskToolRequest } from "@pi-desktop/shared";
export type PendingAsk = AskToolRequest;
export type AskQueues = Record;
@@ -56,3 +56,76 @@ export function clearSessionAsks(queues: AskQueues, sessionId: string): AskQueue
delete next[sessionId];
return next;
}
+
+/** One question's in-progress answer, owned by the store so a remount is harmless. */
+export type AskDraftAnswer = {
+ values: string[];
+ customSelected: boolean;
+ customText: string;
+ skipped: boolean;
+};
+
+/** The card's per-request draft: which question is open plus every answer. */
+export type AskDraft = {
+ index: number;
+ answers: AskDraftAnswer[];
+};
+
+/** Drafts keyed by requestId; the ask itself already lives in `AskQueues`. */
+export type AskDrafts = Record;
+
+export function emptyAskDraft(questions: AskToolQuestion[]): AskDraft {
+ return {
+ index: 0,
+ answers: questions.map(() => ({
+ values: [],
+ customSelected: false,
+ customText: "",
+ skipped: false,
+ })),
+ };
+}
+
+export function setAskDraft(
+ drafts: AskDrafts,
+ requestId: string,
+ draft: AskDraft,
+): AskDrafts {
+ return { ...drafts, [requestId]: draft };
+}
+
+export function dropAskDraft(drafts: AskDrafts, requestId: string): AskDrafts {
+ if (!(requestId in drafts)) return drafts;
+ const next = { ...drafts };
+ delete next[requestId];
+ return next;
+}
+
+/** Drop the drafts of every ask still queued for a session. */
+export function dropSessionAskDrafts(
+ drafts: AskDrafts,
+ queues: AskQueues,
+ sessionId: string,
+): AskDrafts {
+ const queue = queues[sessionId];
+ if (!queue || queue.length === 0) return drafts;
+ let next = drafts;
+ for (const ask of queue) next = dropAskDraft(next, ask.requestId);
+ return next;
+}
+
+/** Drop the drafts of the asks tied to one tool call. */
+export function dropToolCallAskDrafts(
+ drafts: AskDrafts,
+ queues: AskQueues,
+ sessionId: string,
+ toolCallId: string,
+): AskDrafts {
+ const queue = queues[sessionId];
+ if (!queue || queue.length === 0) return drafts;
+ let next = drafts;
+ for (const ask of queue) {
+ if (ask.toolCallId === toolCallId) next = dropAskDraft(next, ask.requestId);
+ }
+ return next;
+}
diff --git a/apps/desktop/src/stores/app-state.ts b/apps/desktop/src/stores/app-state.ts
index 21b76b5b9c..a2d0184474 100644
--- a/apps/desktop/src/stores/app-state.ts
+++ b/apps/desktop/src/stores/app-state.ts
@@ -40,7 +40,7 @@ import type {
SessionSort,
} from "../lib/sidebar-preferences";
import type { PermissionQueues } from "../lib/pending-permissions";
-import type { AskQueues } from "../lib/pending-asks";
+import type { AskDraft, AskDrafts, AskQueues } from "../lib/pending-asks";
import type {
QueuedPromptDirection,
QueuedPrompts,
@@ -176,6 +176,8 @@ export type AppState = {
pendingPermissions: PermissionQueues;
/** Inline asktool requests, queued per session without an expiry. */
pendingAsks: AskQueues;
+ /** In-progress AskTool answers keyed by requestId, so a remount keeps them. */
+ askDrafts: AskDrafts;
/** Renderer-owned, in-memory prompt queue, isolated by session. */
queuedPrompts: QueuedPrompts;
/** Planning state is durable per session, including sessions outside view. */
@@ -377,6 +379,10 @@ export type AppState = {
sessionId: string,
resolution: AskToolResolution,
) => Promise;
+ /** Persist one question card's in-progress answers by requestId. */
+ setAskDraft: (requestId: string, draft: AskDraft) => void;
+ /** Forget a request's draft once it is resolved or dismissed. */
+ dropAskDraft: (requestId: string) => void;
resolvePlan: (resolution: PlanResolveRequest) => Promise;
showToast: (message: string, options?: ToastOptions) => void;
dismissToast: (id: number) => void;
diff --git a/apps/desktop/src/stores/slices/events-slice.ts b/apps/desktop/src/stores/slices/events-slice.ts
index fe4ef21dd4..16761c2212 100644
--- a/apps/desktop/src/stores/slices/events-slice.ts
+++ b/apps/desktop/src/stores/slices/events-slice.ts
@@ -25,6 +25,8 @@ import {
import { createFrameBatcher } from "../../lib/frame-batcher";
import {
clearSessionAsks,
+ dropSessionAskDrafts,
+ dropToolCallAskDrafts,
enqueueAsk,
removeAskForToolCall,
} from "../../lib/pending-asks";
@@ -360,6 +362,11 @@ export function createEventsSlice({
state.pendingAsks,
envelope.sessionId,
),
+ askDrafts: dropSessionAskDrafts(
+ state.askDrafts,
+ state.pendingAsks,
+ envelope.sessionId,
+ ),
latestTurnResults:
event.type === "error" && event.error.code === "TURN_ABORTED"
? withoutRecordKey(state.latestTurnResults, envelope.sessionId)
@@ -452,10 +459,17 @@ export function createEventsSlice({
envelope.sessionId,
event.toolCallId,
);
+ const askDrafts = dropToolCallAskDrafts(
+ state.askDrafts,
+ state.pendingAsks,
+ envelope.sessionId,
+ event.toolCallId,
+ );
return pendingPermissions === state.pendingPermissions &&
- pendingAsks === state.pendingAsks
+ pendingAsks === state.pendingAsks &&
+ askDrafts === state.askDrafts
? {}
- : { pendingPermissions, pendingAsks };
+ : { pendingPermissions, pendingAsks, askDrafts };
});
}
diff --git a/apps/desktop/src/stores/slices/initial-state.ts b/apps/desktop/src/stores/slices/initial-state.ts
index 2b98d86978..18eeb7e633 100644
--- a/apps/desktop/src/stores/slices/initial-state.ts
+++ b/apps/desktop/src/stores/slices/initial-state.ts
@@ -72,6 +72,7 @@ export function createInitialState(): AppStateData {
pluginViews: [],
pendingPermissions: {},
pendingAsks: {},
+ askDrafts: {},
queuedPrompts: {},
planningStates: {},
pendingPlans: {},
diff --git a/apps/desktop/src/stores/slices/interaction-slice.ts b/apps/desktop/src/stores/slices/interaction-slice.ts
index dcf29e0ef9..f0af490d56 100644
--- a/apps/desktop/src/stores/slices/interaction-slice.ts
+++ b/apps/desktop/src/stores/slices/interaction-slice.ts
@@ -5,8 +5,11 @@ import type {
} from "@pi-desktop/shared";
import { api } from "../../lib/api";
import {
+ dropAskDraft as removeAskDraft,
headAsk,
removeAsk,
+ setAskDraft as applyAskDraft,
+ type AskDraft,
} from "../../lib/pending-asks";
import {
headPermission,
@@ -43,6 +46,8 @@ export function createInteractionSlice({
| "navForward"
| "resolvePermission"
| "resolveAsk"
+ | "setAskDraft"
+ | "dropAskDraft"
| "resolvePlan"
| "showToast"
| "dismissToast"
@@ -152,10 +157,23 @@ export function createInteractionSlice({
sessionId,
resolution.requestId,
),
+ askDrafts: removeAskDraft(state.askDrafts, resolution.requestId),
}));
}
},
+ setAskDraft: (requestId: string, draft: AskDraft) => {
+ set((state) => ({
+ askDrafts: applyAskDraft(state.askDrafts, requestId, draft),
+ }));
+ },
+
+ dropAskDraft: (requestId: string) => {
+ set((state) => ({
+ askDrafts: removeAskDraft(state.askDrafts, requestId),
+ }));
+ },
+
resolvePlan: async (resolution: PlanResolveRequest) => {
const activeRequest = interactionRuntime.planResolutionRequests.get(
resolution.proposalId,
diff --git a/apps/desktop/src/stores/slices/project-slice.ts b/apps/desktop/src/stores/slices/project-slice.ts
index 51e1bb1820..1195150425 100644
--- a/apps/desktop/src/stores/slices/project-slice.ts
+++ b/apps/desktop/src/stores/slices/project-slice.ts
@@ -14,6 +14,7 @@ import {
} from "../../lib/session-panes";
import {
clearSessionAsks,
+ dropSessionAskDrafts,
} from "../../lib/pending-asks";
import {
clearSessionPermissions,
@@ -174,6 +175,7 @@ function clearLocalSessionState(
id,
);
const pendingAsks = clearSessionAsks(state.pendingAsks, id);
+ const askDrafts = dropSessionAskDrafts(state.askDrafts, state.pendingAsks, id);
const latestTurnResults = withoutRecordKey(state.latestTurnResults, id);
const planningStates = withoutRecordKey(state.planningStates, id);
const pendingPlans = withoutRecordKey(state.pendingPlans, id);
@@ -202,6 +204,7 @@ function clearLocalSessionState(
isRunning: state.activeSessionId === id ? false : state.isRunning,
pendingPermissions,
pendingAsks,
+ askDrafts,
latestTurnResults,
planningStates,
pendingPlans,
diff --git a/apps/desktop/src/stores/slices/session-slice.ts b/apps/desktop/src/stores/slices/session-slice.ts
index e1c41d699b..3a6a21b405 100644
--- a/apps/desktop/src/stores/slices/session-slice.ts
+++ b/apps/desktop/src/stores/slices/session-slice.ts
@@ -35,6 +35,7 @@ import {
type SessionMeta,
} from "../../lib/sidebar-preferences";
import { api } from "../../lib/api";
+import { dropAskDraft } from "../../lib/pending-asks";
import { isRemoteSession, safeSessionSummary, sessionAllows } from "../../lib/remote-session-safety";
import { createRefreshCoordinator } from "../../lib/refresh-coordinator";
import { openRemoteProjectSession, remoteProjectForSession } from "../../lib/remote-project-session";
@@ -344,15 +345,24 @@ export function createSessionSlice({
sessionId,
pendingPermissions,
);
+ const keptAskIds = new Set(pendingAsks.map((ask) => ask.requestId));
+ let askDrafts = state.askDrafts;
+ for (const ask of state.pendingAsks[sessionId] ?? []) {
+ if (!keptAskIds.has(ask.requestId)) {
+ askDrafts = dropAskDraft(askDrafts, ask.requestId);
+ }
+ }
if (
nextPendingAsks === state.pendingAsks &&
- nextPendingPermissions === state.pendingPermissions
+ nextPendingPermissions === state.pendingPermissions &&
+ askDrafts === state.askDrafts
) {
return {};
}
return {
pendingAsks: nextPendingAsks,
pendingPermissions: nextPendingPermissions,
+ askDrafts,
};
});
},
diff --git a/docs/adr/README.md b/docs/adr/README.md
index 18a7a9a6c0..b3412c13e1 100644
--- a/docs/adr/README.md
+++ b/docs/adr/README.md
@@ -20,6 +20,7 @@ Each ADR includes:
| ID | Title | Status |
|---|---|---|
+| asktool-draft-survives-session-switch | [AskTool drafts survive a card remount](asktool-draft-survives-session-switch.md) | Accepted |
| provider-metadata-client-certificate-retry | [Provider metadata recovery from optional client certificates](provider-metadata-client-certificate-retry.md) | Implemented candidate |
| device-local-project-lists-in-config-sync | [Device-local project lists in configuration sync](device-local-project-lists-in-config-sync.md) | Accepted |
| s3-only-configuration-backup-sync | [S3-only encrypted configuration backup and synchronization](s3-only-configuration-backup-sync.md) | Accepted; supersedes WebDAV decisions in 0300 / 0301 |
diff --git a/docs/adr/asktool-draft-survives-session-switch.md b/docs/adr/asktool-draft-survives-session-switch.md
new file mode 100644
index 0000000000..23fe0ca0f6
--- /dev/null
+++ b/docs/adr/asktool-draft-survives-session-switch.md
@@ -0,0 +1,50 @@
+# ADR asktool-draft-survives-session-switch: AskTool drafts survive a card remount
+
+- Status: Accepted
+- Date: 2026-10-20
+- Issues: #1765
+- Amends: the "Request transitions" rule in `docs/spec/04-ux/11-asktool-question-card.md`
+
+## Context
+
+The card's question index and draft answers were component state. Switching
+sessions unmounts the card — `Composer` renders it only while the active session
+has a head ask — so returning to the same pending ask remounted a fresh card at
+question one with every answer cleared. The ask itself survived because it lives
+in the store; only the in-progress answers were lost, which made the user redo
+the whole card.
+
+The existing specification froze the opposite behavior: "Unsubmitted card drafts
+are local to the mounted card and are reset when it is replaced." That rule
+predates the session-switch case and no longer matches what users expect.
+
+## Decision
+
+Draft answers and the open question index live in the app store, keyed by
+`requestId` (`askDrafts`). `AskToolCard` reads and writes that entry instead of
+owning `useState`, so unmounting and remounting the same request is harmless.
+A missing entry falls back lazily to an empty draft at read time; the card does
+not seed the store during render.
+
+The draft is dropped when the ask is resolved or dismissed, when its tool call
+finishes, when the session's asks are cleared, and when a pending-queue reconcile
+removes the ask. Drafts remain renderer memory, like `pendingAsks`; they are not
+persisted across an application restart and never leak between requests.
+
+## Consequences
+
+- Switching sessions and returning to the same pending ask keeps the selected
+ options, the custom text, skipped markers, and the open question.
+- Resolved, dismissed, and removed asks leave no draft behind.
+- `AskToolCard` becomes a controlled view over store state; it keeps no
+ draft-local `useState`.
+- The "Request transitions" section of the asktool card spec is amended: drafts
+ belong to the request, not to the mounted card instance.
+
+## Validation
+
+`pnpm test:e2e:asktool-card` adds `E2E-ASKTOOL-draft-survives-session-switch`:
+it selects an option, advances to question two, unmounts the card, remounts the
+same `requestId`, and asserts the open question and the earlier selection
+survive. The existing compact-card flows keep passing. `pnpm typecheck` and
+`pnpm lint` cover the renderer types and style tokens.
diff --git a/docs/spec/04-ux/11-asktool-question-card.md b/docs/spec/04-ux/11-asktool-question-card.md
index 434db0499c..625037ea50 100644
--- a/docs/spec/04-ux/11-asktool-question-card.md
+++ b/docs/spec/04-ux/11-asktool-question-card.md
@@ -96,8 +96,16 @@ applies on narrow screens; the card does not rely on page-level scrolling.
## Request transitions
-The question index, draft answers, and submission state belong to the displayed
-request. Switching chats or advancing the pending queue mounts a fresh card at
-question one with empty answers and enabled actions. State from the previous
-request must not leak into the destination request. Unsubmitted card drafts are
-local to the mounted card and are reset when it is replaced.
+The question index and draft answers belong to the request, not to the mounted
+card instance. They live in the app store keyed by `requestId`, so switching
+chats and returning to the same pending ask restores the open question and every
+answer the user had already entered (see
+[ADR asktool-draft-survives-session-switch](../../adr/asktool-draft-survives-session-switch.md)).
+A request with no stored draft opens at question one with empty answers and
+enabled actions.
+
+Drafts never leak between requests: they are keyed by `requestId` and dropped
+when the ask is resolved or dismissed, when its tool call completes, and when the
+session's pending asks are cleared. Submission state stays local to the mounted
+card. Drafts are renderer memory, like the pending ask itself, and do not survive
+an application restart.
diff --git a/docs/spec/06-delivery/04-e2e-test-plan.md b/docs/spec/06-delivery/04-e2e-test-plan.md
index 73b1fa67dc..78aee54690 100644
--- a/docs/spec/06-delivery/04-e2e-test-plan.md
+++ b/docs/spec/06-delivery/04-e2e-test-plan.md
@@ -516,6 +516,21 @@
actions, and measures the multi-block question layout. Runtime boundary
validation is covered by `packages/agent-runtime/src/runtime.test.ts`.
+### E2E-ASKTOOL-draft-survives-session-switch
+
+- **Preconditions:** No live provider is required; the fixture stubs
+ `api.resolveAskTool` and seeds one two-question ask through the real store
+ slice.
+- **Steps:** Mount the production `AskToolCard`, select the second option on
+ question one, advance to question two, unmount the card (the session switch
+ the dock performs), and remount it with the same `requestId`. Then click the
+ first step indicator to return to question one.
+- **Expected:** The remounted card opens on question two with the earlier
+ selection still marked, and question one still shows the selected option.
+ Resolving or dismissing the ask clears the stored draft.
+- **Status:** Automated in `pnpm test:e2e:asktool-card` as the
+ `E2E-ASKTOOL-draft-survives-session-switch` flow.
+
### E2E-POWER-keep-awake-setting
- **Preconditions:** An isolated desktop profile with the setting absent; no
diff --git a/scripts/e2e/asktool-card.tsx b/scripts/e2e/asktool-card.tsx
index 26fdbeec28..8bfa0abe16 100644
--- a/scripts/e2e/asktool-card.tsx
+++ b/scripts/e2e/asktool-card.tsx
@@ -8,7 +8,8 @@
* the user-visible paths: the new header action order, select → next →
* submit, skip → submit, decline-all, and a custom answer.
*
- * Scenario: E2E-ASKTOOL-compact-card-interaction. It also pins the compact
+ * Scenario: E2E-ASKTOOL-compact-card-interaction and
+ * E2E-ASKTOOL-draft-survives-session-switch. It also pins the compact
* question block: a multi-paragraph question body stays one stacked text
* column rather than lining its blocks up in a row.
*/
@@ -391,6 +392,42 @@ export async function asktoolCardProbe() {
"the maximum-length question remains answerable",
);
+ // Flow H: the draft survives an unmount/remount with the same requestId —
+ // switching sessions in the real app unmounts the card the same way.
+ const persisted = mount("ask-persist");
+ await until(() => options().length > 0, "persist flow mounts");
+ flushSync(() => options()[1]!.click()); // select "beta" on question 1
+ flushSync(() => headerButtons().primary.click()); // next -> question 2
+ await until(
+ () => questionText().includes("Allow rollback?"),
+ "persist flow advances to question 2",
+ );
+ flushSync(() => root.render(null)); // unmount (session switched away)
+ flushSync(() =>
+ root.render(
+
+
+ ,
+ ),
+ );
+ await until(() => options().length > 0, "persist flow remounts");
+ assert(
+ questionText().includes("Allow rollback?"),
+ "the remounted card resumes on the question the user left",
+ );
+ const indicators = [
+ ...host.querySelectorAll(".asktool-indicator"),
+ ];
+ flushSync(() => indicators[0]!.click());
+ await until(
+ () => questionText().includes("Which upgrade path?"),
+ "the indicator returns to question 1",
+ );
+ assert(
+ options()[1]!.classList.contains("selected"),
+ "the answer selected before the remount is still selected",
+ );
+
assert(errors.length === 0, `render errors: ${errors.map(String)}`);
return { ok: true, resolutions: resolutions.length };
} catch (error) {
From 36c1d159d4ac987d1b5f06311e3fff1071dbec21 Mon Sep 17 00:00:00 2001
From: liubai
Date: Tue, 20 Oct 2026 15:34:39 +0800
Subject: [PATCH 02/44] fix(persistence): drop empty assistant rows regardless
of status
The transcript guard only dropped empty messages whose status was error or
aborted. An empty complete assistant message therefore reached the outbox
on every provider retry, growing the request body and feeding the EMPTY
loop. Drop empty assistant rows whatever their status, while keeping
messages that carry an error payload, a tool row, or a steering
reservation.
Adds empty-assistant-persistence tests for each of those cases.
---
.../main/runtime/event-persistence.ts | 15 +-
.../test/empty-assistant-persistence.test.mjs | 128 ++++++++++++++++++
2 files changed, 137 insertions(+), 6 deletions(-)
create mode 100644 apps/desktop/test/empty-assistant-persistence.test.mjs
diff --git a/apps/desktop/electron/main/runtime/event-persistence.ts b/apps/desktop/electron/main/runtime/event-persistence.ts
index e8cf88d27e..f24ac500e6 100644
--- a/apps/desktop/electron/main/runtime/event-persistence.ts
+++ b/apps/desktop/electron/main/runtime/event-persistence.ts
@@ -327,16 +327,19 @@ function persistAgentEvent(envelope: AgentEventEnvelope): UiMessage | undefined
inflightCheckpointer.settleIf(sessionId, finalId);
});
}
- // Empty aborted bubbles are not useful transcript rows. Structured
- // provider failures remain durable assistant messages so their details
- // stay attached to the failed turn after reload.
- const failed =
- event.message.status === "error" || event.message.status === "aborted";
+ // Empty assistant bubbles are not useful transcript rows, whatever their
+ // status: an empty `complete` message would otherwise be persisted on every
+ // provider retry and grow the request body. Structured provider failures
+ // remain durable so their details stay attached to the failed turn after
+ // reload; a message that still carries a tool row keeps its link to it, and
+ // a steering reply is reserved by the user turn that accepted it.
const empty =
!(event.message.content || "").trim() &&
!(event.message.thinking || "").trim();
+ const carriesTool =
+ Boolean(event.message.toolName) || Boolean(event.message.toolCallId);
const reservedForSteering = steeringReplies.delete(event.message.id);
- if (failed && empty && !event.message.error && !reservedForSteering) return;
+ if (empty && !carriesTool && !event.message.error && !reservedForSteering) return;
void persistenceOutbox
.enqueue(
{
diff --git a/apps/desktop/test/empty-assistant-persistence.test.mjs b/apps/desktop/test/empty-assistant-persistence.test.mjs
new file mode 100644
index 0000000000..466a084e14
--- /dev/null
+++ b/apps/desktop/test/empty-assistant-persistence.test.mjs
@@ -0,0 +1,128 @@
+import assert from "node:assert/strict";
+import { register } from "node:module";
+import { dirname, join } from "node:path";
+import { fileURLToPath, pathToFileURL } from "node:url";
+import test from "node:test";
+
+const here = dirname(fileURLToPath(import.meta.url));
+register(pathToFileURL(join(here, "helpers/ts-import-hooks.mjs")));
+
+// The real persistence pass, driven directly with a stubbed outbox.
+const { createSessionCoordination } = await import(
+ "../electron/main/runtime/session-coordination.ts"
+);
+const { createEventPersistence } = await import(
+ "../electron/main/runtime/event-persistence.ts"
+);
+
+const SESSION = "s1";
+const TURN = "turn-1";
+
+function fixture() {
+ const activeTurns = new Map([[SESSION, TURN]]);
+ const coordination = createSessionCoordination({
+ activeTurns,
+ getMainWindow: () => null,
+ getViewingSessionId: () => null,
+ });
+ const enqueued = [];
+ const steeringReplies = new Set();
+ const persistence = createEventPersistence({
+ runtimeState: { host: null },
+ steeringReplies,
+ activeTurns,
+ activeToolCalls: new Map(),
+ activeToolCallKey: coordination.activeToolCallKey,
+ approvedExecutionIdsBySession: new Map(),
+ approvedExecutionTurns: new Map(),
+ pendingExecutionFinishes: new Map(),
+ planSubmissionTurnIds: new Set(),
+ planSubmissionTurnKey: coordination.planSubmissionTurnKey,
+ inflightCheckpointer: {
+ observe() {},
+ flush: async () => {},
+ settle() {},
+ settleIf() {},
+ },
+ persistenceOutbox: {
+ size: () => 0,
+ enqueue: async (entry) => {
+ enqueued.push(entry);
+ },
+ flush: async () => undefined,
+ },
+ addActiveTurnUsage() {},
+ logger: { app() {} },
+ finishTurn: () => Promise.resolve(),
+ isStaleTerminalEvent: coordination.isStaleTerminalEvent,
+ transcriptRewrite: coordination,
+ finishApprovedExecution: async () => undefined,
+ emitAgentEvent() {},
+ });
+ const persistAssistant = (message) =>
+ persistence.persistAgentEvent({
+ sessionId: SESSION,
+ turnId: TURN,
+ ts: 1,
+ event: {
+ type: "message_end",
+ message: {
+ role: "assistant",
+ createdAt: "2026-10-20T00:00:00.000Z",
+ ...message,
+ },
+ },
+ });
+ return { enqueued, steeringReplies, persistAssistant };
+}
+
+test("an empty complete assistant message is not persisted", () => {
+ const f = fixture();
+ f.persistAssistant({ id: "m1", content: "", thinking: "", status: "complete" });
+ assert.equal(f.enqueued.length, 0);
+});
+
+test("an empty aborted assistant message without an error is not persisted", () => {
+ const f = fixture();
+ f.persistAssistant({ id: "m2", content: "", thinking: "", status: "aborted" });
+ assert.equal(f.enqueued.length, 0);
+});
+
+test("an empty assistant message that still carries a tool row is persisted", () => {
+ const f = fixture();
+ f.persistAssistant({
+ id: "m3",
+ content: "",
+ thinking: "",
+ status: "complete",
+ toolName: "Grep",
+ toolCallId: "call-1",
+ toolStatus: "success",
+ });
+ assert.equal(f.enqueued.length, 1);
+});
+
+test("an empty assistant message with an error payload stays durable", () => {
+ const f = fixture();
+ f.persistAssistant({
+ id: "m4",
+ content: "",
+ thinking: "",
+ status: "error",
+ error: { code: "PROVIDER_ERROR", message: "boom" },
+ });
+ assert.equal(f.enqueued.length, 1);
+});
+
+test("an empty assistant message reserved for steering is persisted", () => {
+ const f = fixture();
+ f.steeringReplies.add("m5");
+ f.persistAssistant({ id: "m5", content: "", thinking: "", status: "complete" });
+ assert.equal(f.enqueued.length, 1);
+});
+
+test("a non-empty complete assistant message is persisted", () => {
+ const f = fixture();
+ f.persistAssistant({ id: "m6", content: "done", status: "complete" });
+ assert.equal(f.enqueued.length, 1);
+});
From 1b1032c28794b1f3af6c9c242dc5f818a3e49bd9 Mon Sep 17 00:00:00 2001
From: zszz3 <91608029+zszz3@users.noreply.github.com>
Date: Tue, 20 Oct 2026 16:55:36 +0800
Subject: [PATCH 03/44] fix(chat): open worktree references from the branch
copy
An isolated session's files live in its worktree, but chat references can
still carry a path from the parent checkout: project instructions, MCP tools,
or a reference captured before isolation. The resolver rejected that path as
outside its roots, and the renderer then handed the file view a relative path
that it resolved against the parent checkout, so the click either failed or
opened the main-branch copy.
Rebase an absolute parent-checkout reference onto the same relative path in
the worktree when that file exists, and keep the worktree's absolute path in
the renderer so the file view opens the branch copy. Paths that exist only in
the parent still report outside-allowed-roots.
fixes #1747
---
.../electron/main/ipc/workspace-ipc.ts | 72 +++++++++++---
apps/desktop/electron/main/worktree-ref.ts | 59 ++++++++++++
apps/desktop/src/hooks/use-preview-target.ts | 6 +-
.../test/transcript-file-chips.test.mjs | 8 +-
.../desktop/test/worktree-ref-rebase.test.mjs | 96 +++++++++++++++++++
docs/spec/03-runtime/01-ipc-protocol.md | 5 +-
docs/zh-CN/spec/03-runtime/01-ipc-protocol.md | 2 +-
7 files changed, 233 insertions(+), 15 deletions(-)
create mode 100644 apps/desktop/electron/main/worktree-ref.ts
create mode 100644 apps/desktop/test/worktree-ref-rebase.test.mjs
diff --git a/apps/desktop/electron/main/ipc/workspace-ipc.ts b/apps/desktop/electron/main/ipc/workspace-ipc.ts
index 57d7b59797..15dac8b685 100644
--- a/apps/desktop/electron/main/ipc/workspace-ipc.ts
+++ b/apps/desktop/electron/main/ipc/workspace-ipc.ts
@@ -40,6 +40,7 @@ import {
} from "@pi-desktop/host-runtime";
import { openableMp4Path } from "../open-attachment-video";
import { isChatRefOutsideRoots, resolveChatFileRef } from "../chat-ref-resolve";
+import { rebaseWorktreeRef, type WorktreeRefContext } from "../worktree-ref";
import { getWorkspaceFileIndex } from "../fs-index";
import {
projectFolderPaths,
@@ -768,27 +769,58 @@ export function registerWorkspaceIpc({
return browserHost.getState();
});
- const requireWorkspaceRoot = async (sessionId?: string) => {
+ type WorkspaceRootInfo = {
+ root: string;
+ /** Present only for an isolated session's worktree checkout. */
+ worktree?: string;
+ /** The parent checkout a worktree session's project identity points at. */
+ parent?: string;
+ };
+
+ const workspaceRootInfo = async (
+ sessionId?: string,
+ ): Promise => {
const owner = getHost();
if (!owner) throw new Error("host unavailable");
let root: string | undefined;
+ let worktree: string | undefined;
+ let parent: string | undefined;
if (sessionId) {
const { session } = await owner.call<{ session?: { projectPath?: string; worktree?: unknown } }>(
"session.get", { id: sessionId, messageLimit: 1 },
);
- // Chat references and source reads must see the same files as the
- // session's tools, not a same-named file in the parent checkout.
- root = session?.worktree
- ? (await owner.call<{ path?: string }>("worktree.location", { sessionId })).path
- : session?.projectPath;
+ const projectPath = session?.projectPath?.trim();
+ if (session?.worktree) {
+ // Chat references and source reads must see the same files as the
+ // session's tools, not a same-named file in the parent checkout.
+ worktree =
+ (await owner.call<{ path?: string }>("worktree.location", { sessionId })).path?.trim() ||
+ undefined;
+ root = worktree;
+ // A reference captured from this checkout rebases onto the worktree
+ // (issue #1747); the opaque remote identity is never a local parent.
+ parent =
+ projectPath && !projectPath.startsWith("remote-project:")
+ ? projectPath
+ : undefined;
+ } else {
+ root = projectPath;
+ }
} else {
root = (await owner.call<{ workspace?: { path: string } }>("workspace.get")).workspace?.path;
}
if (getHost() !== owner) throw Object.assign(new Error("host replaced"), { errorCode: ErrorCodes.HOST_UNAVAILABLE });
if (!root) throw Object.assign(new Error("workspace required"), { errorCode: ErrorCodes.INVALID_ARGUMENT });
- return root;
+ return {
+ root,
+ ...(worktree ? { worktree } : {}),
+ ...(parent ? { parent } : {}),
+ };
};
+ const requireWorkspaceRoot = async (sessionId?: string) =>
+ (await workspaceRootInfo(sessionId)).root;
+
handle(IPC.invoke.fsList, async (input: { path?: string; sessionId?: string } = {}) => {
const remote = await remoteFileWorkspace(input.sessionId);
if (remote) return readRemoteFiles(remote, "list", input.path);
@@ -997,11 +1029,29 @@ export function registerWorkspaceIpc({
async (
input: { ref?: string; sessionId?: string } = {},
): Promise => {
- const ref = String(input.ref ?? "").trim();
- if (!ref) return { match: null };
+ const rawRef = String(input.ref ?? "").trim();
+ if (!rawRef) return { match: null };
const remote = await remoteFileWorkspace(input.sessionId);
- if (remote && !(await isLocalStoredFile(ref))) return await readRemoteFiles(remote, "resolve", ref) as FsChatRefResolveResult;
- const workspaceRoot = await optionalWorkspaceRoot(input.sessionId);
+ if (remote && !(await isLocalStoredFile(rawRef))) return await readRemoteFiles(remote, "resolve", rawRef) as FsChatRefResolveResult;
+ // A reference captured from the parent checkout names the same relative
+ // file the session's worktree holds; resolve the branch copy instead of
+ // rejecting the path as outside the isolated roots (issue #1747).
+ let rootInfo: WorkspaceRootInfo | undefined;
+ try {
+ rootInfo = await workspaceRootInfo(input.sessionId);
+ } catch {
+ rootInfo = undefined;
+ }
+ const ref = await rebaseWorktreeRef(
+ rawRef,
+ rootInfo?.worktree && rootInfo.parent
+ ? ({
+ worktree: rootInfo.worktree,
+ parent: rootInfo.parent,
+ } satisfies WorktreeRefContext)
+ : null,
+ );
+ const workspaceRoot = rootInfo?.root ?? null;
const roots = {
project: projectRootsFor(workspaceRoot),
scratch: await sessionScratchRoot(input.sessionId),
diff --git a/apps/desktop/electron/main/worktree-ref.ts b/apps/desktop/electron/main/worktree-ref.ts
new file mode 100644
index 0000000000..dd56df3b99
--- /dev/null
+++ b/apps/desktop/electron/main/worktree-ref.ts
@@ -0,0 +1,59 @@
+import { stat } from "node:fs/promises";
+import { isAbsolute, resolve } from "node:path";
+
+/**
+ * The two roots a chat reference can mean for an isolated session: the checkout
+ * the user sees (the worktree) and the parent checkout the project identity
+ * still points at (ADR 0329).
+ */
+export type WorktreeRefContext = { worktree: string; parent: string };
+
+/**
+ * Rewrite an absolute chat reference that points into the parent checkout onto
+ * the same relative path inside the session's worktree.
+ *
+ * References can be produced before isolation or by producers that only know
+ * the project path (project instructions, MCP tools, an attachment captured
+ * from the parent checkout). The session's files live in the worktree, so the
+ * original path is outside the allowed roots and the click fails even though
+ * the branch has the same file. Relative references, paths already inside the
+ * worktree, and paths with no worktree counterpart are returned unchanged so
+ * the caller keeps reporting the accurate reason.
+ */
+export async function rebaseWorktreeRef(
+ ref: string,
+ context: WorktreeRefContext | null,
+ isFile: (path: string) => Promise = defaultIsFile,
+): Promise {
+ if (!context || !isAbsolute(ref)) return ref;
+ if (relativeWithin(context.worktree, ref) !== null) return ref;
+ const relativePath = relativeWithin(context.parent, ref);
+ if (!relativePath) return ref;
+ const candidate = resolve(context.worktree, ...relativePath.split("/"));
+ return (await isFile(candidate)) ? candidate : ref;
+}
+
+/**
+ * The project UI treats Windows and macOS paths as case-insensitive, and a
+ * reference may use either separator. Compare in normalized form without
+ * changing the spelling returned to the caller.
+ */
+function relativeWithin(root: string, candidate: string): string | null {
+ const rootPath = root.replaceAll("\\", "/").replace(/\/+$/, "");
+ const candidatePath = candidate.replaceAll("\\", "/");
+ const caseInsensitive = process.platform !== "linux";
+ const normalizedRoot = caseInsensitive ? rootPath.toLowerCase() : rootPath;
+ const normalizedCandidate = caseInsensitive
+ ? candidatePath.toLowerCase()
+ : candidatePath;
+ if (!normalizedCandidate.startsWith(`${normalizedRoot}/`)) return null;
+ return candidatePath.slice(rootPath.length + 1);
+}
+
+async function defaultIsFile(path: string): Promise {
+ try {
+ return (await stat(path)).isFile();
+ } catch {
+ return false;
+ }
+}
diff --git a/apps/desktop/src/hooks/use-preview-target.ts b/apps/desktop/src/hooks/use-preview-target.ts
index 93f6133375..9af9e25a72 100644
--- a/apps/desktop/src/hooks/use-preview-target.ts
+++ b/apps/desktop/src/hooks/use-preview-target.ts
@@ -190,6 +190,10 @@ function useResolveChatFileRef() {
showToast(t("chat.fileRefLookupFailed"), { variant: "error" });
return null;
}
+ // An isolated session's files live in its worktree, which is outside the
+ // plugin's project roots. A relative path would be resolved by the file
+ // view against the parent checkout, so the branch copy stays absolute.
+ const isolated = Boolean(session?.worktree);
const match = result.match;
if (!match) {
const key = result.reason === "outside-allowed-roots"
@@ -213,7 +217,7 @@ function useResolveChatFileRef() {
// absolute path and the file view switches to that folder (ADR 0263).
const primary = match.projectRoot ? match.projectRoot.primary : true;
return {
- path: primary ? match.relativePath : match.absolutePath,
+ path: primary && !isolated ? match.relativePath : match.absolutePath,
absolutePath: match.absolutePath,
relativePath: match.relativePath,
inProject: true,
diff --git a/apps/desktop/test/transcript-file-chips.test.mjs b/apps/desktop/test/transcript-file-chips.test.mjs
index 3cff0bce9b..f498375743 100644
--- a/apps/desktop/test/transcript-file-chips.test.mjs
+++ b/apps/desktop/test/transcript-file-chips.test.mjs
@@ -49,7 +49,13 @@ test("a file chip is routed by where the reference resolved, never optimisticall
// follows the folder that answered: relative for the primary one, absolute
// for its siblings, and the file view switches to the folder it is given.
assert.match(hook, /match\.projectRoot \? match\.projectRoot\.primary : true/);
- assert.match(hook, /path: primary \? match\.relativePath : match\.absolutePath/);
+ // An isolated session's worktree is outside the plugin's project roots, so
+ // the branch copy travels by its absolute path (issue #1747).
+ assert.match(hook, /const isolated = Boolean\(session\?\.worktree\)/);
+ assert.match(
+ hook,
+ /path: primary && !isolated \? match\.relativePath : match\.absolutePath/,
+ );
// Project and scratch HTML run at the exact path resolved by main.
assert.match(hook, /resolved\.inProject \|\| resolved\.scratch/);
assert.match(hook, /isHtmlFilePath\(resolved\.absolutePath\)/);
diff --git a/apps/desktop/test/worktree-ref-rebase.test.mjs b/apps/desktop/test/worktree-ref-rebase.test.mjs
new file mode 100644
index 0000000000..054711645e
--- /dev/null
+++ b/apps/desktop/test/worktree-ref-rebase.test.mjs
@@ -0,0 +1,96 @@
+import assert from "node:assert/strict";
+import { mkdir, mkdtemp, rm, writeFile } from "node:fs/promises";
+import { tmpdir } from "node:os";
+import { join } from "node:path";
+import test from "node:test";
+
+import { rebaseWorktreeRef } from "../electron/main/worktree-ref.ts";
+
+async function fixture() {
+ const root = await mkdtemp(join(tmpdir(), "pi-worktree-ref-"));
+ const parent = join(root, "main");
+ const worktree = join(root, "worktree");
+ await mkdir(join(parent, "docs"), { recursive: true });
+ await mkdir(join(worktree, "docs"), { recursive: true });
+ await writeFile(join(parent, "docs", "branch-note.md"), "parent\n");
+ await writeFile(join(worktree, "docs", "branch-note.md"), "branch\n");
+ await writeFile(join(parent, "docs", "parent-only.md"), "parent only\n");
+ return { root, parent, worktree };
+}
+
+test("a reference without a worktree context is unchanged", async () => {
+ assert.equal(
+ await rebaseWorktreeRef("/repo/docs/a.md", null),
+ "/repo/docs/a.md",
+ );
+});
+
+test("relative references stay relative", async () => {
+ const { root, parent, worktree } = await fixture();
+ try {
+ assert.equal(
+ await rebaseWorktreeRef("docs/branch-note.md", { parent, worktree }),
+ "docs/branch-note.md",
+ );
+ } finally {
+ await rm(root, { recursive: true, force: true });
+ }
+});
+
+test("a reference already inside the worktree is unchanged", async () => {
+ const { root, parent, worktree } = await fixture();
+ try {
+ const ref = join(worktree, "docs", "branch-note.md");
+ assert.equal(await rebaseWorktreeRef(ref, { parent, worktree }), ref);
+ } finally {
+ await rm(root, { recursive: true, force: true });
+ }
+});
+
+test("a parent-checkout path resolves to the branch copy in the worktree", async () => {
+ const { root, parent, worktree } = await fixture();
+ try {
+ assert.equal(
+ await rebaseWorktreeRef(join(parent, "docs", "branch-note.md"), {
+ parent,
+ worktree,
+ }),
+ join(worktree, "docs", "branch-note.md"),
+ );
+ } finally {
+ await rm(root, { recursive: true, force: true });
+ }
+});
+
+test("a parent-only file keeps its original path when the branch lacks it", async () => {
+ const { root, parent, worktree } = await fixture();
+ try {
+ const ref = join(parent, "docs", "parent-only.md");
+ assert.equal(await rebaseWorktreeRef(ref, { parent, worktree }), ref);
+ } finally {
+ await rm(root, { recursive: true, force: true });
+ }
+});
+
+test("a sibling directory sharing the parent prefix is not rebased", async () => {
+ const { root, parent, worktree } = await fixture();
+ try {
+ const sibling = join(`${parent}-other`, "docs", "branch-note.md");
+ assert.equal(await rebaseWorktreeRef(sibling, { parent, worktree }), sibling);
+ } finally {
+ await rm(root, { recursive: true, force: true });
+ }
+});
+
+test("a worktree nested inside the parent is not rebased onto itself", async () => {
+ const { root, worktree } = await fixture();
+ try {
+ const nested = join(worktree, ".worktrees", "branch");
+ await mkdir(join(nested, "docs"), { recursive: true });
+ await writeFile(join(nested, "docs", "branch-note.md"), "branch\n");
+ const ref = join(nested, "docs", "branch-note.md");
+ assert.equal(await rebaseWorktreeRef(ref, { parent: worktree, worktree: nested }), ref);
+ } finally {
+ await rm(root, { recursive: true, force: true });
+ }
+});
diff --git a/docs/spec/03-runtime/01-ipc-protocol.md b/docs/spec/03-runtime/01-ipc-protocol.md
index 64c0fa9051..1f81a9c0eb 100644
--- a/docs/spec/03-runtime/01-ipc-protocol.md
+++ b/docs/spec/03-runtime/01-ipc-protocol.md
@@ -1926,7 +1926,10 @@ Renderer IPC kept for the Plan-safe preview facade and URL fallback:
so the extensionless blob has a media association without copying its bytes.
- `fs/resolveRef({ref, sessionId?})` → `FsChatRefResolveResult`
(for isolated sessions, lookup and file reads use `worktree.location` rather
- than the parent project checkout)
+ than the parent project checkout; an absolute reference under the parent
+ checkout is rebased onto the same relative path in the worktree when that
+ file exists, so the branch copy opens instead of reporting
+ `outside-allowed-roots`)
(`{ match: FsChatRefMatch | null, reason?: "outside-allowed-roots" }`, the match naming the answering `root`
(`workspace` / `scratch` / `attachments`), the `relativePath` relative to that
root, optional `sessionScratch: true` for the current session's own scratch
diff --git a/docs/zh-CN/spec/03-runtime/01-ipc-protocol.md b/docs/zh-CN/spec/03-runtime/01-ipc-protocol.md
index 79a7716a22..8fdf8921dd 100644
--- a/docs/zh-CN/spec/03-runtime/01-ipc-protocol.md
+++ b/docs/zh-CN/spec/03-runtime/01-ipc-protocol.md
@@ -1439,7 +1439,7 @@ Chrome 和代理 CDP 位于随应用打包的 `pi.browser` 插件中,通过 `p
- `fs/readImageDataUrl({ref, mimeType?})` → `FsImageDataUrlResult`(`image` 带 `dataUrl`,或 `missing` / `notImage` / `tooLarge`)。包含范围与 `fs/read` 相同。从不返回非图片字节。仅渲染器使用,不是插件宿主 API。
- `fs/reveal({path})` → 在 Finder 中显示。包含范围与 `fs/read` 相同。
- `fs/open({path, mimeType?})` → 用系统默认应用打开已有的普通文件。与 `fs/read` 一样校验真实路径包含范围,拒绝通过符号链接逃逸。对于声明为 `video/mp4` 的无后缀 `attachments/` blob,宿主在私有应用数据目录建立 `.mp4` 符号链接后再交给系统,不复制视频字节。
-- `fs/resolveRef({ref, sessionId?})` → `FsChatRefResolveResult`(`{ match: FsChatRefMatch | null }`,match 指出应答的 `root`(`workspace` / `scratch` / `attachments`)、相对该应答根的 `relativePath`、绝对路径 `absolutePath` 与 `matchedBy`(`exact-relative` / `exact-absolute` / `path-suffix` / `basename`),以及在 `workspace` 命中时给出的 `projectRoot`(`{ path, name, primary }`,指出是哪个文件夹应答的));`sessionId` 决定查哪个会话的临时目录。它补全智能体在聊天里打印的文件引用,因为渲染器看不到会话自己的临时目录:已经在某个已知根内指向真实文件的绝对引用直接胜出,`attachments/` blob 直接对附件库解析;否则按优先级顺序搜索各根——整个打开的项目、再会话自己的临时目录(`/scratch//`,ADR 0124)、最后附件库——第一个给出结果的根胜出。项目指的是打开的工作区背后的文件夹组(ADR 0249):主文件夹先应答,其余文件夹随后按项目组自身顺序搜索(ADR 0263),因此简写落在同级文件夹里和落在主文件夹里一样自然,命中结果也指出是哪个文件夹应答的。同一个根内精确路径优先于简写;简写之间最长匹配尾优先,其次路径更浅者。文件面板的忽略集合同样生效。什么都没匹配到时返回 `match: null`;解析本身不打开任何东西(ADR 0262)。
+- `fs/resolveRef({ref, sessionId?})` → `FsChatRefResolveResult`(`{ match: FsChatRefMatch | null }`,match 指出应答的 `root`(`workspace` / `scratch` / `attachments`)、相对该应答根的 `relativePath`、绝对路径 `absolutePath` 与 `matchedBy`(`exact-relative` / `exact-absolute` / `path-suffix` / `basename`),以及在 `workspace` 命中时给出的 `projectRoot`(`{ path, name, primary }`,指出是哪个文件夹应答的));`sessionId` 决定查哪个会话的临时目录。隔离会话以 `worktree.location` 而不是父项目 checkout 作为查找与读取的根;落在父 checkout 内的绝对引用会先映射到 worktree 中的同一相对路径(该文件存在时),从而打开分支上的副本,而不是报 `outside-allowed-roots`。它补全智能体在聊天里打印的文件引用,因为渲染器看不到会话自己的临时目录:已经在某个已知根内指向真实文件的绝对引用直接胜出,`attachments/` blob 直接对附件库解析;否则按优先级顺序搜索各根——整个打开的项目、再会话自己的临时目录(`/scratch//`,ADR 0124)、最后附件库——第一个给出结果的根胜出。项目指的是打开的工作区背后的文件夹组(ADR 0249):主文件夹先应答,其余文件夹随后按项目组自身顺序搜索(ADR 0263),因此简写落在同级文件夹里和落在主文件夹里一样自然,命中结果也指出是哪个文件夹应答的。同一个根内精确路径优先于简写;简写之间最长匹配尾优先,其次路径更浅者。文件面板的忽略集合同样生效。什么都没匹配到时返回 `match: null`;解析本身不打开任何东西(ADR 0262)。
- `fs/list` 仍只限工作区;外面的遍历被拒绝(`INVALID_ARGUMENT`)。
## 13b. 桌面菜单和窗口 API
From 549b67b990cf874c041e7146f3c4332b31a5d739 Mon Sep 17 00:00:00 2001
From: zszz3 <91608029+zszz3@users.noreply.github.com>
Date: Tue, 20 Oct 2026 17:31:29 +0800
Subject: [PATCH 04/44] fix(transcript): let an unpinned bookmark own the pane
reveal
Follow mode can still read pinned when a send or retry hid the pane. On the
next reveal the scroll hook then bottomed the transcript before the
reading-position hook could restore the recorded bookmark, so a reader who
had scrolled up returned to the newest turn.
Route the reveal through one shared ownership rule: an unpinned bookmark or a
pending restore keeps the edge, a genuinely pinned pane bottoms, and an
unpinned pane without a bookmark reapplies its retained offset. Both hooks
now agree on which one acts.
fixes #1771
---
.../transcript/hooks/useTranscriptScroll.ts | 32 ++++++++--
.../hooks/use-transcript-reading-position.ts | 13 +++-
.../src/lib/transcript-reading-position.ts | 17 ++++++
.../test/interaction-performance.test.mjs | 8 ++-
.../test/transcript-reveal-ownership.test.mjs | 60 +++++++++++++++++++
5 files changed, 122 insertions(+), 8 deletions(-)
create mode 100644 apps/desktop/test/transcript-reveal-ownership.test.mjs
diff --git a/apps/desktop/src/features/chat/transcript/hooks/useTranscriptScroll.ts b/apps/desktop/src/features/chat/transcript/hooks/useTranscriptScroll.ts
index 32a3f525f8..4d9d838ca1 100644
--- a/apps/desktop/src/features/chat/transcript/hooks/useTranscriptScroll.ts
+++ b/apps/desktop/src/features/chat/transcript/hooks/useTranscriptScroll.ts
@@ -40,7 +40,10 @@ import { readScrollInputContext } from "../../../../lib/scroll-input";
import { useDisclosureAnchor } from "../../../../hooks/use-disclosure-anchor";
import type { TranscriptSearchTarget } from "../../../../lib/transcript-reading";
import { useTranscriptSearchFocus } from "../../../../hooks/use-transcript-search-focus";
-import { getTranscriptReadingPosition } from "../../../../lib/transcript-reading-position";
+import {
+ getTranscriptReadingPosition,
+ transcriptRevealOwnership,
+} from "../../../../lib/transcript-reading-position";
import { useTranscriptReadingPosition, type RestoreTranscriptReading } from "../../../../hooks/use-transcript-reading-position";
type UseTranscriptScrollOptions = {
@@ -247,8 +250,23 @@ export function useTranscriptScroll({
retainedScrollTopRef.current = lastLaidOutScrollTopRef.current;
return;
}
- if (!becameVisible || readingPositionPendingRef.current) return;
- if (pinnedRef.current) {
+ if (!becameVisible) return;
+ const bookmark = getTranscriptReadingPosition(sessionId);
+ const ownership = transcriptRevealOwnership(
+ bookmark,
+ Boolean(readingPositionPendingRef.current),
+ pinnedRef.current,
+ );
+ if (ownership === "reading-position") {
+ // The reading-position hook restores this bookmark (or reports it
+ // missing). Bottoming here would race it and land on the newest turn.
+ if (bookmark?.pinned === false) {
+ pinnedRef.current = false;
+ setShowJump(true);
+ }
+ return;
+ }
+ if (ownership === "pinned") {
scrollToBottom();
return;
}
@@ -257,7 +275,13 @@ export function useTranscriptScroll({
el.scrollTop = retained;
lastScrollTopRef.current = retained;
lastLaidOutScrollTopRef.current = retained;
- }, [cancelFollowScroll, paneVisible, releaseDisclosureAnchor, scrollToBottom]);
+ }, [
+ cancelFollowScroll,
+ paneVisible,
+ releaseDisclosureAnchor,
+ scrollToBottom,
+ sessionId,
+ ]);
// A hidden pane must not chase its stream: its scroller has no visible
// viewport, and the measurements a follow scroll depends on are unreliable
diff --git a/apps/desktop/src/hooks/use-transcript-reading-position.ts b/apps/desktop/src/hooks/use-transcript-reading-position.ts
index 0c4ad057ee..e2ab87c91b 100644
--- a/apps/desktop/src/hooks/use-transcript-reading-position.ts
+++ b/apps/desktop/src/hooks/use-transcript-reading-position.ts
@@ -34,8 +34,17 @@ export function useTranscriptReadingPosition({
const alignmentUntilRef = useRef(0);
const wasVisibleRef = useRef(visible);
useLayoutEffect(() => {
- if (visible && !wasVisibleRef.current && !pinnedRef.current) {
- pendingRef.current = getTranscriptReadingPosition(sessionId);
+ if (visible && !wasVisibleRef.current) {
+ const bookmark = getTranscriptReadingPosition(sessionId);
+ if (bookmark?.pinned === false) {
+ // The follow flag can still read `true` when a send or retry hid the
+ // pane; the recorded bookmark is the authoritative state for this
+ // reveal, so claim the edge instead of letting follow bottom it.
+ pendingRef.current = bookmark;
+ pinnedRef.current = false;
+ } else if (!pinnedRef.current) {
+ pendingRef.current = bookmark;
+ }
alignmentUntilRef.current = 0;
}
wasVisibleRef.current = visible;
diff --git a/apps/desktop/src/lib/transcript-reading-position.ts b/apps/desktop/src/lib/transcript-reading-position.ts
index b4a5b89115..1090b8bddd 100644
--- a/apps/desktop/src/lib/transcript-reading-position.ts
+++ b/apps/desktop/src/lib/transcript-reading-position.ts
@@ -27,6 +27,23 @@ export function sessionReadingState(sessionId: string): ReadingState {
export function getTranscriptReadingPosition(sessionId: string | undefined) {
return sessionId ? readingStates.get(sessionId)?.position : undefined;
}
+
+export type TranscriptRevealOwnership = "reading-position" | "pinned" | "retained";
+
+/**
+ * Which effect owns a pane reveal. A recorded unpinned bookmark wins over a
+ * stale follow flag: follow mode can still read `true` when a send or retry hid
+ * the pane, and bottoming there would undo the position the reader is meant to
+ * return to (issue #1771).
+ */
+export function transcriptRevealOwnership(
+ bookmark: TranscriptReadingPosition | undefined,
+ pending: boolean,
+ pinned: boolean,
+): TranscriptRevealOwnership {
+ if (bookmark?.pinned === false || pending) return "reading-position";
+ return pinned ? "pinned" : "retained";
+}
export function forgetTranscriptReadingState(sessionId: string) {
readingStates.delete(sessionId);
}
diff --git a/apps/desktop/test/interaction-performance.test.mjs b/apps/desktop/test/interaction-performance.test.mjs
index 4517668c76..37bbce3a89 100644
--- a/apps/desktop/test/interaction-performance.test.mjs
+++ b/apps/desktop/test/interaction-performance.test.mjs
@@ -191,11 +191,15 @@ test("a revealed pane restores its own scroll position in the layout phase", ()
// scroller can be clamped while its content grows off screen, and a passive
// effect would leave one visible frame at the wrong offset (ADR 0137).
const revealEffect = transcript.match(
- /useLayoutEffect\(\(\) => \{([\s\S]*?)\n \}, \[cancelFollowScroll, paneVisible, releaseDisclosureAnchor, scrollToBottom\]\);/,
+ /useLayoutEffect\(\(\) => \{([\s\S]*?)\n \}, \[\n cancelFollowScroll,\n paneVisible,\n releaseDisclosureAnchor,\n scrollToBottom,\n sessionId,\n \]\);/,
)?.[1];
assert.ok(revealEffect, "the reveal must restore position in a layout effect");
assert.match(revealEffect, /retainedScrollTopRef\.current = lastLaidOutScrollTopRef\.current/);
- assert.match(revealEffect, /if \(pinnedRef\.current\) \{\s*scrollToBottom\(\);/);
+ // A recorded unpinned bookmark owns the edge; only a genuinely pinned pane
+ // bottoms. A stale follow flag must not override the bookmark (#1771).
+ assert.match(revealEffect, /transcriptRevealOwnership\(/);
+ assert.match(revealEffect, /ownership === "reading-position"/);
+ assert.match(revealEffect, /ownership === "pinned"\) \{\s*scrollToBottom\(\);/);
assert.match(revealEffect, /el\.scrollTop = retained/);
assert.match(revealEffect, /lastScrollTopRef\.current = retained/);
});
diff --git a/apps/desktop/test/transcript-reveal-ownership.test.mjs b/apps/desktop/test/transcript-reveal-ownership.test.mjs
new file mode 100644
index 0000000000..5a0690b3ad
--- /dev/null
+++ b/apps/desktop/test/transcript-reveal-ownership.test.mjs
@@ -0,0 +1,60 @@
+import assert from "node:assert/strict";
+import { readFile } from "node:fs/promises";
+import { register } from "node:module";
+import test from "node:test";
+
+register(new URL("./helpers/ts-import-hooks.mjs", import.meta.url));
+const { transcriptRevealOwnership } = await import(
+ "../src/lib/transcript-reading-position.ts"
+);
+
+const bookmark = (pinned) => ({
+ pinned,
+ messageId: "m1",
+ offset: 24,
+ scrollTop: 480,
+ windowSize: 20,
+});
+const read = (path) => readFile(new URL(path, import.meta.url), "utf8");
+
+test("an unpinned bookmark owns a reveal even when follow still reads pinned", () => {
+ assert.equal(
+ transcriptRevealOwnership(bookmark(false), false, true),
+ "reading-position",
+ );
+});
+
+test("a pending restore owns the reveal", () => {
+ assert.equal(transcriptRevealOwnership(undefined, true, true), "reading-position");
+});
+
+test("a pinned pane without a bookmark bottoms", () => {
+ assert.equal(transcriptRevealOwnership(undefined, false, true), "pinned");
+});
+
+test("an unpinned pane without a bookmark reapplies its retained offset", () => {
+ assert.equal(transcriptRevealOwnership(undefined, false, false), "retained");
+ assert.equal(transcriptRevealOwnership(bookmark(true), false, false), "retained");
+});
+
+test("both transcript hooks route the reveal edge through the shared rule", async () => {
+ const [readingHook, scrollHook] = await Promise.all([
+ read("../src/hooks/use-transcript-reading-position.ts"),
+ read("../src/features/chat/transcript/hooks/useTranscriptScroll.ts"),
+ ]);
+ // The bookmark, not the possibly stale follow flag, claims an unpinned
+ // reveal; the old `!pinnedRef.current` gate let follow bottom it (#1771).
+ assert.match(
+ readingHook,
+ /bookmark\?\.pinned === false[\s\S]*?pendingRef\.current = bookmark[\s\S]*?pinnedRef\.current = false/,
+ );
+ assert.doesNotMatch(
+ readingHook,
+ /!wasVisibleRef\.current && !pinnedRef\.current/,
+ );
+ assert.match(scrollHook, /transcriptRevealOwnership\(/);
+ assert.match(
+ scrollHook,
+ /ownership === "reading-position"[\s\S]*?pinnedRef\.current = false/,
+ );
+});
From 31caf50d0ad8001ba9a95885231508bc03136a57 Mon Sep 17 00:00:00 2001
From: zszz3 <91608029+zszz3@users.noreply.github.com>
Date: Tue, 20 Oct 2026 21:32:39 +0800
Subject: [PATCH 05/44] fix(composer): search past a truncated file index for @
mentions
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
The file index keeps only the shallowest 8000 entries, so in a large
workspace — a Unity project, where every asset has a .meta sibling — a
script several folders down matches no query at all, even though the
truncation note invites the reader to refine it (#1781).
While the snapshot is truncated, a non-empty query is now also searched
over the workspace's full listing through the read-only fs/search channel,
after a short typing pause, and the best rows merge with the index's own
matches. The listing is the git list the index already builds, or a deeper
ignore-set walk when the index came from the walk. A complete index never
searches, and a remote session keeps its snapshot because the remote file
protocol has no search operation.
fixes #1781
---
apps/desktop/electron/main/fs-index.ts | 2 +-
.../electron/main/ipc/workspace-ipc.ts | 11 +-
.../src/hooks/use-composer-autocomplete.ts | 63 ++++-
apps/desktop/src/lib/api.ts | 2 +
...mposer-deep-file-search-user-path.test.mjs | 258 ++++++++++++++++++
...4-composer-commands-and-file-references.md | 3 +
docs/spec/03-runtime/01-ipc-protocol.md | 25 +-
docs/spec/04-ux/08-component-spec.md | 10 +-
docs/spec/06-delivery/04-e2e-test-plan.md | 36 +++
docs/spec/08-meta/decisions-log.md | 24 ++
docs/zh-CN/spec/03-runtime/01-ipc-protocol.md | 20 +-
docs/zh-CN/spec/04-ux/08-component-spec.md | 7 +-
.../spec/06-delivery/04-e2e-test-plan.md | 28 ++
docs/zh-CN/spec/08-meta/decisions-log.md | 18 ++
packages/host-runtime/src/fs-index.test.ts | 87 ++++++
packages/host-runtime/src/fs-index.ts | 149 +++++++---
packages/shared/src/protocol.ts | 1 +
17 files changed, 693 insertions(+), 51 deletions(-)
create mode 100644 apps/desktop/test/composer-deep-file-search-user-path.test.mjs
create mode 100644 packages/host-runtime/src/fs-index.test.ts
diff --git a/apps/desktop/electron/main/fs-index.ts b/apps/desktop/electron/main/fs-index.ts
index bf41f117d1..4dbb8ba2fc 100644
--- a/apps/desktop/electron/main/fs-index.ts
+++ b/apps/desktop/electron/main/fs-index.ts
@@ -1 +1 @@
-export { FS_INDEX_MAX_ENTRIES, getWorkspaceFileIndex } from "@pi-desktop/host-runtime";
+export { FS_INDEX_MAX_ENTRIES, getWorkspaceFileIndex, searchWorkspaceFiles } from "@pi-desktop/host-runtime";
diff --git a/apps/desktop/electron/main/ipc/workspace-ipc.ts b/apps/desktop/electron/main/ipc/workspace-ipc.ts
index 57d7b59797..dbb604bea9 100644
--- a/apps/desktop/electron/main/ipc/workspace-ipc.ts
+++ b/apps/desktop/electron/main/ipc/workspace-ipc.ts
@@ -40,7 +40,7 @@ import {
} from "@pi-desktop/host-runtime";
import { openableMp4Path } from "../open-attachment-video";
import { isChatRefOutsideRoots, resolveChatFileRef } from "../chat-ref-resolve";
-import { getWorkspaceFileIndex } from "../fs-index";
+import { getWorkspaceFileIndex, searchWorkspaceFiles } from "../fs-index";
import {
projectFolderPaths,
refreshProjectGroups,
@@ -984,6 +984,15 @@ export function registerWorkspaceIpc({
return getWorkspaceFileIndex(root);
});
+ handle(IPC.invoke.fsSearch, async (input: { sessionId?: string; query?: string } = {}) => {
+ // The remote file protocol has no search operation, so a remote session
+ // keeps answering from its truncated snapshot.
+ if (await remoteFileWorkspace(input.sessionId)) return { entries: [], truncated: true };
+ const root = await optionalWorkspaceRoot(input.sessionId);
+ if (!root) return { entries: [], truncated: false };
+ return searchWorkspaceFiles(root, String(input.query ?? ""));
+ });
+
/**
* Resolve a file reference from chat to a real file (D320 follow-up).
* The renderer knows the workspace but not where a session keeps its scratch
diff --git a/apps/desktop/src/hooks/use-composer-autocomplete.ts b/apps/desktop/src/hooks/use-composer-autocomplete.ts
index 00292f44b5..683dcc86a5 100644
--- a/apps/desktop/src/hooks/use-composer-autocomplete.ts
+++ b/apps/desktop/src/hooks/use-composer-autocomplete.ts
@@ -24,13 +24,16 @@ import { useAppStore } from "../stores/app-store";
/**
* Composer autocomplete state machine (D123–D125): trigger detection over
- * draft+cursor, lazily fetched command/file sources, local fuzzy filtering,
- * and insert-on-accept. IME freezing and key routing live in the Composer;
+ * draft+cursor, lazily fetched command/file sources, local fuzzy filtering
+ * (with a main-process search past a truncated file index, D665), and
+ * insert-on-accept. IME freezing and key routing live in the Composer;
* this hook only refuses to update while `composing` is true.
*/
const MAX_FILE_ITEMS = 50;
const SOURCE_TTL_MS = 10_000;
+/** Typing pause before a query searches past a truncated file index. */
+const FILE_SEARCH_DEBOUNCE_MS = 150;
export type AutocompleteItem =
| { kind: "command"; command: ComposerCommand; match: FuzzyMatch }
@@ -102,9 +105,13 @@ function filterCommands(
function filterFiles(entries: FsIndexEntry[], query: string): AutocompleteItem[] {
const matched: Array<{ entry: FsIndexEntry; match: FuzzyMatch }> = [];
+ // Rows found by the main-process search may repeat index entries.
+ const seen = new Set();
for (const entry of entries) {
const match = fuzzyMatchPath(query, entry.path, entry.kind);
- if (match) matched.push({ entry, match });
+ if (!match || seen.has(entry.path)) continue;
+ seen.add(entry.path);
+ matched.push({ entry, match });
}
// The index can hold thousands of entries while the menu shows at most
// MAX_FILE_ITEMS, so only the bounded top slice is ever ordered.
@@ -174,6 +181,11 @@ export function useComposerAutocomplete({
entries: FsIndexEntry[];
truncated: boolean;
} | null>(null);
+ const [found, setFound] = useState<{
+ scope: string;
+ entries: FsIndexEntry[];
+ truncated: boolean;
+ } | null>(null);
const [highlight, setHighlight] = useState(0);
const [dismissedKey, setDismissedKey] = useState(null);
const frozenRef = useRef(null);
@@ -251,6 +263,41 @@ export function useComposerAutocomplete({
};
}, [trigger?.mode, dismissed, workspaceKey, hasWorkspace, sessionId]);
+ // A truncated index keeps only the shallowest entries, so a deep file of a
+ // large tree matches nothing in it. Once typing pauses, the query also
+ // searches the main process's full listing (D665); the answer belongs to
+ // this `@` token and its rows merge with the index's.
+ const fileQuery =
+ trigger?.mode === "file" && !dismissed && files?.truncated ? trigger.query : "";
+ const searchScope = `${sessionId ?? ""}\n${workspaceKey}\n${triggerKey ?? ""}`;
+ useEffect(() => {
+ if (!fileQuery) return;
+ let cancelled = false;
+ const timer = setTimeout(() => {
+ void api
+ .fsSearch(sessionId, fileQuery)
+ .then((res) => {
+ if (!cancelled) setFound({ scope: searchScope, ...res });
+ })
+ .catch(() => {
+ // The index's rows still answer; the truncation note stays.
+ if (!cancelled) setFound({ scope: searchScope, entries: [], truncated: true });
+ });
+ }, FILE_SEARCH_DEBOUNCE_MS);
+ return () => {
+ cancelled = true;
+ clearTimeout(timer);
+ };
+ }, [fileQuery, searchScope, sessionId]);
+ // A later `@` at the same offset is a new token and must not inherit rows.
+ useEffect(() => {
+ if (!triggerKey) setFound(null);
+ }, [triggerKey]);
+ // A bare `@` lists the index alone; searched rows belong to a typed query.
+ const foundHere = fileQuery !== "" && found?.scope === searchScope ? found : null;
+ const fileTruncated =
+ (files?.truncated ?? false) && (!fileQuery || !foundHere || foundHere.truncated);
+
// Warm the `/` source once bootstrap settles, so the first slash of a session
// does not wait for a cold host round trip (#1543). Waiting for `ready` keeps
// the pre-warm off the pre-hydration empty workspace key, which would spend a
@@ -265,8 +312,12 @@ export function useComposerAutocomplete({
if (trigger.mode === "slash") {
return commands ? filterCommands(commands, trigger.query, trigger.tokenStart > 0) : [];
}
- return files ? filterFiles(files.entries, trigger.query) : [];
- }, [trigger, dismissed, commands, files]);
+ if (!files) return [];
+ return filterFiles(
+ foundHere ? [...foundHere.entries, ...files.entries] : files.entries,
+ trigger.query,
+ );
+ }, [trigger, dismissed, commands, files, foundHere]);
// New query or mode restarts keyboard navigation at the top hit.
const itemsKey = trigger ? `${trigger.mode}:${trigger.query}` : "";
@@ -322,7 +373,7 @@ export function useComposerAutocomplete({
hasItems: open && items.length > 0,
highlight,
setHighlight,
- truncated: open && trigger?.mode === "file" ? (files?.truncated ?? false) : false,
+ truncated: open && trigger?.mode === "file" ? fileTruncated : false,
noWorkspace: open && trigger?.mode === "file" && !hasWorkspace,
close,
accept,
diff --git a/apps/desktop/src/lib/api.ts b/apps/desktop/src/lib/api.ts
index 85810d88a6..23af03e78b 100644
--- a/apps/desktop/src/lib/api.ts
+++ b/apps/desktop/src/lib/api.ts
@@ -1596,6 +1596,8 @@ export const api = {
fsOpen: (path: string, mimeType?: string, sessionId?: string) =>
invoke(IPC.invoke.fsOpen, { path, mimeType, ...(sessionId ? { sessionId } : {}) }),
fsIndex: (sessionId?: string) => invoke(IPC.invoke.fsIndex, { ...(sessionId ? { sessionId } : {}) }),
+ fsSearch: (sessionId: string | undefined, query: string) =>
+ invoke(IPC.invoke.fsSearch, { ...(sessionId ? { sessionId } : {}), query }),
/**
* Complete a file reference from chat text to a real file (D320 follow-up).
* The main process owns the root order — project, session scratch,
diff --git a/apps/desktop/test/composer-deep-file-search-user-path.test.mjs b/apps/desktop/test/composer-deep-file-search-user-path.test.mjs
new file mode 100644
index 0000000000..9aa64680be
--- /dev/null
+++ b/apps/desktop/test/composer-deep-file-search-user-path.test.mjs
@@ -0,0 +1,258 @@
+/**
+ * Issue #1781: in a large tree the `@` menu could not reach deep files.
+ *
+ * The file index keeps only the shallowest 8000 entries, so a script deep in a
+ * Unity project matched nothing however much of its name was typed. This drives
+ * the composer pieces the app wires together — draft, completions, input, menu —
+ * against a truncated index and a main-process search the test answers itself.
+ */
+import assert from "node:assert/strict";
+import { spawn } from "node:child_process";
+import { createRequire } from "node:module";
+import { mkdtemp, readFile, rm, writeFile } from "node:fs/promises";
+import { tmpdir } from "node:os";
+import { join } from "node:path";
+import test from "node:test";
+import { repositoryRoot, resolveElectronBinary } from "../../../scripts/e2e/boot.mjs";
+
+const root = repositoryRoot();
+const { build } = createRequire(join(root, "packages/agent-runtime/package.json"))("esbuild");
+
+test("the search channel runs main's listing search and leaves remote sessions on their snapshot", async () => {
+ const [protocol, api, workspaceIpc] = await Promise.all([
+ readFile(join(root, "packages/shared/src/protocol.ts"), "utf8"),
+ readFile(join(root, "apps/desktop/src/lib/api.ts"), "utf8"),
+ readFile(join(root, "apps/desktop/electron/main/ipc/workspace-ipc.ts"), "utf8"),
+ ]);
+ assert.match(protocol, /fsSearch: "pi-desktop\/fs\/search"/);
+ assert.match(api, /invoke\(IPC\.invoke\.fsSearch, \{ \.\.\.\(sessionId \? \{ sessionId \} : \{\}\), query \}\)/);
+ const handler = workspaceIpc.match(/handle\(IPC\.invoke\.fsSearch,[\s\S]*?\n {2}\}\);/)?.[0];
+ assert.ok(handler, "main must register the search channel");
+ assert.match(handler, /remoteFileWorkspace\(input\.sessionId\)\) return \{ entries: \[\], truncated: true \}/);
+ assert.match(handler, /return searchWorkspaceFiles\(root, String\(input\.query \?\? ""\)\)/);
+});
+
+const fixture = String.raw`
+import { createRoot } from "react-dom/client";
+import { flushSync } from "react-dom";
+import i18n from "i18next";
+import { initReactI18next } from "react-i18next";
+import { catalogs, flattenCatalog } from "@pi-desktop/i18n";
+import { useComposerDraft } from "../../apps/desktop/src/features/chat/composer/hooks/useComposerDraft";
+import { useComposerCompletions } from "../../apps/desktop/src/features/chat/composer/hooks/useComposerCompletions";
+import { ComposerInput } from "../../apps/desktop/src/features/chat/composer/ComposerInput";
+import { ComposerAutocomplete } from "../../apps/desktop/src/components/ComposerAutocomplete";
+import { setEditorCaret } from "../../apps/desktop/src/features/chat/composer/editor";
+import { api } from "../../apps/desktop/src/lib/api";
+import { useAppStore } from "../../apps/desktop/src/stores/app-store";
+
+const DEEP = "Assets/_Game/Scripts/Gameplay/Player/Controllers/FeatureController.cs";
+const SAVE = "Assets/_Game/Scripts/Systems/Save/SaveSlots.cs";
+const STALE = "Assets/Stale/SaveFeature.cs";
+// Short enough to rank inside the bare @ menu if a searched row leaked into it.
+const SHORT = "a.cs";
+// The shallowest 8000 entries of a large tree; the deep scripts are not among them.
+const shallow = Array.from({ length: 8000 }, (_, index) => ({
+ path: "Assets/Art/Group" + Math.floor(index / 300) + "/asset_" + index + ".png",
+ kind: "file",
+}));
+let fileIndex = { entries: shallow, truncated: true };
+const searches = [];
+api.fsIndex = async () => fileIndex;
+api.fsSearch = (sessionId, query) =>
+ new Promise((resolve, reject) => searches.push({ sessionId, query, resolve, reject }));
+
+await i18n.use(initReactI18next).init({ lng: "en", keySeparator: false,
+ resources: { en: { translation: flattenCatalog(catalogs.en) } },
+ interpolation: { escapeValue: false } });
+useAppStore.setState({ activeSessionId: "s1", workspace: { path: "/large", name: "large" } });
+
+const noop = () => {};
+let draft;
+function Fixture() {
+ draft = useComposerDraft({
+ variant: "docked", activeSessionId: "s1", workspacePath: "/large",
+ sessions: [{ id: "s1" }], composerPrefill: null, clearComposerPrefill: noop,
+ t: (key) => key, invalidateComposerTransforms: noop, inputBlocked: false,
+ });
+ const completions = useComposerCompletions({
+ value: draft.value, cursor: draft.cursor, composing: draft.composing, enabled: true,
+ referenceSessionId: "s1", fileReferencesRef: draft.fileReferencesRef,
+ applyEditorDraft: draft.applyEditorDraft, handleInput: draft.handleInput,
+ invalidateComposerTransforms: noop,
+ });
+ return <>
+ false}
+ onInput={(source, caret) => completions.handleInput(source, caret)}
+ onCompositionStart={() => draft.setComposing(true)}
+ onCompositionEnd={() => draft.setComposing(false)}
+ onSettledInput={() => draft.setComposing(false)} onFocus={noop} onBlur={noop} />
+
+ >;
+}
+
+const rootNode = createRoot(document.getElementById("root"));
+const settle = async () => {
+ await new Promise((resolve) => requestAnimationFrame(() => requestAnimationFrame(resolve)));
+ await new Promise((resolve) => setTimeout(resolve, 40));
+ await new Promise((resolve) => requestAnimationFrame(() => requestAnimationFrame(resolve)));
+};
+const editor = () => document.querySelector(".composer-input");
+const rows = () => [...document.querySelectorAll('[role="option"] .composer-ac-path')].map((row) => row.textContent);
+const noteShown = () => document.querySelector(".composer-ac-truncated") !== null;
+function check(condition, message) { if (!condition) throw new Error(message + " rows=" + JSON.stringify(rows().slice(0, 5))); }
+async function until(predicate, message) {
+ for (let n = 0; n < 300; n += 1) {
+ if (predicate()) return;
+ await new Promise((resolve) => setTimeout(resolve, 10));
+ }
+ check(false, message);
+}
+async function type(text) {
+ const el = editor();
+ el.textContent = text;
+ setEditorCaret(el, text.length);
+ await settle();
+ el.dispatchEvent(new InputEvent("input", { bubbles: true, inputType: "insertText", data: text }));
+ await settle();
+}
+
+window.deepFileSearchProbe = async () => {
+ flushSync(() => rootNode.render( ));
+ await settle();
+ editor().focus();
+
+ await type("@");
+ await until(() => rows().length > 0, "the @ menu did not open");
+ check(noteShown(), "a truncated index must say so");
+ check(searches.length === 0, "an empty query must not search");
+
+ await type("@FeatureController");
+ check(!rows().includes(DEEP), "the truncated index cannot know the deep file");
+ await until(() => searches.length === 1, "the query was not searched after the pause");
+ check(searches[0].query === "FeatureController" && searches[0].sessionId === "s1",
+ "searched the wrong query or session: " + searches[0].query);
+ searches[0].resolve({ entries: [{ path: DEEP, kind: "file" }], truncated: false });
+ await until(() => rows().includes(DEEP), "the searched deep file did not appear");
+ check(!noteShown(), "a complete search must clear the truncation note");
+ check(searches.length === 1, "one pause must search once");
+
+ editor().dispatchEvent(new KeyboardEvent("keydown", { key: "Enter", bubbles: true }));
+ await settle();
+ check(draft.fileReferencesRef.current.some((reference) => reference.path === DEEP),
+ "accepting the row did not reference the deep file");
+
+ await type("@Feat");
+ check(!rows().includes(DEEP), "a new @ token inherited the previous token's rows");
+ await until(() => searches.length === 2, "the second query was not searched");
+ await type("@Save");
+ await until(() => searches.length === 3, "the third query was not searched");
+ searches[2].resolve({ entries: [{ path: SAVE, kind: "file" }, { path: SHORT, kind: "file" }], truncated: false });
+ await until(() => rows().includes(SAVE), "the current answer did not appear");
+ searches[1].resolve({ entries: [{ path: STALE, kind: "file" }], truncated: false });
+ await settle();
+ check(!rows().includes(STALE), "an answer for an earlier query replaced the current one");
+
+ await type("@");
+ await settle();
+ check(!rows().includes(SHORT), "a bare @ listed rows searched for an earlier query");
+ check(noteShown(), "a bare @ must report that the index alone is incomplete");
+
+ await type("@Missing");
+ await until(() => searches.length === 4, "the incomplete query was not searched");
+ searches[3].resolve({ entries: [], truncated: true });
+ await settle();
+ check(noteShown(), "an incomplete search must keep the truncation note");
+
+ await type("@Broken");
+ await until(() => searches.length === 5, "the failing query was not searched");
+ searches[4].reject(new Error("search failed"));
+ await settle();
+ check(noteShown(), "a failed search must keep the truncation note");
+
+ fileIndex = { entries: [{ path: "README.md", kind: "file" }], truncated: false };
+ useAppStore.setState({ workspace: { path: "/small", name: "small" } });
+ await type("");
+ await type("@nothing");
+ await new Promise((resolve) => setTimeout(resolve, 400));
+ check(searches.length === 5, "a complete index must not search");
+ check(!noteShown(), "a complete index has no truncation note");
+
+ flushSync(() => rootNode.unmount());
+ return { passed: true, queries: searches.map((search) => search.query) };
+};
+`;
+
+test("an @ query reaches deep files past a truncated file index", {
+ skip: process.platform === "linux" && !process.env.DISPLAY ? "Electron requires a display" : false,
+}, async () => {
+ const temp = await mkdtemp(join(tmpdir(), "pi-deep-file-search-ui-"));
+ try {
+ await build({
+ stdin: { contents: fixture, resolveDir: join(root, "scripts/e2e"), loader: "tsx" },
+ outfile: join(temp, "renderer.js"),
+ bundle: true,
+ platform: "browser",
+ format: "esm",
+ jsx: "automatic",
+ define: { "process.env.NODE_ENV": '"production"' },
+ alias: {
+ "@pi-desktop/i18n": join(root, "packages/i18n/src"),
+ "@pi-desktop/shared": join(root, "packages/shared/src"),
+ react: join(root, "apps/desktop/node_modules/react"),
+ "react-dom": join(root, "apps/desktop/node_modules/react-dom"),
+ i18next: join(root, "apps/desktop/node_modules/i18next"),
+ "react-i18next": join(root, "apps/desktop/node_modules/react-i18next"),
+ },
+ nodePaths: [join(root, "apps/desktop/node_modules")],
+ });
+ await writeFile(join(temp, "index.html"),
+ '
');
+ await writeFile(join(temp, "main.cjs"), `
+const { app, BrowserWindow } = require("electron");
+const path = require("node:path");
+app.setPath("userData", path.join(__dirname, "profile"));
+app.whenReady().then(async () => {
+ const win = new BrowserWindow({ show: false, width: 900, height: 700,
+ webPreferences: { sandbox: true, contextIsolation: true, nodeIntegration: false, backgroundThrottling: false } });
+ win.webContents.on("console-message", (event) => console.error(event.message));
+ try {
+ await win.loadFile(path.join(__dirname, "index.html"));
+ console.log("DEEP_FILE_SEARCH_PROBE " + JSON.stringify(await win.webContents.executeJavaScript("window.deepFileSearchProbe()")));
+ app.exit(0);
+ } catch (error) { console.error(error?.stack ?? error); app.exit(1); }
+});`);
+ const env = { ...process.env };
+ delete env.ELECTRON_RUN_AS_NODE;
+ const child = spawn(resolveElectronBinary(root).electronBinary, [join(temp, "main.cjs")], {
+ env,
+ stdio: ["ignore", "pipe", "pipe"],
+ });
+ let output = "";
+ for (const stream of [child.stdout, child.stderr]) {
+ stream.setEncoding("utf8");
+ stream.on("data", (chunk) => { output += chunk; });
+ }
+ const timer = setTimeout(() => child.kill("SIGKILL"), 60_000);
+ let code;
+ try {
+ code = await new Promise((resolve, reject) => {
+ child.once("error", reject);
+ child.once("close", resolve);
+ });
+ } finally {
+ clearTimeout(timer);
+ }
+ assert.equal(code, 0, output.slice(-6000));
+ const line = output.split(/\r?\n/).find((item) => item.startsWith("DEEP_FILE_SEARCH_PROBE "));
+ assert.ok(line, output.slice(-6000));
+ const result = JSON.parse(line.slice("DEEP_FILE_SEARCH_PROBE ".length));
+ assert.equal(result.passed, true);
+ assert.deepEqual(result.queries, ["FeatureController", "Feat", "Save", "Missing", "Broken"]);
+ } finally {
+ await rm(temp, { recursive: true, force: true });
+ }
+});
diff --git a/docs/adr/0024-composer-commands-and-file-references.md b/docs/adr/0024-composer-commands-and-file-references.md
index cfdf9958f4..391f8c3b05 100644
--- a/docs/adr/0024-composer-commands-and-file-references.md
+++ b/docs/adr/0024-composer-commands-and-file-references.md
@@ -62,6 +62,9 @@ exported by the installed package and directly reusable.
fallback, short TTL cache); `pi-desktop/composer/commands` returns the
merged command list. Both fail soft without a workspace. These
Electron-only channels do not change the host RPC protocol version.
+ *(Amended by D665: while that index is truncated, a typed query is also
+ answered from the full listing by the read-only `pi-desktop/fs/search`,
+ because the shallow-first cap leaves deep files of a large tree out.)*
## Alternatives considered
diff --git a/docs/spec/03-runtime/01-ipc-protocol.md b/docs/spec/03-runtime/01-ipc-protocol.md
index 64c0fa9051..6b07edd635 100644
--- a/docs/spec/03-runtime/01-ipc-protocol.md
+++ b/docs/spec/03-runtime/01-ipc-protocol.md
@@ -2153,7 +2153,7 @@ reservation, and background artifacts cannot change visible window geometry.
## 13c. Composer input APIs (D123/D124/D197, ADR 0024/0059)
Electron-only channels backing composer autocomplete and file references.
-`composer/commands` and `fs/index` are read-only and fail soft;
+`composer/commands`, `fs/index`, and `fs/search` are read-only and fail soft;
`composer/pickFiles` opens the unified native picker used by the Composer and
returns a one-shot token; the legacy `composer/pickPhotos` channel remains
available for compatibility but is not exposed by the Composer UI.
@@ -2207,7 +2207,28 @@ Workspace-rooted relative paths for the `@` menu: `git ls-files -co
--exclude-standard` fast path, ignore-set recursive walk fallback,
directories derived from file paths, 8000-entry cap with `truncated: true`,
short TTL cache per root. Fails closed to an empty list without a
-workspace. Fuzzy filtering happens renderer-side.
+workspace. Fuzzy filtering happens renderer-side; a truncated index keeps
+only the shallowest entries, so a query against it is also sent to
+`fs/search`.
+
+### fs/search
+
+```ts
+fs/search({ sessionId?, query }) -> { entries: FsIndexEntry[]; truncated: boolean }
+```
+
+The `@` menu calls this only while its `fs/index` snapshot is truncated and
+the query is non-empty, after a short typing pause, then merges the answer
+with its own matches (D665). Main ranks the query with the renderer's fuzzy
+scorer over the root's full listing and returns the best 50 entries. The
+listing is the `git ls-files` list behind the index, or — when the index came
+from the walk — a deeper ignore-set walk of at most 200,000 entries or two
+seconds. It shares the index's TTL cache and is released when that expires.
+`truncated: true` means the search itself was capped. The query is trimmed and
+bounded to 256 characters; an empty query returns no entries. A remote session
+returns `{ entries: [], truncated: true }` without contacting its host — the
+remote file protocol has no search operation — so the menu keeps filtering
+the remote snapshot alone.
### composer/pickFiles and composer/pickPhotos
diff --git a/docs/spec/04-ux/08-component-spec.md b/docs/spec/04-ux/08-component-spec.md
index 82b7fba024..8f1f78ef5b 100644
--- a/docs/spec/04-ux/08-component-spec.md
+++ b/docs/spec/04-ux/08-component-spec.md
@@ -3454,9 +3454,13 @@ Anatomy:
at the caret — the same sentinel-backed chip as a pasted file — whose
canonical value is the original `entry.path`; the menu closes and that Enter
does not send. Accepting a directory keeps the literal path in the draft so
- completion can continue. Entries come from `fs/index` (D124, D209, D362). A
- truncation footnote appears when the index is capped; without a workspace the
- menu shows an "open a project" empty state.
+ completion can continue. Entries come from `fs/index` (D124, D209, D362).
+ When that index is capped, a typed query is also searched over the whole
+ listing through `fs/search` once typing pauses, and the found rows merge
+ with the local matches (D665). A truncation footnote appears while the list
+ may be incomplete — the bare `@`, until the first search for the token
+ answers, and when a search is itself capped or unavailable, as in remote
+ sessions; without a workspace the menu shows an "open a project" empty state.
- Accepting commands and directories inserts text (`/name ` / `@dir/`);
accepting a completed file inserts the inline chip rather than deleting the
trigger. Immediately
diff --git a/docs/spec/06-delivery/04-e2e-test-plan.md b/docs/spec/06-delivery/04-e2e-test-plan.md
index 5b00986fae..69f9b00f21 100644
--- a/docs/spec/06-delivery/04-e2e-test-plan.md
+++ b/docs/spec/06-delivery/04-e2e-test-plan.md
@@ -8764,6 +8764,40 @@ must keep splitting are covered by `markdown-blocks.test.mjs`.
layout covered by `scripts/e2e-composer-autocomplete.mjs`; full UI journey
Draft (run only in a capable environment when this surface changes)
+#### E2E-COMPOSER-deep-file-mentions: `@` reaches deep files in a large workspace
+
+- **Preconditions**: The app is running with an Agent session in a workspace
+ whose index is truncated (more than 8000 files and directories), with a
+ script several folders below thousands of shallow assets — for example a
+ Unity project's `Assets/_Game/Scripts/Gameplay/Player/FeatureController.cs`.
+ Run once with the workspace under git and once without.
+- **Steps**: 1) Type `@` and inspect the footnote. 2) Type the script's name
+ and pause. 3) Accept the script's row with Enter. 4) Edit the query quickly
+ through several prefixes. 5) Repeat in a small workspace and in a remote
+ session.
+- **Expected**:
+ - The bare `@` lists the index and shows the truncation footnote.
+ - After the pause the deep script appears as a row, ranked like any other
+ match, and the footnote disappears once that search has answered; files
+ excluded by `.gitignore` or the ignore set never appear.
+ - Accepting it inserts the same file chip as any other reference.
+ - Rows never belong to an earlier query. The menu keeps the local matches
+ while a search is pending.
+ - A small workspace issues no search request; a remote session keeps its
+ snapshot and footnote.
+- **Specs linked**: `04-ux/08-component-spec.md` §11.8,
+ `03-runtime/01-ipc-protocol.md` §13c, `08-meta/decisions-log.md` (D124,
+ D665), ADR 0024
+- **Acceptance**: C (conversation & stream), Quality
+- **Milestone**: M5
+- **Status**: Unit-covered (`packages/host-runtime/src/fs-index.test.ts`
+ covers the git and walk listings, ignore rules, directories, and the result
+ limit); the renderer journey — search after the pause, merge, accept, stale
+ answers, the footnote, and the complete-index path — is covered by
+ `apps/desktop/test/composer-deep-file-search-user-path.test.mjs` in a real
+ Electron renderer. The full desktop journey against a large real tree is
+ Draft (run only in a capable environment when this surface changes).
+
#### E2E-102b: Unanswered Stop restores compact file-reference drafts
- **Preconditions**: An Agent session can delay its first assistant event. The
@@ -10227,6 +10261,7 @@ must keep splitting are covered by `markdown-blocks.test.mjs`.
| C / Quality / Security (Conversation MP4 attachments) | E2E-CHAT-mp4-attachment-opens-in-system-player |
| G — Plugins (Chat file references) | E2E-CHAT-file-ref-opens-the-surface-that-owns-it, E2E-PLUGIN-file-view-collapse-persists |
| Quality (Chat file references) | E2E-CHAT-shorthand-file-ref-opens-the-matching-file, E2E-CHAT-file-ref-opens-the-surface-that-owns-it, E2E-PLUGIN-file-view-collapse-persists |
+| C / Quality (Composer deep file mentions) | E2E-COMPOSER-deep-file-mentions |
| G — Plugins (project folder roots) | E2E-PLUGIN-file-view-switches-folder-per-project |
| Security (project folder roots) | E2E-PLUGIN-file-view-switches-folder-per-project |
| Quality (project folder roots) | E2E-PLUGIN-file-view-switches-folder-per-project |
@@ -10264,6 +10299,7 @@ must keep splitting are covered by `markdown-blocks.test.mjs`.
| M6+ (Windows updater cache) | E2E-260 |
| M6+ (Independent session communication) | E2E-SESSION-independent-top-level-communication, E2E-SESSION-hover-card-model-and-links |
| M5 (Chat file references) | E2E-CHAT-shorthand-file-ref-opens-the-matching-file, E2E-CHAT-file-ref-opens-the-surface-that-owns-it |
+| M5 (Composer deep file mentions) | E2E-COMPOSER-deep-file-mentions |
| M5 (Conversation MP4 attachments) | E2E-CHAT-mp4-attachment-opens-in-system-player |
| M6+ (Chat file references) | E2E-PLUGIN-file-view-collapse-persists |
| M6+ (project folder roots) | E2E-PLUGIN-file-view-switches-folder-per-project |
diff --git a/docs/spec/08-meta/decisions-log.md b/docs/spec/08-meta/decisions-log.md
index 057e6fc9af..757538dbf8 100644
--- a/docs/spec/08-meta/decisions-log.md
+++ b/docs/spec/08-meta/decisions-log.md
@@ -72,6 +72,7 @@ This log freezes previously open questions into concrete decisions.
| D021 | First-run onboarding | **Inline checklist (not modal wizard)** |
| D022 | Local telemetry | **Local logs only in MVP (no remote telemetry)** |
| D664 | Sidebar running activity defaults | **When unset, the master and Count badge resolve on while Activity rail resolves off. Explicit saved values remain authoritative. The master continues gating both affordances; turning it off does not rewrite either child preference. No schema or migration change.** |
+| D665 | `@` queries search past a truncated file index | **Amend D124: while the 8000-entry `fs/index` snapshot is truncated, a non-empty `@` query is also searched over the root's full listing through the read-only Electron channel `pi-desktop/fs/search` once typing pauses, and its best 50 rows merge with the local matches. A complete index never searches. Remote sessions keep their snapshot. No host RPC, storage, or schema change.** |
## C. Provider & model coverage decisions (0.3.4)
@@ -7778,3 +7779,26 @@ must keep splitting are covered by `markdown-blocks.test.mjs`.
default. Settings reads apply these defaults through renderer API
normalization; no persisted schema or migration change is required. See
`04-ux/01-ui-ia.md`, `04-ux/06-settings-ia.md`, and E2E-266.
+
+## 2026-10-19 — `@` queries search past a truncated file index (D665)
+
+- The `fs/index` snapshot keeps the shallowest 8000 entries, and the menu
+ fuzzy-filtered only that snapshot. In a large tree — a Unity project, where
+ every asset has a `.meta` sibling — scripts several folders deep were never
+ in it, so no query could reach them even though the truncation footnote
+ invited refining the query (issue #1781).
+- While the snapshot is truncated, a non-empty query is now also sent to
+ `fs/search` after a 150 ms typing pause. Main ranks it with the renderer's
+ scorer over the listing it already built for the index (`git ls-files`), or
+ over a deeper ignore-set walk (at most 200,000 entries or two seconds) when
+ the index came from the walk, and returns the best 50 rows. The menu merges
+ them with its local matches; an answer for an earlier query is dropped.
+- A complete index never searches, so small projects behave as before. The
+ footnote stays while the list may be incomplete. Remote sessions keep their
+ snapshot because the remote file protocol has no search operation. Bundling
+ a native lister (ripgrep, bfs) was not needed: git already lists the whole
+ repository, and searching 60,000 paths takes a few milliseconds.
+- Covered by `packages/host-runtime/src/fs-index.test.ts` and
+ `apps/desktop/test/composer-deep-file-search-user-path.test.mjs`. See
+ `03-runtime/01-ipc-protocol.md` §13c, `04-ux/08-component-spec.md` §11.8,
+ and E2E-COMPOSER-deep-file-mentions.
diff --git a/docs/zh-CN/spec/03-runtime/01-ipc-protocol.md b/docs/zh-CN/spec/03-runtime/01-ipc-protocol.md
index 79a7716a22..10c9a8395e 100644
--- a/docs/zh-CN/spec/03-runtime/01-ipc-protocol.md
+++ b/docs/zh-CN/spec/03-runtime/01-ipc-protocol.md
@@ -1618,7 +1618,7 @@ Electron 报告的右侧角)改变的是面板目标。Main 通过
## 13c. Composer 输入 API(D123/D124/D197、ADR 0024/0059)
仅电子通道支持输入框自动完成和剪贴板文件
-参考。 `composer/commands` 和 `fs/index` 是只读且软故障;
+参考。 `composer/commands`、`fs/index` 和 `fs/search` 是只读且软故障;
`composer/pasteFiles` 仅写入原始会话的 Electron 拥有的
暂存目录。 None 添加主机 RPC 方法或更改主机协议
版本。
@@ -1664,7 +1664,23 @@ type FsIndexEntry = { path: string; kind: "file" | "dir" };
--exclude-standard`快速路径,忽略设置递归行走回退,
从文件路径派生的目录,8000 个条目上限,`truncated: true`,
每个根的短 TTL 缓存。无法关闭到空列表而没有
-工作区。模糊过滤发生在渲染器端。
+工作区。模糊过滤发生在渲染器端;被截断的索引只保留最浅的条目,因此针对它的
+查询还会发给 `fs/search`。
+
+### fs/search
+
+```ts
+fs/search({ sessionId?, query }) -> { entries: FsIndexEntry[]; truncated: boolean }
+```
+
+只有当 `fs/index` 快照被截断且查询非空时,`@` 菜单才会在输入短暂停顿后调用它,
+并把结果与自己的匹配合并(D665)。主进程用与渲染器相同的模糊打分,在该根目录的
+完整清单上排序,返回最好的 50 个条目。清单就是索引背后的 `git ls-files` 列表;
+若索引来自目录遍历,则改为一次更深的遍历(遵守同一忽略集,最多 200,000 个条目或
+2 秒)。清单与索引共用 TTL 缓存,过期即释放。`truncated: true` 表示搜索本身被截断。
+查询会去掉首尾空白并限制在 256 个字符内;空查询不返回条目。远程会话直接返回
+`{ entries: [], truncated: true }`,不联系远程主机——远程文件协议没有搜索操作——
+菜单继续只在远程快照里过滤。
### composer/pickFiles 和 composer/pickPhotos
diff --git a/docs/zh-CN/spec/04-ux/08-component-spec.md b/docs/zh-CN/spec/04-ux/08-component-spec.md
index 07d75aa4ea..4afd8c37cc 100644
--- a/docs/zh-CN/spec/04-ux/08-component-spec.md
+++ b/docs/zh-CN/spec/04-ux/08-component-spec.md
@@ -2290,8 +2290,11 @@ Live Voice 受现有开发者模式和开发构建门控约束,包含四种展
(Enter、Tab 或点击)会把 `@` 标记替换为光标处的行内叶名芯片
—— 与粘贴文件相同的哨兵芯片 —— 其规范值为原始 `entry.path`;
菜单关闭且这次 Enter 不会发送。接受目录会将文字路径保留在草稿中,
- 以便完成可以继续。条目来自 `fs/index`(D124、D209、D362)。一个
- 当索引被限制时出现截断脚注;没有工作空间
+ 以便完成可以继续。条目来自 `fs/index`(D124、D209、D362)。
+ 索引被截断时,输入停顿后查询还会通过 `fs/search` 在完整清单中搜索,
+ 搜到的行与本地匹配合并(D665)。列表可能不完整时显示截断脚注——
+ 只输入 `@` 时、该标记的第一次搜索返回之前,以及搜索本身被截断或不可用
+ (如远程会话)时;没有工作空间
菜单显示“打开项目”空状态。
- 接受命令和目录插入文本(`/name ` / `@dir/`);
接受完成的文件会插入行内芯片,而不是删除触发符。立即
diff --git a/docs/zh-CN/spec/06-delivery/04-e2e-test-plan.md b/docs/zh-CN/spec/06-delivery/04-e2e-test-plan.md
index 1bf5205a08..086d23b4e3 100644
--- a/docs/zh-CN/spec/06-delivery/04-e2e-test-plan.md
+++ b/docs/zh-CN/spec/06-delivery/04-e2e-test-plan.md
@@ -5288,6 +5288,32 @@ eleven-tool-round desktop paths are verified by
布局由 `scripts/e2e-composer-autocomplete.mjs` 覆盖;完整的用户界面
旅程草稿(适用变更合入前需在具备条件的环境中运行 E2E)
+#### E2E-COMPOSER-deep-file-mentions:`@` 能找到大型工作区里的深层文件
+
+- **先决条件**:应用程序正在一个索引被截断(超过 8000 个文件和目录)的工作区中使用
+ Agent 会话运行,其中有一个脚本位于数千个浅层资源之下的几层目录里——例如 Unity
+ 项目的 `Assets/_Game/Scripts/Gameplay/Player/FeatureController.cs`。工作区在 git
+ 管理下和不在 git 管理下各运行一次。
+- **步骤**:1) 输入 `@` 并检查脚注。2) 输入脚本名称后停顿。3) 用 Enter 接受该脚本的行。
+ 4) 快速把查询改成几个不同的前缀。5) 在小工作区和远程会话中重复。
+- **预期**:
+ - 只输入 `@` 时列出索引并显示截断脚注。
+ - 停顿后深层脚本作为一行出现,排序与其他匹配一致;这次搜索返回后脚注消失;被
+ `.gitignore` 或忽略集排除的文件从不出现。
+ - 接受后插入与其他引用相同的文件芯片。
+ - 行永远不属于更早的查询。搜索进行中菜单保留本地匹配。
+ - 小工作区不发出搜索请求;远程会话保持使用快照并保留脚注。
+- **链接规格**:`04-ux/08-component-spec.md` §11.8、`03-runtime/01-ipc-protocol.md`
+ §13c、`08-meta/decisions-log.md`(D124、D665)、ADR 0024
+- **接受**:C(对话和直播),质量
+- **里程碑**:M5
+- **状态**:单元覆盖(`packages/host-runtime/src/fs-index.test.ts` 覆盖 git 与遍历两种
+ 清单、忽略规则、目录以及结果上限);渲染层旅程——停顿后搜索、合并、接受、过期
+ 结果、脚注以及完整索引路径——由
+ `apps/desktop/test/composer-deep-file-search-user-path.test.mjs` 在真实 Electron
+ 渲染器中覆盖。针对大型真实目录树的完整桌面旅程为草稿(适用变更合入前需在具备
+ 条件的环境中运行 E2E)。
+
#### E2E-102b:未答复的停止恢复紧凑的文件参考草稿
- **先决条件**:Agent 会话可以延迟其第一个辅助事件。的
@@ -5806,6 +5832,7 @@ eleven-tool-round desktop paths are verified by
| C / 质量 / 安全(对话 MP4 附件) | E2E-CHAT-mp4-attachment-opens-in-system-player |
| G——插件(聊天文件引用) | E2E-CHAT-file-ref-opens-the-surface-that-owns-it、E2E-PLUGIN-file-view-collapse-persists |
| 品质(聊天文件引用) | E2E-CHAT-shorthand-file-ref-opens-the-matching-file、E2E-CHAT-file-ref-opens-the-surface-that-owns-it、E2E-PLUGIN-file-view-collapse-persists |
+| C / 品质(Composer 深层文件引用) | E2E-COMPOSER-deep-file-mentions |
| G——插件(项目文件夹根) | E2E-PLUGIN-file-view-switches-folder-per-project |
| 安全性(项目文件夹根) | E2E-PLUGIN-file-view-switches-folder-per-project |
| 品质(项目文件夹根) | E2E-PLUGIN-file-view-switches-folder-per-project |
@@ -5860,6 +5887,7 @@ eleven-tool-round desktop paths are verified by
| M6+(Windows 更新缓存) | E2E-260 |
| M6+(独立会话通信) | E2E-SESSION-independent-top-level-communication、E2E-SESSION-hover-card-model-and-links |
| M5(聊天文件引用) | E2E-CHAT-shorthand-file-ref-opens-the-matching-file、E2E-CHAT-file-ref-opens-the-surface-that-owns-it |
+| M5(Composer 深层文件引用) | E2E-COMPOSER-deep-file-mentions |
| M5(对话 MP4 附件) | E2E-CHAT-mp4-attachment-opens-in-system-player |
| M6+(聊天文件引用) | E2E-PLUGIN-file-view-collapse-persists |
| M6+(项目文件夹根) | E2E-PLUGIN-file-view-switches-folder-per-project |
diff --git a/docs/zh-CN/spec/08-meta/decisions-log.md b/docs/zh-CN/spec/08-meta/decisions-log.md
index c5792d5581..1b25b35aa3 100644
--- a/docs/zh-CN/spec/08-meta/decisions-log.md
+++ b/docs/zh-CN/spec/08-meta/decisions-log.md
@@ -74,6 +74,7 @@
| D021 | 首次运行新手引导 | **内联清单(不是模式向导)** |
| D022 | 本地遥测 | **仅在 MVP 中记录本地日志(无远程遥测)** |
| D664 | 侧边栏运行活动默认值 | **未设置时,总开关和数量徽标默认开启,活动流光默认关闭。已保存的值优先生效。总开关仍控制两种提示;关闭总开关不会改写任一子开关偏好。不更改 schema 或执行迁移。** |
+| D665 | `@` 查询越过被截断的文件索引 | **修订 D124:8000 条的 `fs/index` 快照被截断时,非空的 `@` 查询会在输入停顿后,通过只读的 Electron 通道 `pi-desktop/fs/search` 在该根目录的完整清单中搜索,最好的 50 行与本地匹配合并。完整的索引从不搜索。远程会话保持使用快照。不改变主机 RPC、存储或 schema。** |
## C. 提供商和模型覆盖决策 (0.3.4)
@@ -5488,3 +5489,20 @@ Markdown 源码,不是 `text/html` 负载;对禁用行内 HTML 的外部编
- 数量徽标保留运行状态的可发现性,同时避免动画轨道成为默认界面。不需要更改持久化
schema 或迁移。设置读取通过渲染层 API 规范化应用这些默认值。见
`04-ux/01-ui-ia.md`、`04-ux/06-settings-ia.md` 与 E2E-266。
+
+## 2026-10-19 —— `@` 查询越过被截断的文件索引(D665)
+
+- `fs/index` 快照只保留最浅的 8000 个条目,菜单也只在这份快照里模糊过滤。在大项目里
+ ——例如每个资源都带一个 `.meta` 文件的 Unity 项目——藏在几层目录下的脚本根本不在
+ 快照中,无论怎么输入都找不到,尽管截断脚注提示用户继续输入(issue #1781)。
+- 快照被截断时,非空查询现在会在输入停顿 150 ms 后同时发给 `fs/search`。主进程用与
+ 渲染器相同的打分,在它为索引已经构建好的清单(`git ls-files`)上排序;若索引来自
+ 目录遍历,则改为一次更深的遍历(遵守同一忽略集,最多 200,000 个条目或 2 秒),
+ 返回最好的 50 行。菜单把它们与本地匹配合并;较早查询的结果会被丢弃。
+- 完整的索引从不搜索,小项目行为不变。列表可能不完整时截断脚注保留。远程会话继续
+ 使用快照,因为远程文件协议没有搜索操作。不需要打包原生列文件工具(ripgrep、bfs):
+ git 本来就能列出整个仓库,搜索 60,000 个路径只需几毫秒。
+- 由 `packages/host-runtime/src/fs-index.test.ts` 与
+ `apps/desktop/test/composer-deep-file-search-user-path.test.mjs` 覆盖。见
+ `03-runtime/01-ipc-protocol.md` §13c、`04-ux/08-component-spec.md` §11.8 与
+ E2E-COMPOSER-deep-file-mentions。
diff --git a/packages/host-runtime/src/fs-index.test.ts b/packages/host-runtime/src/fs-index.test.ts
new file mode 100644
index 0000000000..ffe96c1d0b
--- /dev/null
+++ b/packages/host-runtime/src/fs-index.test.ts
@@ -0,0 +1,87 @@
+import { spawnSync } from "node:child_process";
+import { mkdir, mkdtemp, rm, writeFile } from "node:fs/promises";
+import { tmpdir } from "node:os";
+import { dirname, join } from "node:path";
+import { afterAll, expect, it } from "vitest";
+import {
+ FS_INDEX_MAX_ENTRIES,
+ getWorkspaceFileIndex,
+ searchWorkspaceFiles,
+} from "./fs-index.js";
+
+const DEEP_SCRIPT = "Assets/_Game/Scripts/Gameplay/Player/Controllers/FeatureController.cs";
+
+const temps: string[] = [];
+afterAll(async () => {
+ await Promise.all(temps.splice(0).map((dir) => rm(dir, { recursive: true, force: true })));
+});
+
+async function writeFiles(root: string, paths: string[]): Promise {
+ for (let at = 0; at < paths.length; at += 500) {
+ await Promise.all(
+ paths.slice(at, at + 500).map(async (path) => {
+ await mkdir(dirname(join(root, path)), { recursive: true });
+ await writeFile(join(root, path), "x");
+ }),
+ );
+ }
+}
+
+/** A Unity-like tree: more shallow assets than the snapshot holds, one deep script. */
+async function largeTree(prefix: string): Promise {
+ const root = await mkdtemp(join(tmpdir(), prefix));
+ temps.push(root);
+ const assets = Array.from(
+ { length: FS_INDEX_MAX_ENTRIES + 100 },
+ (_, index) => `Assets/Art/Group${Math.floor(index / 300)}/asset_${index}.png`,
+ );
+ await writeFiles(root, [...assets, DEEP_SCRIPT, "node_modules/pkg/FeatureController.cs"]);
+ return root;
+}
+
+function gitAvailable(): boolean {
+ return spawnSync("git", ["--version"]).status === 0;
+}
+
+it("finds a deep file that the truncated snapshot leaves out", async () => {
+ const root = await largeTree("pi-fs-search-walk-");
+
+ const index = await getWorkspaceFileIndex(root);
+ expect(index.truncated).toBe(true);
+ expect(index.entries).toHaveLength(FS_INDEX_MAX_ENTRIES);
+ expect(index.entries.some((entry) => entry.path === DEEP_SCRIPT)).toBe(false);
+
+ const found = await searchWorkspaceFiles(root, "FeatureController");
+ expect(found.truncated).toBe(false);
+ expect(found.entries[0]).toEqual({ path: DEEP_SCRIPT, kind: "file" });
+ expect(found.entries.some((entry) => entry.path.startsWith("node_modules/"))).toBe(false);
+});
+
+it("searches a git repository's full listing and keeps its ignore rules", async (ctx) => {
+ if (!gitAvailable()) ctx.skip();
+ const root = await largeTree("pi-fs-search-git-");
+ await writeFiles(root, ["Generated/FeatureController.cs"]);
+ await writeFile(join(root, ".gitignore"), "Generated/\n");
+ expect(spawnSync("git", ["init", "-q"], { cwd: root }).status).toBe(0);
+
+ const index = await getWorkspaceFileIndex(root);
+ expect(index.truncated).toBe(true);
+ expect(index.entries.some((entry) => entry.path === DEEP_SCRIPT)).toBe(false);
+
+ const found = await searchWorkspaceFiles(root, "FeatureController");
+ expect(found.truncated).toBe(false);
+ expect(found.entries.map((entry) => entry.path)).toEqual([DEEP_SCRIPT]);
+});
+
+it("returns directories and honors the result limit", async () => {
+ const root = await largeTree("pi-fs-search-limit-");
+
+ const dirs = await searchWorkspaceFiles(root, "Controllers");
+ expect(dirs.entries[0]).toEqual({
+ path: "Assets/_Game/Scripts/Gameplay/Player/Controllers",
+ kind: "dir",
+ });
+
+ const limited = await searchWorkspaceFiles(root, "asset_", 5);
+ expect(limited.entries).toHaveLength(5);
+});
diff --git a/packages/host-runtime/src/fs-index.ts b/packages/host-runtime/src/fs-index.ts
index 5f4673a280..5a63abab27 100644
--- a/packages/host-runtime/src/fs-index.ts
+++ b/packages/host-runtime/src/fs-index.ts
@@ -1,7 +1,12 @@
import { spawn } from "node:child_process";
import { readdir } from "node:fs/promises";
import { join } from "node:path";
-import type { FsIndexEntry, FsIndexResult } from "@pi-desktop/shared";
+import {
+ fuzzyMatchPath,
+ selectBestMatches,
+ type FsIndexEntry,
+ type FsIndexResult,
+} from "@pi-desktop/shared";
import { isIgnoredName } from "./workspace-files.js";
/**
@@ -10,16 +15,33 @@ import { isIgnoredName } from "./workspace-files.js";
* Served from the main process like the files tab (ADR 0019): user-driven
* browsing must not round-trip agent tools or permission prompts. The index
* prefers `git ls-files` for exact gitignore semantics and falls back to a
- * bounded walk over the panel's ignore set. Fuzzy filtering happens in the
- * renderer; this only snapshots relative paths.
+ * bounded walk over the panel's ignore set. The renderer fuzzy-filters the
+ * snapshot itself; when the snapshot is truncated, a query is also answered
+ * here from the full listing (D665).
*/
export const FS_INDEX_MAX_ENTRIES = 8000;
+/** Most entries a query searches when the snapshot is truncated. */
+const FS_SEARCH_MAX_ENTRIES = 200_000;
+/** The composer menu shows at most this many file rows. */
+const FS_SEARCH_MAX_RESULTS = 50;
+/** `fuzzyMatchPath` lowercases the query once per entry. */
+const FS_SEARCH_MAX_QUERY = 256;
+const SEARCH_WALK_TIMEOUT_MS = 2000;
const CACHE_TTL_MS = 15_000;
const GIT_TIMEOUT_MS = 4000;
const MAX_GIT_BUFFER = 32 * 1024 * 1024;
-type CacheSlot = { at: number; result: FsIndexResult };
+/** Shallow-first entries; `complete` is false when a cap or timeout cut them short. */
+type Listing = { entries: FsIndexEntry[]; complete: boolean };
+type CacheSlot = {
+ at: number;
+ index: FsIndexResult;
+ listing: Listing;
+ /** The listing came from the snapshot-sized walk, so a query may deepen it. */
+ walked: boolean;
+ deeper?: Promise;
+};
const cache = new Map();
function hasIgnoredSegment(path: string): boolean {
@@ -66,13 +88,18 @@ function gitListFiles(root: string): Promise {
async function walkFiles(
root: string,
budget: number,
+ deadline = Number.POSITIVE_INFINITY,
): Promise<{ files: string[]; dirs: string[]; exhausted: boolean }> {
const files: string[] = [];
const dirs: string[] = [];
let exhausted = false;
const queue: string[] = [""];
- while (queue.length > 0) {
- const rel = queue.shift()!;
+ for (let next = 0; next < queue.length; next += 1) {
+ if (Date.now() > deadline) {
+ exhausted = true;
+ break;
+ }
+ const rel = queue[next]!;
let dirents;
try {
dirents = await readdir(join(root, rel), { withFileTypes: true });
@@ -124,46 +151,57 @@ function compareEntries(a: FsIndexEntry, b: FsIndexEntry): number {
return a.path.localeCompare(b.path);
}
-async function buildIndex(root: string): Promise {
- const viaGit = await gitListFiles(root);
- let files: string[];
- let dirs: string[];
- let exhausted = false;
- if (viaGit) {
- // -o lists untracked-but-not-ignored files; repos without a .gitignore
- // would still surface build output, so the panel ignore set applies too.
- files = viaGit.filter((p) => !hasIgnoredSegment(p));
- dirs = dirsFromFilePaths(files);
- } else {
- const walked = await walkFiles(root, FS_INDEX_MAX_ENTRIES + 1);
- files = walked.files;
- dirs = walked.dirs;
- exhausted = walked.exhausted;
- }
-
+function toListing(files: string[], dirs: string[], complete: boolean): Listing {
const entries: FsIndexEntry[] = [
...dirs.map((path): FsIndexEntry => ({ path, kind: "dir" })),
...files.map((path): FsIndexEntry => ({ path, kind: "file" })),
].sort(compareEntries);
+ if (entries.length > FS_SEARCH_MAX_ENTRIES) {
+ return { entries: entries.slice(0, FS_SEARCH_MAX_ENTRIES), complete: false };
+ }
+ return { entries, complete };
+}
- if (entries.length > FS_INDEX_MAX_ENTRIES) {
- return { entries: entries.slice(0, FS_INDEX_MAX_ENTRIES), truncated: true };
+async function walkListing(root: string, budget: number, deadline?: number): Promise {
+ const walked = await walkFiles(root, budget, deadline);
+ return toListing(walked.files, walked.dirs, !walked.exhausted);
+}
+
+async function buildSlot(root: string): Promise {
+ const viaGit = await gitListFiles(root);
+ let listing: Listing;
+ if (viaGit) {
+ // -o lists untracked-but-not-ignored files; repos without a .gitignore
+ // would still surface build output, so the panel ignore set applies too.
+ const files = viaGit.filter((p) => !hasIgnoredSegment(p));
+ listing = toListing(files, dirsFromFilePaths(files), true);
+ } else {
+ listing = await walkListing(root, FS_INDEX_MAX_ENTRIES + 1);
}
- return { entries, truncated: exhausted };
+ const { entries, complete } = listing;
+ const index =
+ entries.length > FS_INDEX_MAX_ENTRIES
+ ? { entries: entries.slice(0, FS_INDEX_MAX_ENTRIES), truncated: true }
+ : { entries, truncated: !complete };
+ return { at: Date.now(), index, listing, walked: !viaGit };
}
-/** TTL-cached workspace index; concurrent calls share one build. */
-const pending = new Map>();
+/** TTL-cached workspace listing; concurrent calls share one build. */
+const pending = new Map>();
-export async function getWorkspaceFileIndex(root: string): Promise {
+function slotFor(root: string): Promise {
const cached = cache.get(root);
- if (cached && Date.now() - cached.at < CACHE_TTL_MS) return cached.result;
+ if (cached && Date.now() - cached.at < CACHE_TTL_MS) return Promise.resolve(cached);
const inFlight = pending.get(root);
if (inFlight) return inFlight;
- const build = buildIndex(root)
- .then((result) => {
- cache.set(root, { at: Date.now(), result });
- return result;
+ const build = buildSlot(root)
+ .then((slot) => {
+ cache.set(root, slot);
+ // A large tree's listing is held for the TTL only, not until the next build.
+ setTimeout(() => {
+ if (cache.get(root) === slot) cache.delete(root);
+ }, CACHE_TTL_MS).unref();
+ return slot;
})
.finally(() => {
pending.delete(root);
@@ -171,3 +209,46 @@ export async function getWorkspaceFileIndex(root: string): Promise {
+ return (await slotFor(root)).index;
+}
+
+/**
+ * The best `limit` entries for an "@" query over the whole listing, ranked
+ * like the renderer ranks the snapshot. A truncated snapshot keeps the
+ * shallowest entries, so deep files of a large tree can only be found here
+ * (#1781). A listing from the snapshot-sized walk is deepened once per slot.
+ */
+export async function searchWorkspaceFiles(
+ root: string,
+ query: string,
+ limit = FS_SEARCH_MAX_RESULTS,
+): Promise {
+ const needle = query.trim().slice(0, FS_SEARCH_MAX_QUERY);
+ if (!needle) return { entries: [], truncated: false };
+ const slot = await slotFor(root);
+ const listing =
+ slot.walked && !slot.listing.complete
+ ? await (slot.deeper ??= walkListing(
+ root,
+ FS_SEARCH_MAX_ENTRIES,
+ Date.now() + SEARCH_WALK_TIMEOUT_MS,
+ ))
+ : slot.listing;
+ const best = selectBestMatches(matchEntries(listing.entries, needle), limit, (hit) => ({
+ score: hit.score,
+ text: hit.entry.path,
+ }));
+ return { entries: best.map((hit) => hit.entry), truncated: !listing.complete };
+}
+
+function* matchEntries(
+ entries: FsIndexEntry[],
+ query: string,
+): Generator<{ entry: FsIndexEntry; score: number }> {
+ for (const entry of entries) {
+ const match = fuzzyMatchPath(query, entry.path, entry.kind);
+ if (match) yield { entry, score: match.score };
+ }
+}
diff --git a/packages/shared/src/protocol.ts b/packages/shared/src/protocol.ts
index 7635845243..761fcb4bbc 100644
--- a/packages/shared/src/protocol.ts
+++ b/packages/shared/src/protocol.ts
@@ -417,6 +417,7 @@ export const IPC = {
fsReveal: "pi-desktop/fs/reveal",
fsOpen: "pi-desktop/fs/open",
fsIndex: "pi-desktop/fs/index",
+ fsSearch: "pi-desktop/fs/search",
fsResolveRef: "pi-desktop/fs/resolveRef",
windowSetWorkPanelReservation:
"pi-desktop/window/setWorkPanelReservation",
From 399dd26e5d5df63d2817d8be05058087a716d3fa Mon Sep 17 00:00:00 2001
From: blackEvil217 <1278844978@qq.com>
Date: Mon, 19 Oct 2026 13:04:21 -0700
Subject: [PATCH 06/44] fix(work-panel): keep the active tab's close button
inside the strip
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
The close button is a sibling of the tab button inside the tab wrapper, but
scroll-into-view targeted only the button. With `inline: "nearest"` a button
that is already visible scrolls zero pixels, so the sibling close button
stayed clipped outside the strip's overflow edge — the tab looked like it had
no close control at all (issue #1762).
Scroll the wrapper instead (falling back to the button), and reserve the
close button's width at the inline end via `scroll-padding-inline` so
sub-pixel rounding cannot reintroduce the clip.
---
.../src/components/workpanel/WorkPanel.tsx | 41 ++++
apps/desktop/src/styles/work-panel.css | 5 +-
apps/desktop/test/work-panel.test.mjs | 19 ++
package.json | 1 +
scripts/e2e-work-panel-tab-close.mjs | 122 ++++++++++
scripts/e2e/work-panel-tab-close.tsx | 217 ++++++++++++++++++
6 files changed, 404 insertions(+), 1 deletion(-)
create mode 100644 scripts/e2e-work-panel-tab-close.mjs
create mode 100644 scripts/e2e/work-panel-tab-close.tsx
diff --git a/apps/desktop/src/components/workpanel/WorkPanel.tsx b/apps/desktop/src/components/workpanel/WorkPanel.tsx
index 1802a1ec92..8d4280773c 100644
--- a/apps/desktop/src/components/workpanel/WorkPanel.tsx
+++ b/apps/desktop/src/components/workpanel/WorkPanel.tsx
@@ -312,8 +312,31 @@ function LocalWorkPanel({
setNativeSurfaceReadyForExit(true);
}, [exiting]);
+ /**
+ * Reveal one tab's full box — the wrapper, not the button alone. The close
+ * control is a 24px sibling inside that wrapper, so scrolling only the button
+ * leaves the close control clipped by the strip's overflow edge (issue
+ * #1762). The button is the fallback for a tab rendered without a wrapper.
+ */
+ const revealTab = useCallback((tabId: string) => {
+ tabWrapperRefs.current[tabId]?.scrollIntoView({
+ block: "nearest",
+ inline: "nearest",
+ });
+ tabButtonRefs.current[tabId]?.scrollIntoView({
+ block: "nearest",
+ inline: "nearest",
+ });
+ tabCloseButtonRefs.current[tabId]?.scrollIntoView({
+ block: "nearest",
+ inline: "nearest",
+ });
+ }, []);
+
useLayoutEffect(() => {
if (!activeTabId) return;
+ // Inline rather than a helper call: `work-panel.test.mjs` pins this effect
+ // body as the contract for "wrapper, then button, then close control".
tabWrapperRefs.current[activeTabId]?.scrollIntoView({
block: "nearest",
inline: "nearest",
@@ -328,6 +351,18 @@ function LocalWorkPanel({
});
}, [activeTabId, tabs.length]);
+ // A narrowed panel clips a tab that was fully visible a moment ago, and
+ // neither `activeTabId` nor `tabs.length` changes when only the width does —
+ // so the reveal above would not re-run and the close control would stay
+ // clipped after a resize (issue #1762). Observe the strip itself.
+ useLayoutEffect(() => {
+ const strip = tabStripRef.current;
+ if (!strip || !activeTabId || typeof ResizeObserver === "undefined") return;
+ const observer = new ResizeObserver(() => revealTab(activeTabId));
+ observer.observe(strip);
+ return () => observer.disconnect();
+ }, [activeTabId, revealTab]);
+
const finishTabReorder = useCallback(() => {
const state = tabReorderState.current;
if (state) {
@@ -871,6 +906,12 @@ function LocalWorkPanel({
(dropIndicator.insertAfter ? "is-drop-after" : "is-drop-before"),
)}
data-work-panel-tab-id={tab.id}
+ // A partly visible inactive tab reveals its close
+ // control on hover (`.work-panel-tab:hover
+ // .work-panel-tab-close`, styles/work-panel.css:314) —
+ // revealing opacity is not enough when the control sits
+ // outside the strip, so bring the whole box in first.
+ onPointerEnter={() => revealTab(tab.id)}
key={tab.id}
>
{
+ // Issue #1762: the close button is a sibling of the tab button inside the
+ // tab wrapper. Scrolling the button with `inline: "nearest"` moves nothing
+ // once the button is visible, leaving the close button clipped outside the
+ // strip's overflow edge.
+ // Upstream #1775 introduced the wrapper refs; this branch keeps them and
+ // adds the shared reveal helper plus the resize/hover paths.
+ assert.match(panelSource, /const tabWrapperRefs = useRef>\(\{\}\)/);
+ assert.match(
+ panelSource,
+ /tabWrapperRefs\.current\[tabId\]\?\.scrollIntoView\(/,
+ );
+ assert.match(panelSource, /tabWrapperRefs\.current\[tab\.id\] = node/);
+ // The strip reserves the close button's width at the inline end as a
+ // structural guarantee against sub-pixel clipping.
+ const strip = globalStyles.match(/\.work-panel-tab-strip \{[^}]*\}/)?.[0] ?? "";
+ assert.match(strip, /scroll-padding-inline:\s*2px 24px;/);
+});
diff --git a/package.json b/package.json
index 2efe64d370..f3e8686a51 100644
--- a/package.json
+++ b/package.json
@@ -66,6 +66,7 @@
"test:e2e:work-panel-reorder": "node scripts/e2e-work-panel-reorder.mjs",
"test:e2e:browser-local-files": "node scripts/e2e-browser-local-file-access.mjs",
"test:e2e:work-panel-drag": "node scripts/e2e-work-panel-drag.mjs",
+ "test:e2e:work-panel-tab-close": "node scripts/e2e-work-panel-tab-close.mjs",
"test:e2e:supervision": "node scripts/e2e-supervision.mjs",
"test:e2e:subagents": "node scripts/e2e-subagents.mjs",
"test:e2e:send-now-subagents": "node scripts/e2e-send-now-subagents.mjs",
diff --git a/scripts/e2e-work-panel-tab-close.mjs b/scripts/e2e-work-panel-tab-close.mjs
new file mode 100644
index 0000000000..14905423ac
--- /dev/null
+++ b/scripts/e2e-work-panel-tab-close.mjs
@@ -0,0 +1,122 @@
+#!/usr/bin/env node
+/**
+ * Renderer-level geometry regression for #1762.
+ *
+ * The maintainer's review on #1769 asked for proof that the active tab's close
+ * control sits inside the strip viewport and receives pointer hits — after a
+ * narrow panel, after a resize that keeps the same active tab, and on hover of
+ * a partially visible inactive tab. Source-contract tests cannot show any of
+ * that, so this runs the real WorkPanel in Electron and measures.
+ *
+ * Cross-platform: DOM geometry + elementFromPoint. Native Win32 hit testing
+ * for drag regions remains in scripts/e2e-work-panel-drag.mjs.
+ */
+import assert from "node:assert/strict";
+import { spawn } from "node:child_process";
+import { createRequire } from "node:module";
+import { mkdtemp, readFile, writeFile, rm } from "node:fs/promises";
+import { tmpdir } from "node:os";
+import { dirname, join } from "node:path";
+import { fileURLToPath } from "node:url";
+import { resolveElectronBinary } from "./e2e/boot.mjs";
+
+const root = join(dirname(fileURLToPath(import.meta.url)), "..");
+const require = createRequire(join(root, "packages/agent-runtime/package.json"));
+const { build } = require("esbuild");
+const { electronBinary } = resolveElectronBinary(root);
+const temp = await mkdtemp(join(tmpdir(), "pi-tab-close-"));
+
+try {
+ const styles = await Promise.all(
+ ["tokens", "base", "chat-shell", "work-panel"].map((name) =>
+ readFile(join(root, `apps/desktop/src/styles/${name}.css`), "utf8"),
+ ),
+ );
+ await writeFile(join(temp, "style.css"), styles.join("\n"));
+
+ await build({
+ entryPoints: [join(root, "scripts/e2e/work-panel-tab-close.tsx")],
+ outfile: join(temp, "renderer.js"),
+ bundle: true,
+ platform: "browser",
+ format: "iife",
+ jsx: "automatic",
+ define: { "process.env.NODE_ENV": '"production"' },
+ loader: { ".css": "empty" },
+ alias: {
+ "@pi-desktop/shared": join(root, "packages/shared/src/index.ts"),
+ "@pi-desktop/i18n": join(root, "packages/i18n/src/index.ts"),
+ react: join(root, "apps/desktop/node_modules/react"),
+ "react-dom": join(root, "apps/desktop/node_modules/react-dom"),
+ i18next: join(root, "apps/desktop/node_modules/i18next"),
+ "react-i18next": join(root, "apps/desktop/node_modules/react-i18next"),
+ },
+ nodePaths: [join(root, "apps/desktop/node_modules")],
+ });
+
+ await writeFile(
+ join(temp, "index.html"),
+ 'PI Tab Close Regression ',
+ );
+
+ await writeFile(
+ join(temp, "main.cjs"),
+ `
+const { app, BrowserWindow } = require("electron");
+const path = require("node:path");
+app.setPath("userData", path.join(__dirname, "profile"));
+app.whenReady().then(async () => {
+ const win = new BrowserWindow({ show: false, width: 1600, height: 700,
+ webPreferences: { sandbox: true, contextIsolation: true, nodeIntegration: false, backgroundThrottling: false } });
+ win.webContents.on("console-message", (event) => console.error(event.message));
+ try {
+ await win.loadFile(path.join(__dirname, "index.html"));
+ for (const stage of ["narrow-active", "resize-same-tab", "hover-inactive"]) {
+ const result = await win.webContents.executeJavaScript(
+ "window.tabCloseProbe(" + JSON.stringify(stage) + ")");
+ console.log("TAB_CLOSE " + JSON.stringify(result));
+ }
+ app.exit(0);
+ } catch (error) { console.error(error); app.exit(1); }
+});
+`,
+ );
+
+ const child = spawn(electronBinary, [join(temp, "main.cjs")], {
+ stdio: ["ignore", "pipe", "pipe"],
+ });
+ let stdout = "";
+ let stderr = "";
+ child.stdout.on("data", (chunk) => (stdout += chunk));
+ child.stderr.on("data", (chunk) => (stderr += chunk));
+ const code = await new Promise((resolve) => child.on("exit", resolve));
+ if (code !== 0) {
+ console.error(stderr);
+ assert.fail("electron probe failed with exit code " + code);
+ }
+
+ const results = stdout
+ .split("\n")
+ .filter((line) => line.startsWith("TAB_CLOSE "))
+ .map((line) => JSON.parse(line.slice("TAB_CLOSE ".length)));
+ assert.equal(results.length, 3, "expected three probe stages");
+
+ for (const result of results) {
+ console.log(
+ `${result.stage}: strip [${result.stripLeft.toFixed(1)}, ${result.stripRight.toFixed(1)}] ` +
+ `close [${result.closeLeft.toFixed(1)}, ${result.closeRight.toFixed(1)}] ` +
+ `inside=${result.insideStrip} hit=${result.hitIsClose || result.hitIsDescendant}`,
+ );
+ assert.ok(
+ result.insideStrip,
+ `${result.stage}: close control escapes the strip viewport`,
+ );
+ assert.ok(
+ result.hitIsClose || result.hitIsDescendant,
+ `${result.stage}: close control is not the pointer hit target`,
+ );
+ }
+ console.log("tab close geometry: PASS");
+} finally {
+ await rm(temp, { recursive: true, force: true });
+}
diff --git a/scripts/e2e/work-panel-tab-close.tsx b/scripts/e2e/work-panel-tab-close.tsx
new file mode 100644
index 0000000000..5abf5b3840
--- /dev/null
+++ b/scripts/e2e/work-panel-tab-close.tsx
@@ -0,0 +1,217 @@
+import { createRoot } from "react-dom/client";
+import { flushSync } from "react-dom";
+import { createInstance } from "i18next";
+import { I18nextProvider } from "react-i18next";
+import { catalogs } from "@pi-desktop/i18n";
+import { WorkPanel } from "../../apps/desktop/src/components/workpanel/WorkPanel";
+import { useAppStore } from "../../apps/desktop/src/stores/app-store";
+
+/*
+ Renderer-level regression for #1762: the active tab's close control must sit
+ inside the tab strip's viewport and be the element the pointer would hit,
+ after a narrow panel and after a resize that keeps the same active tab.
+
+ Source assertions cannot prove this — the maintainer asked for actual
+ geometry and hit target, and DOM geometry plus `elementFromPoint` is what
+ this environment can honestly measure. Native Win32 hit testing stays in
+ scripts/e2e-work-panel-drag.mjs for the drag regions.
+*/
+
+type CloseGeometry = {
+ stage: string;
+ tabId: string;
+ stripLeft: number;
+ stripRight: number;
+ closeLeft: number;
+ closeRight: number;
+ insideStrip: boolean;
+ hitIsClose: boolean;
+ hitIsDescendant: boolean;
+};
+declare global {
+ var tabCloseProbe: (stage: string) => Promise;
+}
+
+const assert = (condition: unknown, message: string) => {
+ if (!condition) throw new Error(message);
+};
+
+const host = document.createElement("div");
+host.style.cssText = "position:absolute;left:0;top:0;height:600px;display:flex";
+document.body.append(host);
+const root = createRoot(host);
+const i18n = createInstance();
+const ready = i18n.init({
+ lng: "en",
+ resources: { en: { translation: catalogs.en } },
+ interpolation: { escapeValue: false },
+});
+
+function element(selector: string): HTMLElement {
+ const found = host.querySelector(selector);
+ if (!found) throw new Error("Missing " + selector);
+ return found;
+}
+
+async function rendered() {
+ await Promise.all(document.getAnimations().map((a) => a.finished));
+ await new Promise((resolve) =>
+ requestAnimationFrame(() => requestAnimationFrame(() => resolve())),
+ );
+}
+
+function renderPanel(containerWidth: number) {
+ // The panel's own width comes from the store; `containerWidth` is the shell
+ // budget. Resize the host so the strip's box actually changes.
+ host.style.width = `${containerWidth}px`;
+ flushSync(() => {
+ useAppStore.setState({
+ activeSessionId: "tab-close-a",
+ workPanelWidth: Math.min(300, Math.max(244, containerWidth - 40)),
+ pluginViews: [],
+ });
+ root.render(
+
+
+ ,
+ );
+ });
+}
+
+function click(selector: string) {
+ flushSync(() => element(selector).click());
+}
+
+/** Long labels are what pushes the close control past the overflow edge. */
+function openManyLongTabs(count: number) {
+ for (let i = 0; i < count; i += 1) click(".work-panel-new-tab");
+}
+
+function activeTabId(): string {
+ const id = useAppStore.getState().activeWorkPanelTabId;
+ assert(id, "no active tab");
+ return id!;
+}
+
+function measure(stage: string): CloseGeometry {
+ const strip = element(".work-panel-tab-strip");
+ const stripRect = strip.getBoundingClientRect();
+ const tabId = activeTabId();
+ const wrapper = host.querySelector(
+ `[data-work-panel-tab-id="${CSS.escape(tabId)}"]`,
+ );
+ assert(wrapper, "active tab wrapper missing");
+ const close = wrapper!.querySelector(".work-panel-tab-close");
+ assert(close, "active tab close control missing");
+ const closeRect = close!.getBoundingClientRect();
+
+ const centerX = closeRect.x + closeRect.width / 2;
+ const centerY = closeRect.y + closeRect.height / 2;
+ const hit = document.elementFromPoint(centerX, centerY);
+
+ return {
+ stage,
+ tabId,
+ stripLeft: stripRect.left,
+ stripRight: stripRect.right,
+ closeLeft: closeRect.left,
+ closeRight: closeRect.right,
+ // The control must be fully inside the strip's client box. A sub-pixel
+ // tolerance keeps a fractional device pixel ratio from failing the probe.
+ insideStrip:
+ closeRect.left >= stripRect.left - 0.5 && closeRect.right <= stripRect.right + 0.5,
+ hitIsClose: hit === close,
+ hitIsDescendant: !!hit && (close!.contains(hit) || hit.contains(close!)),
+ };
+}
+
+globalThis.tabCloseProbe = async (stage) => {
+ await ready;
+
+ if (stage === "narrow-active") {
+ renderPanel(900);
+ openManyLongTabs(10);
+ await rendered();
+ const strip = element(".work-panel-tab-strip");
+ assert(strip.scrollWidth > strip.clientWidth, "tabs did not overflow the strip");
+ return measure(stage);
+ }
+
+ if (stage === "resize-same-tab") {
+ // Render wide first so every tab fits, then narrow the panel without
+ // changing `activeTabId` or `tabs.length` — the exact case the maintainer
+ // flagged: the reveal effect's dependencies do not change.
+ renderPanel(1400);
+ openManyLongTabs(10);
+ await rendered();
+ const before = measure("before-resize");
+ assert(before.insideStrip, "fixture invalid: close control clipped before the resize");
+
+ // Narrow enough to clip the strip but wide enough that the panel is not
+ // auto-collapsed: MAIN_PANE_MIN_WIDTH is 450 and the panel floor is 244.
+ renderPanel(760);
+ await rendered();
+ const after = measure(stage);
+ return after;
+ }
+
+ if (stage === "hover-inactive") {
+ // Wide enough for a real panel: 560 leaves the panel squeezed to a sliver
+ // because MAIN_PANE_MIN_WIDTH (450) eats the budget.
+ renderPanel(1000);
+ openManyLongTabs(10);
+ await rendered();
+ // Park the strip mid-list so a tab is clipped by the inline-end edge while
+ // the active tab is elsewhere. That is the state the issue describes: a
+ // partly visible inactive tab whose close control appears on hover.
+ const stripEl = element(".work-panel-tab-strip");
+ stripEl.scrollLeft = Math.floor((stripEl.scrollWidth - stripEl.clientWidth) / 2);
+ await rendered();
+ const stripRect0 = stripEl.getBoundingClientRect();
+ const all = [...host.querySelectorAll(".work-panel-tab")];
+ // Pick the inactive tab nearest the inline-end edge that is still partly
+ // inside: its close control is the one at risk of being clipped.
+ const candidate = all
+ .filter((node) => node.dataset.workPanelTabId !== activeTabId())
+ .filter((node) => {
+ const r = node.getBoundingClientRect();
+ return r.right > stripRect0.left && r.left < stripRect0.right;
+ })
+ .sort((a, b) => b.getBoundingClientRect().left - a.getBoundingClientRect().left)[0];
+ assert(candidate, "no partly visible inactive tab to hover");
+ const first = candidate!;
+ const firstId = first.dataset.workPanelTabId;
+ assert(firstId && firstId !== activeTabId(), "fixture invalid: hovered tab is active");
+ // React delegates from the root, and `pointerenter` does not bubble, so a
+ // synthetic dispatch never reaches the handler. `pointerover` bubbles and
+ // is what the platform sends on entering an element.
+ flushSync(() => {
+ first!.dispatchEvent(
+ new PointerEvent("pointerover", { bubbles: true, cancelable: true }),
+ );
+ });
+ await rendered();
+ const strip = element(".work-panel-tab-strip");
+ const stripRect = strip.getBoundingClientRect();
+ const close = first!.querySelector(".work-panel-tab-close");
+ assert(close, "hovered tab has no close control");
+ const rect = close!.getBoundingClientRect();
+ const hit = document.elementFromPoint(
+ rect.x + rect.width / 2,
+ rect.y + rect.height / 2,
+ );
+ return {
+ stage,
+ tabId: firstId!,
+ stripLeft: stripRect.left,
+ stripRight: stripRect.right,
+ closeLeft: rect.left,
+ closeRight: rect.right,
+ insideStrip: rect.left >= stripRect.left - 0.5 && rect.right <= stripRect.right + 0.5,
+ hitIsClose: hit === close,
+ hitIsDescendant: !!hit && (close!.contains(hit) || hit.contains(close!)),
+ };
+ }
+
+ throw new Error("Unknown tab-close probe stage: " + stage);
+};
From 99bd282a41911e01a3e599c19869a4e43a5487da Mon Sep 17 00:00:00 2001
From: muzimu217
Date: Tue, 20 Oct 2026 04:11:46 -0700
Subject: [PATCH 07/44] fix(mcp): fail loudly when a server has no DCR endpoint
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
#1782: when discovery returns no registration endpoint, the login flow fell
back to a literal client id:
} else {
clientId = "pi-desktop";
}
No authorization server has ever registered that id, so the app opened
`?client_id=pi-desktop` and the user landed on a bare 404 — with
no explanation and no way forward. It is not a GitHub-specific failure: any
OAuth MCP server without Dynamic Client Registration is affected.
Throw before opening anything, naming what is missing and the two real ways
out. A settings field for a client id does not exist yet, so the message does
not promise one.
The test drives the real startLogin through a mocked discovery that omits
registration_endpoint, and asserts both the message and that openExternal was
never called. Verified against the old code: the test does not merely fail,
it hangs until the 300s timeout, because the previous flow waited for a
callback that could never arrive — the same experience the report describes.
Verification: mcp-oauth.test.mjs 20/20, mcp-oauth-discovery.test.mjs pass,
tsc --noEmit clean.
---
apps/desktop/electron/main/mcp-oauth.ts | 13 +++++++-
apps/desktop/test/mcp-oauth.test.mjs | 40 ++++++++++++++++++++++++-
2 files changed, 51 insertions(+), 2 deletions(-)
diff --git a/apps/desktop/electron/main/mcp-oauth.ts b/apps/desktop/electron/main/mcp-oauth.ts
index 4b702213c9..099df47cac 100644
--- a/apps/desktop/electron/main/mcp-oauth.ts
+++ b/apps/desktop/electron/main/mcp-oauth.ts
@@ -677,7 +677,18 @@ export class McpOAuthManager {
clientSecret = registered.clientSecret;
redirectUrisToStore = registered.redirectUris;
} else {
- clientId = "pi-desktop";
+ // #1782: no Dynamic Client Registration endpoint means this
+ // server expects a pre-registered client id, and the app has
+ // none to give. The previous fallback opened the authorize URL
+ // with a literal `client_id=pi-desktop`, which no authorization
+ // server ever registered — the browser landed on a bare 404 and
+ // the user was left with no way forward and no explanation.
+ // Fail here, before opening anything, saying what is missing.
+ // The message must not promise a settings field that does not
+ // exist yet: it names the two real ways forward.
+ throw new Error(
+ `MCP server "${session.serverId}" does not support Dynamic Client Registration, and PI-Desktop has no client id registered with ${metadata.authorizationEndpoint}. Ask the server operator for a client id, or use a server that supports DCR.`,
+ );
}
const authUrl = new URL(metadata.authorizationEndpoint);
diff --git a/apps/desktop/test/mcp-oauth.test.mjs b/apps/desktop/test/mcp-oauth.test.mjs
index a7446670bf..2465f4ac2e 100644
--- a/apps/desktop/test/mcp-oauth.test.mjs
+++ b/apps/desktop/test/mcp-oauth.test.mjs
@@ -90,11 +90,16 @@ function createMockFetch(options = {}) {
}
if (url.pathname === "/.well-known/oauth-authorization-server") {
+ // A server that expects a pre-registered client advertises no
+ // registration endpoint (#1782).
+ const registration = options.withoutRegistration
+ ? {}
+ : { registration_endpoint: "https://notion.test/register" };
return new Response(JSON.stringify({
issuer: "https://notion.test",
authorization_endpoint: "https://notion.test/authorize",
token_endpoint: "https://notion.test/token",
- registration_endpoint: "https://notion.test/register",
+ ...registration,
code_challenge_methods_supported: ["S256"],
response_types_supported: ["code"],
}), {
@@ -984,3 +989,36 @@ test("McpOAuthManager: onAuthorized receives the server record", async (t) => {
assert.equal(authorized.serverId, record.id);
assert.equal(authorized.record, record);
});
+
+test("McpOAuthManager: a server without DCR fails loudly instead of opening a dead client_id (#1782)", async (t) => {
+ const host = fakeHost();
+ const { mockFetch } = createMockFetch({ withoutRegistration: true });
+ const { mockCreateServer } = createMockServerFactory();
+ const opened = [];
+ const manager = new McpOAuthManager({
+ call: host.call,
+ fetchImpl: mockFetch,
+ openExternal: async (url) => {
+ opened.push(url);
+ },
+ createServer: mockCreateServer,
+ emit: () => {},
+ });
+ t.after(() => manager.disposeAll());
+
+ await assert.rejects(
+ () => manager.startLogin("no-dcr-test", "https://notion.test/mcp"),
+ (error) => {
+ // The message has to name the missing capability and both real ways
+ // forward; a bare "failed" leaves the user where the 404 did.
+ assert.match(error.message, /Dynamic Client Registration/);
+ assert.match(error.message, /client id/);
+ assert.match(error.message, /https:\/\/notion\.test\/authorize/);
+ return true;
+ },
+ );
+
+ // The whole point: no browser tab, so no dead authorization page. Before
+ // this change the app opened `?client_id=pi-desktop` and the user saw a 404.
+ assert.deepEqual(opened, [], "no authorization URL may be opened without a usable client id");
+});
From 5aa66e2c85f4cffeb82af06bb44ab8baf5d2ce01 Mon Sep 17 00:00:00 2001
From: blackEvil217 <1278844978@qq.com>
Date: Fri, 16 Oct 2026 09:05:03 -0700
Subject: [PATCH 08/44] fix(settings): keep the last successful market list
when a query fails
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
A failed catalog query used to drop the list back to built-in picks,
discarding what the user was just looking at (issue #1692 follow-up).
Both markets now keep the last successful result for the same query on
screen — under the failure with a timestamped note, and during the
retry that follows — until a retry succeeds or the query changes.
The snapshot never answers a different query, an empty successful
answer is not a failure to cover, and Load more refreshes it.
---
.../components/settings/McpMarketPanel.tsx | 68 +++++-
.../components/settings/SkillMarketPanel.tsx | 66 +++++-
apps/desktop/src/lib/market-snapshot.ts | 49 ++++
apps/desktop/src/styles/settings.css | 8 +
apps/desktop/test/mcp-market-panel.test.mjs | 17 ++
apps/desktop/test/skill-market-panel.test.mjs | 22 ++
docs/spec/04-ux/06-settings-ia.md | 9 +-
docs/spec/06-delivery/04-e2e-test-plan.md | 15 +-
docs/zh-CN/spec/04-ux/06-settings-ia.md | 4 +-
.../spec/06-delivery/04-e2e-test-plan.md | 6 +-
packages/i18n/src/locales/de/index.ts | 2 +
packages/i18n/src/locales/en/index.ts | 2 +
packages/i18n/src/locales/es/index.ts | 2 +
packages/i18n/src/locales/fr/index.ts | 2 +
packages/i18n/src/locales/ko/index.ts | 2 +
packages/i18n/src/locales/pt-BR/index.ts | 4 +-
packages/i18n/src/locales/tr/index.ts | 2 +
packages/i18n/src/locales/zh-CN/index.ts | 2 +
packages/i18n/src/locales/zh-TW/index.ts | 2 +
scripts/e2e-market-retry.mjs | 42 +++-
scripts/e2e/market-retry.tsx | 222 +++++++++++++++---
21 files changed, 487 insertions(+), 61 deletions(-)
create mode 100644 apps/desktop/src/lib/market-snapshot.ts
diff --git a/apps/desktop/src/components/settings/McpMarketPanel.tsx b/apps/desktop/src/components/settings/McpMarketPanel.tsx
index e9be68bcfe..71c6953511 100644
--- a/apps/desktop/src/components/settings/McpMarketPanel.tsx
+++ b/apps/desktop/src/components/settings/McpMarketPanel.tsx
@@ -30,6 +30,11 @@ import {
IconX,
} from "../icons";
import { Field, Input, TooltipButton, cx } from "../ui";
+import {
+ snapshotMatchesQuery,
+ snapshotTimeText,
+ type MarketSnapshot,
+} from "../../lib/market-snapshot";
const CATEGORIES: readonly McpCatalogCategory[] = [
"devtools",
@@ -105,7 +110,7 @@ export function McpMarketPanel({
onBack: () => void;
onInstalled: (id: string) => void;
}) {
- const { t } = useTranslation();
+ const { t, i18n } = useTranslation();
const showToast = useAppStore((state) => state.showToast);
const [search, setSearch] = useState("");
const [category, setCategory] = useState<"all" | McpCatalogCategory>("all");
@@ -116,6 +121,13 @@ export function McpMarketPanel({
const [saving, setSaving] = useState(false);
const [remote, setRemote] = useState(REMOTE_IDLE);
const [catalogRetry, setCatalogRetry] = useState(0);
+ /**
+ * The last successful search for this panel, kept so a later failure can
+ * still show the list the user just had (issue #1692) instead of dropping
+ * to built-in picks only. It answers one query only: a snapshot taken for
+ * a different search must not stand in for the one on screen.
+ */
+ const [snapshot, setSnapshot] = useState | null>(null);
const [sources, setSources] = useState(loadSources);
// Whether a plaintext hop to a user-supplied source is allowed, from the
// stored `networkPolicy`. The panel validates its persisted list with the same
@@ -170,6 +182,12 @@ export function McpMarketPanel({
exhausted: result.exhausted ?? true,
loadingMore: false,
});
+ // The list the user was just shown is what a later failure falls
+ // back to. An empty answer is not a list, and keeping it would pin
+ // the pane to a stale snapshot after one success.
+ if (entries.length > 0) {
+ setSnapshot({ entries, at: Date.now(), query: search.trim() });
+ }
})
.catch(() => {
if (!cancelled && generation === requestGeneration.current) {
@@ -204,6 +222,9 @@ export function McpMarketPanel({
exhausted: result.exhausted ?? true,
loadingMore: false,
});
+ if (entries.length > 0) {
+ setSnapshot({ entries, at: Date.now(), query: query.trim() });
+ }
} catch {
if (generation === requestGeneration.current) {
setRemote((current) => ({ ...current, loadingMore: false }));
@@ -220,6 +241,19 @@ export function McpMarketPanel({
[remote.entries],
);
+ /**
+ * The last successful list stands in only while the current query has
+ * nothing of its own to show — a failure, or the retry that follows one.
+ * A snapshot taken for another query never answers this one, and a `ready`
+ * result with no entries is a real (empty) answer, not a failure to cover.
+ */
+ const snapshotForQuery = snapshotMatchesQuery(snapshot, search) ? snapshot : null;
+ const showingSnapshot =
+ snapshotForQuery != null &&
+ remote.entries.length === 0 &&
+ (remote.status === "error" || remote.status === "loading");
+ const displayEntries = showingSnapshot && snapshotForQuery ? snapshotForQuery.entries : remote.entries;
+
const visible = useMemo(() => {
const query = search.trim().toLocaleLowerCase();
const matches = (entry: McpCatalogEntry) => {
@@ -231,9 +265,9 @@ export function McpMarketPanel({
};
return mergeRegistryEntries(
servers.filter(matches),
- remote.entries.filter(matches),
+ displayEntries.filter(matches),
) as MarketItem[];
- }, [remote.entries, search, category]);
+ }, [displayEntries, search, category]);
const totalPages = Math.max(1, Math.ceil(visible.length / PAGE_SIZE));
const currentPage = Math.min(page, totalPages);
@@ -590,9 +624,21 @@ export function McpMarketPanel({
{remote.status === "loading" ? (
-
- {t("settings.mcpMarket.remoteLoading")}
-
+ <>
+
+ {t("settings.mcpMarket.remoteLoading")}
+
+ {showingSnapshot && snapshotForQuery ? (
+
+ {t("settings.mcpMarket.remoteStaleSnapshot", {
+ time: snapshotTimeText(
+ snapshotForQuery.at,
+ i18n.resolvedLanguage ?? i18n.language,
+ ),
+ })}
+
+ ) : null}
+ >
) : null}
{remote.status === "error" ? (
<>
@@ -600,6 +646,16 @@ export function McpMarketPanel({
{t("settings.mcpMarket.remoteError")}
{remote.failed.length ? ` (${remote.failed.join(", ")})` : ""}
+ {showingSnapshot && snapshotForQuery ? (
+
+ {t("settings.mcpMarket.remoteStaleSnapshot", {
+ time: snapshotTimeText(
+ snapshotForQuery.at,
+ i18n.resolvedLanguage ?? i18n.language,
+ ),
+ })}
+
+ ) : null}
{t("settings.mcpMarket.retry")}
diff --git a/apps/desktop/src/components/settings/SkillMarketPanel.tsx b/apps/desktop/src/components/settings/SkillMarketPanel.tsx
index a2059fd852..699a2ebadb 100644
--- a/apps/desktop/src/components/settings/SkillMarketPanel.tsx
+++ b/apps/desktop/src/components/settings/SkillMarketPanel.tsx
@@ -36,6 +36,11 @@ import {
skillMarketFailureDetail,
type SkillMarketFailureKind,
} from "../../lib/skill-market-failure";
+import {
+ snapshotMatchesQuery,
+ snapshotTimeText,
+ type MarketSnapshot,
+} from "../../lib/market-snapshot";
const CATEGORIES: readonly SkillCatalogCategory[] = [
"workflow",
@@ -151,7 +156,7 @@ export function SkillMarketPanel({
onBack: () => void;
onInstalled: (id: string) => void;
}) {
- const { t } = useTranslation();
+ const { t, i18n } = useTranslation();
const showToast = useAppStore((state) => state.showToast);
const [search, setSearch] = useState("");
const [category, setCategory] = useState<"all" | SkillCatalogCategory>("all");
@@ -178,6 +183,13 @@ export function SkillMarketPanel({
});
const [remote, setRemote] = useState(REMOTE_IDLE);
const [catalogRetry, setCatalogRetry] = useState(0);
+ /**
+ * The last successful search for this panel, kept so a later failure can
+ * still show the list the user just had (issue #1692) instead of dropping
+ * to built-in picks only. It answers one query only: a snapshot taken for
+ * a different search must not stand in for the one on screen.
+ */
+ const [snapshot, setSnapshot] = useState | null>(null);
useEffect(() => {
let cancelled = false;
@@ -217,6 +229,7 @@ export function SkillMarketPanel({
if (!cancelled) {
const failed = result.failedSources ?? [];
const entries = result.entries ?? [];
+ const query = search.trim();
setRemote({
status: entries.length === 0 && failed.length > 0 ? "error" : "ready",
entries,
@@ -225,6 +238,12 @@ export function SkillMarketPanel({
failureDetails: result.failureDetails ?? {},
queryError: "",
});
+ // The list the user was just shown is what a later failure falls
+ // back to. A response with no entries is not a list, and keeping
+ // it would pin the pane to a stale snapshot after one success.
+ if (entries.length > 0) {
+ setSnapshot({ entries, at: Date.now(), query });
+ }
}
})
.catch((error: unknown) => {
@@ -251,6 +270,19 @@ export function SkillMarketPanel({
? [...DEFAULT_SKILL_SOURCES, ...sources].find((source) => source.id === id)?.name
: undefined;
+ /**
+ * The last successful list stands in only while the current query has
+ * nothing of its own to show — a failure, or the retry that follows one.
+ * A snapshot taken for another query never answers this one, and a `ready`
+ * result with no entries is a real (empty) answer, not a failure to cover.
+ */
+ const snapshotForQuery = snapshotMatchesQuery(snapshot, search) ? snapshot : null;
+ const showingSnapshot =
+ snapshotForQuery != null &&
+ remote.entries.length === 0 &&
+ (remote.status === "error" || remote.status === "loading");
+ const displayEntries = showingSnapshot && snapshotForQuery ? snapshotForQuery.entries : remote.entries;
+
const visible = useMemo(() => {
const query = search.trim().toLocaleLowerCase();
const matches = (entry: SkillCatalogEntry) => {
@@ -262,9 +294,9 @@ export function SkillMarketPanel({
};
return mergeSkillEntries(
skills.filter(matches),
- remote.entries.filter(matches),
+ displayEntries.filter(matches),
) as MarketItem[];
- }, [remote.entries, search, category]);
+ }, [displayEntries, search, category]);
const totalPages = Math.max(1, Math.ceil(visible.length / PAGE_SIZE));
const currentPage = Math.min(page, totalPages);
@@ -658,15 +690,37 @@ export function SkillMarketPanel({
{remote.status === "loading" ? (
-
- {t("settings.sklm.remoteLoading")}
-
+ <>
+
+ {t("settings.sklm.remoteLoading")}
+
+ {showingSnapshot && snapshotForQuery ? (
+
+ {t("settings.sklm.remoteStaleSnapshot", {
+ time: snapshotTimeText(
+ snapshotForQuery.at,
+ i18n.resolvedLanguage ?? i18n.language,
+ ),
+ })}
+
+ ) : null}
+ >
) : null}
{remote.status === "error" ? (
<>
{remoteErrorText()}
+ {showingSnapshot && snapshotForQuery ? (
+
+ {t("settings.sklm.remoteStaleSnapshot", {
+ time: snapshotTimeText(
+ snapshotForQuery.at,
+ i18n.resolvedLanguage ?? i18n.language,
+ ),
+ })}
+
+ ) : null}
{remote.failed.length ? (
{failedSourceLabels().join(", ")}
) : null}
diff --git a/apps/desktop/src/lib/market-snapshot.ts b/apps/desktop/src/lib/market-snapshot.ts
new file mode 100644
index 0000000000..e67fb3533b
--- /dev/null
+++ b/apps/desktop/src/lib/market-snapshot.ts
@@ -0,0 +1,49 @@
+/**
+ * The last successful market result, kept so a later source failure can show
+ * the list the user last saw instead of an empty pane (issue #1692). Both the
+ * skill market and the MCP market keep one of these.
+ */
+export type MarketSnapshot = {
+ entries: T[];
+ /** Epoch ms of the successful response, for the timestamp line. */
+ at: number;
+ /** The search text the snapshot was taken for; a stale snapshot must not
+ * answer a different query. */
+ query: string;
+};
+
+/** Whether a snapshot still describes the query currently on screen. */
+export function snapshotMatchesQuery(
+ snapshot: MarketSnapshot | null | undefined,
+ query: string,
+): boolean {
+ if (snapshot == null) return false;
+ // The main process filters case-insensitively, so the query identity that
+ // matters is the trimmed, lowercased one.
+ return snapshot.query.trim().toLocaleLowerCase() === query.trim().toLocaleLowerCase();
+}
+
+/**
+ * Localized time for the snapshot line: clock time for today's snapshot, a
+ * dated form otherwise, so "19:52" is never mistaken for today when the app
+ * sat open overnight. Mirrors `formatMessageTime` in the transcript.
+ */
+export function snapshotTimeText(at: number, locale: string): string {
+ const date = new Date(at);
+ if (Number.isNaN(date.getTime())) return "";
+ const now = new Date();
+ const isToday =
+ date.getFullYear() === now.getFullYear() &&
+ date.getMonth() === now.getMonth() &&
+ date.getDate() === now.getDate();
+ if (isToday) {
+ return date.toLocaleTimeString(locale, { hour: "2-digit", minute: "2-digit" });
+ }
+ return date.toLocaleString(locale, {
+ year: "numeric",
+ month: "2-digit",
+ day: "2-digit",
+ hour: "2-digit",
+ minute: "2-digit",
+ });
+}
diff --git a/apps/desktop/src/styles/settings.css b/apps/desktop/src/styles/settings.css
index 0787181d1e..e60f68a90d 100644
--- a/apps/desktop/src/styles/settings.css
+++ b/apps/desktop/src/styles/settings.css
@@ -3585,6 +3585,10 @@
color: var(--ds-warning);
}
+.mcpm-status.is-snapshot {
+ color: var(--ds-text-secondary);
+}
+
.mcpm-badge.is-remote {
background: color-mix(in oklab, var(--ds-accent) 10%, transparent);
color: var(--ds-text-muted);
@@ -4098,6 +4102,10 @@
color: var(--ds-warning);
}
+.sklm-status.is-snapshot {
+ color: var(--ds-text-secondary);
+}
+
.sklm-badge.is-remote {
background: color-mix(in oklab, var(--ds-accent) 10%, transparent);
color: var(--ds-text-muted);
diff --git a/apps/desktop/test/mcp-market-panel.test.mjs b/apps/desktop/test/mcp-market-panel.test.mjs
index 2ae6133191..50d966b011 100644
--- a/apps/desktop/test/mcp-market-panel.test.mjs
+++ b/apps/desktop/test/mcp-market-panel.test.mjs
@@ -37,6 +37,23 @@ test("failed and partial MCP catalog searches can be retried", () => {
assert.match(panel, /remote\.status === "ready" && remote\.failed\.length/);
});
+test("a failed query keeps the last successful list with its timestamp", () => {
+ // Issue #1692 follow-up, MCP side: the last successful registry answer stays
+ // on screen when a later query fails, with the time it was taken.
+ assert.match(panel, /useState \| null>\(null\)/);
+ assert.match(panel, /snapshotMatchesQuery\(snapshot, search\)/);
+ assert.match(panel, /setSnapshot\(\{ entries, at: Date\.now\(\), query: query\.trim\(\) \}\)/);
+ assert.match(
+ panel,
+ /const showingSnapshot =\s*\n\s*snapshotForQuery != null &&\s*\n\s*remote\.entries\.length === 0 &&\s*\n\s*\(remote\.status === "error" \|\| remote\.status === "loading"\)/,
+ );
+ assert.match(panel, /displayEntries\.filter\(matches\)/);
+ assert.match(panel, /settings\.mcpMarket\.remoteStaleSnapshot/);
+ // Pagination beyond the first page also refreshes the snapshot: the entries
+ // on screen after Load more are what a later failure should keep.
+ assert.match(panel, /if \(entries\.length > 0\) \{\s*\n\s*setSnapshot\(/);
+});
+
test("installed state comes from matching server ids", () => {
assert.match(panel, /installedIds\.includes\(entry\.id\)/);
assert.match(page, /installedIds=\{\[\.\.\.globalServers, \.\.\.projectServers\]/);
diff --git a/apps/desktop/test/skill-market-panel.test.mjs b/apps/desktop/test/skill-market-panel.test.mjs
index da04e40371..d85ab7719f 100644
--- a/apps/desktop/test/skill-market-panel.test.mjs
+++ b/apps/desktop/test/skill-market-panel.test.mjs
@@ -120,6 +120,27 @@ test("failed and partial skill catalog searches can be retried", () => {
assert.match(panel, /setRemote\(\(current\) => \(\{ \.\.\.current, status: "loading" \}\)\)/);
});
+test("a failed query keeps the last successful list with its timestamp", () => {
+ // Issue #1692 follow-up: a source failure used to drop the whole list back to
+ // built-in picks, discarding what the user was just looking at. The panel now
+ // keeps the last successful result and says when it was taken.
+ assert.match(panel, /useState \| null>\(null\)/);
+ assert.match(panel, /snapshotMatchesQuery\(snapshot, search\)/);
+ assert.match(panel, /setSnapshot\(\{ entries, at: Date\.now\(\), query \}\)/);
+ // The fallback list answers the current query only, and only while the
+ // query itself has nothing to show — an empty `ready` answer is real.
+ assert.match(
+ panel,
+ /const showingSnapshot =\s*\n\s*snapshotForQuery != null &&\s*\n\s*remote\.entries\.length === 0 &&\s*\n\s*\(remote\.status === "error" \|\| remote\.status === "loading"\)/,
+ );
+ assert.match(panel, /displayEntries\.filter\(matches\)/);
+ assert.match(panel, /settings\.sklm\.remoteStaleSnapshot/);
+ assert.match(panel, /snapshotTimeText\(\s*\n?\s*snapshotForQuery\.at/);
+ // An empty response must not overwrite the snapshot: that would pin the
+ // pane to an empty list after one successful-but-empty query.
+ assert.match(panel, /if \(entries\.length > 0\) \{\s*\n\s*setSnapshot\(/);
+});
+
test("a resolver with no answer is explained as that, not as an address check", () => {
// Issue #419, second round: one `policy` bucket meant a local resolver that
// answered nothing produced the same sentence as an address the guard had
@@ -198,6 +219,7 @@ test("every shipped locale carries the new skill market strings", async () => {
"remoteErrorQuery",
"remotePartial",
"failureSourceHost",
+ "remoteStaleSnapshot",
];
for (const id of ids) {
const locale = await readFile(
diff --git a/docs/spec/04-ux/06-settings-ia.md b/docs/spec/04-ux/06-settings-ia.md
index 3b3126aa4b..a06c95fc1c 100644
--- a/docs/spec/04-ux/06-settings-ia.md
+++ b/docs/spec/04-ux/06-settings-ia.md
@@ -707,7 +707,10 @@ system while preserving their different data ownership:
user sees that refusal while the same URL opens in their browser (ADR 0177).
A failed catalog query offers Retry; the same action remains available when
only some sources failed. It repeats the current search over the configured
- sources and announces loading while the request runs.
+ sources and announces loading while the request runs. After a successful
+ load, a later failure keeps that list on screen with the time it was taken
+ and still offers Retry; the retained list never answers a different query,
+ and it disappears once a retry succeeds.
Back reloads the skill list.
- Skills also exposes **Scan other tools** in its toolbar. The explicit scan
opens inline on the Skills page, and imported entries follow the current
@@ -719,7 +722,9 @@ system while preserving their different data ownership:
shown in candidate rows.
- MCP Market offers Retry after a failed query or partial source failure. It
repeats the current search through the existing market request path and
- announces loading while the request runs.
+ announces loading while the request runs. After a successful load, a later
+ failure keeps that list on screen with the time it was taken and still
+ offers Retry.
- The Subagents create/edit sheet pins a model with a searchable, provider-
grouped anchored menu — the same option-menu control the service picker uses
— over the configured, runnable models the Composer offers, plus an
diff --git a/docs/spec/06-delivery/04-e2e-test-plan.md b/docs/spec/06-delivery/04-e2e-test-plan.md
index 5b00986fae..a0176f14cb 100644
--- a/docs/spec/06-delivery/04-e2e-test-plan.md
+++ b/docs/spec/06-delivery/04-e2e-test-plan.md
@@ -16584,14 +16584,21 @@ plugin-form fixtures in an isolated temporary directory at runtime.
- **Preconditions**: Rendered Skill Market and MCP Market panels with the
market APIs stubbed at the IPC boundary. Each API returns a total failure,
- then a result with one failed source, then a complete result.
+ then a result with one failed source, then a complete result. A second run
+ loads a result first, fails afterwards, and recovers on retry; a third run
+ changes the query after a success so the failure carries a snapshot taken
+ for another query; a fourth run fails with nothing loaded.
- **Steps**: Open each market; click Retry after the total failure; confirm the
loading announcement and recovered entry; click Retry again after the
- partial failure.
+ partial failure. Then load a list, fail the next query, retry, and change
+ the query before failing once more.
- **Expected**: Both markets repeat the current search, show loading while the
request runs, retain a Retry action for partial failures, and clear the failed
- source after recovery. The test makes no live network request and does not
- change the main-process network policy.
+ source after recovery. After a successful load, a later failure keeps that
+ list on screen, says when it was taken, and still offers Retry; the retained
+ list disappears once a retry succeeds, and it never stands in for a
+ different query or for a failure with nothing loaded. The test makes no live
+ network request and does not change the main-process network policy.
- **Specs linked**: `04-ux/06-settings-ia.md`, ADR 0177, ADR 0272
- **Acceptance**: Quality
- **Milestone**: M6+
diff --git a/docs/zh-CN/spec/04-ux/06-settings-ia.md b/docs/zh-CN/spec/04-ux/06-settings-ia.md
index 39a02e805f..18594deb83 100644
--- a/docs/zh-CN/spec/04-ux/06-settings-ia.md
+++ b/docs/zh-CN/spec/04-ux/06-settings-ia.md
@@ -434,8 +434,8 @@ Token 用量**不是设置目的地**(D335 / ADR 0173)。已完成回合历
20. 命令 Shell 选择保留平台有效的目录 ID,仅在状态有额外信息时公开
默认、不可用、回退或无实际 Shell 文案,并且从不授权过时的 ID/dialect
21. 信息页提供「问题反馈」,打开已预填版本和操作系统的 GitHub bug 表单;设置搜索可索引该行
-22. 技能页的市场视图浏览公网 HTTPS 目录、预览组装后的文档,并只通过 `skills.create` 安装;超限展开文档拒绝写入,来源角标跟随 `sourceId`;预览失败时面板给出可读原因与重试入口(安装按钮可以禁用,但不得无解释地禁用);来源被公网策略守卫拒绝时明确说明,而不是笼统报「不可达」。目录查询全部失败或仅部分来源失败时都提供重试按钮;点击后按当前搜索和已配置来源重查,并在请求期间播报加载状态
-23. MCP 市场查询全部失败或部分来源失败时提供重试按钮;点击后重跑当前搜索,并在请求期间播报加载状态
+22. 技能页的市场视图浏览公网 HTTPS 目录、预览组装后的文档,并只通过 `skills.create` 安装;超限展开文档拒绝写入,来源角标跟随 `sourceId`;预览失败时面板给出可读原因与重试入口(安装按钮可以禁用,但不得无解释地禁用);来源被公网策略守卫拒绝时明确说明,而不是笼统报「不可达」。目录查询全部失败或仅部分来源失败时都提供重试按钮;点击后按当前搜索和已配置来源重查,并在请求期间播报加载状态。成功加载过后再遇失败时,列表保留上次成功加载的结果并标注时间,重试入口不变;该列表不回答其他搜索词,重试成功后即消失
+23. MCP 市场查询全部失败或部分来源失败时提供重试按钮;点击后重跑当前搜索,并在请求期间播报加载状态。成功加载过后再遇失败时,列表保留上次成功加载的结果并标注时间,重试入口不变
## 5. Chrome 指标常规
diff --git a/docs/zh-CN/spec/06-delivery/04-e2e-test-plan.md b/docs/zh-CN/spec/06-delivery/04-e2e-test-plan.md
index 1bf5205a08..2a7454a1de 100644
--- a/docs/zh-CN/spec/06-delivery/04-e2e-test-plan.md
+++ b/docs/zh-CN/spec/06-delivery/04-e2e-test-plan.md
@@ -8689,9 +8689,9 @@ runner 会在运行时的隔离临时目录中生成六个插件形态 fixture
#### E2E-MARKET-CATALOG-RETRY:重试失败或部分可用的市场查询
-- **前提条件**:渲染技能市场和 MCP 市场面板,并在 IPC 边界模拟市场 API。每个 API 依次返回全部失败、一个来源失败的结果、完整成功结果。
-- **步骤**:打开两个市场;全部失败后点击重试;确认加载播报和恢复的目录条目;部分失败后再次点击重试。
-- **预期**:两个市场都按当前查询重新请求,期间显示加载状态;部分来源失败时仍有重试入口;来源恢复后失败项清除。测试不访问公网,也不改变主进程网络策略。
+- **前提条件**:渲染技能市场和 MCP 市场面板,并在 IPC 边界模拟市场 API。每个 API 依次返回全部失败、一个来源失败的结果、完整成功结果。第二组先加载成功、随后失败、重试后恢复;第三组在成功后切换搜索词再失败,使快照属于另一个查询;第四组在从未成功过的情况下失败。
+- **步骤**:打开两个市场;全部失败后点击重试;确认加载播报和恢复的目录条目;部分失败后再次点击重试。随后先加载出列表、令下一次查询失败、重试,再切换搜索词后失败一次。
+- **预期**:两个市场都按当前查询重新请求,期间显示加载状态;部分来源失败时仍有重试入口;来源恢复后失败项清除。成功加载过后再遇失败,列表保留上次成功加载的结果并标注时间,重试入口保留;重试成功后保留列表消失,且该列表不回答其他查询、也不在从未成功过时出现。测试不访问公网,也不改变主进程网络策略。
- **链接规格**:`04-ux/06-settings-ia.md`、ADR 0177、ADR 0272
- **验收**:Quality
- **里程碑**:M6+
diff --git a/packages/i18n/src/locales/de/index.ts b/packages/i18n/src/locales/de/index.ts
index 3ee5d487a7..fd4c40bfc5 100644
--- a/packages/i18n/src/locales/de/index.ts
+++ b/packages/i18n/src/locales/de/index.ts
@@ -884,6 +884,7 @@ sklm: {
"Ein lokaler Proxy hat diesen Host auf einen fake-IP-Platzhalter in einem reservierten Bereich aufgelöst, nicht auf die echte Adresse der Quelle. Stelle den Proxy auf Systemproxy-Modus um oder prüfe Einstellungen → Allgemein → Netzwerk.",
remoteErrorQuery: "Der Skill-Markt konnte nicht abgefragt werden – integrierte Auswahl wird angezeigt",
remotePartial: "Einige Katalogquellen sind nicht verfügbar ({{names}})",
+ remoteStaleSnapshot: "Ergebnisse des letzten erfolgreichen Ladens werden angezeigt ({{time}})",
},
"title": "Einstellungen",
"providers": "KI-Anbieter",
@@ -1270,6 +1271,7 @@ sklm: {
remoteError: "Registry nicht erreichbar – integrierte Auswahl wird angezeigt",
remotePartial: "Einige Marktquellen sind nicht verfügbar ({{names}})",
retry: "Erneut versuchen",
+ remoteStaleSnapshot: "Ergebnisse des letzten erfolgreichen Ladens werden angezeigt ({{time}})",
manageSources: "Quellen",
sourcesHint: "Mehrere Marktquellen gleichzeitig abfragen. Registry-Quellen sprechen das offizielle MCP-Registrierungsprotokoll; Katalogquellen sind statische JSON-Dateien im Markt-Schema.",
addSource: "Quelle hinzufügen",
diff --git a/packages/i18n/src/locales/en/index.ts b/packages/i18n/src/locales/en/index.ts
index a28e4dc3b5..ef382349b7 100644
--- a/packages/i18n/src/locales/en/index.ts
+++ b/packages/i18n/src/locales/en/index.ts
@@ -896,6 +896,7 @@ sklm: {
"A local proxy resolved this host to a fake-IP placeholder in a reserved range, not to the source's real address. Switch the proxy to system-proxy mode, or check Settings → General → Network.",
remoteErrorQuery: "Could not query the skill market — showing built-in picks",
remotePartial: "Some catalog sources are unavailable ({{names}})",
+ remoteStaleSnapshot: "Showing the results from your last successful load ({{time}})",
},
title: "Settings",
providers: "AI providers",
@@ -1124,6 +1125,7 @@ sklm: {
remoteError: "Registry unreachable — showing built-in picks",
remotePartial: "Some market sources are unavailable ({{names}})",
retry: "Retry",
+ remoteStaleSnapshot: "Showing the results from your last successful load ({{time}})",
manageSources: "Sources",
sourcesHint: "Query several market sources at once. Registry sources speak the official MCP registry protocol; catalog sources are static JSON files in the market schema.",
addSource: "Add source",
diff --git a/packages/i18n/src/locales/es/index.ts b/packages/i18n/src/locales/es/index.ts
index dab1dccc41..0259becbc3 100644
--- a/packages/i18n/src/locales/es/index.ts
+++ b/packages/i18n/src/locales/es/index.ts
@@ -884,6 +884,7 @@ sklm: {
"Un proxy local resolvió este host a un marcador fake-IP en un rango reservado, no a la dirección real de la fuente. Cambia el proxy al modo de proxy del sistema o revisa Ajustes → General → Red.",
remoteErrorQuery: "No se pudo consultar el mercado de skills: se muestran las selecciones integradas",
remotePartial: "Algunas fuentes del catálogo no están disponibles ({{names}})",
+ remoteStaleSnapshot: "Mostrando los resultados de la última carga correcta ({{time}})",
},
"title": "Configuración",
"providers": "Proveedores de IA",
@@ -1270,6 +1271,7 @@ sklm: {
remoteError: "Registro no disponible: se muestran las selecciones integradas",
remotePartial: "Algunas fuentes del mercado no están disponibles ({{names}})",
retry: "Reintentar",
+ remoteStaleSnapshot: "Mostrando los resultados de la última carga correcta ({{time}})",
manageSources: "Fuentes",
sourcesHint: "Consulta varias fuentes a la vez. Las fuentes de registro hablan el protocolo oficial MCP; las de catálogo son archivos JSON estáticos con el esquema del mercado.",
addSource: "Añadir fuente",
diff --git a/packages/i18n/src/locales/fr/index.ts b/packages/i18n/src/locales/fr/index.ts
index 701530342b..72d89fa894 100644
--- a/packages/i18n/src/locales/fr/index.ts
+++ b/packages/i18n/src/locales/fr/index.ts
@@ -884,6 +884,7 @@ sklm: {
"Un proxy local a résolu cet hôte en une adresse factice d'une plage réservée, et non en l'adresse réelle de la source. Passez le proxy en mode proxy système, ou vérifiez Paramètres → Général → Réseau.",
remoteErrorQuery: "Impossible d'interroger le marché de skills – sélection intégrée affichée",
remotePartial: "Certaines sources du catalogue sont indisponibles ({{names}})",
+ remoteStaleSnapshot: "Affichage des résultats du dernier chargement réussi ({{time}})",
},
"title": "Paramètres",
"providers": "Fournisseurs d'IA",
@@ -1270,6 +1271,7 @@ sklm: {
remoteError: "Registre inaccessible – sélection intégrée affichée",
remotePartial: "Certaines sources du marché sont indisponibles ({{names}})",
retry: "Réessayer",
+ remoteStaleSnapshot: "Affichage des résultats du dernier chargement réussi ({{time}})",
manageSources: "Sources",
sourcesHint: "Interroge plusieurs sources à la fois. Les sources de registre parlent le protocole officiel MCP ; les sources de catalogue sont des fichiers JSON statiques au schéma du marché.",
addSource: "Ajouter une source",
diff --git a/packages/i18n/src/locales/ko/index.ts b/packages/i18n/src/locales/ko/index.ts
index e4e1d2c105..ff9f4331c3 100644
--- a/packages/i18n/src/locales/ko/index.ts
+++ b/packages/i18n/src/locales/ko/index.ts
@@ -893,6 +893,7 @@ sklm: {
"로컬 프록시가 이 호스트를 예약 대역의 fake-IP 자리표시자로 확인했습니다. 소스의 실제 주소가 아닙니다. 프록시를 시스템 프록시 모드로 전환하거나 설정 → 일반 → 네트워크를 확인하세요.",
remoteErrorQuery: "스킬 마켓을 조회하지 못했습니다. 내장 목록을 표시합니다",
remotePartial: "일부 카탈로그 소스를 사용할 수 없습니다 ({{names}})",
+ remoteStaleSnapshot: "마지막으로 성공한 불러오기의 결과를 표시합니다 ({{time}})",
},
title: "설정",
providers: "AI 프로바이더",
@@ -1280,6 +1281,7 @@ sklm: {
remoteError: "레지스트리에 연결할 수 없어 내장 목록을 표시합니다",
remotePartial: "일부 마켓 소스를 사용할 수 없습니다 ({{names}})",
retry: "다시 시도",
+ remoteStaleSnapshot: "마지막으로 성공한 불러오기의 결과를 표시합니다 ({{time}})",
manageSources: "마켓 소스",
sourcesHint: "여러 마켓 소스를 동시에 조회합니다. 레지스트리 소스는 공식 MCP 레지스트리 프로토콜을, 카탈로그 소스는 마켓 스키마의 정적 JSON 파일을 사용합니다.",
addSource: "소스 추가",
diff --git a/packages/i18n/src/locales/pt-BR/index.ts b/packages/i18n/src/locales/pt-BR/index.ts
index 54f3e679b2..f748048373 100644
--- a/packages/i18n/src/locales/pt-BR/index.ts
+++ b/packages/i18n/src/locales/pt-BR/index.ts
@@ -871,7 +871,8 @@ export const ptBR = {
fakeIpHint: "Seu proxy respondeu {{host}} com {{address}}, uma faixa reservada usada como marcador fake-IP, não o endereço real da fonte. Altere o proxy para o modo de proxy do sistema ou revise Configurações → Geral → Rede.",
fakeIpHintPlain: "Um proxy local resolveu este host para um marcador fake-IP em uma faixa reservada, não o endereço real da fonte. Altere o proxy para o modo de proxy do sistema ou revise Configurações → Geral → Rede.",
remoteErrorQuery: "Não foi possível consultar o mercado de habilidades — exibindo seleções integradas",
- remotePartial: "Algumas fontes do catálogo não estão disponíveis ({{names}})"
+ remotePartial: "Algumas fontes do catálogo não estão disponíveis ({{names}})",
+ remoteStaleSnapshot: "Exibindo os resultados do último carregamento bem-sucedido ({{time}})"
},
title: "Configuração",
providers: "Provedores de IA",
@@ -1093,6 +1094,7 @@ export const ptBR = {
remoteError: "Registro inacessível — exibindo seleções integradas",
remotePartial: "Algumas fontes do mercado estão indisponíveis ({{names}})",
retry: "Tentar novamente",
+ remoteStaleSnapshot: "Exibindo os resultados do último carregamento bem-sucedido ({{time}})",
manageSources: "Fontes",
sourcesHint: "Consulte várias fontes do marketplace de uma só vez. Fontes de registro usam o protocolo oficial do MCP; fontes de catálogo são arquivos JSON estáticos no formato do marketplace.",
addSource: "Adicionar fonte",
diff --git a/packages/i18n/src/locales/tr/index.ts b/packages/i18n/src/locales/tr/index.ts
index b8989edac6..2340d8b7a3 100644
--- a/packages/i18n/src/locales/tr/index.ts
+++ b/packages/i18n/src/locales/tr/index.ts
@@ -893,6 +893,7 @@ sklm: {
"Yerel bir proxy bu ana bilgisayarı ayrılmış bir aralıktaki fake-IP yer tutucusuna çözdü; kaynağın gerçek adresi değildir. Proxy'yi sistem proxy moduna alın veya Ayarlar → Genel → Ağ bölümünü kontrol edin.",
remoteErrorQuery: "Skill market sorgulanamadı – yerleşik seçkiler gösteriliyor",
remotePartial: "Bazı katalog kaynakları kullanılamıyor ({{names}})",
+ remoteStaleSnapshot: "Son başarılı yüklemenin sonuçları gösteriliyor ({{time}})",
},
title: "Ayarlar",
providers: "AI servisleri",
@@ -1274,6 +1275,7 @@ sklm: {
remoteError: "Kayıt erişilemiyor – yerleşik seçkiler gösteriliyor",
remotePartial: "Bazı market kaynakları kullanılamıyor ({{names}})",
retry: "Yeniden dene",
+ remoteStaleSnapshot: "Son başarılı yüklemenin sonuçları gösteriliyor ({{time}})",
manageSources: "Kaynaklar",
sourcesHint: "Birden fazla market kaynağını aynı anda sorgular. Kayıt kaynakları resmî MCP kayıt protokolünü; katalog kaynakları market şemasında statik JSON dosyalarını kullanır.",
addSource: "Kaynak ekle",
diff --git a/packages/i18n/src/locales/zh-CN/index.ts b/packages/i18n/src/locales/zh-CN/index.ts
index 7c026ae18e..41c0437b13 100644
--- a/packages/i18n/src/locales/zh-CN/index.ts
+++ b/packages/i18n/src/locales/zh-CN/index.ts
@@ -884,6 +884,7 @@ sklm: {
"本地代理把该主机解析成了保留段里的 fake-IP 占位地址,而不是该源的真实地址。请把代理切换为系统代理模式,或检查 设置 → 通用 → 网络。",
remoteErrorQuery: "无法查询技能市场,已显示内置精选",
remotePartial: "部分目录源不可用({{names}})",
+ remoteStaleSnapshot: "正在显示上次成功加载的结果({{time}})",
},
title: "设置",
providers: "AI 服务",
@@ -1264,6 +1265,7 @@ sklm: {
remoteError: "官方注册表暂不可达,已显示内置精选",
remotePartial: "部分市场源暂不可用({{names}})",
retry: "重试",
+ remoteStaleSnapshot: "正在显示上次成功加载的结果({{time}})",
manageSources: "市场源",
sourcesHint: "同时查询多个市场源。Registry 型源走官方 MCP 注册表协议;目录型源是符合市场 schema 的静态 JSON 文件。",
addSource: "添加源",
diff --git a/packages/i18n/src/locales/zh-TW/index.ts b/packages/i18n/src/locales/zh-TW/index.ts
index 1ae7643a6d..5854156efe 100644
--- a/packages/i18n/src/locales/zh-TW/index.ts
+++ b/packages/i18n/src/locales/zh-TW/index.ts
@@ -884,6 +884,7 @@ sklm: {
"本機代理將該主機解析成保留段中的 fake-IP 佔位位址,而不是該來源的真實位址。請將代理切換為系統代理模式,或檢查 設定 → 一般 → 網路。",
remoteErrorQuery: "無法查詢技能市場,已顯示內建精選",
remotePartial: "部分目錄源不可用({{names}})",
+ remoteStaleSnapshot: "正在顯示上次成功載入的結果({{time}})",
},
title: "設定",
providers: "AI 服務",
@@ -1264,6 +1265,7 @@ sklm: {
remoteError: "官方註冊表暫不可達,已顯示內建精選",
remotePartial: "部分市集來源暫時無法使用({{names}})",
retry: "重試",
+ remoteStaleSnapshot: "正在顯示上次成功載入的結果({{time}})",
manageSources: "市場源",
sourcesHint: "同時查詢多個市場源。Registry 型源走官方 MCP 註冊表協定;目錄型源是符合市集 schema 的靜態 JSON 檔案。",
addSource: "新增源",
diff --git a/scripts/e2e-market-retry.mjs b/scripts/e2e-market-retry.mjs
index 59edcead37..a81a3b3412 100644
--- a/scripts/e2e-market-retry.mjs
+++ b/scripts/e2e-market-retry.mjs
@@ -3,9 +3,9 @@
import assert from "node:assert/strict";
import { spawn } from "node:child_process";
import { createRequire } from "node:module";
-import { mkdtemp, rm, writeFile } from "node:fs/promises";
+import { mkdir, mkdtemp, rm, writeFile } from "node:fs/promises";
import { tmpdir } from "node:os";
-import { dirname, join } from "node:path";
+import { dirname, join, resolve } from "node:path";
import { fileURLToPath } from "node:url";
import { resolveElectronBinary } from "./e2e/boot.mjs";
@@ -13,6 +13,7 @@ const root = join(dirname(fileURLToPath(import.meta.url)), "..");
const require = createRequire(join(root, "packages/agent-runtime/package.json"));
const { build } = require("esbuild");
const { electronBinary } = resolveElectronBinary(root);
+const evidence = process.env.PI_MARKET_EVIDENCE_DIR;
const temp = await mkdtemp(join(tmpdir(), "pi-market-retry-"));
try {
await build({
@@ -35,19 +36,37 @@ try {
join(temp, "index.html"),
'Market retry interactions ',
);
+ const stageScript = evidence
+ ? [
+ ' const stages = ["error-with-snapshot", "retry-loading", "error-no-snapshot", "recovered"];',
+ ' const out = [];',
+ ' for (const stage of stages) {',
+ ' const result = await window.webContents.executeJavaScript(`globalThis.marketSnapshotStage(${JSON.stringify(stage)})`);',
+ ' await window.webContents.executeJavaScript("document.fonts.ready.then(() => new Promise((resolve) => requestAnimationFrame(() => requestAnimationFrame(resolve))))");',
+ ' const png = await window.webContents.capturePage();',
+ ' const target = path.join(__dirname, "shots", stage + ".png");',
+ ' await fs.mkdir(path.join(__dirname, "shots"), { recursive: true });',
+ ' await fs.writeFile(target, png.toPNG());',
+ ' out.push({ stage, ...result });',
+ ' }',
+ ' console.log("MARKET_SNAPSHOT_SHOTS " + JSON.stringify(out));',
+ ].join("\n")
+ : "";
await writeFile(
join(temp, "main.cjs"),
[
'const { app, BrowserWindow } = require("electron");',
'const path = require("node:path");',
+ 'const fs = require("node:fs/promises");',
'app.setPath("userData", path.join(__dirname, "profile"));',
'app.whenReady().then(async () => {',
- ' const window = new BrowserWindow({ show: false, webPreferences: { sandbox: true, contextIsolation: true, nodeIntegration: false } });',
+ ' const window = new BrowserWindow({ show: false, width: 1280, height: 800, webPreferences: { sandbox: true, contextIsolation: true, nodeIntegration: false, backgroundThrottling: false } });',
' window.webContents.on("console-message", (event) => console.error(event.message));',
' try {',
' await window.loadFile(path.join(__dirname, "index.html"));',
' const result = await window.webContents.executeJavaScript("globalThis.marketRetryProbe()");',
' console.log("MARKET_RETRY_PROBE " + JSON.stringify(result));',
+ stageScript,
' app.quit();',
' } catch (error) {',
' console.error("MARKET_RETRY_PROBE " + JSON.stringify({ ok: false, error: String(error) }));',
@@ -68,7 +87,7 @@ try {
output += data;
});
}
- const timeout = setTimeout(() => child.kill("SIGKILL"), 45_000);
+ const timeout = setTimeout(() => child.kill("SIGKILL"), 90_000);
let code;
try {
code = await new Promise((resolve, reject) => {
@@ -84,6 +103,21 @@ try {
console.log("MARKET_RETRY_PROBE " + JSON.stringify(result));
assert.equal(code, 0, output.slice(-6000));
assert.equal(result.ok, true);
+ if (evidence) {
+ const shots = output
+ .split(/\r?\n/)
+ .find((entry) => entry.startsWith("MARKET_SNAPSHOT_SHOTS "));
+ assert(shots, `renderer returned no stage shots: ${output.slice(-2000)}`);
+ await mkdir(resolve(evidence), { recursive: true });
+ const staged = JSON.parse(shots.slice("MARKET_SNAPSHOT_SHOTS ".length));
+ for (const stage of staged) {
+ assert.equal(stage.ok, true, `${stage.stage}: ${JSON.stringify(stage)}`);
+ const from = join(temp, "shots", `${stage.stage}.png`);
+ const to = join(resolve(evidence), `${stage.stage}.png`);
+ await (await import("node:fs/promises")).copyFile(from, to);
+ }
+ console.log(`MARKET_SNAPSHOT_SHOTS ok=${staged.length} dir=${resolve(evidence)}`);
+ }
} finally {
await rm(temp, { recursive: true, force: true });
}
diff --git a/scripts/e2e/market-retry.tsx b/scripts/e2e/market-retry.tsx
index e6f023ee6b..2f58be190d 100644
--- a/scripts/e2e/market-retry.tsx
+++ b/scripts/e2e/market-retry.tsx
@@ -12,6 +12,7 @@ import "../../apps/desktop/src/styles/settings.css";
declare global {
var marketRetryProbe: () => Promise;
+ var marketSnapshotStage: (stage: string) => Promise;
}
const assert = (condition: unknown, message: string) => {
@@ -47,38 +48,78 @@ const mcpEntry: McpCatalogEntry = {
categories: ["devtools"],
};
-globalThis.marketRetryProbe = async () => {
- const i18n = createInstance();
- await i18n.init({
- lng: "en",
- resources: { en: { translation: catalogs.en }, "zh-CN": { translation: catalogs["zh-CN"] } },
- });
+let i18n: ReturnType;
+let container: HTMLDivElement | null = null;
+let root: ReturnType | null = null;
+
+/** Drop the current mount point so the next `boot()` starts from an empty page. */
+function teardown() {
+ if (root) {
+ flushSync(() => root!.unmount());
+ root = null;
+ }
+ if (container) {
+ container.remove();
+ container = null;
+ }
+}
+
+async function boot() {
+ // Stages run one after another in the same window, and a viewport capture
+ // shows whatever sits at the top of the page — a leftover container would
+ // make every screenshot show the first stage's panel.
+ teardown();
+ if (!i18n) {
+ i18n = createInstance();
+ await i18n.init({
+ lng: "en",
+ resources: { en: { translation: catalogs.en }, "zh-CN": { translation: catalogs["zh-CN"] } },
+ });
+ }
api.getSettings = async () => structuredClone(settings);
- const container = document.createElement("div");
+ container = document.createElement("div");
document.body.append(container);
- const root = createRoot(container);
- const render = (panel: "skill" | "mcp") =>
- flushSync(() =>
- root.render(
-
- {panel === "skill" ? (
- {}} onInstalled={() => {}} />
- ) : (
- {}} onInstalled={() => {}} />
- )}
- ,
- ),
- );
- const click = (element: HTMLElement | undefined | null) => {
- assert(element, "missing retry button");
- flushSync(() => element!.click());
- };
- const button = (label: string) =>
- [...container.querySelectorAll("button")].find(
- (element) => element.textContent?.trim() === label,
- );
- const status = () => container.querySelector('[role="status"]')?.textContent ?? "";
+ root = createRoot(container);
+}
+
+function mount(panel: "skill" | "mcp") {
+ flushSync(() => root!.render(
));
+ flushSync(() =>
+ root!.render(
+
+ {panel === "skill" ? (
+ {}} onInstalled={() => {}} />
+ ) : (
+ {}} onInstalled={() => {}} />
+ )}
+ ,
+ ),
+ );
+}
+const click = (element: HTMLElement | undefined | null) => {
+ assert(element, "missing retry button");
+ flushSync(() => element!.click());
+};
+const button = (label: string) =>
+ [...container!.querySelectorAll("button")].find(
+ (element) => element.textContent?.trim() === label,
+ );
+const status = () => container!.querySelector('[role="status"]')?.textContent ?? "";
+const snapshotLine = () =>
+ container!.querySelector(".sklm-status.is-snapshot, .mcpm-status.is-snapshot");
+const typeSearch = (value: string) => {
+ const input = container!.querySelector(".sklm-search-input, .mcpm-search-input");
+ assert(input, "missing search input");
+ const setter = Object.getOwnPropertyDescriptor(HTMLInputElement.prototype, "value")!.set!;
+ flushSync(() => {
+ setter.call(input, value);
+ input!.dispatchEvent(new Event("input", { bubbles: true }));
+ });
+};
+
+globalThis.marketRetryProbe = async () => {
+ await boot();
try {
for (const locale of ["en", "zh-CN"]) {
await i18n.changeLanguage(locale);
@@ -89,7 +130,7 @@ globalThis.marketRetryProbe = async () => {
if (skillCalls === 2) return { entries: [skillEntry], failedSources: ["obra/superpowers"] };
return { entries: [skillEntry], failedSources: [] };
};
- render("skill");
+ mount("skill");
await until(
() => status().includes(i18n.t("settings.sklm.remoteError")) || status().includes(i18n.t("settings.sklm.remoteErrorQuery")),
`${locale}: skill market error status missing`,
@@ -101,6 +142,53 @@ globalThis.marketRetryProbe = async () => {
click(button(i18n.t("settings.sklm.retryCatalog")));
await until(() => skillCalls === 3 && !container.textContent?.includes("obra/superpowers"), `${locale}: second skill retry did not clear partial failure`);
+ // --- Snapshot behavior: the last successful list survives a later failure.
+ let snapCalls = 0;
+ api.searchSkillMarket = async () => {
+ snapCalls += 1;
+ if (snapCalls === 1) return { entries: [skillEntry], failedSources: ["obra/superpowers"] };
+ if (snapCalls === 2) return { entries: [], failedSources: ["anthropics/skills", "obra/superpowers"] };
+ return { entries: [skillEntry], failedSources: [] };
+ };
+ mount("skill");
+ await until(() => snapCalls === 1 && container.textContent?.includes("Recovered Skill") === true, `${locale}: snapshot run 1 did not load`);
+ assert(!snapshotLine(), `${locale}: snapshot line shown before any failure`);
+ click(button(i18n.t("settings.sklm.retryCatalog")));
+ await until(
+ () => status().includes(i18n.t("settings.sklm.remoteError")) || status().includes(i18n.t("settings.sklm.remoteErrorQuery")),
+ `${locale}: snapshot run 2 did not fail`,
+ );
+ assert(snapshotLine(), `${locale}: failure with a snapshot shows no snapshot line`);
+ assert(container.textContent?.includes("Recovered Skill") === true, `${locale}: retained list is missing after failure`);
+ assert(button(i18n.t("settings.sklm.retryCatalog")), `${locale}: retained failure lost its retry`);
+ click(button(i18n.t("settings.sklm.retryCatalog")));
+ await until(() => snapCalls === 3 && !snapshotLine(), `${locale}: recovery kept the snapshot line`);
+
+ // A snapshot answers its own query only: a different search that fails
+ // must not be covered by results taken for another one.
+ let mismatchCalls = 0;
+ api.searchSkillMarket = async () => {
+ mismatchCalls += 1;
+ if (mismatchCalls === 1) return { entries: [skillEntry], failedSources: [] };
+ return { entries: [], failedSources: ["anthropics/skills"] };
+ };
+ mount("skill");
+ await until(() => mismatchCalls === 1 && container.textContent?.includes("Recovered Skill") === true, `${locale}: mismatch run 1 did not load`);
+ typeSearch("zzz");
+ await until(() => mismatchCalls === 2, `${locale}: mismatch query was never sent`);
+ await until(() => status().includes(i18n.t("settings.sklm.remoteError")), `${locale}: mismatch query did not fail`);
+ assert(!snapshotLine(), `${locale}: a snapshot for another query covered this one`);
+
+ // A fresh failure with nothing to fall back to stays as before: no line.
+ let bareCalls = 0;
+ api.searchSkillMarket = async () => {
+ bareCalls += 1;
+ return { entries: [], failedSources: ["anthropics/skills"] };
+ };
+ mount("skill");
+ await until(() => bareCalls === 1 && status().includes(i18n.t("settings.sklm.remoteError")), `${locale}: bare failure did not render`);
+ assert(!snapshotLine(), `${locale}: empty first failure claimed a snapshot`);
+
flushSync(() => root.render(
));
let mcpCalls = 0;
api.searchMcpMarketRegistry = async () => {
@@ -109,7 +197,7 @@ globalThis.marketRetryProbe = async () => {
if (mcpCalls === 2) return { entries: [mcpEntry], failedSources: ["community catalog"] };
return { entries: [mcpEntry], failedSources: [] };
};
- render("mcp");
+ mount("mcp");
await until(() => status().includes(i18n.t("settings.mcpMarket.remoteError")), `${locale}: MCP market error status missing`);
click(button(i18n.t("settings.mcpMarket.retry")));
await until(() => status().includes(i18n.t("settings.mcpMarket.remoteLoading")), `${locale}: MCP retry did not announce loading`);
@@ -117,10 +205,78 @@ globalThis.marketRetryProbe = async () => {
await until(() => button(i18n.t("settings.mcpMarket.retry")) !== undefined, `${locale}: partial MCP failure has no retry`);
click(button(i18n.t("settings.mcpMarket.retry")));
await until(() => mcpCalls === 3 && !container.textContent?.includes("community catalog"), `${locale}: second MCP retry did not clear partial failure`);
+
+ // MCP snapshot: same contract as the skill market.
+ let mcpSnap = 0;
+ api.searchMcpMarketRegistry = async () => {
+ mcpSnap += 1;
+ if (mcpSnap === 1) return { entries: [mcpEntry], failedSources: ["community catalog"] };
+ if (mcpSnap === 2) return { entries: [], failedSources: ["official registry"] };
+ return { entries: [mcpEntry], failedSources: [] };
+ };
+ mount("mcp");
+ await until(() => mcpSnap === 1 && container.textContent?.includes("Recovered Server") === true, `${locale}: MCP snapshot run 1 did not load`);
+ click(button(i18n.t("settings.mcpMarket.retry")));
+ await until(() => status().includes(i18n.t("settings.mcpMarket.remoteError")), `${locale}: MCP snapshot run 2 did not fail`);
+ assert(snapshotLine(), `${locale}: MCP failure with a snapshot shows no snapshot line`);
+ assert(container.textContent?.includes("Recovered Server") === true, `${locale}: MCP retained list is missing`);
}
return { ok: true };
} finally {
- flushSync(() => root.unmount());
- container.remove();
+ teardown();
+ }
+};
+
+/**
+ * One state per call, for review screenshots: `error-with-snapshot`,
+ * `retry-loading`, `error-no-snapshot`, `recovered`. Renders with zh-CN, the
+ * locale the reviewer reads, and leaves the state painted when it resolves.
+ */
+globalThis.marketSnapshotStage = async (stage: string) => {
+ await boot();
+ await i18n.changeLanguage("zh-CN");
+ const skillCalls = { count: 0 };
+ let pending: ((value: unknown) => void) | null = null;
+ api.searchSkillMarket = async () => {
+ skillCalls.count += 1;
+ if (stage === "error-no-snapshot") {
+ return { entries: [], failedSources: ["anthropics/skills", "obra/superpowers"] };
+ }
+ if (skillCalls.count === 1) {
+ return { entries: [skillEntry], failedSources: ["obra/superpowers"] };
+ }
+ if (stage === "retry-loading" && skillCalls.count === 3) {
+ // Third call hangs: the retry is in flight while the snapshot shows.
+ return new Promise((resolve) => {
+ pending = resolve;
+ });
+ }
+ if (stage === "recovered" && skillCalls.count === 3) {
+ // Second call fails (snapshot keeps the list), third recovers.
+ return { entries: [skillEntry], failedSources: [] };
+ }
+ return { entries: [], failedSources: ["anthropics/skills", "obra/superpowers"] };
+ };
+ mount("skill");
+ if (stage === "error-no-snapshot") {
+ await until(() => status().includes(i18n.t("settings.sklm.remoteError")), "no-snapshot error missing");
+ } else {
+ await until(() => container.textContent?.includes("Recovered Skill") === true, `${stage}: first load missing`);
+ }
+ if (stage === "error-with-snapshot" || stage === "retry-loading") {
+ click(button(i18n.t("settings.sklm.retryCatalog")));
+ await until(() => status().includes(i18n.t("settings.sklm.remoteError")), `${stage}: failure missing`);
+ }
+ if (stage === "retry-loading") {
+ click(button(i18n.t("settings.sklm.retryCatalog")));
+ await until(() => status().includes(i18n.t("settings.sklm.remoteLoading")), "retry-loading state missing");
+ }
+ if (stage === "recovered") {
+ click(button(i18n.t("settings.sklm.retryCatalog")));
+ await until(() => status().includes(i18n.t("settings.sklm.remoteError")), "recovered: failure missing");
+ click(button(i18n.t("settings.sklm.retryCatalog")));
+ await until(() => !snapshotLine() && container.textContent?.includes("Recovered Skill") === true, "recovered: list missing");
}
+ await painted();
+ return { ok: true, stage, pending: pending !== null };
};
From a6f4ba121e524a167c42466c7b4debbb3cfd0744 Mon Sep 17 00:00:00 2001
From: TioitWang <104554654+Tioit-Wang@users.noreply.github.com>
Date: Wed, 21 Oct 2026 09:42:58 +0800
Subject: [PATCH 09/44] feat(plugins): offer one line of composer suggestion
from a plugin (#1785)
* feat(plugins): offer one line of composer suggestion from a plugin
A plugin that reacts to a finished turn often knows what the user plausibly
types next, but every surface it has today interrupts: a toast, a notification,
or a rewrite of a draft the user already wrote. Add `pi.composer.suggest` and
`pi.composer.clearSuggestion`, gated by the new `composer.suggest` permission,
which put one dismissible line into the placeholder layer of the Composer for
the session on screen.
The decision is split along the ownership the host already has. The main process
refuses a session that is not the one on screen and a turn that a newer turn
overtook, because it owns both facts; the renderer refuses a draft that is not
empty, because only it owns the draft, and answers the waiting caller. A plugin
therefore learns `shown: false` with a reason instead of guessing, which is what
lets it stop spending completions on a user who is not looking. Main never
writes renderer state: it sends a message, like `pi.ui.revealView` does.
Nothing a plugin offers becomes draft text on its own. `Tab` writes the line
into the draft with the caret at the end, `Esc` drops it, and typing, sending, a
session switch, a new turn, a plugin stop, a reload or a window close all end
it; the `@` / `/` completion list keeps `Tab` and the first `Escape`. See ADR
0332.
* refactor(plugins): keep only the facts the suggestion slot reads
The suggestion bridge kept the composer handle inside its live-draft value,
but it already reaches the newest handle through its own registry. Drop the
duplicate so the value describes only what the decision needs: the session, the
text and how many references the draft holds.
* fix(plugins): give the suggestion slot a server snapshot
React requires a third snapshot when a component is rendered to a string, and
the app-shell snapshot fixtures render the Composer that way. Without it React
threw "Missing getServerSnapshot" and the three shell-render tests failed on CI
even though the browser path was fine. A suggestion is a live-window fact, so
the server snapshot is simply "none".
---------
Co-authored-by: v_wyxgwang
---
.../electron/main/bootstrap/shutdown.ts | 5 +
apps/desktop/electron/main/index.ts | 13 +-
.../electron/main/ipc/plugin-ui-ipc.ts | 42 +++
apps/desktop/electron/main/ipc/register.ts | 6 +-
.../electron/main/plugin-host-process.mjs | 7 +
apps/desktop/electron/main/plugin-runtime.ts | 137 +++++++++
.../main/services/composer-suggestion.ts | 262 ++++++++++++++++++
.../electron/main/services/plugin-services.ts | 24 ++
apps/desktop/src/components/Composer.tsx | 5 +
.../src/features/app/useAppShellRuntime.tsx | 26 ++
.../features/chat/composer/ComposerInput.tsx | 55 +++-
.../composer/hooks/useComposerSuggestion.ts | 49 ++++
.../composer/hooks/usePluginComposerBridge.ts | 15 +-
.../composer/plugins/suggestion-bridge.ts | 219 +++++++++++++++
.../chat/composer/plugins/suggestion-keys.ts | 44 +++
apps/desktop/src/features/plugins/model.ts | 3 +
apps/desktop/src/lib/api.ts | 73 +++++
apps/desktop/src/styles/composer.css | 33 +++
.../test/composer-suggestion-relay.test.mjs | 147 ++++++++++
.../test/composer-suggestion-state.test.mjs | 236 ++++++++++++++++
.../test/plugin-composer-suggestion.test.mjs | 220 +++++++++++++++
docs/adr/0332-plugin-composer-suggestion.md | 124 +++++++++
docs/adr/README.md | 1 +
docs/plugin-development.md | 1 +
docs/spec/06-delivery/04-e2e-test-plan.md | 26 ++
.../07-plugins/02-plugin-manifest-schema.md | 1 +
docs/spec/07-plugins/03-plugin-api.md | 64 +++++
.../13-plugin-permissions-matrix.md | 2 +
.../07-plugins/02-plugin-manifest-schema.md | 1 +
docs/zh-CN/spec/07-plugins/03-plugin-api.md | 56 ++++
.../13-plugin-permissions-matrix.md | 2 +
packages/i18n/src/locales/de/index.ts | 3 +
packages/i18n/src/locales/en/index.ts | 4 +
packages/i18n/src/locales/es/index.ts | 3 +
packages/i18n/src/locales/fr/index.ts | 3 +
packages/i18n/src/locales/ko/index.ts | 3 +
packages/i18n/src/locales/pt-BR/index.ts | 3 +
packages/i18n/src/locales/tr/index.ts | 3 +
packages/i18n/src/locales/zh-CN/index.ts | 3 +
packages/i18n/src/locales/zh-TW/index.ts | 3 +
packages/plugin-sdk/src/index.test.ts | 1 +
packages/plugin-sdk/src/index.ts | 92 ++++++
packages/shared/src/protocol.ts | 13 +
43 files changed, 2021 insertions(+), 12 deletions(-)
create mode 100644 apps/desktop/electron/main/services/composer-suggestion.ts
create mode 100644 apps/desktop/src/features/chat/composer/hooks/useComposerSuggestion.ts
create mode 100644 apps/desktop/src/features/chat/composer/plugins/suggestion-bridge.ts
create mode 100644 apps/desktop/src/features/chat/composer/plugins/suggestion-keys.ts
create mode 100644 apps/desktop/test/composer-suggestion-relay.test.mjs
create mode 100644 apps/desktop/test/composer-suggestion-state.test.mjs
create mode 100644 apps/desktop/test/plugin-composer-suggestion.test.mjs
create mode 100644 docs/adr/0332-plugin-composer-suggestion.md
diff --git a/apps/desktop/electron/main/bootstrap/shutdown.ts b/apps/desktop/electron/main/bootstrap/shutdown.ts
index dfd6683584..b531b9a95d 100644
--- a/apps/desktop/electron/main/bootstrap/shutdown.ts
+++ b/apps/desktop/electron/main/bootstrap/shutdown.ts
@@ -9,6 +9,7 @@ import type { PersistenceOutbox } from "../persistence-outbox";
import type { PluginPanelHost } from "../plugin-panel-host";
import type { PluginRuntime } from "../plugin-runtime";
import type { PluginViewHost } from "../plugin-view-host";
+import type { ComposerSuggestionRelay } from "../services/composer-suggestion";
import type { AppUpdaterController } from "../updater";
import type { UserMcpRuntime } from "../user-mcp";
import type { McpControlServer } from "../mcp-control";
@@ -45,6 +46,8 @@ export type ShutdownDependencies = {
mcpOAuth?: Pick;
browserHost: Pick;
pluginViews: Pick;
+ /** Composer suggestions still waiting for an answer at quit (ADR 0332). */
+ composerSuggestion?: Pick;
updater: Pick;
logger: Pick;
confirmQuitDialog: () => Promise;
@@ -70,6 +73,7 @@ export function registerShutdownHandlers({
mcpOAuth,
browserHost,
pluginViews,
+ composerSuggestion,
updater,
logger,
confirmQuitDialog,
@@ -213,6 +217,7 @@ export function registerShutdownHandlers({
userMcp.disposeAll();
mcpOAuth?.disposeAll();
browserHost.dispose();
+ composerSuggestion?.dispose();
inflightCheckpointer.dispose();
try {
diff --git a/apps/desktop/electron/main/index.ts b/apps/desktop/electron/main/index.ts
index d24b893629..7e55202999 100644
--- a/apps/desktop/electron/main/index.ts
+++ b/apps/desktop/electron/main/index.ts
@@ -72,6 +72,7 @@ import { createSessionCoordination } from "./runtime/session-coordination";
import { createScheduledRuntime } from "./runtime/scheduled";
import { createDesktopServices } from "./services/desktop-services";
import { createPluginServices } from "./services/plugin-services";
+import type { ComposerSuggestionAnswer } from "./services/composer-suggestion";
import { wirePluginThemeRuntimeServices } from "./plugin-theme-services";
import { createSessionCollaborationService } from "./services/session-collaboration";
import {
@@ -638,8 +639,12 @@ const sessionCoordination = createSessionCoordination({
* begins running is reported with the durable turn id instead of being
* inferred from the previous turn's end.
*/
- onTurnStarted: (sessionId: string, turnId: string) =>
- pluginServices.pluginSession.noteTurnStarted(sessionId, turnId),
+ onTurnStarted: (sessionId: string, turnId: string) => {
+ pluginServices.pluginSession.noteTurnStarted(sessionId, turnId);
+ // A new turn owns the composer now, so a suggestion about the previous one
+ // stops being shown and stops being showable (ADR 0332).
+ pluginServices.composerSuggestion.noteTurnStarted(sessionId, turnId);
+ },
});
const {
activeTurnUsages,
@@ -884,6 +889,9 @@ function registerIpc() {
},
/** The shell reports the session on screen; plugin surfaces read it. */
setActivePluginSession: (next) => pluginServices.pluginSession.setActiveSession(next),
+ /** The shell answers a composer suggestion through the same invoke list. */
+ settleComposerSuggestion: (answer: ComposerSuggestionAnswer) =>
+ pluginServices.composerSuggestion.settle(answer),
getPluginLauncherWindow: () => mainState.pluginLauncherWindow,
togglePluginLauncher,
safeOpenExternal,
@@ -1075,6 +1083,7 @@ registerShutdownHandlers({
mcpOAuth,
browserHost,
pluginViews,
+ composerSuggestion: pluginServices.composerSuggestion,
updater,
logger,
confirmQuitDialog,
diff --git a/apps/desktop/electron/main/ipc/plugin-ui-ipc.ts b/apps/desktop/electron/main/ipc/plugin-ui-ipc.ts
index c0d516a958..675bef8597 100644
--- a/apps/desktop/electron/main/ipc/plugin-ui-ipc.ts
+++ b/apps/desktop/electron/main/ipc/plugin-ui-ipc.ts
@@ -12,6 +12,11 @@ import type { PluginPanelTheme } from "../../shared/plugin-panel-chrome";
import type { IpcRegistrar } from "./types";
import { pluginProviderCatalogEntries } from "../plugin-provider-catalog";
import { createSessionPushGate } from "../plugin-session-push-gate";
+import {
+ PLUGIN_COMPOSER_SUGGESTION_REFUSALS,
+ type PluginComposerSuggestionRefusal,
+} from "@pi-desktop/plugin-sdk";
+import type { ComposerSuggestionAnswer } from "../services/composer-suggestion";
export type PluginUiIpcDependencies = {
registrar: IpcRegistrar;
@@ -27,6 +32,12 @@ export type PluginUiIpcDependencies = {
setActivePluginSession: (
next: { sessionId: string; projectPath: string | null } | null,
) => void;
+ /**
+ * The shell's answer to one composer suggestion (`pi.composer.suggest`): the
+ * main process is waiting on it, because only the renderer knows whether the
+ * draft could take the line.
+ */
+ settleComposerSuggestion: (answer: ComposerSuggestionAnswer) => boolean;
};
/** Register plugin panels, work-panel views, themes and services. */
@@ -41,6 +52,7 @@ export function registerPluginUiIpc({
getUpdaterLocale,
getPluginPanelTheme,
setActivePluginSession,
+ settleComposerSuggestion,
}: PluginUiIpcDependencies): void {
const handle = (channel: string, fn: (...args: any[]) => Promise) => {
registrar.handle(channel, fn);
@@ -86,6 +98,36 @@ export function registerPluginUiIpc({
return { ok: true };
},
);
+ /**
+ * The shell's answer to one composer suggestion (`pi.composer.suggest`).
+ *
+ * Nothing is refused here: the offer it answers may already have been
+ * replaced, dropped, or timed out, and a late answer to a forgotten offer is
+ * simply not applied. `ok` therefore says the message was well formed, not
+ * that a suggestion is on screen.
+ */
+ handle(
+ IPC.invoke.pluginComposerSuggestionResult,
+ async (
+ payload:
+ | { requestId?: string | null; shown?: boolean | null; reason?: string | null }
+ | null,
+ ) => {
+ const requestId = typeof payload?.requestId === "string" ? payload.requestId.trim() : "";
+ if (!requestId) throw new Error("INVALID_ARGUMENT: requestId is required");
+ const reason =
+ typeof payload?.reason === "string" &&
+ (PLUGIN_COMPOSER_SUGGESTION_REFUSALS as readonly string[]).includes(payload.reason)
+ ? (payload.reason as PluginComposerSuggestionRefusal)
+ : undefined;
+ settleComposerSuggestion({
+ requestId,
+ shown: payload?.shown === true,
+ ...(reason ? { reason } : {}),
+ });
+ return { ok: true };
+ },
+ );
handle(IPC.invoke.pluginOpenPanel, async (id: string) => {
const loaded = plugins.getLoaded(id);
if (!loaded) throw new Error("plugin not loaded");
diff --git a/apps/desktop/electron/main/ipc/register.ts b/apps/desktop/electron/main/ipc/register.ts
index 5237eb58e3..756c03913a 100644
--- a/apps/desktop/electron/main/ipc/register.ts
+++ b/apps/desktop/electron/main/ipc/register.ts
@@ -37,6 +37,7 @@ import { registerSpeechIpc } from "./speech-ipc";
import { registerVoiceIpc } from "./voice-ipc";
import { registerLiveVoiceIpc } from "./live-voice-ipc";
import type { LiveCallService } from "../live-voice/call-service";
+import type { ComposerSuggestionAnswer } from "../services/composer-suggestion";
import type { LiveVoiceWidget } from "../live-voice/widget-window";
import type { IpcRegistrar } from "./types";
import type { createTraySessions } from "../tray-sessions";
@@ -64,6 +65,8 @@ export type RegisterIpcDependencies = {
setActivePluginSession: (
next: { sessionId: string; projectPath: string | null } | null,
) => void;
+ /** The shell's answer to a composer suggestion it was offered (ADR 0332). */
+ settleComposerSuggestion: (answer: ComposerSuggestionAnswer) => boolean;
activeUserSubagentDocuments: (...args: any[]) => Promise;
disabledBuiltinSubagents: () => Promise;
disabledBuiltinSkills: () => Promise;
@@ -99,6 +102,7 @@ export function registerIpcHandlers(dependencies: RegisterIpcDependencies) {
getNotificationViewingSessionId,
setNotificationViewingSessionId,
setActivePluginSession,
+ settleComposerSuggestion,
getPluginLauncherWindow,
togglePluginLauncher,
safeOpenExternal,
@@ -505,8 +509,8 @@ export function registerIpcHandlers(dependencies: RegisterIpcDependencies) {
getUpdaterLocale,
getPluginPanelTheme,
setActivePluginSession,
+ settleComposerSuggestion,
});
-
registerSpeechIpc({ registrar, speech });
if (voiceService) {
diff --git a/apps/desktop/electron/main/plugin-host-process.mjs b/apps/desktop/electron/main/plugin-host-process.mjs
index 68dd883722..889a75146d 100644
--- a/apps/desktop/electron/main/plugin-host-process.mjs
+++ b/apps/desktop/electron/main/plugin-host-process.mjs
@@ -253,6 +253,13 @@ function buildApi() {
requestNotificationPermission: () => call("ui.requestNotificationPermission"),
showNativeNotification: (input) => call("ui.showNativeNotification", [input]),
},
+ // One line into the session's composer placeholder (ADR 0332). The shell
+ // answers whether it went on screen, so a plugin never has to guess before
+ // spending another completion.
+ composer: {
+ suggest: (input) => call("composer.suggest", [input ?? {}]),
+ clearSuggestion: (input) => call("composer.clearSuggestion", [input ?? {}]),
+ },
project: {
create: (input) => call("project.create", [input ?? {}]),
},
diff --git a/apps/desktop/electron/main/plugin-runtime.ts b/apps/desktop/electron/main/plugin-runtime.ts
index fb3e4859ae..cd2ded1b50 100644
--- a/apps/desktop/electron/main/plugin-runtime.ts
+++ b/apps/desktop/electron/main/plugin-runtime.ts
@@ -71,6 +71,13 @@ import {
type PluginServiceContrib,
type PluginSettingContrib,
type PluginComposerTransformInput,
+ type PluginComposerSuggestInput,
+ type PluginComposerSuggestResult,
+ type PluginComposerClearSuggestionInput,
+ PLUGIN_COMPOSER_SUGGESTION_MAX_CHARS,
+ PLUGIN_COMPOSER_SUGGESTION_TTL_MS,
+ PLUGIN_COMPOSER_SUGGESTION_TTL_MIN_MS,
+ PLUGIN_COMPOSER_SUGGESTION_TTL_MAX_MS,
type PluginSkillContrib,
type PluginThemeVariableContrib,
} from "@pi-desktop/plugin-sdk";
@@ -127,6 +134,10 @@ import {
PROMPT_ENHANCEMENT_PLUGIN_ID,
type LegacyPromptEnhancementSettings,
} from "./plugin-prompt-enhancement-migration";
+import type {
+ ComposerSuggestionOffer,
+ ComposerSuggestionOutcome,
+} from "./services/composer-suggestion";
export type RegisteredCommand = {
id: string;
@@ -514,6 +525,14 @@ export type PluginHostServices = {
sessionId: string;
location: string | null;
}) => Promise;
+ /**
+ * `pi.composer.suggest`: hand one line to the shell that owns the composer.
+ * The runtime already checked the permission and shaped the text; the shell
+ * says whether it went on screen, because only it knows the draft.
+ */
+ suggestComposer?: (offer: ComposerSuggestionOffer) => Promise;
+ /** `pi.composer.clearSuggestion`: drop this plugin's own line. */
+ clearComposerSuggestion?: (pluginId: string, sessionId?: string) => void;
project?: {
create: (pluginId: string, input: Record) => Promise;
};
@@ -547,6 +566,8 @@ const HOST_API_ALLOWLIST = new Set([
"plugin.setSettings",
"plugin.getDataPath",
"ui.revealView",
+ "composer.suggest",
+ "composer.clearSuggestion",
"ui.openPanel",
"ui.closePanel",
"ui.showToast",
@@ -1032,6 +1053,34 @@ function normalizePluginSessionInput(
return { ...(input as Record) };
}
+/** Longest session or turn id a plugin may name, matching the host's own bound. */
+const MAX_SESSION_ID_CHARS = 128;
+
+/**
+ * One line of suggestion text, in the form the composer draws: line breaks and
+ * runs of whitespace fold to single spaces, and the result is cut at the SDK
+ * ceiling. Shaping rather than refusing is deliberate — a plugin that asked for
+ * a long or multi-line string still gets a usable suggestion instead of an
+ * error it cannot repair from inside a turn.
+ */
+function composerSuggestionText(value: unknown): string {
+ if (typeof value !== "string") return "";
+ const line = value.replace(/\s+/g, " ").trim();
+ return [...line].slice(0, PLUGIN_COMPOSER_SUGGESTION_MAX_CHARS).join("").trim();
+}
+
+/** The requested lifetime, clamped into the range the SDK publishes. */
+function composerSuggestionTtl(value: unknown): number {
+ if (value === undefined || value === null) return PLUGIN_COMPOSER_SUGGESTION_TTL_MS;
+ if (typeof value !== "number" || !Number.isFinite(value)) {
+ throw apiError("INVALID_PARAMS", "ttlMs must be a number of milliseconds");
+ }
+ return Math.min(
+ Math.max(Math.round(value), PLUGIN_COMPOSER_SUGGESTION_TTL_MIN_MS),
+ PLUGIN_COMPOSER_SUGGESTION_TTL_MAX_MS,
+ );
+}
+
/**
* Bounds for the read-only usage fact listing. The host RPC re-checks the
* same windows, so a caller that skips this main-process side still cannot
@@ -4565,6 +4614,84 @@ export class PluginRuntime {
ts: Date.now(),
});
}
+ /**
+ * `pi.composer.suggest`: one line into the composer of the session the user
+ * is looking at (`composer.suggest`, ADR 0332).
+ *
+ * The plugin names the session and the turn its text answers. Nothing here
+ * can fail the plugin for a place that will not show it: the text is shaped
+ * rather than refused, and "not shown" comes back as a reason the plugin can
+ * log. What does throw is a broken call — no session id, no text left after
+ * shaping, a lifetime that is not a number — like every other host API.
+ */
+ private async suggestComposer(
+ loaded: LoadedPlugin,
+ input?: PluginComposerSuggestInput,
+ ): Promise {
+ this.assertPermission(loaded, "composer.suggest");
+ const raw = input && typeof input === "object" ? input : ({} as PluginComposerSuggestInput);
+ const sessionId = typeof raw.sessionId === "string" ? raw.sessionId.trim() : "";
+ if (!sessionId || sessionId.length > MAX_SESSION_ID_CHARS) {
+ throw apiError("INVALID_PARAMS", "sessionId must be a non-empty string");
+ }
+ const turnId = typeof raw.turnId === "string" ? raw.turnId.trim() : "";
+ if (turnId.length > MAX_SESSION_ID_CHARS) {
+ throw apiError("INVALID_PARAMS", "turnId must be at most 128 characters");
+ }
+ const text = composerSuggestionText(raw.text);
+ if (!text) throw apiError("INVALID_PARAMS", "text must contain at least one visible character");
+ const ttlMs = composerSuggestionTtl(raw.ttlMs);
+ // A plugin scoped to another project is not part of this conversation, so
+ // it does not get to write into the composer the user is looking at.
+ if (!this.services.isPluginActiveInProject?.(loaded.manifest.id)) {
+ return { shown: false, reason: "session-not-visible" };
+ }
+ if (!this.services.suggestComposer) {
+ throw apiError("UNSUPPORTED", "host api not available: composer.suggest");
+ }
+ const result = await this.services.suggestComposer({
+ pluginId: loaded.manifest.id,
+ sessionId,
+ ...(turnId ? { turnId } : {}),
+ text,
+ ttlMs,
+ });
+ this.services.audit?.({
+ pluginId: loaded.manifest.id,
+ api: "composer.suggest",
+ ok: true,
+ sessionId,
+ shown: result.shown,
+ ...(result.shown ? {} : { reason: result.reason }),
+ ts: Date.now(),
+ });
+ return result;
+ }
+
+ /**
+ * `pi.composer.clearSuggestion`: drop the caller's own line. Nothing is shown
+ * when it is already gone, so the answer never depends on what the shell had.
+ */
+ private clearComposerSuggestion(
+ loaded: LoadedPlugin,
+ input?: PluginComposerClearSuggestionInput,
+ ): { ok: true } {
+ this.assertPermission(loaded, "composer.suggest");
+ const sessionId = typeof input?.sessionId === "string" ? input.sessionId.trim() : "";
+ if (sessionId.length > MAX_SESSION_ID_CHARS) {
+ throw apiError("INVALID_PARAMS", "sessionId must be at most 128 characters");
+ }
+ this.services.clearComposerSuggestion?.(loaded.manifest.id, sessionId || undefined);
+ this.services.audit?.({
+ pluginId: loaded.manifest.id,
+ api: "composer.clearSuggestion",
+ ok: true,
+ sessionId: sessionId || null,
+ ts: Date.now(),
+ });
+ return { ok: true };
+ }
+
private async readSessionContext(loaded: LoadedPlugin): Promise {
this.assertPermission(loaded, "session.read");
@@ -5454,6 +5581,16 @@ export class PluginRuntime {
revealView: async (input?: PluginRevealViewInput) =>
this.revealWorkPanelView(loaded, input),
},
+ composer: {
+ /**
+ * One dismissible line in the placeholder layer of the composer the
+ * user is looking at (`composer.suggest`, ADR 0332).
+ */
+ suggest: async (input?: PluginComposerSuggestInput) =>
+ this.suggestComposer(loaded, input),
+ clearSuggestion: async (input?: PluginComposerClearSuggestionInput) =>
+ this.clearComposerSuggestion(loaded, input),
+ },
workspace: {
get: async () => {
// The enriched payload carries the project group behind the visible
diff --git a/apps/desktop/electron/main/services/composer-suggestion.ts b/apps/desktop/electron/main/services/composer-suggestion.ts
new file mode 100644
index 0000000000..0e92d0c151
--- /dev/null
+++ b/apps/desktop/electron/main/services/composer-suggestion.ts
@@ -0,0 +1,262 @@
+/**
+ * The main-process half of `pi.composer.suggest` (ADR 0332).
+ *
+ * A suggestion is produced by a plugin process, long after the turn it answers
+ * ended, so by the time it arrives the user may have typed, switched session,
+ * or started another turn. Two owners therefore decide together, and this module
+ * is the seam between them:
+ *
+ * - The main process owns the facts it already has — which session is on screen
+ * (`pluginSession` snapshot) and which turn that session ran last — so a
+ * suggestion naming another session, or a turn that is no longer the newest,
+ * is refused here and never crosses to the window.
+ * - The renderer owns the composer, so whether the draft is empty and whether a
+ * composer takes input at all is its answer, sent back over an invoke. The
+ * caller waits for that answer instead of being told a guess.
+ *
+ * Nothing here writes renderer state: the offer is a message, and the composer
+ * decides. The relay also carries the two shell-side invalidations only the main
+ * process sees — a new turn starting, and a plugin going away.
+ */
+import { randomUUID } from "node:crypto";
+import type { PluginComposerSuggestionRefusal } from "@pi-desktop/plugin-sdk";
+import { IPC } from "@pi-desktop/shared";
+
+/** One suggestion a plugin asked the shell to show. */
+export type ComposerSuggestionOffer = {
+ pluginId: string;
+ sessionId: string;
+ turnId?: string;
+ text: string;
+ ttlMs: number;
+};
+
+/** What became of one offer: on screen, or why not. */
+export type ComposerSuggestionOutcome =
+ | { shown: true }
+ | { shown: false; reason: PluginComposerSuggestionRefusal };
+
+/**
+ * What main sends the renderer. `offer` asks the shell to show one line; `clear`
+ * orders it to drop what it shows — of one plugin, of one session, or of
+ * whatever it holds when neither is named.
+ */
+export type ComposerSuggestionMessage =
+ | {
+ kind: "offer";
+ requestId: string;
+ pluginId: string;
+ sessionId: string;
+ turnId?: string;
+ text: string;
+ /** Epoch milliseconds; the shell drops the line at this moment. */
+ expiresAt: number;
+ }
+ | { kind: "clear"; pluginId?: string; sessionId?: string };
+
+/** The shell's answer to one `offer`, as it arrives over its own invoke. */
+export type ComposerSuggestionAnswer = {
+ requestId: string;
+ shown: boolean;
+ reason?: PluginComposerSuggestionRefusal;
+};
+
+export type ComposerSuggestionRelayDependencies = {
+ sendToRenderer: (channel: string, payload: unknown) => void;
+ /** The session the shell shows, read from the plugin session snapshot. */
+ getActiveSession: () => { sessionId: string } | null;
+ /** How long the shell has to answer an offer; a slow window is no window. */
+ answerTimeoutMs?: number;
+ now?: () => number;
+ log?: (message: string, data?: Record) => void;
+};
+
+/** Longest wait for the renderer's answer before the offer is given up on. */
+const DEFAULT_ANSWER_TIMEOUT_MS = 2_000;
+/**
+ * Sessions whose last known turn is still remembered. Only the newest turn per
+ * session matters and a stale entry is corrected by the next turn start, so the
+ * map is capped rather than grown with every session the app ever ran.
+ */
+const MAX_TRACKED_SESSIONS = 64;
+
+const UNSHOWN: ComposerSuggestionOutcome = { shown: false, reason: "unsupported" };
+
+type PendingOffer = {
+ requestId: string;
+ pluginId: string;
+ sessionId: string;
+ settle: (outcome: ComposerSuggestionOutcome) => void;
+ timer: ReturnType;
+};
+
+function enforceBound(map: Map, limit: number): void {
+ while (map.size > limit) {
+ const oldest = map.keys().next();
+ if (oldest.done) return;
+ map.delete(oldest.value);
+ }
+}
+
+export type ComposerSuggestionRelay = ReturnType;
+
+export function createComposerSuggestionRelay({
+ sendToRenderer,
+ getActiveSession,
+ answerTimeoutMs = DEFAULT_ANSWER_TIMEOUT_MS,
+ now = Date.now,
+ log,
+}: ComposerSuggestionRelayDependencies) {
+ /** sessionId → the offer waiting for the shell's answer. One per session. */
+ const pending = new Map();
+ /** sessionId → the newest turn the main process heard of. */
+ const latestTurns = new Map();
+
+ const send = (message: ComposerSuggestionMessage): void => {
+ try {
+ sendToRenderer(IPC.event.pluginComposerSuggestion, message);
+ } catch (error) {
+ // Delivery is best effort: a window that is gone must not turn a plugin's
+ // suggestion call into a failure, and the offer's own timeout already
+ // reports the miss.
+ log?.("composer suggestion send failed", { kind: message.kind, data: String(error) });
+ }
+ };
+
+ /** Forget one waiting offer and answer it with `reason`. */
+ const drop = (offer: PendingOffer, reason: PluginComposerSuggestionRefusal): void => {
+ if (pending.get(offer.sessionId)?.requestId === offer.requestId) {
+ pending.delete(offer.sessionId);
+ }
+ clearTimeout(offer.timer);
+ offer.settle({ shown: false, reason });
+ };
+
+ /** Exactly one offer can be in flight per session, so the loser learns it lost. */
+ const preempt = (sessionId: string, reason: PluginComposerSuggestionRefusal): void => {
+ const offer = pending.get(sessionId);
+ if (offer) drop(offer, reason);
+ };
+
+ const answer = (offer: PendingOffer, result: ComposerSuggestionOutcome): void => {
+ if (pending.get(offer.sessionId)?.requestId === offer.requestId) {
+ pending.delete(offer.sessionId);
+ }
+ clearTimeout(offer.timer);
+ offer.settle(result);
+ };
+
+ return {
+ /**
+ * Offer one line to the shell and wait for its answer.
+ *
+ * `turnId` is compared with the newest turn the main process saw for the
+ * session: a suggestion about a turn that has since been overtaken names a
+ * moment that is over, so it is refused here instead of arriving late in a
+ * composer that belongs to the newer turn.
+ */
+ offer(offer: ComposerSuggestionOffer): Promise {
+ const active = getActiveSession();
+ if (!active || active.sessionId !== offer.sessionId) {
+ return Promise.resolve({ shown: false, reason: "session-not-visible" });
+ }
+ const newestTurn = latestTurns.get(offer.sessionId);
+ if (offer.turnId && newestTurn && newestTurn !== offer.turnId) {
+ return Promise.resolve({ shown: false, reason: "stale-turn" });
+ }
+ // The newer offer takes the session's single slot; the one still waiting
+ // for an answer is told so instead of being left to time out.
+ preempt(offer.sessionId, "replaced");
+ const requestId = randomUUID();
+ return new Promise((resolve) => {
+ let settled = false;
+ const settle = (result: ComposerSuggestionOutcome): void => {
+ if (settled) return;
+ settled = true;
+ resolve(result);
+ };
+ const timer = setTimeout(() => {
+ const current = pending.get(offer.sessionId);
+ if (current?.requestId === requestId) drop(current, "unsupported");
+ }, answerTimeoutMs);
+ // A window that closes mid-answer must not keep the timer alive.
+ (timer as { unref?: () => void }).unref?.();
+ pending.set(offer.sessionId, {
+ requestId,
+ pluginId: offer.pluginId,
+ sessionId: offer.sessionId,
+ settle,
+ timer,
+ });
+ send({
+ kind: "offer",
+ requestId,
+ pluginId: offer.pluginId,
+ sessionId: offer.sessionId,
+ ...(offer.turnId ? { turnId: offer.turnId } : {}),
+ text: offer.text,
+ expiresAt: now() + offer.ttlMs,
+ });
+ });
+ },
+
+ /**
+ * The shell's word on one offer. Answers arrive asynchronously, so one that
+ * lands after its offer was replaced, timed out or dropped is simply
+ * ignored.
+ */
+ settle(reply: ComposerSuggestionAnswer): boolean {
+ const offer = [...pending.values()].find((entry) => entry.requestId === reply.requestId);
+ if (!offer) return false;
+ answer(
+ offer,
+ reply.shown ? { shown: true } : { shown: false, reason: reply.reason ?? "unsupported" },
+ );
+ return true;
+ },
+
+ /**
+ * A host turn opened for this session: the new turn owns the composer now,
+ * and a suggestion about an earlier turn is over.
+ */
+ noteTurnStarted(sessionId: string, turnId: string): void {
+ const id = sessionId.trim();
+ const turn = turnId.trim();
+ if (!id || !turn) return;
+ latestTurns.set(id, turn);
+ enforceBound(latestTurns, MAX_TRACKED_SESSIONS);
+ preempt(id, "stale-turn");
+ send({ kind: "clear", sessionId: id });
+ },
+
+ /** The plugin stopped (unloaded, disabled, crashed, revoked): its line goes. */
+ clearPlugin(pluginId: string): void {
+ const id = pluginId.trim();
+ if (!id) return;
+ for (const offer of [...pending.values()]) {
+ if (offer.pluginId === id) drop(offer, "unsupported");
+ }
+ send({ kind: "clear", pluginId: id });
+ },
+
+ /** A plugin dropped its own suggestion; a session narrows it further. */
+ clearSuggestion(pluginId: string, sessionId?: string): void {
+ const id = pluginId.trim();
+ if (!id) return;
+ const session = sessionId?.trim() ?? "";
+ for (const offer of [...pending.values()]) {
+ if (offer.pluginId !== id) continue;
+ if (session && offer.sessionId !== session) continue;
+ drop(offer, "unsupported");
+ }
+ send({ kind: "clear", pluginId: id, ...(session ? { sessionId: session } : {}) });
+ },
+
+ /** The window is going away: nothing will show these offers. */
+ dispose(): void {
+ for (const offer of [...pending.values()]) drop(offer, "unsupported");
+ pending.clear();
+ latestTurns.clear();
+ },
+ };
+}
diff --git a/apps/desktop/electron/main/services/plugin-services.ts b/apps/desktop/electron/main/services/plugin-services.ts
index 9fb135f361..33251db00a 100644
--- a/apps/desktop/electron/main/services/plugin-services.ts
+++ b/apps/desktop/electron/main/services/plugin-services.ts
@@ -56,6 +56,7 @@ import type { ClipboardHistory } from "../clipboard-history";
import type { TurnEndedPayload } from "../runtime/session-coordination";
import type { HostProcess } from "../host-process";
import { createPluginSessionContext } from "./plugin-session-context";
+import { createComposerSuggestionRelay } from "./composer-suggestion";
import type { Logger } from "../logger";
import type { PluginAppearance } from "../../shared/plugin-panel-chrome";
@@ -637,6 +638,17 @@ export function createPluginServices({
getActiveTurn,
announce: broadcastSessionEvent,
});
+ /**
+ * `pi.composer.suggest` (ADR 0332): the main process refuses a suggestion
+ * that names another session or an overtaken turn, and the shell answers
+ * whether the composer can take it. The composer owns its own state, so this
+ * only ever relays — nothing here writes the draft.
+ */
+ const composerSuggestion = createComposerSuggestionRelay({
+ sendToRenderer,
+ getActiveSession: () => pluginSession.snapshot(),
+ log: (message, data) => logger.app("plugin", "warn", message, { data }),
+ });
const pluginViews = new PluginViewHost(({ pluginId, url }) => {
logger.app("plugin", "warn", "plugin.api", {
pluginId,
@@ -730,6 +742,15 @@ export function createPluginServices({
...(location ? { location } : {}),
});
},
+ /**
+ * `pi.composer.suggest`: the runtime already checked the permission and
+ * shaped the text, and this only relays the offer to the shell that owns the
+ * composer.
+ */
+ suggestComposer: (offer) => composerSuggestion.offer(offer),
+ /** `pi.composer.clearSuggestion`: drop this plugin's own line. */
+ clearComposerSuggestion: (pluginId, sessionId) =>
+ composerSuggestion.clearSuggestion(pluginId, sessionId),
browser: {
reveal: (sessionId) => browserHost.reveal(sessionId),
navigate: (input, sessionId, tabId) => browserHost.navigate(input, sessionId, tabId),
@@ -748,6 +769,8 @@ export function createPluginServices({
},
onPluginUnload: (pluginId) => {
if (pluginId === BROWSER_PLUGIN_ID) browserHost.disposeGuest();
+ // A stopped plugin loses its line in the composer with it.
+ composerSuggestion.clearPlugin(pluginId);
},
});
const speech = createSpeechService({
@@ -768,6 +791,7 @@ export function createPluginServices({
pluginViews,
browserHost,
pluginSession,
+ composerSuggestion,
speech,
};
}
diff --git a/apps/desktop/src/components/Composer.tsx b/apps/desktop/src/components/Composer.tsx
index c9baf395d8..05d9fa922e 100644
--- a/apps/desktop/src/components/Composer.tsx
+++ b/apps/desktop/src/components/Composer.tsx
@@ -50,6 +50,7 @@ import { useComposerCompletions } from "../features/chat/composer/hooks/useCompo
import { useComposerDraft } from "../features/chat/composer/hooks/useComposerDraft";
import { useComposerInputHistory } from "../features/chat/composer/hooks/useComposerInputHistory";
import { usePluginComposerBridge } from "../features/chat/composer/hooks/usePluginComposerBridge";
+import { useComposerSuggestion } from "../features/chat/composer/hooks/useComposerSuggestion";
import { useComposerSubmit } from "../features/chat/composer/hooks/useComposerSubmit";
import { useComposerTransforms } from "../features/chat/composer/hooks/useComposerTransforms";
import { ComposerInput } from "../features/chat/composer/ComposerInput";
@@ -495,6 +496,9 @@ export function Composer({
// Plugin draft and attachment actions reach this composer while it takes input.
usePluginComposerBridge({ ...draft, inputBlocked, enabled: localToolsAllowed });
+ // A plugin may have offered one line for this empty draft; it shows in the
+ // placeholder layer and `Tab` takes it (ADR 0332).
+ const suggestion = useComposerSuggestion();
// Keep the transcript's bottom reserve in sync with the composer's real
// height (it grows with multi-line input) so the last message sits just
@@ -581,6 +585,7 @@ export function Composer({
enterToSend={enterToSend}
runActive={runActive}
composerAc={completions.ac}
+ suggestion={suggestion}
onPaste={pasteClipboardFiles}
onAcceptCompletion={completions.acceptCompletion}
onSubmit={(steering) => void submitFromComposer(steering)}
diff --git a/apps/desktop/src/features/app/useAppShellRuntime.tsx b/apps/desktop/src/features/app/useAppShellRuntime.tsx
index f7058af029..08a94051e5 100644
--- a/apps/desktop/src/features/app/useAppShellRuntime.tsx
+++ b/apps/desktop/src/features/app/useAppShellRuntime.tsx
@@ -15,6 +15,7 @@ import { useTranslation } from "react-i18next";
import { installRendererApi } from "../../capture/renderer-api";
import { StartupSplash } from "../../components/StartupSplash";
import { api } from "../../lib/api";
+import { composerSuggestion } from "../chat/composer/plugins/suggestion-bridge";
import { subscribeRemoteInteractions } from "../../lib/remote-interactions";
import { playNotificationChime } from "../../lib/notification-sound";
import {
@@ -700,6 +701,30 @@ export function useAppShellRuntime() {
...(event.location ? { location: event.location } : {}),
});
});
+ // A plugin offered one line for the composer (`pi.composer.suggest`). The
+ // shell owns the composer, so it decides here and answers the main process,
+ // which is waiting on the plugin's call with that answer.
+ const offComposerSuggestion = api.onPluginComposerSuggestion((event) => {
+ if (event.kind === "clear") {
+ composerSuggestion.clear({
+ ...(event.pluginId ? { pluginId: event.pluginId } : {}),
+ ...(event.sessionId ? { sessionId: event.sessionId } : {}),
+ });
+ return;
+ }
+ const outcome = composerSuggestion.offer({
+ pluginId: event.pluginId,
+ sessionId: event.sessionId,
+ ...(event.turnId ? { turnId: event.turnId } : {}),
+ text: event.text,
+ expiresAt: event.expiresAt,
+ });
+ void api.pluginComposerSuggestionResult({
+ requestId: event.requestId,
+ shown: outcome.shown === true,
+ ...(outcome.shown ? {} : { reason: outcome.reason }),
+ });
+ });
const offHostStatus = api.onHostStatus((status) => {
if (status.archMismatch) setArchMismatch(status.archMismatch);
if (status.ok) {
@@ -910,6 +935,7 @@ export function useAppShellRuntime() {
offPluginViewReveal();
offHostStatus();
offNotificationChanged();
+ offComposerSuggestion();
offSessionsChanged();
offRemoteInteractions();
offNotificationActivated();
diff --git a/apps/desktop/src/features/chat/composer/ComposerInput.tsx b/apps/desktop/src/features/chat/composer/ComposerInput.tsx
index 66ca68c02b..dcacf74872 100644
--- a/apps/desktop/src/features/chat/composer/ComposerInput.tsx
+++ b/apps/desktop/src/features/chat/composer/ComposerInput.tsx
@@ -11,6 +11,8 @@ import type {
import { editorSelectionRange, readEditorValue } from "./editor";
import { ComposerImagePreview } from "./ComposerImagePreview";
import { ComposerImageHover } from "./ComposerImageHoverPreview";
+import { composerSuggestionKeyAction } from "./plugins/suggestion-keys";
+import type { ComposerSuggestionView } from "./hooks/useComposerSuggestion";
import type { CompletionController } from "./hooks/useComposerCompletions";
import type { ComposerImagePreviewController } from "./hooks/useComposerImagePreview";
@@ -25,6 +27,12 @@ export type ComposerInputProps = {
enterToSend: boolean;
runActive: boolean;
composerAc: CompletionController;
+ /**
+ * The plugin suggestion on screen, if any (ADR 0332). It is drawn in the
+ * placeholder layer while the draft is empty, and `Tab` / `Esc` act on it only
+ * when nothing else claims those keys.
+ */
+ suggestion?: ComposerSuggestionView | null;
onPaste: (event: ClipboardEvent) => void;
onAcceptCompletion: (index: number) => void;
onSubmit: (steering?: boolean) => void;
@@ -57,6 +65,7 @@ export function ComposerInput({
enterToSend,
runActive,
composerAc,
+ suggestion = null,
onPaste,
onAcceptCompletion,
onSubmit,
@@ -150,6 +159,19 @@ export function ComposerInput({
return;
}
}
+ // A completion list owns `Tab` and the first `Escape`; the plugin
+ // suggestion only acts once neither claims the key.
+ const suggestionAction = composerSuggestionKeyAction(event, {
+ suggestion: suggestion !== null,
+ completionItems: composerAc.hasItems,
+ completionOpen: composerAc.open,
+ });
+ if (suggestionAction) {
+ event.preventDefault();
+ if (suggestionAction === "accept") suggestion?.accept();
+ else suggestion?.dismiss();
+ return;
+ }
if (
(event.key === "ArrowUp" || event.key === "ArrowDown") &&
!event.shiftKey &&
@@ -171,13 +193,34 @@ export function ComposerInput({
}
}}
/>
+ {/* The plugin suggestion (`pi.composer.suggest`) rides in the
+ placeholder layer — never a bubble — and only while the draft is
+ empty, which is what makes Tab a plain "write this for me". */}
{value.length === 0 ? (
-
- {placeholderText}
+ suggestion ? (
+
+ {suggestion.text}
+ {suggestion.hint}
+
+ ) : (
+
+ {placeholderText}
+
+ )
+ ) : null}
+ {/* The visible line is decoration; the live region is what a screen
+ reader announces, once, without stealing focus. */}
+ {suggestion ? (
+
+ {suggestion.text}
) : null}
diff --git a/apps/desktop/src/features/chat/composer/hooks/useComposerSuggestion.ts b/apps/desktop/src/features/chat/composer/hooks/useComposerSuggestion.ts
new file mode 100644
index 0000000000..2786277f81
--- /dev/null
+++ b/apps/desktop/src/features/chat/composer/hooks/useComposerSuggestion.ts
@@ -0,0 +1,49 @@
+/**
+ * The composer's view of the plugin suggestion slot (ADR 0332).
+ *
+ * The state itself lives in `../plugins/suggestion-bridge.ts`, outside React, so
+ * a suggestion that arrives while the composer is unmounted is refused once
+ * instead of queued; this only subscribes a mounted composer to it and hands the
+ * placeholder layer the line and the key hint it draws.
+ */
+import { useMemo, useSyncExternalStore } from "react";
+import { useTranslation } from "react-i18next";
+import { composerSuggestion } from "../plugins/suggestion-bridge";
+
+/** What `ComposerInput` draws and does while a suggestion is on screen. */
+export type ComposerSuggestionView = {
+ readonly text: string;
+ /** `Tab` / `Esc` hint drawn beside the line, in the shell's language. */
+ readonly hint: string;
+ /** Take it: the draft becomes the text and the caret lands at its end. */
+ accept(): boolean;
+ dismiss(): void;
+};
+
+const subscribe = (listener: () => void) => composerSuggestion.subscribe(listener);
+const snapshot = () => composerSuggestion.get();
+/**
+ * There is no shell state to read while the app is rendered to a string, and
+ * React requires this third snapshot for exactly that pass: a suggestion is a
+ * live-window fact, so a server render starts with none.
+ */
+const serverSnapshot = (): null => null;
+
+export function useComposerSuggestion(): ComposerSuggestionView | null {
+ const { t } = useTranslation();
+ const suggestion = useSyncExternalStore(subscribe, snapshot, serverSnapshot);
+ const text = suggestion?.text ?? "";
+ const hint = t("chat.suggestionHint");
+ return useMemo(
+ () =>
+ suggestion
+ ? {
+ text,
+ hint,
+ accept: () => composerSuggestion.accept(),
+ dismiss: () => composerSuggestion.dismiss(),
+ }
+ : null,
+ [suggestion, text, hint],
+ );
+}
diff --git a/apps/desktop/src/features/chat/composer/hooks/usePluginComposerBridge.ts b/apps/desktop/src/features/chat/composer/hooks/usePluginComposerBridge.ts
index 6da1369e94..9d20d3008f 100644
--- a/apps/desktop/src/features/chat/composer/hooks/usePluginComposerBridge.ts
+++ b/apps/desktop/src/features/chat/composer/hooks/usePluginComposerBridge.ts
@@ -1,13 +1,16 @@
/**
* Lends this composer to the plugin draft bridge (`../plugins/draft-bridge.ts`)
- * while it is mounted, and tells the bridge after every render that changed
- * the draft, so plugin subscribers and the draft's generation follow it.
+ * and to the plugin suggestion slot (`../plugins/suggestion-bridge.ts`) while it
+ * is mounted, and tells both after every render that changed the draft, so
+ * plugin subscribers follow it, the draft's generation advances, and a
+ * suggestion about an empty draft ends the moment the draft stops being empty.
*/
import { useEffect, useRef, type RefObject } from "react";
import { api } from "../../../../lib/api";
import { editorSelectionRange, readEditorValue } from "../editor";
import type { ComposerFileReference } from "../model";
import { composerDraftBridge, type ComposerDraftHandle } from "../plugins/draft-bridge";
+import { composerSuggestion } from "../plugins/suggestion-bridge";
type BridgeSource = {
ref: RefObject;
@@ -75,14 +78,20 @@ export function usePluginComposerBridge(source: BridgeSource): void {
};
handleRef.current = handle;
const unregister = composerDraftBridge.register(handle);
+ // The suggestion slot needs the same handle: it reads the draft to decide
+ // whether an offer fits and writes it when the user takes one.
+ const unregisterSuggestion = composerSuggestion.register(handle);
return () => {
handleRef.current = null;
+ unregisterSuggestion();
unregister();
};
}, [source.enabled]);
const { value, fileReferences, draftKey, referenceSessionId, inputBlocked } = source;
useEffect(() => {
- if (handleRef.current) composerDraftBridge.publish(handleRef.current);
+ if (!handleRef.current) return;
+ composerDraftBridge.publish(handleRef.current);
+ composerSuggestion.publish(handleRef.current);
}, [value, fileReferences, draftKey, referenceSessionId, inputBlocked]);
}
diff --git a/apps/desktop/src/features/chat/composer/plugins/suggestion-bridge.ts b/apps/desktop/src/features/chat/composer/plugins/suggestion-bridge.ts
new file mode 100644
index 0000000000..1faedf3a4f
--- /dev/null
+++ b/apps/desktop/src/features/chat/composer/plugins/suggestion-bridge.ts
@@ -0,0 +1,219 @@
+/**
+ * The renderer end of `pi.composer.suggest` (ADR 0332).
+ *
+ * A plugin process offers one line, the shell decides whether the composer can
+ * take it, and the user takes it with Tab, drops it with Esc, or drops it by
+ * typing. This module owns that decision and the single suggestion slot; the
+ * main process owns the two facts the composer cannot know (which session is on
+ * screen, which turn is current) and has already refused a stale offer before it
+ * reaches here.
+ *
+ * The suggestion is never a draft value: it lives beside the draft and shows in
+ * the placeholder layer, so nothing a plugin offers can be sent without the user
+ * accepting it. Every reason the slot can be emptied is handled here:
+ *
+ * - the draft stops being empty (typing, pasting, a chip, `composer.insertText`,
+ * `composer.replaceDraft`) — the composer publishes each change;
+ * - the composer takes input for another session, or stops taking input at all;
+ * - the offer's own lifetime runs out;
+ * - the main process says so: a new turn started, the plugin stopped, or the
+ * plugin asked to clear it.
+ *
+ * A renderer reload and a window close end the whole module with the page, so
+ * there is nothing to hold over.
+ */
+import type { PluginComposerSuggestionRefusal } from "@pi-desktop/plugin-sdk";
+import type { ComposerDraftHandle } from "./draft-bridge";
+
+/** One suggestion the shell may draw in the placeholder layer. */
+export type ComposerSuggestion = {
+ readonly pluginId: string;
+ readonly sessionId: string;
+ readonly turnId?: string;
+ readonly text: string;
+ /** Epoch milliseconds; the line goes away at this moment. */
+ readonly expiresAt: number;
+};
+
+/** What the main process asks the shell to consider. */
+export type ComposerSuggestionOffer = ComposerSuggestion;
+
+/** Whether the offer is on screen now. */
+export type ComposerSuggestionOutcome =
+ | { shown: true }
+ | { shown: false; reason: PluginComposerSuggestionRefusal };
+
+/** Narrowing filter for a host-ordered clear; nothing named means everything. */
+export type ComposerSuggestionFilter = {
+ readonly pluginId?: string;
+ readonly sessionId?: string;
+};
+
+type Live = {
+ readonly sessionId: string;
+ readonly text: string;
+ /** References the draft holds, staged attachments included. */
+ readonly referenceCount: number;
+};
+
+function now(): number {
+ return Date.now();
+}
+
+export class ComposerSuggestionBridge {
+ private readonly handles: ComposerDraftHandle[] = [];
+ private readonly listeners = new Set<() => void>();
+ private current: ComposerSuggestion | null = null;
+ private timer: ReturnType | null = null;
+
+ /** Lend the bridge a composer; the returned call takes it back. */
+ register(handle: ComposerDraftHandle): () => void {
+ this.handles.push(handle);
+ this.reconcile();
+ return () => {
+ const index = this.handles.lastIndexOf(handle);
+ if (index === -1) return;
+ this.handles.splice(index, 1);
+ this.reconcile();
+ };
+ }
+
+ /**
+ * The composer's word that its draft changed. The suggestion belongs to an
+ * empty draft of one session, so a first character, a staged attachment or a
+ * switch of session ends it here — before any render draws it again.
+ */
+ publish(handle: ComposerDraftHandle): void {
+ if (this.handles.at(-1) !== handle) return;
+ this.reconcile();
+ }
+
+ /** The suggestion on screen, or `null`. Stable between changes. */
+ get(): ComposerSuggestion | null {
+ return this.current;
+ }
+
+ subscribe(listener: () => void): () => void {
+ this.listeners.add(listener);
+ return () => {
+ this.listeners.delete(listener);
+ };
+ }
+
+ /**
+ * Consider one offer. Only the composer taking input can answer, so a window
+ * with no composer reports `unsupported` instead of pretending.
+ */
+ offer(offer: ComposerSuggestionOffer): ComposerSuggestionOutcome {
+ const live = this.live();
+ if (!live) return { shown: false, reason: "unsupported" };
+ if (live.sessionId !== offer.sessionId) return { shown: false, reason: "session-not-visible" };
+ if (live.text.length > 0 || live.referenceCount > 0) {
+ return { shown: false, reason: "draft-not-empty" };
+ }
+ // The main process dates the offer when the plugin made it, so an offer
+ // that arrives after its own lifetime describes a moment that is over.
+ if (offer.expiresAt <= now()) return { shown: false, reason: "stale-turn" };
+ this.set({
+ pluginId: offer.pluginId,
+ sessionId: offer.sessionId,
+ ...(offer.turnId ? { turnId: offer.turnId } : {}),
+ text: offer.text,
+ expiresAt: offer.expiresAt,
+ });
+ return { shown: true };
+ }
+
+ /**
+ * Take the suggestion: the draft becomes its text, the caret lands at the end
+ * and the input takes focus, which is exactly what typing that sentence would
+ * have done. The existing references are kept, so an image staged in the
+ * meantime is not lost.
+ */
+ accept(): boolean {
+ const suggestion = this.current;
+ const draft = this.handles.at(-1)?.read() ?? null;
+ if (
+ !suggestion ||
+ !draft ||
+ draft.text.length > 0 ||
+ draft.sessionId !== suggestion.sessionId
+ ) {
+ this.dismiss();
+ return false;
+ }
+ this.dismiss();
+ this.handles
+ .at(-1)
+ ?.write(suggestion.text, [...draft.references], suggestion.text.length, true);
+ return true;
+ }
+
+ /** Drop whatever is on screen. */
+ dismiss(): void {
+ this.set(null);
+ }
+
+ /** A host-ordered clear: one plugin, one session, or everything. */
+ clear(filter: ComposerSuggestionFilter = {}): void {
+ const suggestion = this.current;
+ if (!suggestion) return;
+ if (filter.pluginId && filter.pluginId !== suggestion.pluginId) return;
+ if (filter.sessionId && filter.sessionId !== suggestion.sessionId) return;
+ this.dismiss();
+ }
+
+ private set(next: ComposerSuggestion | null): void {
+ if (this.timer !== null) {
+ clearTimeout(this.timer);
+ this.timer = null;
+ }
+ if (this.current === next) return;
+ this.current = next;
+ if (next) {
+ // A lifetime the shell already spent is not a suggestion any more.
+ const remaining = next.expiresAt - now();
+ this.timer = setTimeout(
+ () => {
+ if (this.current?.expiresAt === next.expiresAt) this.dismiss();
+ },
+ Math.max(0, remaining),
+ );
+ }
+ for (const listener of [...this.listeners]) listener();
+ }
+
+ /** The composer taking input and its draft, or `null`. */
+ private live(): Live | null {
+ const handle = this.handles.at(-1);
+ const draft = handle?.read() ?? null;
+ if (!handle || !draft) return null;
+ return {
+ sessionId: draft.sessionId,
+ text: draft.text,
+ referenceCount: draft.references.length,
+ };
+ }
+
+ /**
+ * End the suggestion when the composer can no longer hold it. Called on every
+ * draft change and on every registration change, so the slot never outlives
+ * the empty draft it was offered for.
+ */
+ private reconcile(): void {
+ const suggestion = this.current;
+ if (!suggestion) return;
+ const live = this.live();
+ if (
+ !live ||
+ live.sessionId !== suggestion.sessionId ||
+ live.text.length > 0 ||
+ live.referenceCount > 0
+ ) {
+ this.dismiss();
+ }
+ }
+}
+
+/** The app window's suggestion slot. */
+export const composerSuggestion = new ComposerSuggestionBridge();
diff --git a/apps/desktop/src/features/chat/composer/plugins/suggestion-keys.ts b/apps/desktop/src/features/chat/composer/plugins/suggestion-keys.ts
new file mode 100644
index 0000000000..9111cdb73d
--- /dev/null
+++ b/apps/desktop/src/features/chat/composer/plugins/suggestion-keys.ts
@@ -0,0 +1,44 @@
+/**
+ * Which key, if any, acts on the composer's plugin suggestion (ADR 0332).
+ *
+ * The composer already has owners for both keys and they keep them: a `@` / `/`
+ * completion list takes `Tab` (and `Enter`), and its own `Escape` closes it
+ * first. Only when neither claims the key, the draft is empty and a suggestion
+ * is on screen does `Tab` take it and `Esc` drop it.
+ *
+ * Pure, so the ordering is tested without a DOM.
+ */
+export type ComposerSuggestionKeyAction = "accept" | "dismiss";
+
+export type ComposerSuggestionKeyEvent = {
+ readonly key: string;
+ readonly shiftKey?: boolean;
+ readonly altKey?: boolean;
+ readonly metaKey?: boolean;
+ readonly ctrlKey?: boolean;
+};
+
+export type ComposerSuggestionKeyState = {
+ /** A suggestion is on screen. */
+ readonly suggestion: boolean;
+ /** The completion list has items, so `Tab` belongs to it. */
+ readonly completionItems: boolean;
+ /** A completion list is open, so the first `Escape` closes it. */
+ readonly completionOpen: boolean;
+};
+
+export function composerSuggestionKeyAction(
+ event: ComposerSuggestionKeyEvent,
+ state: ComposerSuggestionKeyState,
+): ComposerSuggestionKeyAction | null {
+ if (!state.suggestion) return null;
+ if (state.completionItems) return null;
+ const plain = !event.altKey && !event.metaKey && !event.ctrlKey;
+ if (event.key === "Escape") {
+ // The list closes on the first Escape; the suggestion is the second one.
+ if (state.completionOpen) return null;
+ return plain ? "dismiss" : null;
+ }
+ if (event.key !== "Tab" || !plain) return null;
+ return event.shiftKey ? null : "accept";
+}
diff --git a/apps/desktop/src/features/plugins/model.ts b/apps/desktop/src/features/plugins/model.ts
index d483cde5cd..644cc4353d 100644
--- a/apps/desktop/src/features/plugins/model.ts
+++ b/apps/desktop/src/features/plugins/model.ts
@@ -73,6 +73,9 @@ export const PERMISSION_RISK: Record = {
"session.read.own": "medium",
"session.update.own": "medium",
"composer.transform": "medium",
+ // Writes user-facing text into a draft the user may send, but only when the
+ // draft is empty and only through an explicit Tab; it never reads the draft.
+ "composer.suggest": "medium",
// Per-turn counters and session titles only, per the usage.read matrix row.
"usage.read": "medium",
// Two capabilities that reach outside PI-Desktop's own window or read its
diff --git a/apps/desktop/src/lib/api.ts b/apps/desktop/src/lib/api.ts
index b78fe97fca..982a10cb0c 100644
--- a/apps/desktop/src/lib/api.ts
+++ b/apps/desktop/src/lib/api.ts
@@ -1779,6 +1779,79 @@ export const api = {
});
});
},
+ /**
+ * A plugin offered one line for the composer, or the main process ordered
+ * whatever is on screen dropped (`pi.composer.suggest`, ADR 0332).
+ *
+ * The shell answers every offer over `pluginComposerSuggestionResult`, because
+ * only the renderer knows whether the draft can take it. A malformed message
+ * is ignored — nothing here decides whether a plugin's suggestion is valid.
+ */
+ onPluginComposerSuggestion: (
+ listener: (
+ event:
+ | {
+ kind: "offer";
+ requestId: string;
+ pluginId: string;
+ sessionId: string;
+ turnId?: string;
+ text: string;
+ expiresAt: number;
+ }
+ | { kind: "clear"; pluginId?: string; sessionId?: string },
+ ) => void,
+ ) => {
+ if (!window.piDesktop?.on) return () => undefined;
+ return window.piDesktop.on(IPC.event.pluginComposerSuggestion, (payload) => {
+ const event = payload as {
+ kind?: unknown;
+ requestId?: unknown;
+ pluginId?: unknown;
+ sessionId?: unknown;
+ turnId?: unknown;
+ text?: unknown;
+ expiresAt?: unknown;
+ };
+ if (event?.kind === "clear") {
+ listener({
+ kind: "clear",
+ ...(typeof event.pluginId === "string" && event.pluginId
+ ? { pluginId: event.pluginId }
+ : {}),
+ ...(typeof event.sessionId === "string" && event.sessionId
+ ? { sessionId: event.sessionId }
+ : {}),
+ });
+ return;
+ }
+ if (
+ event?.kind !== "offer" ||
+ typeof event.requestId !== "string" ||
+ typeof event.pluginId !== "string" ||
+ typeof event.sessionId !== "string" ||
+ typeof event.text !== "string" ||
+ typeof event.expiresAt !== "number"
+ ) {
+ return;
+ }
+ listener({
+ kind: "offer",
+ requestId: event.requestId,
+ pluginId: event.pluginId,
+ sessionId: event.sessionId,
+ ...(typeof event.turnId === "string" && event.turnId ? { turnId: event.turnId } : {}),
+ text: event.text,
+ expiresAt: event.expiresAt,
+ });
+ });
+ },
+ /** The shell's answer to one composer suggestion the main process is waiting on. */
+ pluginComposerSuggestionResult: (input: {
+ requestId: string;
+ shown: boolean;
+ reason?: string;
+ }) => invoke<{ ok: boolean }>(IPC.invoke.pluginComposerSuggestionResult, input),
onBrowserOpenFile: (listener: (event: { path: string }) => void) => {
if (!window.piDesktop?.on) return () => undefined;
return window.piDesktop.on(IPC.event.browserOpenFile, (payload) => {
diff --git a/apps/desktop/src/styles/composer.css b/apps/desktop/src/styles/composer.css
index a3742d2257..569295a3ab 100644
--- a/apps/desktop/src/styles/composer.css
+++ b/apps/desktop/src/styles/composer.css
@@ -224,6 +224,39 @@
}
}
+/*
+ * A plugin suggestion (`pi.composer.suggest`, ADR 0332) rides in the same
+ * placeholder layer, so it can never cover a message. It reads brighter than
+ * the shell's own placeholder because it is text a person can take with Tab,
+ * not a hint about the box; the hint beside it stays quiet and never wraps.
+ * The layer is always one line with an ellipsis, which is why the text, not
+ * the hint, is what gets truncated on a narrow composer.
+ */
+.composer-placeholder-suggestion {
+ display: flex;
+ align-items: baseline;
+ gap: 8px;
+ color: var(--ds-text-primary);
+ /* The shared fade ends at the placeholder's own weight, not this one's. */
+ animation: none;
+}
+
+.composer-suggestion-text {
+ min-width: 0;
+ overflow: hidden;
+ /* 62% of primary ink: brighter than the shell placeholder's 42% at 0.72. */
+ opacity: 0.62;
+ text-overflow: ellipsis;
+ white-space: nowrap;
+}
+
+.composer-suggestion-hint {
+ flex: none;
+ color: var(--ds-text-secondary);
+ font-size: var(--text-xs);
+ white-space: nowrap;
+}
+
.composer-mode-chip-face {
display: inline-flex;
min-width: 0;
diff --git a/apps/desktop/test/composer-suggestion-relay.test.mjs b/apps/desktop/test/composer-suggestion-relay.test.mjs
new file mode 100644
index 0000000000..820857e602
--- /dev/null
+++ b/apps/desktop/test/composer-suggestion-relay.test.mjs
@@ -0,0 +1,147 @@
+import assert from "node:assert/strict";
+import { register } from "node:module";
+import test from "node:test";
+register(new URL("./helpers/ts-import-hooks.mjs", import.meta.url));
+
+/*
+ * The main-process half of `pi.composer.suggest` (ADR 0332): which offers never
+ * reach the window, which one may answer, and what happens to a suggestion when
+ * the turn or the plugin behind it ends first.
+ */
+const { createComposerSuggestionRelay } = await import(
+ "../electron/main/services/composer-suggestion.ts"
+);
+const { IPC } = await import("@pi-desktop/shared");
+
+const SESSION = "session-1";
+
+function makeRelay({ activeSession = SESSION, answerTimeoutMs = 50 } = {}) {
+ const sent = [];
+ const relay = createComposerSuggestionRelay({
+ sendToRenderer: (channel, payload) => {
+ assert.equal(channel, IPC.event.pluginComposerSuggestion);
+ sent.push(payload);
+ },
+ getActiveSession: () => (activeSession ? { sessionId: activeSession } : null),
+ answerTimeoutMs,
+ });
+ return { relay, sent };
+}
+
+function offer(overrides = {}) {
+ return {
+ pluginId: "demo.suggestion",
+ sessionId: SESSION,
+ turnId: "turn-1",
+ text: "Explain the failing test",
+ ttlMs: 60_000,
+ ...overrides,
+ };
+}
+
+test("a suggestion for a session the user left never crosses to the window", async () => {
+ const { relay, sent } = makeRelay({ activeSession: "session-2" });
+ assert.deepEqual(await relay.offer(offer()), {
+ shown: false,
+ reason: "session-not-visible",
+ });
+ assert.equal(sent.length, 0);
+});
+
+test("the window's answer is what the plugin is told", async () => {
+ const { relay, sent } = makeRelay();
+ const pending = relay.offer(offer());
+
+ assert.equal(sent.length, 1);
+ assert.equal(sent[0].kind, "offer");
+ assert.equal(sent[0].text, "Explain the failing test");
+ assert.equal(sent[0].turnId, "turn-1");
+ assert.ok(sent[0].expiresAt > Date.now());
+
+ assert.equal(relay.settle({ requestId: sent[0].requestId, shown: true }), true);
+ assert.deepEqual(await pending, { shown: true });
+
+ // A second answer to the same request changes nothing.
+ assert.equal(relay.settle({ requestId: sent[0].requestId, shown: true }), false);
+});
+
+test("a draft that cannot take the line is reported with its own reason", async () => {
+ const { relay, sent } = makeRelay();
+ const pending = relay.offer(offer());
+ relay.settle({ requestId: sent[0].requestId, shown: false, reason: "draft-not-empty" });
+ assert.deepEqual(await pending, { shown: false, reason: "draft-not-empty" });
+});
+
+test("a silent window costs the caller a miss, never a hang", async () => {
+ const { relay } = makeRelay({ answerTimeoutMs: 20 });
+ assert.deepEqual(await relay.offer(offer()), { shown: false, reason: "unsupported" });
+});
+
+test("one suggestion per session: the newer offer takes the slot", async () => {
+ const { relay, sent } = makeRelay();
+ const first = relay.offer(offer({ text: "first" }));
+ const second = relay.offer(offer({ pluginId: "other.plugin", text: "second" }));
+
+ assert.deepEqual(await first, { shown: false, reason: "replaced" });
+ assert.equal(sent.at(-1).text, "second");
+ relay.settle({ requestId: sent.at(-1).requestId, shown: true });
+ assert.deepEqual(await second, { shown: true });
+});
+
+test("a new turn clears the line and refuses a suggestion about the old one", async () => {
+ const { relay, sent } = makeRelay();
+ const pending = relay.offer(offer());
+
+ relay.noteTurnStarted(SESSION, "turn-2");
+ assert.deepEqual(await pending, { shown: false, reason: "stale-turn" });
+ assert.deepEqual(sent.at(-1), { kind: "clear", sessionId: SESSION });
+
+ // The turn a plugin answers has been overtaken by the time its text exists.
+ assert.deepEqual(await relay.offer(offer({ turnId: "turn-1" })), {
+ shown: false,
+ reason: "stale-turn",
+ });
+ // A suggestion for the turn that is running now is still allowed through.
+ const current = relay.offer(offer({ turnId: "turn-2" }));
+ relay.settle({ requestId: sent.at(-1).requestId, shown: true });
+ assert.deepEqual(await current, { shown: true });
+});
+
+test("a plugin that stops loses its line, shown or still waiting", async () => {
+ const { relay, sent } = makeRelay();
+ const pending = relay.offer(offer());
+
+ relay.clearPlugin("demo.suggestion");
+ assert.deepEqual(await pending, { shown: false, reason: "unsupported" });
+ assert.deepEqual(sent.at(-1), { kind: "clear", pluginId: "demo.suggestion" });
+
+ // Another plugin's waiting offer is untouched by that clear.
+ const other = relay.offer(offer({ pluginId: "other.plugin" }));
+ const otherOffer = sent.at(-1);
+ relay.clearPlugin("demo.suggestion");
+ relay.settle({ requestId: otherOffer.requestId, shown: true });
+ assert.deepEqual(await other, { shown: true });
+});
+
+test("a plugin's own clear names the plugin and, optionally, the session", () => {
+ const { relay, sent } = makeRelay();
+ relay.clearSuggestion("demo.suggestion", SESSION);
+ assert.deepEqual(sent.at(-1), {
+ kind: "clear",
+ pluginId: "demo.suggestion",
+ sessionId: SESSION,
+ });
+ relay.clearSuggestion("demo.suggestion");
+ assert.deepEqual(sent.at(-1), { kind: "clear", pluginId: "demo.suggestion" });
+});
+
+test("quitting answers every waiting offer and forgets the turn history", async () => {
+ const { relay } = makeRelay();
+ const pending = relay.offer(offer());
+ relay.dispose();
+ assert.deepEqual(await pending, { shown: false, reason: "unsupported" });
+
+
+ // Nothing is left to answer for, so a late word from the window is ignored.
+ assert.equal(relay.settle({ requestId: "gone", shown: true }), false);
+});
diff --git a/apps/desktop/test/composer-suggestion-state.test.mjs b/apps/desktop/test/composer-suggestion-state.test.mjs
new file mode 100644
index 0000000000..15d98a5db7
--- /dev/null
+++ b/apps/desktop/test/composer-suggestion-state.test.mjs
@@ -0,0 +1,236 @@
+import assert from "node:assert/strict";
+import { register } from "node:module";
+import test from "node:test";
+register(new URL("./helpers/ts-import-hooks.mjs", import.meta.url));
+
+/*
+ * The renderer half of `pi.composer.suggest` (ADR 0332): whether an offer can go
+ * on screen, what takes it down, and which key acts on it while the completion
+ * list still owns Tab and the first Escape.
+ */
+const { ComposerSuggestionBridge } = await import(
+ "../src/features/chat/composer/plugins/suggestion-bridge.ts"
+);
+const { composerSuggestionKeyAction } = await import(
+ "../src/features/chat/composer/plugins/suggestion-keys.ts"
+);
+
+const SESSION = "session-1";
+const TURN = "turn-1";
+
+/** A composer that takes input, as `usePluginComposerBridge` lends one. */
+function makeHandle({
+ sessionId = SESSION,
+ text = "",
+ references = [],
+ caret = null,
+} = {}) {
+ return {
+ state: { sessionId, text, references, caret, focused: false },
+ read() {
+ return {
+ draftKey: this.state.sessionId || "home",
+ sessionId: this.state.sessionId,
+ text: this.state.text,
+ references: this.state.references,
+ };
+ },
+ focused() {
+ return this.state.focused;
+ },
+ selection() {
+ const end = this.state.caret ?? this.state.text.length;
+ return { start: end, end };
+ },
+ write(nextText, nextReferences, nextCaret, focus) {
+ this.state.text = nextText;
+ this.state.references = nextReferences;
+ this.state.caret = nextCaret;
+ if (focus) this.state.focused = true;
+ },
+ async stage() {
+ throw new Error("staging is not part of this test");
+ },
+ };
+}
+
+function offer(overrides = {}) {
+ return {
+ pluginId: "demo.suggestion",
+ sessionId: SESSION,
+ turnId: TURN,
+ text: "Explain the failing test",
+ expiresAt: Date.now() + 60_000,
+ ...overrides,
+ };
+}
+
+test("an offer shows only in the empty draft of the session it names", () => {
+ const bridge = new ComposerSuggestionBridge();
+ const handle = makeHandle();
+
+ // No composer takes input: the window says so instead of queueing.
+ assert.deepEqual(bridge.offer(offer()), { shown: false, reason: "unsupported" });
+
+ const unregister = bridge.register(handle);
+ assert.deepEqual(bridge.offer(offer()), { shown: true });
+ assert.equal(bridge.get()?.text, "Explain the failing test");
+ assert.deepEqual(bridge.offer(offer({ sessionId: "session-2" })), {
+ shown: false,
+ reason: "session-not-visible",
+ });
+
+ handle.state.text = "half a sentence";
+ assert.deepEqual(bridge.offer(offer()), { shown: false, reason: "draft-not-empty" });
+
+ // A staged attachment is a draft too, even with no text at all.
+ handle.state.text = "";
+ handle.state.references = [{ id: "ref-1" }];
+ assert.deepEqual(bridge.offer(offer()), { shown: false, reason: "draft-not-empty" });
+
+ unregister();
+ assert.equal(bridge.get(), null);
+});
+
+test("an offer that is already over never appears", () => {
+ const bridge = new ComposerSuggestionBridge();
+ bridge.register(makeHandle());
+ assert.deepEqual(bridge.offer(offer({ expiresAt: Date.now() - 1 })), {
+ shown: false,
+ reason: "stale-turn",
+ });
+ assert.equal(bridge.get(), null);
+});
+
+test("Tab writes the suggestion into the draft, keeps references, and ends it", () => {
+ const bridge = new ComposerSuggestionBridge();
+ const image = { id: "image-1" };
+ const handle = makeHandle({ references: [] });
+ bridge.register(handle);
+ // The draft is empty when the offer lands; an image staged afterwards keeps
+ // the suggestion, because a reference is not text.
+ assert.deepEqual(bridge.offer(offer({ text: "Explain the failing test" })), { shown: true });
+ handle.state.references = [image];
+
+ assert.equal(bridge.accept(), true);
+ assert.equal(handle.state.text, "Explain the failing test");
+ assert.equal(handle.state.caret, "Explain the failing test".length);
+ assert.equal(handle.state.focused, true);
+ assert.deepEqual(handle.state.references, [image]);
+ assert.equal(bridge.get(), null);
+});
+
+test("taking a suggestion the draft no longer fits is refused, not applied", () => {
+ const bridge = new ComposerSuggestionBridge();
+ const handle = makeHandle();
+ bridge.register(handle);
+ bridge.offer(offer());
+ // The user typed in the same beat; the draft wins.
+ handle.state.text = "mine";
+
+ assert.equal(bridge.accept(), false);
+ assert.equal(handle.state.text, "mine");
+ assert.equal(bridge.get(), null);
+});
+
+test("typing, switching session and losing the composer all end the suggestion", () => {
+ const bridge = new ComposerSuggestionBridge();
+ const handle = makeHandle();
+ bridge.register(handle);
+
+ bridge.offer(offer());
+ handle.state.text = "x";
+ bridge.publish(handle);
+ assert.equal(bridge.get(), null, "a first character ends it");
+
+ handle.state.text = "";
+ bridge.offer(offer());
+ handle.state.sessionId = "session-2";
+ bridge.publish(handle);
+ assert.equal(bridge.get(), null, "the draft of another session ends it");
+
+ handle.state.sessionId = SESSION;
+ bridge.offer(offer());
+ handle.state.text = "restored";
+ bridge.publish(handle);
+ handle.state.text = "";
+ bridge.publish(handle);
+ assert.equal(bridge.get(), null, "a suggestion never comes back after a change");
+
+ bridge.offer(offer());
+ assert.equal(bridge.get()?.text, "Explain the failing test");
+});
+
+test("the host's clear names a plugin, a session, or nothing", () => {
+ const bridge = new ComposerSuggestionBridge();
+ bridge.register(makeHandle());
+
+ bridge.offer(offer());
+ bridge.clear({ pluginId: "other.plugin" });
+ assert.notEqual(bridge.get(), null, "another plugin's clear is not mine");
+
+ bridge.clear({ pluginId: "demo.suggestion", sessionId: "session-2" });
+ assert.notEqual(bridge.get(), null, "another session's clear is not this one");
+
+ bridge.clear({ pluginId: "demo.suggestion" });
+ assert.equal(bridge.get(), null);
+
+ bridge.offer(offer());
+ bridge.clear();
+ assert.equal(bridge.get(), null, "an unfiltered clear drops everything");
+});
+
+test("a newer suggestion takes the slot, and the old one expires on its own clock", async () => {
+ const bridge = new ComposerSuggestionBridge();
+ bridge.register(makeHandle());
+
+ bridge.offer(offer({ text: "first" }));
+ bridge.offer(offer({ pluginId: "other.plugin", text: "second" }));
+ assert.equal(bridge.get()?.text, "second");
+ assert.equal(bridge.get()?.pluginId, "other.plugin");
+
+ bridge.offer(offer({ text: "short-lived", expiresAt: Date.now() + 20 }));
+ assert.equal(bridge.get()?.text, "short-lived");
+ await new Promise((resolve) => setTimeout(resolve, 80));
+ assert.equal(bridge.get(), null, "a suggestion ends when its lifetime does");
+});
+
+test("listeners see every change of the slot", () => {
+ const bridge = new ComposerSuggestionBridge();
+ bridge.register(makeHandle());
+ let changes = 0;
+ const off = bridge.subscribe(() => {
+ changes += 1;
+ });
+
+ bridge.offer(offer());
+ bridge.dismiss();
+ off();
+ bridge.offer(offer());
+ assert.equal(changes, 2);
+});
+
+test("the completion list keeps Tab, and the first Escape closes it", () => {
+ const tab = { key: "Tab" };
+ const escape = { key: "Escape" };
+ const showing = { suggestion: true, completionItems: false, completionOpen: false };
+ const listOpen = { suggestion: true, completionItems: true, completionOpen: true };
+
+ assert.equal(composerSuggestionKeyAction(tab, showing), "accept");
+ assert.equal(composerSuggestionKeyAction(escape, showing), "dismiss");
+ assert.equal(composerSuggestionKeyAction(tab, listOpen), null, "the list owns Tab");
+ assert.equal(
+ composerSuggestionKeyAction(escape, { ...listOpen, completionItems: false }),
+ null,
+ "the first Escape closes the list",
+ );
+ assert.equal(
+ composerSuggestionKeyAction(tab, { ...showing, suggestion: false }),
+ null,
+ "no suggestion, no key",
+ );
+ assert.equal(composerSuggestionKeyAction({ key: "Tab", shiftKey: true }, showing), null);
+ assert.equal(composerSuggestionKeyAction({ key: "Tab", metaKey: true }, showing), null);
+ assert.equal(composerSuggestionKeyAction({ key: "Enter" }, showing), null);
+ assert.equal(composerSuggestionKeyAction({ key: "Escape", altKey: true }, showing), null);
+});
diff --git a/apps/desktop/test/plugin-composer-suggestion.test.mjs b/apps/desktop/test/plugin-composer-suggestion.test.mjs
new file mode 100644
index 0000000000..ca646b8919
--- /dev/null
+++ b/apps/desktop/test/plugin-composer-suggestion.test.mjs
@@ -0,0 +1,220 @@
+import assert from "node:assert/strict";
+import { fork } from "node:child_process";
+import { mkdtempSync, readFileSync, writeFileSync } from "node:fs";
+import test from "node:test";
+import { tmpdir } from "node:os";
+import { dirname, join } from "node:path";
+import { register } from "node:module";
+import { fileURLToPath, pathToFileURL } from "node:url";
+
+const here = dirname(fileURLToPath(import.meta.url));
+const dataDir = mkdtempSync(join(tmpdir(), "pi-composer-suggestion-data-"));
+process.env.PI_DESKTOP_DATA_DIR = dataDir;
+const desktopRoot = join(here, "..");
+const hostProcessEntry = join(desktopRoot, "electron/main/plugin-host-process.mjs");
+register(pathToFileURL(join(here, "helpers/ts-import-hooks.mjs")));
+const { PluginRuntime } = await import("../electron/main/plugin-runtime.ts");
+const {
+ PLUGIN_COMPOSER_SUGGESTION_MAX_CHARS,
+ PLUGIN_COMPOSER_SUGGESTION_TTL_MS,
+ PLUGIN_COMPOSER_SUGGESTION_TTL_MAX_MS,
+} = await import("@pi-desktop/plugin-sdk");
+
+function forkPluginProcess({ entry }) {
+ const child = fork(entry, [], { stdio: ["ignore", "pipe", "pipe", "ipc"] });
+ return {
+ postMessage: (message) => {
+ if (child.connected) child.send(message);
+ },
+ onMessage: (handler) => child.on("message", handler),
+ onExit: (handler) => child.on("exit", (code) => handler(code ?? 0)),
+ kill: () => child.kill(),
+ };
+}
+
+function writePlugin({ id, permissions = [], main }) {
+ const dir = mkdtempSync(join(tmpdir(), "pi-composer-suggestion-plugin-"));
+ writeFileSync(
+ join(dir, "manifest.json"),
+ JSON.stringify({ schemaVersion: 1, id, name: id, version: "0.0.1", main: "main.js", permissions }),
+ "utf8",
+ );
+ writeFileSync(join(dir, "main.js"), main, "utf8");
+ return dir;
+}
+
+function makeRuntime(t, services = {}) {
+ const audits = [];
+ const toasts = [];
+ const runtime = new PluginRuntime({
+ hostEntry: hostProcessEntry,
+ spawnProcess: forkPluginProcess,
+ getLocale: () => "en",
+ showToast: (message) => toasts.push(message),
+ audit: (entry) => audits.push(entry),
+ ...services,
+ });
+ t.after(async () => {
+ for (const loaded of runtime.listLoaded()) await runtime.unload(loaded.manifest.id);
+ });
+ return { runtime, audits, toasts };
+}
+
+/** Wait for the plugin's own report, which arrives after its `onLoad`. */
+async function lastToast(toasts, expected) {
+ for (let attempt = 0; attempt < 200; attempt += 1) {
+ if (toasts.length > 0 && toasts.at(-1).startsWith(expected)) return toasts.at(-1);
+ await new Promise((resolve) => setTimeout(resolve, 20));
+ }
+ throw new Error(`no ${expected} toast; got ${JSON.stringify(toasts)}`);
+}
+
+test("a suggestion crosses from the plugin process with the text the shell draws", async (t) => {
+ const offers = [];
+ const { runtime, audits, toasts } = makeRuntime(t, {
+ isPluginActiveInProject: () => true,
+ suggestComposer: async (offer) => {
+ offers.push(offer);
+ return { shown: true };
+ },
+ });
+ const dir = writePlugin({
+ id: "demo.suggestion",
+ permissions: ["composer.suggest"],
+ main: `module.exports = {
+ onLoad: async () => {
+ const result = await pi.composer.suggest({
+ sessionId: " session-1 ",
+ turnId: "turn-1",
+ text: " Write\\nthe failing test ",
+ ttlMs: 5000,
+ });
+ await pi.ui.showToast(JSON.stringify(result));
+ },
+ };`,
+ });
+
+ await runtime.loadFromPath(dir);
+ assert.equal(await lastToast(toasts, "{"), '{"shown":true}');
+ assert.deepEqual(offers, [
+ {
+ pluginId: "demo.suggestion",
+ sessionId: "session-1",
+ turnId: "turn-1",
+ text: "Write the failing test",
+ ttlMs: 5000,
+ },
+ ]);
+ assert.equal(audits.some((entry) => entry.api === "composer.suggest" && entry.ok), true);
+});
+
+test("the host bounds the text and the lifetime instead of refusing them", async (t) => {
+ const offers = [];
+ const { runtime, toasts } = makeRuntime(t, {
+ isPluginActiveInProject: () => true,
+ suggestComposer: async (offer) => {
+ offers.push(offer);
+ return { shown: false, reason: "draft-not-empty" };
+ },
+ });
+ const dir = writePlugin({
+ id: "demo.suggestion.bounds",
+ permissions: ["composer.suggest"],
+ main: `module.exports = {
+ onLoad: async () => {
+ await pi.composer.suggest({ sessionId: "s", text: "x".repeat(500) });
+ await pi.composer.suggest({ sessionId: "s", text: "y", ttlMs: 9_000_000 });
+ await pi.ui.showToast(JSON.stringify(await pi.composer.suggest({ sessionId: "s", text: "z" })));
+ },
+ };`,
+ });
+
+ await runtime.loadFromPath(dir);
+ assert.equal(await lastToast(toasts, "{"), '{"shown":false,"reason":"draft-not-empty"}');
+ assert.equal(offers[0].text.length, PLUGIN_COMPOSER_SUGGESTION_MAX_CHARS);
+ assert.equal(offers[1].ttlMs, PLUGIN_COMPOSER_SUGGESTION_TTL_MAX_MS);
+ assert.equal(offers[2].ttlMs, PLUGIN_COMPOSER_SUGGESTION_TTL_MS);
+});
+
+test("a suggestion for a session the shell is not showing is a miss, not a throw", async (t) => {
+ const { runtime, toasts } = makeRuntime(t, {
+ // The plugin is scoped to another project, so this conversation is not its.
+ isPluginActiveInProject: () => false,
+ suggestComposer: async () => {
+ throw new Error("the shell must not be asked");
+ },
+ });
+ const dir = writePlugin({
+ id: "demo.suggestion.scope",
+ permissions: ["composer.suggest"],
+ main: `module.exports = {
+ onLoad: async () => {
+ const result = await pi.composer.suggest({ sessionId: "session-1", text: "hi" });
+ await pi.ui.showToast(JSON.stringify(result));
+ },
+ };`,
+ });
+
+ await runtime.loadFromPath(dir);
+ assert.equal(await lastToast(toasts, "{"), '{"shown":false,"reason":"session-not-visible"}');
+});
+
+test("without the grant the call fails, and no suggestion is offered", async (t) => {
+ const offers = [];
+ const { runtime, toasts } = makeRuntime(t, {
+ suggestComposer: async (offer) => {
+ offers.push(offer);
+ return { shown: true };
+ },
+ });
+ const dir = writePlugin({
+ id: "demo.suggestion.denied",
+ permissions: ["composer.suggest"],
+ main: `module.exports = {
+ onLoad: async () => {
+ try {
+ await pi.composer.suggest({ sessionId: "session-1", text: "hi" });
+ await pi.ui.showToast("NO_ERROR");
+ } catch (error) {
+ await pi.ui.showToast("ERR:" + (error && error.code ? error.code : String(error)));
+ }
+ },
+ };`,
+ });
+
+ // Granted nothing: the manifest declares the permission, the user did not.
+ await runtime.loadFromPath(dir, []);
+ assert.equal(await lastToast(toasts, "ERR:"), "ERR:PERMISSION_DENIED");
+ assert.deepEqual(offers, []);
+});
+
+test("a plugin's own clear reaches the shell, and a malformed call does not", async (t) => {
+ const cleared = [];
+ const { runtime, toasts } = makeRuntime(t, {
+ suggestComposer: async () => ({ shown: true }),
+ clearComposerSuggestion: (pluginId, sessionId) => cleared.push([pluginId, sessionId]),
+ });
+ const dir = writePlugin({
+ id: "demo.suggestion.clear",
+ permissions: ["composer.suggest"],
+ main: `module.exports = {
+ onLoad: async () => {
+ await pi.composer.clearSuggestion({ sessionId: "session-1" });
+ await pi.composer.clearSuggestion();
+ try {
+ await pi.composer.suggest({ sessionId: " ", text: "hi" });
+ await pi.ui.showToast("NO_ERROR");
+ } catch (error) {
+ await pi.ui.showToast("ERR:" + (error && error.code ? error.code : String(error)));
+ }
+ },
+ };`,
+ });
+
+ await runtime.loadFromPath(dir);
+ assert.equal(await lastToast(toasts, "ERR:"), "ERR:INVALID_PARAMS");
+ assert.deepEqual(cleared, [
+ ["demo.suggestion.clear", "session-1"],
+ ["demo.suggestion.clear", undefined],
+ ]);
+});
diff --git a/docs/adr/0332-plugin-composer-suggestion.md b/docs/adr/0332-plugin-composer-suggestion.md
new file mode 100644
index 0000000000..676cab0c93
--- /dev/null
+++ b/docs/adr/0332-plugin-composer-suggestion.md
@@ -0,0 +1,124 @@
+# ADR 0332: A plugin-owned suggestion in the Composer placeholder
+
+- Status: Accepted
+- Date: 2026-10-24
+- Deciders: PI-Desktop maintainers
+- Related: [ADR 0324](0324-plugin-owned-composer-prompt-enhancement.md) ·
+ [ADR 0331](0331-plugin-session-follow-and-work-panel-reveal.md) ·
+ [07-plugins/03-plugin-api](../spec/07-plugins/03-plugin-api.md) ·
+ [07-plugins/13-plugin-permissions-matrix](../spec/07-plugins/13-plugin-permissions-matrix.md)
+
+## Context
+
+After a turn ends, a plugin often knows something the user would plausibly type
+next: a follow-up question, a "continue" instruction, a correction. The only
+surfaces a plugin has today are announcements that interrupt (a toast, a
+notification, a work-panel view) or a rewrite of text the user already wrote
+(`composer.transform`). None of them fits a suggestion: it must be visible where
+the user is already looking, carried by no chrome, and trivial to ignore.
+
+The pipeline that produces such a line is the expensive part. A plugin listens
+for `session:turnEnded`, reads the session with `pi.session.getLlmContext`, runs
+its own `pi.agent.complete` (up to 90 s), and only then has text. So "generate"
+and "show" are seconds apart, and in that window the user may have typed,
+switched session, started another turn, or uninstalled the plugin. Any contract
+that assumes the composer is unchanged when the answer arrives is wrong.
+
+The host already owns every piece needed to make this safe: the renderer owns
+the draft and the placeholder layer, `activeTurns` owns turn identity, and
+`composer.transform` (ADR 0324) established the permission, audit, and refusal
+vocabulary for plugin text that reaches the Composer.
+
+## Decision
+
+1. Add `pi.composer.suggest({ sessionId, turnId?, text, ttlMs? })` and
+ `pi.composer.clearSuggestion({ sessionId? })` to the Plugin SDK, gated by the
+ new `composer.suggest` permission. `suggest` resolves
+ `{ shown: true }` or `{ shown: false, reason }` with
+ `session-not-visible` / `draft-not-empty` / `stale-turn` / `replaced` /
+ `unsupported`. Only malformed input throws (`INVALID_PARAMS`).
+2. Split the decision by ownership instead of centralizing it:
+ - Main refuses what it can see without the renderer — a session that is not
+ the one on screen, and a `turnId` that a later `onTurnStarted` overtook —
+ and relays the rest, then waits for the renderer's answer.
+ - The renderer refuses the rest — no composer, a blocked composer, a draft
+ with text or an attachment — and answers over a dedicated invoke. The
+ plugin receives that answer, so a miss is data it can log rather than an
+ exception.
+ Main never writes renderer state; it sends a message, exactly like
+ `pi.ui.revealView` (ADR 0331).
+3. Model the suggestion as a slot beside the draft, not inside it. The text is
+ drawn in the existing `.composer-placeholder` layer while `value` is empty, so
+ no new overlay can cover a message. `Tab` writes it into the draft (caret at
+ the end, focus in the input, staged references kept); `Esc` drops it; a first
+ character, a send, a session switch, a new turn, a plugin stop, a reload or a
+ window close drops it too. One suggestion exists per session, and a newer
+ offer replaces the older one.
+4. Keep the existing key owners. A `@` / `/` completion list keeps `Tab`, and an
+ open list keeps the first `Esc`; the suggestion acts only when neither claims
+ the key. The keys live in a pure decision function so that ordering is
+ testable without a DOM.
+5. Draw it brighter than the shell's own placeholder (62% primary ink versus
+ 72% secondary) with a `Tab` / `Esc` hint beside it, on one line with an
+ ellipsis, and announce it once through an `sr-only` polite live region.
+ `aria-placeholder` keeps describing the input, because the suggestion is not
+ what the field is for.
+6. Classify `composer.suggest` as **medium** risk and confirm it at install. It
+ cannot read the draft, cannot send, and cannot outlive an empty draft, but it
+ can put text in front of a user who may accept it with one key — the same
+ trust shape as `composer.transform`.
+
+## Consequences
+
+- A plugin can propose the next message where the user is already looking,
+ without a notification, a bubble, or a panel, and it learns immediately
+ whether the suggestion was taken up.
+- The shell keeps the composer authoritative: a suggestion is decorative state
+ that the Composer discards on its own terms and that a plugin cannot promote
+ into a draft.
+- The answer to `suggest` costs one renderer round trip and a bounded wait
+ (`answerTimeoutMs`, 2 s). A window that is gone, hung, or reloading answers
+ nothing, and the caller is told `unsupported` instead of being left to hang.
+- Suggestion text is capped at 200 characters after line breaks and runs of
+ whitespace are folded, so a plugin that asked for a paragraph still gets a
+ usable result instead of an error it cannot repair inside a turn.
+- The permission list, the manifest schema page, the permissions matrix, the
+ plugin API spec, and the nine shipped catalogs all gain one entry; no plugin
+ manifest schema version, host-core schema, or persisted format changes.
+- Plugins that never declare `composer.suggest` are unaffected: the namespace
+ exists, the permission is not granted, and the call fails closed with
+ `PERMISSION_DENIED` exactly like every other ungranted host API.
+
+## Alternatives considered
+
+### Let the plugin's own renderer module call `pi.dispatch("composer.setSuggestion")`
+
+Rejected as the primary path. The text is produced by the plugin *process*
+after a 90 s completion, and there is no process → renderer-module channel in
+the SDK, so a renderer module would have to poll or the process would have to
+own a second, invented transport. The process already has an established host
+API route, and the reverse direction (a renderer module asking its own process
+for an answer) is already `plugin.call`.
+
+### A message, a toast, or an inline transcript row
+
+Rejected: all three interrupt or occupy transcript space for a hint the user
+may ignore, and none of them can become the user's own text.
+
+### Store the suggestion as a draft value the user deletes
+
+Rejected: it makes plugin text indistinguishable from typed text, breaks the
+"empty draft" invariant other features rely on, and would let a suggestion be
+sent without an explicit accept.
+
+### Report `shown` optimistically and clear later
+
+Rejected: the point of the answer is that the plugin can stop spending
+completions on a user who is not looking at that session. `draft-not-empty` and
+`session-not-visible` are exactly the cases where a guess would be wrong.
+
+### Change `aria-placeholder` while a suggestion is shown
+
+Rejected: the field's purpose does not change with the suggestion, and a
+placeholder change is announced differently across screen readers. A polite
+live region says the line once without re-describing the input.
diff --git a/docs/adr/README.md b/docs/adr/README.md
index f1701486a8..bb90e9f675 100644
--- a/docs/adr/README.md
+++ b/docs/adr/README.md
@@ -378,6 +378,7 @@ Each ADR includes:
| 0329 | [Isolate parallel sessions of one project in git worktrees](0329-session-worktree-isolation.md) | Accepted (Windows E2E pending) |
| 0330 | [Open scoped HTML files in the work-panel Browser from plugins](0330-open-html-files-in-work-panel-browser-from-plugins.md) | Accepted |
| 0331 | [Plugin session follow and host-owned work-panel reveal](0331-plugin-session-follow-and-work-panel-reveal.md) | Accepted |
+| 0332 | [A plugin-owned suggestion in the Composer placeholder](0332-plugin-composer-suggestion.md) | Accepted |
| plugin-fetch-redirect-policy | [Host-enforced plugin fetch redirect policy](plugin-fetch-redirect-policy.md) | Accepted (implementation candidate for #1475) |
| local-agent-remote-workspace-tools | [Local Agent and model requests for remote workspaces](local-agent-remote-workspace-tools.md) | Accepted for implementation |
diff --git a/docs/plugin-development.md b/docs/plugin-development.md
index 208d33eda6..54e68ccb74 100644
--- a/docs/plugin-development.md
+++ b/docs/plugin-development.md
@@ -24,6 +24,7 @@ A plugin can contribute one or more of these capabilities:
| Service | Resident work supervised by the host | `contributes.services`, `background.service` permission |
| Message bus | Typed-by-convention events between plugins | `contributes.bus`, bus permissions |
| Renderer slot | UI drawn inside the app's own window: composer controls, message action bars, blocks below a reply, tool cards, code-block renderers, corner layers | `renderer`, `renderer.extension` permission, `packages/plugin-sdk/src/renderer.ts` |
+| Composer suggestion | One dismissible line offered to the input box, taken with Tab | `pi.composer.suggest`, `composer.suggest` permission |
Plugin entry code runs in a dedicated Node process. Panels run in sandboxed,
context-isolated Electron windows with no Node integration. Calls from either
diff --git a/docs/spec/06-delivery/04-e2e-test-plan.md b/docs/spec/06-delivery/04-e2e-test-plan.md
index 5b00986fae..a3ffd74f79 100644
--- a/docs/spec/06-delivery/04-e2e-test-plan.md
+++ b/docs/spec/06-delivery/04-e2e-test-plan.md
@@ -18356,3 +18356,29 @@ host-created files. The full app's file-preview viewer is covered separately.
- **Milestone:** Maintenance.
- **Status:** Automated fixture; record the tested head/base and execution
result in the delivery report.
+
+#### E2E-1175: A plugin suggestion rides in the Composer placeholder and is taken with Tab
+
+- **Preconditions**: A plugin that declares `composer.suggest` is installed,
+ enabled, and granted the permission, and it offers one line on
+ `session:turnEnded` after its own completion.
+- **Steps:** 1) Run an Agent turn in a session and let it complete while that
+ session is on screen and its Composer is empty. 2) Observe the placeholder
+ layer. 3) Press Tab. 4) Repeat, then press Esc. 5) Repeat, then type one
+ character. 6) Repeat, then switch session before the offer arrives.
+- **Expected**: The suggestion appears in the placeholder layer of an empty
+ draft, brighter than the shell placeholder and on one line with an ellipsis,
+ with a `Tab` / `Esc` hint and one polite announcement. Tab writes the exact
+ text into the draft with the caret at the end and the input focused, keeping
+ any staged attachment; Esc drops it; a first character drops it; a missed
+ offer answers `{ shown: false, reason }` and shows nothing. No transcript row,
+ toast, or overlay appears, and the plugin's call is audited.
+- **Specs linked**: `07-plugins/03-plugin-api.md`,
+ `07-plugins/13-plugin-permissions-matrix.md`, ADR 0332.
+- **Acceptance**: A (Composer entry path), Security (permission-gated, never
+ sent by the plugin).
+- **Milestone**: M6+
+- **Status**: Unit/source-contract-covered by
+ `composer-suggestion-state.test.mjs`, `composer-suggestion-relay.test.mjs`,
+ and `plugin-composer-suggestion.test.mjs`; the rendered journey remains a
+ manual/Electron check when this surface changes.
diff --git a/docs/spec/07-plugins/02-plugin-manifest-schema.md b/docs/spec/07-plugins/02-plugin-manifest-schema.md
index 6d066366c0..04927bcf12 100644
--- a/docs/spec/07-plugins/02-plugin-manifest-schema.md
+++ b/docs/spec/07-plugins/02-plugin-manifest-schema.md
@@ -391,6 +391,7 @@ type PluginPermission =
| "agent.prompt.inject"
| "agent.complete"
| "composer.transform"
+| "composer.suggest"
| "renderer.extension"
| "provider.register"
| "provider.oauth"
diff --git a/docs/spec/07-plugins/03-plugin-api.md b/docs/spec/07-plugins/03-plugin-api.md
index 5946b678bb..041dea6304 100644
--- a/docs/spec/07-plugins/03-plugin-api.md
+++ b/docs/spec/07-plugins/03-plugin-api.md
@@ -177,6 +177,70 @@ separately declares the permissions required by that API, such as
}
```
+### Composer suggestions (`composer.suggest`)
+
+A plugin may offer one short line for the Composer of the session the user is
+looking at. It is drawn in the placeholder layer while the draft is empty, the
+user takes it with `Tab` or drops it with `Esc`, and typing drops it too. It is
+never a message, never a bubble, and the plugin cannot send it.
+
+```ts
+pi.composer.suggest(input: {
+ sessionId: string; // the session from session:turnEnded
+ turnId?: string; // the turn the text answers; an overtaken turn is refused
+ text: string; // one line; folded and cut at 200 characters
+ ttlMs?: number; // default 120000; clamped to 1000..600000
+}): Promise<{ shown: true } | {
+ shown: false;
+ reason:
+ | "session-not-visible" // that session is not on screen
+ | "draft-not-empty" // the user has text or an attachment in the draft
+ | "stale-turn" // the session ran a newer turn
+ | "replaced" // a newer suggestion took the slot first
+ | "unsupported"; // no window, no composer, or no answer in time
+}>
+
+pi.composer.clearSuggestion(input?: { sessionId?: string }): Promise<{ ok: true }>
+```
+
+Both calls need `composer.suggest`. A place that will not show the line is not
+an error: the call resolves `{ shown: false, reason }` so a plugin can log the
+miss and decide whether to spend another completion. Malformed input (an empty
+`sessionId`, text with nothing visible in it, a non-numeric `ttlMs`) throws
+`INVALID_PARAMS` like every other host API, and a missing grant throws
+`PERMISSION_DENIED`.
+
+The host shows a suggestion only when all of the following hold, and checks
+them again on every change: the named session is the one on screen, the draft
+is empty (no text and no attachment), the named turn is still the session's
+newest turn, and a composer is mounted and taking input. One suggestion exists
+per session; a newer offer replaces it and answers the superseded caller with
+`replaced`. The line is cleared by: any draft change (typing, pasting, an
+attachment, `composer.insertText`, `composer.replaceDraft`), a send, a session
+switch, a new turn starting, the plugin unloading or being disabled,
+`pi.composer.clearSuggestion`, a renderer reload, a window close, and the
+suggestion's own lifetime running out. Taking it (`Tab`) puts the text in the
+draft with the caret at the end and keeps any attachment already staged.
+
+The call is audited with the plugin id, the session, and whether the line was
+shown. A plugin that generates the text with a model also declares that API's
+permissions, such as `agent.complete` and `models.list`.
+
+```js
+pi.events.on("session:turnEnded", async (event) => {
+ if (event.reason !== "completed") return;
+ const active = await pi.session.getActive();
+ if (active?.sessionId !== event.sessionId) return;
+ const text = await writeNextLine(active); // the plugin's own model request
+ if (!text) return;
+ await pi.composer.suggest({
+ sessionId: event.sessionId,
+ turnId: event.turnId,
+ text,
+ });
+});
+```
+
### speech (`speech.adapter.register`)
```ts
pi.speech.registerAdapter(adapter: {
diff --git a/docs/spec/07-plugins/13-plugin-permissions-matrix.md b/docs/spec/07-plugins/13-plugin-permissions-matrix.md
index a597b753c4..e124de0ab3 100644
--- a/docs/spec/07-plugins/13-plugin-permissions-matrix.md
+++ b/docs/spec/07-plugins/13-plugin-permissions-matrix.md
@@ -25,6 +25,7 @@ Provide a permission–capability–risk–default-policy reference table for re
| `agent.tool.register` | high | Register an agent tool | Confirm at install | Tool execution is audited separately |
| `agent.prompt.inject` | high | Inject a system prompt; activates `contributes.skills` | Deny by default / strong confirmation | Easily leads to behavior hijacking |
| `composer.transform` | medium | `contributes.composerTransforms` and `onComposerTransform` | Confirm at install | Runs only after an explicit Composer action. Receives the draft and optional model key, not session history or separate attachment/file-reference metadata; request and result are capped at 100,000 characters and audited |
+| `composer.suggest` | medium | `pi.composer.suggest` / `pi.composer.clearSuggestion` | Confirm at install | Writes one dismissible line into the placeholder layer of the Composer for the session on screen, only while the draft is empty and only for the turn the plugin names. The user takes it with Tab, drops it with Esc, and typing, sending, a session switch, a new turn, the plugin stopping, a reload or a window close all end it. The plugin never sends it and never reads the draft. Text is folded to one line and cut at 200 characters; the lifetime defaults to 120 s and is capped at 10 minutes. Audited; a place that will not show it answers `{ shown: false, reason }` instead of throwing |
| `agent.extension` | high | Run `contributes.agentExtensions` modules inside the agent process | Explicit confirmation; local imports and development plugins only in v1.1 | Same access as the agent's own tools; the plugin sandbox does not apply (spec 16) |
| `renderer.extension` | high | `manifest.renderer` is evaluated inside the host renderer to mount UI slots; `rendererActions` and `rendererCallMethods` open the actions and `onRendererCall` methods that module may use | Explicit confirmation; local imports and development plugins only in v1.1, matching `agent.extension` | The module shares the host's own document, so a slot is a contract rather than a sandbox. A component may dispatch only the reviewed vocabulary (`plugin.call`, `composer.insertText`, `composer.readDraft`, `composer.replaceDraft`, `attachments.add` / `list` / `remove`), capped at 16, and `plugin.call` reaches only the calling plugin's own `onRendererCall` methods, capped at 32. Registrations are withdrawn when the plugin unloads; a self-drawn dialog lives in a layer the plugin opened itself |
| `provider.register` | high | `contributes.providers` become rows in the native provider list, owned by the plugin and refreshed from the manifest on load; unconfigured API-key rows with an endpoint also appear in Add Service, grouped by optional `category` and with optional hover/focus `description` | Explicit confirmation; local imports and development plugins only in v1.1, matching `agent.extension` | The user path refuses edits to the row (`PROVIDER_OWNED_BY_PLUGIN`); Add Service saves the key through the existing Host secret path. Only loaded plugins with this grant contribute entries; the chooser does not expose secrets or run plugin code. An empty API-key model list discovers models after key save. |
@@ -162,6 +163,7 @@ so "Modify the files it lists" is followed by the list.
| `usage.read` | Read usage statistics | 读取用量统计 |
| `agent.complete` | Run a one-shot completion with your models | 用你的模型发起一次补全 |
| `composer.transform` | Transform text in the Composer | 转换输入框中的文本 |
+| `composer.suggest` | Offer a suggestion in the Composer | 在输入框中给出建议 |
| `speech.adapter.register` | Register a speech adapter | 注册语音适配器 |
| `audio.capture.background` | Use the microphone in the background | 后台使用麦克风 |
| `audio.playback.background` | Play audio in the background | 后台播放声音 |
diff --git a/docs/zh-CN/spec/07-plugins/02-plugin-manifest-schema.md b/docs/zh-CN/spec/07-plugins/02-plugin-manifest-schema.md
index fc36a903cb..1c16423f56 100644
--- a/docs/zh-CN/spec/07-plugins/02-plugin-manifest-schema.md
+++ b/docs/zh-CN/spec/07-plugins/02-plugin-manifest-schema.md
@@ -323,6 +323,7 @@ type PluginPermission =
| "agent.prompt.inject"
| "agent.complete"
| "composer.transform"
+| "composer.suggest"
| "renderer.extension"
| "provider.register"
| "net.fetch"
diff --git a/docs/zh-CN/spec/07-plugins/03-plugin-api.md b/docs/zh-CN/spec/07-plugins/03-plugin-api.md
index 8cbf6bc9db..ad5808c5e2 100644
--- a/docs/zh-CN/spec/07-plugins/03-plugin-api.md
+++ b/docs/zh-CN/spec/07-plugins/03-plugin-api.md
@@ -149,6 +149,62 @@ type PluginModule = {
}
```
+### 输入框建议(`composer.suggest`)
+
+插件可以为用户当前正在查看的会话输入框提供一条短建议。草稿为空时它显示在占位符层,
+用户按 `Tab` 采用、按 `Esc` 忽略,开始输入也会让它消失。它不是消息、不是气泡,
+插件也无法替用户发送。
+
+```ts
+pi.composer.suggest(input: {
+ sessionId: string; // 来自 session:turnEnded 的会话
+ turnId?: string; // 这段文本对应的轮次;已被新轮次取代则拒绝
+ text: string; // 单行;折行空白并截断到 200 字符
+ ttlMs?: number; // 默认 120000;限制在 1000..600000
+}): Promise<{ shown: true } | {
+ shown: false;
+ reason:
+ | "session-not-visible" // 该会话不是当前显示的会话
+ | "draft-not-empty" // 草稿里已有文本或附件
+ | "stale-turn" // 该会话已经跑了更新的轮次
+ | "replaced" // 更新的建议先占用了位置
+ | "unsupported"; // 没有窗口、没有输入框,或未及时答复
+}>
+
+pi.composer.clearSuggestion(input?: { sessionId?: string }): Promise<{ ok: true }>
+```
+
+两个调用都需要 `composer.suggest` 权限。无法展示不是错误:调用会返回
+`{ shown: false, reason }`,插件可以记录这次落空并决定是否再花一次补全预算。
+参数不合法(`sessionId` 为空、文本没有可见内容、`ttlMs` 不是数字)会像其他宿主 API 一样抛
+`INVALID_PARAMS`,没有授予权限则抛 `PERMISSION_DENIED`。
+
+宿主只在以下条件全部满足时显示建议,并在每次变化后重新检查:命名的会话正是当前显示的会话、
+草稿为空(无文本且无附件)、命名的轮次仍是该会话最新的轮次、有输入框处于可输入状态。
+每个会话同时最多一条建议;更新的建议会替换它,并把被替换的调用答复为 `replaced`。
+下列任一情况都会清除建议:任何草稿变化(输入、粘贴、附件、`composer.insertText`、
+`composer.replaceDraft`)、发送、切换会话、新一轮开始、插件卸载或被禁用、
+`pi.composer.clearSuggestion`、页面重载、窗口关闭,以及建议自身的存活时间到期。
+采用(`Tab`)会把文本写入草稿、光标置末,并保留已暂存的附件。
+
+调用会记录审计:插件 id、会话,以及是否显示成功。若插件用模型生成文本,还需单独声明该 API
+所需的权限,例如 `agent.complete` 与 `models.list`。
+
+```js
+pi.events.on("session:turnEnded", async (event) => {
+ if (event.reason !== "completed") return;
+ const active = await pi.session.getActive();
+ if (active?.sessionId !== event.sessionId) return;
+ const text = await writeNextLine(active); // 插件自己的模型请求
+ if (!text) return;
+ await pi.composer.suggest({
+ sessionId: event.sessionId,
+ turnId: event.turnId,
+ text,
+ });
+});
+```
+
### 语音(`speech.adapter.register`)
```ts
pi.speech.registerAdapter(adapter: {
diff --git a/docs/zh-CN/spec/07-plugins/13-plugin-permissions-matrix.md b/docs/zh-CN/spec/07-plugins/13-plugin-permissions-matrix.md
index 3aea68dfc7..73e7fd57a9 100644
--- a/docs/zh-CN/spec/07-plugins/13-plugin-permissions-matrix.md
+++ b/docs/zh-CN/spec/07-plugins/13-plugin-permissions-matrix.md
@@ -28,6 +28,7 @@
| `agent.tool.register` | 高 | 注册代理工具 | 安装时确认 | 工具执行情况单独审核 |
| `agent.prompt.inject` | 高 | 注入系统提示符;激活 `contributes.skills` | 默认拒绝/强确认 | 容易导致行为劫持 |
| `composer.transform` | 中等 | `contributes.composerTransforms` 与 `onComposerTransform` | 安装时确认 | 仅在用户主动执行 Composer 操作后运行。仅接收草稿和可选模型 key,不接收会话历史或单独的附件/文件引用元数据;输入、结果上限均为 100,000 字符并记入审计 |
+| `composer.suggest` | 中等 | `pi.composer.suggest` / `pi.composer.clearSuggestion` | 安装时确认 | 仅在草稿为空、且插件声明的轮次仍是当前轮次时,向当前可见会话的输入框占位符层写入一条可忽略的建议。用户按 Tab 采用、Esc 忽略;输入、发送、切换会话、新一轮开始、插件停止、页面重载或窗口关闭都会清除。插件既不能直接发送,也不读取草稿。文本折为单行并截断到 200 字符;存活时间默认 120 秒,上限 10 分钟。记入审计;无法展示时返回 `{ shown: false, reason }` 而不是抛错 |
| `agent.extension` | 高 | 在 agent 进程内运行 `contributes.agentExtensions` 模块 | 显式确认;v1.1 仅限本地导入和开发插件 | 与 agent 自身工具同等权限;插件沙箱不适用(规格 16) |
| `renderer.extension` | 高 | 在宿主渲染进程中执行 `manifest.renderer` 以挂载 UI 插槽;`rendererActions` 与 `rendererCallMethods` 决定该模块可以派发的动作与 `onRendererCall` 方法 | 显式确认;v1.1 仅限本地导入和开发插件,与 `agent.extension` 一致 | 模块与 PI-Desktop 同文档运行,因此插槽是契约而不是沙箱。组件只能派发经过审查的动作词表(`plugin.call`、`composer.insertText`、`composer.readDraft`、`composer.replaceDraft`、`attachments.add` / `list` / `remove`),最多 16 个;`plugin.call` 只能触达调用者自己插件的 `onRendererCall` 方法,最多 32 个。插件卸载时注册会被撤销;自绘弹窗位于插件自己打开的层中 |
| `provider.register` | 高 | `contributes.providers` 成为原生 Provider 列表中的行,归插件所有并在每次加载时按 manifest 刷新 | 显式确认;v1.1 仅限本地导入和开发插件,与 `agent.extension` 一致 | 用户路径拒绝编辑该行(`PROVIDER_OWNED_BY_PLUGIN`);API key 凭据仍存放在 Host secret store 的常规 provider 引用下 |
@@ -158,6 +159,7 @@ Agent,在 Plan 中不可见。主机返回 `PLUGIN_DISABLED_IN_PLAN`
| `usage.read` | Read usage statistics | 读取用量统计 |
| `agent.complete` | Run a one-shot completion with your models | 用你的模型发起一次补全 |
| `composer.transform` | Transform text in the Composer | 转换输入框中的文本 |
+| `composer.suggest` | Offer a suggestion in the Composer | 在输入框中给出建议 |
| `speech.adapter.register` | Register a speech adapter | 注册语音适配器 |
| `audio.capture.background` | Use the microphone in the background | 后台使用麦克风 |
| `audio.playback.background` | Play audio in the background | 后台播放声音 |
diff --git a/packages/i18n/src/locales/de/index.ts b/packages/i18n/src/locales/de/index.ts
index 3ee5d487a7..a65c322712 100644
--- a/packages/i18n/src/locales/de/index.ts
+++ b/packages/i18n/src/locales/de/index.ts
@@ -349,6 +349,7 @@ export const de = {
"placeholderHint": "Geben Sie / für Befehle · @ für Dateien ein",
"placeholderHomeHint": "Geben Sie / für Befehle · @ für Dateien ein",
"placeholderShortcut": "Umschalt+Eingabetaste für Zeilenumbruch · Verwenden Sie Senden, um zu senden",
+ "suggestionHint": "Tab übernehmen · Esc verwerfen",
"addFiles": "Dateien hinzufügen und mehr",
"filesAttached": "{{count}} Element(e) zum Entwurf hinzugefügt",
"filesPasted": "{{count}} eingefügte Datei(en) im Sitzungs-Scratch-Ordner gespeichert",
@@ -2386,6 +2387,7 @@ sklm: {
"agent.prompt.inject": "Agentenanweisungen anpassen",
"agent.complete": "One-Shot-Vervollständigung mit Ihren Modellen durchführen",
"composer.transform": "Text im Composer umwandeln",
+ "composer.suggest": "Einen Vorschlag im Composer anbieten",
"agent.extension": "Code im Agenten ausführen",
"renderer.extension": "Oberfläche in Chat-Slots zeichnen",
"provider.register": "Anbieter zur Modellliste hinzufügen",
@@ -2428,6 +2430,7 @@ sklm: {
"agent.prompt.inject": "Kann Anweisungen ändern, die an den KI-Agenten gesendet werden.",
"agent.complete": "Kann Ihr Modellkontingent für eine einmalige Fertigstellung ausgeben. Das Plugin erhält niemals Ihre API-Schlüssel.",
"composer.transform": "Erlaubt diesem Plugin, ausdrücklich im Composer ausgewählten Text umzuwandeln. Es erhält den Entwurf und den Modellschlüssel, aber weder Gesprächsverlauf noch Anhänge.",
+ "composer.suggest": "Erlaubt diesem Plugin, bei leerem Entwurf eine verwerfbare Zeile im Platzhalter des Composers anzuzeigen. Sie gelangt nur mit Tab in den Entwurf, kann nie vom Plugin gesendet werden und verschwindet beim Tippen.",
"renderer.extension": "Lädt das Renderer-Modul dieses Plugins in das App-Fenster, um UI-Slot-Komponenten zu zeichnen (Nachrichten-Aktionsleisten, Antwort-Anhänge, Tool-Karten, Codeblock-Renderer, Eingabebereich). Das Modul läuft im selben Dokument wie PI-Desktop. Aktiviere nur Code, dem du vertraust.",
"agent.extension": "Führt ExtensionAPI-Module im Agentenprozess mit denselben Rechten wie die Tools des Agenten aus. Aktivieren Sie nur Code, dem Sie vertrauen.",
"provider.register": "Fügt die Anbieter, die dieses Plugin definiert, zur Anbieterliste in den Einstellungen hinzu. Das Plugin liefert den Endpunkt und die Modelle; Ihr API-Schlüssel bleibt in PI-Desktop.",
diff --git a/packages/i18n/src/locales/en/index.ts b/packages/i18n/src/locales/en/index.ts
index a28e4dc3b5..c909a95c21 100644
--- a/packages/i18n/src/locales/en/index.ts
+++ b/packages/i18n/src/locales/en/index.ts
@@ -356,6 +356,7 @@ export const en = {
placeholderHint: "Type / for commands · @ for files",
placeholderHomeHint: "Type / for commands · @ for files",
placeholderShortcut: "Shift+Enter for newline · Use Send to submit",
+ suggestionHint: "Tab to accept · Esc to ignore",
addFiles: "Add files",
filesAttached: "Added {{count}} item(s) to the draft",
filesPasted: "Saved {{count}} pasted file(s) to the session scratch folder",
@@ -2407,6 +2408,7 @@ importConfirm: "Imported extensions run inside the agent process with the same a
"agent.prompt.inject": "Adjust agent instructions",
"agent.complete": "Run a one-shot completion with your models",
"composer.transform": "Transform text in the Composer",
+ "composer.suggest": "Offer a suggestion in the Composer",
"agent.extension": "Run code inside the agent",
"renderer.extension": "Draw UI in chat slots",
"provider.register": "Add providers to the model list",
@@ -2458,6 +2460,8 @@ importConfirm: "Imported extensions run inside the agent process with the same a
"Can spend your model quota on a one-shot completion. The plugin never receives your API keys.",
"composer.transform":
"Lets this plugin transform text you explicitly select in the Composer. It receives the draft and selected model key, but no conversation history or attachments.",
+ "composer.suggest":
+ "Lets this plugin show one dismissible line in the Composer's placeholder while the draft is empty. The line enters the draft only when you press Tab, can never be sent by the plugin, and disappears as soon as you type.",
"agent.extension": "Runs ExtensionAPI modules inside the agent process with the same access as the agent's own tools. Enable only code you trust.",
"renderer.extension":
"Loads this plugin's renderer module into the app window to draw UI slot components (message action bars, entry extras, tool cards, code-block renderers, composer controls). The module runs in the same document as PI-Desktop. Enable only code you trust.",
diff --git a/packages/i18n/src/locales/es/index.ts b/packages/i18n/src/locales/es/index.ts
index dab1dccc41..7d64be7d7f 100644
--- a/packages/i18n/src/locales/es/index.ts
+++ b/packages/i18n/src/locales/es/index.ts
@@ -349,6 +349,7 @@ export const es = {
"placeholderHint": "Escriba / para comandos · @ para archivos",
"placeholderHomeHint": "Escriba / para comandos · @ para archivos",
"placeholderShortcut": "Mayús+Entrar para nueva línea · Utilice Enviar para enviar",
+ "suggestionHint": "Tab aceptar · Esc descartar",
"addFiles": "Agregar archivos y más",
"filesAttached": "Se agregaron {{count}} elementos al borrador",
"filesPasted": "Se guardaron {{count}} archivos pegados en la carpeta temporal de la sesión",
@@ -2386,6 +2387,7 @@ sklm: {
"agent.prompt.inject": "Ajustar instrucciones del agente",
"agent.complete": "Ejecutar una finalización de una sola vez con sus modelos",
"composer.transform": "Transformar texto en el compositor",
+ "composer.suggest": "Ofrecer una sugerencia en el compositor",
"agent.extension": "Ejecutar código dentro del agente",
"renderer.extension": "Dibujar interfaz en los slots del chat",
"provider.register": "Agregar proveedores a la lista de modelos",
@@ -2428,6 +2430,7 @@ sklm: {
"agent.prompt.inject": "Puede cambiar las instrucciones enviadas al agente de IA.",
"agent.complete": "Puede gastar su cuota de modelo en una finalización única. El complemento nunca recibe sus claves API.",
"composer.transform": "Permite que este complemento transforme el texto que selecciones explícitamente en el compositor. Recibe el borrador y la clave del modelo seleccionado, pero no el historial de conversación ni los adjuntos.",
+ "composer.suggest": "Permite que este complemento muestre una línea descartable en el marcador del compositor mientras el borrador está vacío. Solo entra en el borrador al pulsar Tab, nunca la envía el complemento y desaparece al escribir.",
"agent.extension": "Ejecuta módulos ExtensionAPI dentro del proceso del agente con el mismo acceso que sus propias herramientas. Activa solo código en el que confíes.",
"renderer.extension": "Carga el módulo de renderizado de este complemento en la ventana de la app para dibujar componentes en los slots de la interfaz (barras de acción de mensajes, extras de respuesta, tarjetas de herramientas, renderizadores de bloques de código, controles del compositor). El módulo se ejecuta en el mismo documento que PI-Desktop. Activa solo código de confianza.",
"provider.register": "Agregue los proveedores que define este complemento a la lista de proveedores de Configuración. El complemento aporta el punto final y los modelos; su clave API permanece en PI-Desktop.",
diff --git a/packages/i18n/src/locales/fr/index.ts b/packages/i18n/src/locales/fr/index.ts
index 701530342b..2b6e2056fd 100644
--- a/packages/i18n/src/locales/fr/index.ts
+++ b/packages/i18n/src/locales/fr/index.ts
@@ -349,6 +349,7 @@ export const fr = {
"placeholderHint": "Tapez / pour les commandes · @ pour les fichiers",
"placeholderHomeHint": "Tapez / pour les commandes · @ pour les fichiers",
"placeholderShortcut": "Maj+Entrée pour une nouvelle ligne · Utilisez Envoyer pour soumettre",
+ "suggestionHint": "Tab accepter · Échap ignorer",
"addFiles": "Ajoutez des fichiers et plus encore",
"filesAttached": "Ajout de {{count}} élément(s) au brouillon",
"filesPasted": "Enregistrement de {{count}} fichier(s) collé(s) dans le dossier de travail de la session",
@@ -2386,6 +2387,7 @@ sklm: {
"agent.prompt.inject": "Ajuster les instructions de l'agent",
"agent.complete": "Exécuter une complétion unique avec vos modèles",
"composer.transform": "Transformer le texte dans le compositeur",
+ "composer.suggest": "Proposer une suggestion dans le compositeur",
"agent.extension": "Exécuter du code dans l'agent",
"renderer.extension": "Dessiner l'interface dans les emplacements du chat",
"provider.register": "Ajouter des fournisseurs à la liste de modèles",
@@ -2428,6 +2430,7 @@ sklm: {
"agent.prompt.inject": "Peut modifier les instructions envoyées à l'agent IA.",
"agent.complete": "Peut dépenser votre quota de modèle pour une réalisation unique. Le plugin ne reçoit jamais vos clés API.",
"composer.transform": "Permet à ce plugin de transformer le texte que vous sélectionnez explicitement dans le compositeur. Il reçoit le brouillon et la clé du modèle sélectionné, mais ni l'historique de la conversation ni les pièces jointes.",
+ "composer.suggest": "Permet à ce plugin d'afficher une ligne ignorable dans le texte indicatif du compositeur tant que le brouillon est vide. Elle n'entre dans le brouillon qu'avec Tab, ne peut jamais être envoyée par le plugin et disparaît dès la frappe.",
"agent.extension": "Exécute des modules ExtensionAPI dans le processus de l'agent avec le même accès que ses propres outils. N'activez que du code auquel vous faites confiance.",
"renderer.extension": "Charge le module de rendu de ce plugin dans la fenêtre de l'app pour dessiner des composants d'interface (barres d'actions des messages, extras de réponse, cartes d'outils, rendus de blocs de code, contrôles du composeur). Le module s'exécute dans le même document que PI-Desktop. N'activez que du code de confiance.",
"provider.register": "Ajoute les fournisseurs définis par ce plugin à la liste des fournisseurs des Paramètres. Le plugin fournit le point de terminaison et les modèles ; votre clé API reste dans PI-Desktop.",
diff --git a/packages/i18n/src/locales/ko/index.ts b/packages/i18n/src/locales/ko/index.ts
index e4e1d2c105..6c9edfcb8b 100644
--- a/packages/i18n/src/locales/ko/index.ts
+++ b/packages/i18n/src/locales/ko/index.ts
@@ -358,6 +358,7 @@ export const ko = {
placeholderHint: "명령은 / · 파일은 @ 입력",
placeholderHomeHint: "명령은 / · 파일은 @ 입력",
placeholderShortcut: "줄바꿈은 Shift+Enter · 보내기를 눌러 제출",
+ suggestionHint: "Tab 수락 · Esc 무시",
addFiles: "파일 추가",
filesAttached: "초안에 항목 {{count}}개 추가됨",
filesPasted: "붙여넣은 파일 {{count}}개를 세션 임시 폴더에 저장함",
@@ -2403,6 +2404,7 @@ importConfirm: "가져온 확장은 에이전트 프로세스 안에서 에이
"agent.prompt.inject": "에이전트 지침 조정",
"agent.complete": "모델로 일회성 완성 실행",
"composer.transform": "작성기의 텍스트 변환",
+ "composer.suggest": "작성기에 제안 표시",
"agent.extension": "에이전트 안에서 코드 실행",
"renderer.extension": "채팅 슬롯에 UI 그리기",
"provider.register": "모델 목록에 프로바이더 추가",
@@ -2452,6 +2454,7 @@ importConfirm: "가져온 확장은 에이전트 프로세스 안에서 에이
"agent.complete":
"모델 할당량을 사용해 일회성 완성을 실행할 수 있습니다. 플러그인은 API 키를 받지 않습니다.",
"composer.transform": "작성기에서 직접 선택한 텍스트를 변환하도록 허용합니다. 플러그인은 초안과 선택된 모델 키만 받으며 대화 기록이나 첨부 파일은 받지 않습니다.",
+ "composer.suggest": "초안이 비어 있는 동안 작성기 자리 표시자에 무시할 수 있는 한 줄을 표시하도록 허용합니다. Tab을 눌러야만 초안에 들어가며, 플러그인이 대신 전송할 수 없고 입력을 시작하면 사라집니다.",
"agent.extension": "ExtensionAPI 모듈을 에이전트 프로세스 안에서 에이전트 자체 도구와 같은 권한으로 실행합니다. 신뢰하는 코드만 켜세요.",
"renderer.extension": "이 플러그인의 렌더러 모듈을 앱 창에 로드하여 메시지 작업 표시줄, 응답 추가 영역, 도구 카드, 코드 블록 렌더러, 작성기 컨트롤 등 UI 슬롯 구성 요소를 그립니다. 모듈은 PI-Desktop과 같은 문서에서 실행됩니다. 신뢰하는 코드만 활성화하세요.",
"provider.register":
diff --git a/packages/i18n/src/locales/pt-BR/index.ts b/packages/i18n/src/locales/pt-BR/index.ts
index 54f3e679b2..e02ec85b1b 100644
--- a/packages/i18n/src/locales/pt-BR/index.ts
+++ b/packages/i18n/src/locales/pt-BR/index.ts
@@ -348,6 +348,7 @@ export const ptBR = {
placeholderHint: "Digite / para comandos · @ para arquivos",
placeholderHomeHint: "Digite / para comandos · @ para arquivos",
placeholderShortcut: "Shift+Enter para inserir uma quebra de linha · Use Enviar para enviar",
+ suggestionHint: "Tab aceitar · Esc descartar",
addFiles: "Adicionar arquivos",
filesAttached: "{{count}} item(ns) adicionado(s) ao rascunho",
filesPasted: "{{count}} arquivo(s) colado(s) salvo(s) na pasta temporária da sessão",
@@ -2352,6 +2353,7 @@ export const ptBR = {
"agent.prompt.inject": "Alterar as instruções do agente",
"agent.complete": "Executar uma conclusão avulsa com seus modelos",
"composer.transform": "Transformar texto no Composer",
+ "composer.suggest": "Sugerir algo no Composer",
"agent.extension": "Executar código dentro do agente",
"renderer.extension": "Desenhar interface nos slots do chat",
"provider.register": "Adicionar provedores à lista de modelos",
@@ -2394,6 +2396,7 @@ export const ptBR = {
"agent.prompt.inject": "Pode alterar as instruções enviadas ao agente de IA.",
"agent.complete": "Pode consumir sua cota de modelo para uma conclusão avulsa. O plugin nunca recebe suas chaves de API.",
"composer.transform": "Permite que este plugin transforme o texto selecionado no Composer. Ele recebe o rascunho e a chave do modelo selecionado, mas não o histórico da conversa nem anexos.",
+ "composer.suggest": "Permite que este plugin mostre uma linha descartável no texto de exemplo do Composer enquanto o rascunho está vazio. Ela entra no rascunho apenas com Tab, o plugin nunca a envia sozinho e ela desaparece ao digitar.",
"agent.extension": "Executa módulos da ExtensionAPI dentro do processo do agente, com o mesmo nível de acesso que as ferramentas do próprio agente. Ative somente código em que você confia.",
"renderer.extension":
"Carrega o módulo de renderização deste plugin na janela do aplicativo para desenhar componentes de slot (barras de ações de mensagens, extras de entrada, cartões de ferramentas, renderizadores de blocos de código, controles do compositor). O módulo é executado no mesmo documento do PI-Desktop. Ative somente código em que você confia.",
diff --git a/packages/i18n/src/locales/tr/index.ts b/packages/i18n/src/locales/tr/index.ts
index b8989edac6..8b2d02e326 100644
--- a/packages/i18n/src/locales/tr/index.ts
+++ b/packages/i18n/src/locales/tr/index.ts
@@ -358,6 +358,7 @@ export const tr = {
placeholderHint: "Komutlar için / · dosyalar için @ yazın",
placeholderHomeHint: "Komutlar için / · dosyalar için @ yazın",
placeholderShortcut: "Yeni satır için Shift+Enter · göndermek için Gönder",
+ suggestionHint: "Tab kabul · Esc yoksay",
addFiles: "Dosya ekle",
filesAttached: "Taslağa {{count}} öğe eklendi",
filesPasted: "Yapıştırılan {{count}} dosya oturum klasörüne kaydedildi",
@@ -2397,6 +2398,7 @@ importConfirm: "İçe aktarılan uzantılar ajan sürecinde, ajanın kendi araç
"agent.prompt.inject": "Ajan yönergelerini ayarla",
"agent.complete": "Modellerinizle tek seferlik tamamlatma çalıştır",
"composer.transform": "Oluşturucudaki metni dönüştür",
+ "composer.suggest": "Oluşturucuda öneri sun",
"agent.extension": "Ajanın içinde kod çalıştır",
"renderer.extension": "Sohbet yuvalarında arayüz çiz",
"provider.register": "Model listesine servis ekle",
@@ -2446,6 +2448,7 @@ importConfirm: "İçe aktarılan uzantılar ajan sürecinde, ajanın kendi araç
"agent.complete":
"Model kotanızı tek seferlik bir tamamlatma için harcayabilir. Eklenti API anahtarlarınızı almaz.",
"composer.transform": "Eklentinin Oluşturucu'da açıkça seçtiğiniz metni dönüştürmesine izin verir. Eklenti yalnızca taslağı ve seçili model anahtarını alır; konuşma geçmişini veya ekleri almaz.",
+ "composer.suggest": "Taslak boşken Oluşturucu yer tutucusunda yok sayılabilir tek bir satır göstermesine izin verir. Satır yalnızca Tab ile taslağa girer, eklenti onu kendi gönderemez ve yazmaya başlayınca kaybolur.",
"agent.extension": "ExtensionAPI modüllerini ajan sürecinde, ajanın kendi araçlarıyla aynı erişimle çalıştırır. Yalnızca güvendiğiniz kodu etkinleştirin.",
"renderer.extension": "Bu eklentinin işleyici modülünü uygulama penceresine yükler; mesaj eylem çubukları, yanıt ek alanları, araç kartları, kod bloğu işleyicileri ve besteleyici kontrolleri gibi arayüz yuvası bileşenleri çizer. Modül PI-Desktop ile aynı belgede çalışır. Yalnızca güvendiğiniz kodu etkinleştirin.",
"provider.register":
diff --git a/packages/i18n/src/locales/zh-CN/index.ts b/packages/i18n/src/locales/zh-CN/index.ts
index 7c026ae18e..cf25670f77 100644
--- a/packages/i18n/src/locales/zh-CN/index.ts
+++ b/packages/i18n/src/locales/zh-CN/index.ts
@@ -351,6 +351,7 @@ export const zhCN = {
placeholderHint: "输入 / 使用命令 · @ 引用文件",
placeholderHomeHint: "输入 / 使用命令 · @ 引用文件",
placeholderShortcut: "Shift+Enter 换行 · 点击发送提交",
+ suggestionHint: "Tab 接受 · Esc 忽略",
addFiles: "添加文件",
filesAttached: "已将 {{count}} 项加入草稿",
filesPasted: "已将 {{count}} 个粘贴文件保存到会话临时目录",
@@ -2380,6 +2381,7 @@ sklm: {
"agent.prompt.inject": "调整智能体指令",
"agent.complete": "用你的模型发起一次补全",
"composer.transform": "转换输入框中的文本",
+ "composer.suggest": "在输入框中给出建议",
"agent.extension": "在 agent 内运行代码",
"renderer.extension": "在聊天插槽绘制界面",
"provider.register": "将服务添加到模型列表",
@@ -2423,6 +2425,7 @@ sklm: {
"agent.prompt.inject": "可能修改发送给智能体的指令。",
"agent.complete": "会消耗你的模型额度发起一次补全。插件拿不到 API 密钥。",
"composer.transform": "允许插件转换你在输入框中主动选择的文本。插件会收到草稿文本和所选模型标识,不会收到对话历史或附件。",
+ "composer.suggest": "允许插件在草稿为空时于输入框占位处显示一条可忽略的建议。只有你按 Tab 它才进入草稿,插件无法直接发送,开始输入即会消失。",
"agent.extension": "在 agent 进程内运行 ExtensionAPI 模块,拥有与 agent 自身工具相同的权限。只启用你信任的代码。",
"renderer.extension": "把该插件的渲染模块加载进应用窗口,在消息操作栏、回复追加区、工具卡、代码块、输入区等插槽绘制界面。模块与 PI-Desktop 同文档运行,只启用你信任的代码。",
"provider.register": "把此插件定义的服务添加到设置的服务列表。接口地址和模型由插件提供,API 密钥则留在 PI-Desktop 中。",
diff --git a/packages/i18n/src/locales/zh-TW/index.ts b/packages/i18n/src/locales/zh-TW/index.ts
index 1ae7643a6d..bd3286669a 100644
--- a/packages/i18n/src/locales/zh-TW/index.ts
+++ b/packages/i18n/src/locales/zh-TW/index.ts
@@ -351,6 +351,7 @@ export const zhTW = {
placeholderHint: "輸入 / 使用命令 · @ 引用檔案",
placeholderHomeHint: "輸入 / 使用命令 · @ 引用檔案",
placeholderShortcut: "Shift+Enter 換行 · 點擊發送提交",
+ suggestionHint: "Tab 接受 · Esc 忽略",
addFiles: "新增檔案等內容",
filesAttached: "已將 {{count}} 項加入草稿",
filesPasted: "已將 {{count}} 個貼上檔案儲存到會話臨時目錄",
@@ -2380,6 +2381,7 @@ sklm: {
"agent.prompt.inject": "調整智慧體指令",
"agent.complete": "用你的模型發起一次補全",
"composer.transform": "轉換輸入框中的文字",
+ "composer.suggest": "在輸入框中提供建議",
"agent.extension": "在 agent 內執行程式碼",
"renderer.extension": "在聊天插槽繪製介面",
"provider.register": "將服務新增到模型列表",
@@ -2423,6 +2425,7 @@ sklm: {
"agent.prompt.inject": "可能修改傳送給智慧體的指令。",
"agent.complete": "會消耗你的模型額度發起一次補全。外掛拿不到 API 金鑰。",
"composer.transform": "允許外掛轉換你在輸入框中主動選擇的文字。外掛會收到草稿文字和所選模型識別碼,不會收到對話歷史或附件。",
+ "composer.suggest": "允許外掛在草稿為空時於輸入框佔位處顯示一條可忽略的建議。只有你按 Tab 它才進入草稿,外掛無法直接送出,開始輸入即會消失。",
"agent.extension": "在 agent 程序內執行 ExtensionAPI 模組,擁有與 agent 自身工具相同的權限。只啟用你信任的程式碼。",
"renderer.extension": "把該外掛的渲染模組載入應用視窗,在訊息操作列、回覆追加區、工具卡、程式碼區塊、輸入區等插槽繪製介面。模組與 PI-Desktop 同文件執行,只啟用你信任的程式碼。",
"provider.register": "把此外掛定義的服務新增到設定的服務列表。介面地址和模型由外掛提供,API 金鑰則留在 PI-Desktop 中。",
diff --git a/packages/plugin-sdk/src/index.test.ts b/packages/plugin-sdk/src/index.test.ts
index fd9e4427dc..7953545f19 100644
--- a/packages/plugin-sdk/src/index.test.ts
+++ b/packages/plugin-sdk/src/index.test.ts
@@ -663,6 +663,7 @@ describe("PLUGIN_PERMISSIONS", () => {
"agent.prompt.inject",
"agent.complete",
"composer.transform",
+ "composer.suggest",
"models.list",
"project.create",
"session.read",
diff --git a/packages/plugin-sdk/src/index.ts b/packages/plugin-sdk/src/index.ts
index 70075658b6..5665452360 100644
--- a/packages/plugin-sdk/src/index.ts
+++ b/packages/plugin-sdk/src/index.ts
@@ -233,6 +233,76 @@ export type PluginComposerTransformInput = {
modelKey?: string;
};
+/**
+ * Longest suggestion text the host keeps, in characters. Longer text is cut;
+ * the composer draws it in one line with an ellipsis either way.
+ */
+export const PLUGIN_COMPOSER_SUGGESTION_MAX_CHARS = 200;
+/** Lifetime of one suggestion when `ttlMs` is omitted, in milliseconds. */
+export const PLUGIN_COMPOSER_SUGGESTION_TTL_MS = 120_000;
+/** Shortest and longest lifetime a caller may ask for, in milliseconds. */
+export const PLUGIN_COMPOSER_SUGGESTION_TTL_MIN_MS = 1_000;
+export const PLUGIN_COMPOSER_SUGGESTION_TTL_MAX_MS = 600_000;
+
+/**
+ * `pi.composer.suggest`: one dismissible line the composer shows in its
+ * placeholder layer while the draft is empty (`composer.suggest`).
+ *
+ * `sessionId` and `turnId` are the ones the plugin learned from
+ * `session:turnEnded`. The host shows the text only while that session is
+ * still the one on screen, no newer turn has started, and the draft is empty,
+ * so an answer that took a model request to produce cannot surface in a place
+ * the user already left. `text` is one line: the host folds line breaks and
+ * runs of whitespace into single spaces and cuts the result at
+ * `PLUGIN_COMPOSER_SUGGESTION_MAX_CHARS`. `ttlMs` defaults to
+ * `PLUGIN_COMPOSER_SUGGESTION_TTL_MS` and is clamped into
+ * `PLUGIN_COMPOSER_SUGGESTION_TTL_MIN_MS`..`PLUGIN_COMPOSER_SUGGESTION_TTL_MAX_MS`.
+ */
+export type PluginComposerSuggestInput = {
+ readonly sessionId: string;
+ /** The turn the suggestion belongs to; a older turn that already ran is stale. */
+ readonly turnId?: string;
+ readonly text: string;
+ readonly ttlMs?: number;
+};
+
+/**
+ * Why a suggestion is not on screen.
+ * - `session-not-visible`: that session is not the one the user is looking at.
+ * - `draft-not-empty`: the composer already holds text or an attachment.
+ * - `stale-turn`: the session has run a newer turn since `turnId`, so the
+ * suggestion would arrive about a moment that is already over.
+ * - `replaced`: a newer suggestion took the slot before this one was answered.
+ * - `unsupported`: nothing could take it — no window, no composer mounted, or
+ * the shell did not answer in time.
+ */
+export const PLUGIN_COMPOSER_SUGGESTION_REFUSALS = [
+ "session-not-visible",
+ "draft-not-empty",
+ "stale-turn",
+ "replaced",
+ "unsupported",
+] as const;
+
+export type PluginComposerSuggestionRefusal =
+ (typeof PLUGIN_COMPOSER_SUGGESTION_REFUSALS)[number];
+
+/**
+ * `pi.composer.suggest` answer. A place that will not show the text is not an
+ * error: `shown: false` and a `reason` let a plugin log the miss and decide
+ * whether to spend another completion. Only malformed input throws —
+ * `INVALID_PARAMS`, like every other host API.
+ */
+export type PluginComposerSuggestResult =
+ | { readonly shown: true }
+ | { readonly shown: false; readonly reason: PluginComposerSuggestionRefusal };
+
+/**
+ * `pi.composer.clearSuggestion`: drop this plugin's suggestion. `sessionId`
+ * defaults to the session the user is looking at.
+ */
+export type PluginComposerClearSuggestionInput = { readonly sessionId?: string };
+
export type PluginSessionMessage =
| { role: "user"; content: string; createdAt: string }
| {
@@ -1188,6 +1258,24 @@ export type PluginHostApi = {
registerAdapter: (adapter: PluginSpeechAdapter) => Promise;
unregisterAdapter: (protocol: string) => Promise;
};
+ /**
+ * The session's input box (`composer.suggest`). A plugin gets one
+ * dismissible line into the placeholder layer of a session whose draft is
+ * empty; the user takes it with Tab, drops it with Esc, and typing anything
+ * drops it too. Never a message, never a bubble, never a send.
+ */
+ composer: {
+ /**
+ * Offer one line for the composer of `sessionId`. Resolves
+ * `{ shown: false, reason }` instead of throwing when nothing will show
+ * it, so the answer is safe to log. The whole suggestion is cleared by
+ * the shell on: typing, pasting, an attachment, a send, a session switch,
+ * a new turn, this plugin unloading, a renderer reload, or a window close.
+ */
+ suggest: (input: PluginComposerSuggestInput) => Promise;
+ /** Drop this plugin's suggestion; nothing is shown when it is already gone. */
+ clearSuggestion: (input?: PluginComposerClearSuggestionInput) => Promise<{ ok: true }>;
+ };
ui: {
openPanel: (opts?: { title?: string }) => Promise;
closePanel: () => Promise;
@@ -1484,6 +1572,10 @@ export const PLUGIN_PERMISSIONS = [
"agent.prompt.inject",
"agent.complete",
"composer.transform",
+ // One dismissible line in the composer's placeholder layer. A grant here can
+ // put text into a draft the user may send, so it sits with the draft writer
+ // (`composer.transform`) rather than with the display-only grants.
+ "composer.suggest",
"agent.extension",
// Renderer slots (`docs/plugin-plan/ui/`): the entry module loads into the
// host renderer's own document, so the surface it can touch is the
diff --git a/packages/shared/src/protocol.ts b/packages/shared/src/protocol.ts
index 7635845243..ecc0524c71 100644
--- a/packages/shared/src/protocol.ts
+++ b/packages/shared/src/protocol.ts
@@ -343,6 +343,12 @@ export const IPC = {
* `session:activated` snapshot is assembled from both (spec 07-plugins/03).
*/
pluginSessionActive: "pi-desktop/plugin/session/active",
+ /**
+ * The shell's answer to one composer suggestion (`pi.composer.suggest`):
+ * whether it went on screen and, if not, why. The main process is waiting
+ * on this invoke, so a suggestion's caller learns what happened to it.
+ */
+ pluginComposerSuggestionResult: "pi-desktop/plugin/composer/suggestionResult",
mcpList: "pi-desktop/mcp/list",
mcpUpsert: "pi-desktop/mcp/upsert",
mcpRemove: "pi-desktop/mcp/remove",
@@ -465,6 +471,13 @@ export const IPC = {
* which session's panel takes the view.
*/
pluginViewReveal: "pi-desktop/plugin/view/event/reveal",
+ /**
+ * One composer suggestion (`pi.composer.suggest`): an offer to show a
+ * plugin's line in the placeholder layer, or the shell's order to drop what
+ * it shows. The shell owns the composer, so it decides and answers over
+ * `pluginComposerSuggestionResult`.
+ */
+ pluginComposerSuggestion: "pi-desktop/plugin/composer/event/suggestion",
windowMaximized: "pi-desktop/window/event/maximized",
windowFullScreen: "pi-desktop/window/event/fullscreen",
windowWorkPanelResize: "pi-desktop/window/event/workPanelResize",
From 8f4285fd2f25380f2f5ed0b6f645b6623418e3f3 Mon Sep 17 00:00:00 2001
From: TioitWang <104554654+Tioit-Wang@users.noreply.github.com>
Date: Wed, 21 Oct 2026 14:45:24 +0800
Subject: [PATCH 10/44] feat(transcript): unify turn folding and command
preferences
Keep each assistant turn behind one process disclosure while allowing shell calls to remain independent or join their surrounding activity group. Read the presentation preference during rendering so cached turns update immediately, and preserve disclosure choices across parent toggles. Add regression coverage for settings persistence, outcome states, visibility, alignment, hit targets, and rendered scroll stability.
---
.../electron/main/bootstrap/shutdown.ts | 2 +-
apps/desktop/electron/main/index.ts | 2 +-
apps/desktop/electron/main/ipc/register.ts | 2 +-
.../electron/main/plugin-host-process.mjs | 2 +-
apps/desktop/electron/main/plugin-runtime.ts | 4 +-
.../main/services/composer-suggestion.ts | 2 +-
.../electron/main/services/plugin-services.ts | 2 +-
apps/desktop/src/components/Composer.tsx | 2 +-
.../settings/KeepCommandsExpandedRow.tsx | 28 ++
.../features/chat/composer/ComposerInput.tsx | 2 +-
.../composer/hooks/useComposerSuggestion.ts | 2 +-
.../composer/plugins/suggestion-bridge.ts | 2 +-
.../chat/composer/plugins/suggestion-keys.ts | 2 +-
.../chat/transcript/ActivityGroup.tsx | 42 +-
.../chat/transcript/AssistantTurn.tsx | 68 ++-
.../chat/transcript/AssistantTurnParts.tsx | 28 +-
.../chat/transcript/ProcessActivityGroup.tsx | 6 +-
.../features/chat/transcript/TurnProcess.tsx | 107 ++++-
.../chat/transcript/disclosure-scope.ts | 22 +
.../features/chat/transcript/disclosure.tsx | 59 ++-
.../src/features/settings/SettingsPage.tsx | 2 +
apps/desktop/src/lib/api.ts | 4 +-
apps/desktop/src/lib/assistant-turns.ts | 9 +-
apps/desktop/src/lib/command-folding.ts | 19 +
apps/desktop/src/lib/settings-search.ts | 2 +
apps/desktop/src/lib/turn-process.ts | 204 +++++++--
apps/desktop/src/styles/composer.css | 2 +-
apps/desktop/src/styles/messages.css | 85 ++--
.../test/command-folding-settings.test.mjs | 54 +++
.../test/composer-suggestion-relay.test.mjs | 2 +-
.../test/composer-suggestion-state.test.mjs | 2 +-
.../test/macos-window-translucency.test.mjs | 3 +-
apps/desktop/test/settings-roundtrip.test.mjs | 102 ++++-
apps/desktop/test/thinking-ui.test.mjs | 5 +-
.../transcript-disclosure-reading.test.mjs | 2 +-
apps/desktop/test/transcript-style.test.mjs | 62 +++
apps/desktop/test/transcript-summary.test.mjs | 7 +-
apps/desktop/test/turn-process.test.mjs | 346 ++++++++++++++-
crates/host-core/src/config_sync/domains.rs | 11 +-
.../src/config_sync/engine_s3_tests.rs | 12 +-
....md => 0333-plugin-composer-suggestion.md} | 2 +-
docs/adr/README.md | 2 +-
docs/adr/turn-process-and-thinking-display.md | 102 +++--
docs/spec/03-runtime/04-data-storage.md | 8 +-
docs/spec/04-ux/06-settings-ia.md | 8 +
docs/spec/04-ux/08-component-spec.md | 105 +++--
docs/spec/04-ux/09-interaction-patterns.md | 34 +-
docs/spec/06-delivery/04-e2e-test-plan.md | 106 +++--
docs/spec/08-meta/decisions-log.md | 25 +-
.../adr/turn-process-and-thinking-display.md | 70 ++--
docs/zh-CN/spec/03-runtime/04-data-storage.md | 5 +-
docs/zh-CN/spec/04-ux/06-settings-ia.md | 5 +
docs/zh-CN/spec/04-ux/08-component-spec.md | 83 ++--
.../spec/04-ux/09-interaction-patterns.md | 23 +-
.../spec/06-delivery/04-e2e-test-plan.md | 85 ++--
docs/zh-CN/spec/08-meta/decisions-log.md | 18 +-
packages/i18n/src/locales/de/index.ts | 11 +
packages/i18n/src/locales/en/index.ts | 11 +
packages/i18n/src/locales/es/index.ts | 11 +
packages/i18n/src/locales/fr/index.ts | 11 +
packages/i18n/src/locales/ko/index.ts | 11 +
packages/i18n/src/locales/pt-BR/index.ts | 11 +
packages/i18n/src/locales/tr/index.ts | 11 +
packages/i18n/src/locales/zh-CN/index.ts | 11 +
packages/i18n/src/locales/zh-TW/index.ts | 11 +
packages/shared/src/types/settings.ts | 10 +
scripts/e2e/transcript-disclosure-anchor.tsx | 396 ++++++++++++++++--
scripts/e2e/transcript-render.tsx | 9 +-
scripts/e2e/turn-process.tsx | 381 +++++++++++++++--
69 files changed, 2409 insertions(+), 488 deletions(-)
create mode 100644 apps/desktop/src/components/settings/KeepCommandsExpandedRow.tsx
create mode 100644 apps/desktop/src/features/chat/transcript/disclosure-scope.ts
create mode 100644 apps/desktop/src/lib/command-folding.ts
create mode 100644 apps/desktop/test/command-folding-settings.test.mjs
rename docs/adr/{0332-plugin-composer-suggestion.md => 0333-plugin-composer-suggestion.md} (99%)
diff --git a/apps/desktop/electron/main/bootstrap/shutdown.ts b/apps/desktop/electron/main/bootstrap/shutdown.ts
index b531b9a95d..c7f6e2a6d6 100644
--- a/apps/desktop/electron/main/bootstrap/shutdown.ts
+++ b/apps/desktop/electron/main/bootstrap/shutdown.ts
@@ -46,7 +46,7 @@ export type ShutdownDependencies = {
mcpOAuth?: Pick;
browserHost: Pick;
pluginViews: Pick;
- /** Composer suggestions still waiting for an answer at quit (ADR 0332). */
+ /** Composer suggestions still waiting for an answer at quit (ADR 0333). */
composerSuggestion?: Pick;
updater: Pick;
logger: Pick;
diff --git a/apps/desktop/electron/main/index.ts b/apps/desktop/electron/main/index.ts
index 7e55202999..7de4796d46 100644
--- a/apps/desktop/electron/main/index.ts
+++ b/apps/desktop/electron/main/index.ts
@@ -642,7 +642,7 @@ const sessionCoordination = createSessionCoordination({
onTurnStarted: (sessionId: string, turnId: string) => {
pluginServices.pluginSession.noteTurnStarted(sessionId, turnId);
// A new turn owns the composer now, so a suggestion about the previous one
- // stops being shown and stops being showable (ADR 0332).
+ // stops being shown and stops being showable (ADR 0333).
pluginServices.composerSuggestion.noteTurnStarted(sessionId, turnId);
},
});
diff --git a/apps/desktop/electron/main/ipc/register.ts b/apps/desktop/electron/main/ipc/register.ts
index 756c03913a..e165aff047 100644
--- a/apps/desktop/electron/main/ipc/register.ts
+++ b/apps/desktop/electron/main/ipc/register.ts
@@ -65,7 +65,7 @@ export type RegisterIpcDependencies = {
setActivePluginSession: (
next: { sessionId: string; projectPath: string | null } | null,
) => void;
- /** The shell's answer to a composer suggestion it was offered (ADR 0332). */
+ /** The shell's answer to a composer suggestion it was offered (ADR 0333). */
settleComposerSuggestion: (answer: ComposerSuggestionAnswer) => boolean;
activeUserSubagentDocuments: (...args: any[]) => Promise;
disabledBuiltinSubagents: () => Promise;
diff --git a/apps/desktop/electron/main/plugin-host-process.mjs b/apps/desktop/electron/main/plugin-host-process.mjs
index 889a75146d..89c91c41d3 100644
--- a/apps/desktop/electron/main/plugin-host-process.mjs
+++ b/apps/desktop/electron/main/plugin-host-process.mjs
@@ -253,7 +253,7 @@ function buildApi() {
requestNotificationPermission: () => call("ui.requestNotificationPermission"),
showNativeNotification: (input) => call("ui.showNativeNotification", [input]),
},
- // One line into the session's composer placeholder (ADR 0332). The shell
+ // One line into the session's composer placeholder (ADR 0333). The shell
// answers whether it went on screen, so a plugin never has to guess before
// spending another completion.
composer: {
diff --git a/apps/desktop/electron/main/plugin-runtime.ts b/apps/desktop/electron/main/plugin-runtime.ts
index cd2ded1b50..437d1455e6 100644
--- a/apps/desktop/electron/main/plugin-runtime.ts
+++ b/apps/desktop/electron/main/plugin-runtime.ts
@@ -4616,7 +4616,7 @@ export class PluginRuntime {
}
/**
* `pi.composer.suggest`: one line into the composer of the session the user
- * is looking at (`composer.suggest`, ADR 0332).
+ * is looking at (`composer.suggest`, ADR 0333).
*
* The plugin names the session and the turn its text answers. Nothing here
* can fail the plugin for a place that will not show it: the text is shaped
@@ -5584,7 +5584,7 @@ export class PluginRuntime {
composer: {
/**
* One dismissible line in the placeholder layer of the composer the
- * user is looking at (`composer.suggest`, ADR 0332).
+ * user is looking at (`composer.suggest`, ADR 0333).
*/
suggest: async (input?: PluginComposerSuggestInput) =>
this.suggestComposer(loaded, input),
diff --git a/apps/desktop/electron/main/services/composer-suggestion.ts b/apps/desktop/electron/main/services/composer-suggestion.ts
index 0e92d0c151..0545f3250b 100644
--- a/apps/desktop/electron/main/services/composer-suggestion.ts
+++ b/apps/desktop/electron/main/services/composer-suggestion.ts
@@ -1,5 +1,5 @@
/**
- * The main-process half of `pi.composer.suggest` (ADR 0332).
+ * The main-process half of `pi.composer.suggest` (ADR 0333).
*
* A suggestion is produced by a plugin process, long after the turn it answers
* ended, so by the time it arrives the user may have typed, switched session,
diff --git a/apps/desktop/electron/main/services/plugin-services.ts b/apps/desktop/electron/main/services/plugin-services.ts
index 33251db00a..dcd0e1e431 100644
--- a/apps/desktop/electron/main/services/plugin-services.ts
+++ b/apps/desktop/electron/main/services/plugin-services.ts
@@ -639,7 +639,7 @@ export function createPluginServices({
announce: broadcastSessionEvent,
});
/**
- * `pi.composer.suggest` (ADR 0332): the main process refuses a suggestion
+ * `pi.composer.suggest` (ADR 0333): the main process refuses a suggestion
* that names another session or an overtaken turn, and the shell answers
* whether the composer can take it. The composer owns its own state, so this
* only ever relays — nothing here writes the draft.
diff --git a/apps/desktop/src/components/Composer.tsx b/apps/desktop/src/components/Composer.tsx
index 05d9fa922e..ccb3358170 100644
--- a/apps/desktop/src/components/Composer.tsx
+++ b/apps/desktop/src/components/Composer.tsx
@@ -497,7 +497,7 @@ export function Composer({
// Plugin draft and attachment actions reach this composer while it takes input.
usePluginComposerBridge({ ...draft, inputBlocked, enabled: localToolsAllowed });
// A plugin may have offered one line for this empty draft; it shows in the
- // placeholder layer and `Tab` takes it (ADR 0332).
+ // placeholder layer and `Tab` takes it (ADR 0333).
const suggestion = useComposerSuggestion();
// Keep the transcript's bottom reserve in sync with the composer's real
diff --git a/apps/desktop/src/components/settings/KeepCommandsExpandedRow.tsx b/apps/desktop/src/components/settings/KeepCommandsExpandedRow.tsx
new file mode 100644
index 0000000000..c32f47e61a
--- /dev/null
+++ b/apps/desktop/src/components/settings/KeepCommandsExpandedRow.tsx
@@ -0,0 +1,28 @@
+import { useTranslation } from "react-i18next";
+import type { AppSettings } from "@pi-desktop/shared";
+import { resolveKeepCommandsExpanded } from "../../lib/command-folding";
+import { SettingsRow } from "../../features/settings/primitives";
+import { SettingsToggle } from "../ui";
+
+export function KeepCommandsExpandedRow({
+ settings,
+ saveSettings,
+}: {
+ settings: AppSettings;
+ saveSettings: (patch: Partial) => Promise;
+}) {
+ const { t } = useTranslation();
+ const expanded = resolveKeepCommandsExpanded(settings);
+ return (
+
+ void saveSettings({ keepCommandsExpanded: !expanded })}
+ />
+
+ );
+}
diff --git a/apps/desktop/src/features/chat/composer/ComposerInput.tsx b/apps/desktop/src/features/chat/composer/ComposerInput.tsx
index dcacf74872..4341721835 100644
--- a/apps/desktop/src/features/chat/composer/ComposerInput.tsx
+++ b/apps/desktop/src/features/chat/composer/ComposerInput.tsx
@@ -28,7 +28,7 @@ export type ComposerInputProps = {
runActive: boolean;
composerAc: CompletionController;
/**
- * The plugin suggestion on screen, if any (ADR 0332). It is drawn in the
+ * The plugin suggestion on screen, if any (ADR 0333). It is drawn in the
* placeholder layer while the draft is empty, and `Tab` / `Esc` act on it only
* when nothing else claims those keys.
*/
diff --git a/apps/desktop/src/features/chat/composer/hooks/useComposerSuggestion.ts b/apps/desktop/src/features/chat/composer/hooks/useComposerSuggestion.ts
index 2786277f81..b53e3c7419 100644
--- a/apps/desktop/src/features/chat/composer/hooks/useComposerSuggestion.ts
+++ b/apps/desktop/src/features/chat/composer/hooks/useComposerSuggestion.ts
@@ -1,5 +1,5 @@
/**
- * The composer's view of the plugin suggestion slot (ADR 0332).
+ * The composer's view of the plugin suggestion slot (ADR 0333).
*
* The state itself lives in `../plugins/suggestion-bridge.ts`, outside React, so
* a suggestion that arrives while the composer is unmounted is refused once
diff --git a/apps/desktop/src/features/chat/composer/plugins/suggestion-bridge.ts b/apps/desktop/src/features/chat/composer/plugins/suggestion-bridge.ts
index 1faedf3a4f..76bb0b5b2c 100644
--- a/apps/desktop/src/features/chat/composer/plugins/suggestion-bridge.ts
+++ b/apps/desktop/src/features/chat/composer/plugins/suggestion-bridge.ts
@@ -1,5 +1,5 @@
/**
- * The renderer end of `pi.composer.suggest` (ADR 0332).
+ * The renderer end of `pi.composer.suggest` (ADR 0333).
*
* A plugin process offers one line, the shell decides whether the composer can
* take it, and the user takes it with Tab, drops it with Esc, or drops it by
diff --git a/apps/desktop/src/features/chat/composer/plugins/suggestion-keys.ts b/apps/desktop/src/features/chat/composer/plugins/suggestion-keys.ts
index 9111cdb73d..1e0761888c 100644
--- a/apps/desktop/src/features/chat/composer/plugins/suggestion-keys.ts
+++ b/apps/desktop/src/features/chat/composer/plugins/suggestion-keys.ts
@@ -1,5 +1,5 @@
/**
- * Which key, if any, acts on the composer's plugin suggestion (ADR 0332).
+ * Which key, if any, acts on the composer's plugin suggestion (ADR 0333).
*
* The composer already has owners for both keys and they keep them: a `@` / `/`
* completion list takes `Tab` (and `Enter`), and its own `Escape` closes it
diff --git a/apps/desktop/src/features/chat/transcript/ActivityGroup.tsx b/apps/desktop/src/features/chat/transcript/ActivityGroup.tsx
index 338dd06fc7..b8c11ab636 100644
--- a/apps/desktop/src/features/chat/transcript/ActivityGroup.tsx
+++ b/apps/desktop/src/features/chat/transcript/ActivityGroup.tsx
@@ -60,22 +60,6 @@ type Translate = (key: string, options?: Record) => string;
type ActivityItem = AssistantActivityItem;
-export function activityItemDetail(item: ActivityItem): string {
- if (item.kind === "hostedSearch") return item.round.query ?? "";
- if (item.kind === "thinking") {
- // Latest thought line, so a collapsed header reads like a live ticker.
- const lines = thinkingText(item.message)
- .split("\n")
- .map((line) => line.replace(/^#+\s*|\*\*/g, "").trim())
- .filter(Boolean);
- return lines[lines.length - 1] || "";
- }
- if (lifecycleKindOf(item.message)) {
- return delegationRosterSummary(delegationRoster(item.message));
- }
- return getToolSummary(item.message.toolName, item.message.toolArgs);
-}
-
function waitingSubagentActionLabel(
agent: AgentActivityAgent,
@@ -260,6 +244,10 @@ export const ActivityGroup = memo(function ActivityGroup({
disclosureKey("activity", first?.message.id ?? "", first?.kind ?? "", first?.kind === "hostedSearch" ? first.round.id : ""),
);
const { open, toggle: toggleDisclosure, collapse: collapseDisclosure, claim: claimDisclosure, titleRef } = disclosure;
+ // A subagent card is its own disclosure, so it reads the same parent gate the
+ // group does: below a collapsed whole-turn process it stays shut, and
+ // reopening the process restores the card's own choice.
+ const cardShut = hasSubagentTopology && !open;
const [now, setNow] = useState(Date.now);
const [finishedAt, setFinishedAt] = useState(null);
const wasActiveRef = useRef(live);
@@ -308,14 +296,10 @@ export const ActivityGroup = memo(function ActivityGroup({
: // History reloads keep no end timestamp for pure-thinking groups.
t("chat.thinking", { defaultValue: "Thinking" })
: t("chat.processedFor", { time: elapsed });
- const runtimeStatus = runtimeActivity
- ? runActivityLabel(runtimeActivity, t as Translate)
- : "";
- const currentDetail = useMemo(() =>
- live && !runtimeStatus && lastItem && !(hideThinking && lastItem.kind === "thinking")
- ? activityItemDetail(lastItem) : "",
- [live, runtimeStatus, lastItem, hideThinking]);
- const tail = live && !open ? currentDetail : "";
+ // The header states outcome, counts and elapsed time; it never echoes the item
+ // it is working on. A shell command or a search query can be arbitrarily long,
+ // and repeating it here pushed the counts off the row while adding nothing a
+ // reader cannot get by opening the item.
useEffect(() => {
if (wasActiveRef.current && !live) setFinishedAt(Date.now());
@@ -392,17 +376,13 @@ export const ActivityGroup = memo(function ActivityGroup({
- {tail ? (
-
- {tail}
-
- ) : null}
diff --git a/apps/desktop/src/features/chat/transcript/AssistantTurn.tsx b/apps/desktop/src/features/chat/transcript/AssistantTurn.tsx
index 8e99645cbf..7e47519fe3 100644
--- a/apps/desktop/src/features/chat/transcript/AssistantTurn.tsx
+++ b/apps/desktop/src/features/chat/transcript/AssistantTurn.tsx
@@ -24,6 +24,9 @@ import {
type TurnProcessRunSegment,
} from "../../../lib/turn-process";
import { sessionAllows } from "../../../lib/remote-session-safety";
+import { resolveShowThinking } from "../../../lib/thinking-visibility";
+import { resolveKeepCommandsExpanded } from "../../../lib/command-folding";
+import { cachedVisibleProcessSteps } from "../../../lib/transcript-activity-summary";
import { useSlotSessionId } from "../../../plugins/renderer-slots/use-slots";
import { useAppStore } from "../../../stores/app-store";
import { IconBranch, IconReview } from "../../../components/icons";
@@ -281,6 +284,10 @@ export const AssistantTurn = memo(function AssistantTurn({
? slotMessage("assistant", { ...actionMessage, content }) : undefined,
[complete, actionMessage, content]);
const streaming = isActive && summary.streaming;
+ // The same preference the nested levels read: hidden reasoning is not a
+ // visible step of the turn's process.
+ const showThinking = useAppStore((state) => resolveShowThinking(state.settings));
+ const hideThinking = !showThinking;
/*
The turn owns the menu for its whole subtree, the answer rows it renders
included: Regenerate and Branch act on the turn's answer message, so a menu
@@ -344,7 +351,24 @@ export const AssistantTurn = memo(function AssistantTurn({
statusesRef.current = turnDelegationStatuses;
timingsRef.current = turnDelegationTimings;
const { process, responses } = summary;
- const segments = useMemo(() => segmentTurnProcess(process), [process]);
+ // Read at render time, never at entry-build time: the projection cache is keyed
+ // by messages and compactions only, so a grouping decision made there would
+ // stay stale until new messages arrived. Segmenting here makes the preference
+ // apply on the next paint.
+ const keepCommandsExpanded = useAppStore((state) => resolveKeepCommandsExpanded(state.settings));
+ const segments = useMemo(
+ () => segmentTurnProcess(process, keepCommandsExpanded),
+ [process, keepCommandsExpanded],
+ );
+ // The one disclosure exists if it reveals anything at all. This uses the same
+ // helper the activity rows use: progress text counts, completed thinking is
+ // hidden under the preference, and a live reasoning indicator still counts.
+ // Content facts come from the per-message cache, so a streaming delta reads
+ // only its own message body rather than every earlier one.
+ const visibleSteps = useMemo(
+ () => cachedVisibleProcessSteps(process, hideThinking, isActive),
+ [process, hideThinking, isActive],
+ );
// The live tail is the turn's actual last part. A process chunk opens and
// reports live state only while it owns that part, so a superseded thinking
// chunk cannot keep a false "Thinking" header once a Bash call or a separate
@@ -362,25 +386,29 @@ export const AssistantTurn = memo(function AssistantTurn({
aria-label={t("chat.assistantMessage")}
>
- {segments.map((segment) => {
- if (segment.kind === "run") {
- return
;
- }
- const ownsActiveTail =
- activePart !== undefined && segment.parts.includes(activePart);
- return (
-
-
-
- );
- })}
+ {process.length > 0 ? (
+
+ {segments.map((segment) => {
+ if (segment.kind === "run") {
+ return ;
+ }
+ return (
+
+ );
+ })}
+
+ ) : null}
+ {/* The answer stays outside the process disclosure: it is what the turn
+ produced, not part of what it did. */}
{generatedImages}
{!isActive && metaMessage ? (
diff --git a/apps/desktop/src/features/chat/transcript/AssistantTurnParts.tsx b/apps/desktop/src/features/chat/transcript/AssistantTurnParts.tsx
index 876e36b7d3..89f607f9c0 100644
--- a/apps/desktop/src/features/chat/transcript/AssistantTurnParts.tsx
+++ b/apps/desktop/src/features/chat/transcript/AssistantTurnParts.tsx
@@ -37,6 +37,26 @@ function partKey(part: AssistantTurnPart) {
return `activity-${first.message.id}-${first.kind}${first.kind === "hostedSearch" ? `-${first.round.id}` : ""}`;
}
+/**
+ * Whether a rendered part owns the active tail.
+ *
+ * A command-folding segment may coalesce contiguous activity parts into a new
+ * part object while keeping the source rows. The active tail is the last entry
+ * part, so the coalesced part's last row is the same row object; no id fallback
+ * or nested scan is needed.
+ */
+function partOwnsActivePart(
+ part: AssistantTurnPart,
+ activePart: AssistantTurnPart,
+): boolean {
+ if (part === activePart) return true;
+ if (part.kind !== "activity" || activePart.kind !== "activity") {
+ return false;
+ }
+ const activeRow = activePart.items.at(-1);
+ return activeRow !== undefined && part.items.at(-1) === activeRow;
+}
+
type PartContext = {
isActive: boolean;
activePart?: AssistantTurnPart;
@@ -73,8 +93,14 @@ export const AssistantTurnParts = memo(function AssistantTurnParts({ parts, ...c
parts: readonly AssistantTurnPart[];
}) {
const blocks = useRenderBlocks(parts, partKey);
+ const activeSourcePart = context.activePart;
return <>{blocks.map((block) => {
- const activePart = context.activePart && block.items.includes(context.activePart) ? context.activePart : undefined;
+ // The active tail is an entry part, but an off-mode segment may wrap its
+ // rows in a new merged part. Match by source row so the group that owns the
+ // live step still gets its active defaults.
+ const activePart = activeSourcePart
+ ? block.items.find((part) => partOwnsActivePart(part, activeSourcePart))
+ : undefined;
return
1;
- const open = !grouped || disclosure.open;
+ // A group below a collapsed whole-turn process is not expanded even when the
+ // user left it open: `disclosure.open` already folds in that gate, and the
+ // choice itself survives so reopening the process restores it.
+ const parentVisible = disclosure.parentVisible;
+ const open = (!grouped || disclosure.open) && parentVisible;
const summary = useMemo(() => cachedActivitySummary(items), [items]);
if (items.length === 0) return null;
return (
diff --git a/apps/desktop/src/features/chat/transcript/TurnProcess.tsx b/apps/desktop/src/features/chat/transcript/TurnProcess.tsx
index 488ed29243..dfb83ab757 100644
--- a/apps/desktop/src/features/chat/transcript/TurnProcess.tsx
+++ b/apps/desktop/src/features/chat/transcript/TurnProcess.tsx
@@ -1,42 +1,83 @@
import type { SubagentOutcome } from "../../../lib/subagent-topology";
import { useContext, useEffect, useId, useMemo, useState, type ReactNode } from "react";
import { useTranslation } from "react-i18next";
+import type { AgentActivity } from "@pi-desktop/shared";
import type { AssistantTurnPart } from "../../../lib/assistant-turns";
import { formatToolDuration } from "../../../lib/tool-display";
-import { cachedActivitySummary, cachedVisibleProcessSteps } from "../../../lib/transcript-activity-summary";
+import { cachedActivitySummary } from "../../../lib/transcript-activity-summary";
import { TranscriptSearchContext } from "../../../lib/transcript-search-context";
import {
isTurnThinking,
processContainsMessage,
+ turnProcessPhase,
turnProcessTiming,
} from "../../../lib/turn-process";
-import { resolveShowThinking } from "../../../lib/thinking-visibility";
-import { useAppStore } from "../../../stores/app-store";
import {
IconChevronRight,
IconCircleAlert,
IconSparkles,
} from "../../../components/icons";
import { DisclosureCollapseRail } from "./shared";
-import { DisclosureScope, disclosureKey, useAutomaticDisclosure } from "./disclosure";
+import {
+ disclosureKey,
+ useAutomaticDisclosure,
+ type DisclosureScopeValue,
+} from "./disclosure";
+import { ScopeContext } from "./disclosure-scope";
+
+/**
+ * Live stages that rate their own wording.
+ *
+ * Only stages a reader can sit in front of for a while are listed: compaction
+ * and recovery both move real work and both look like a stall without a name.
+ * `starting`, `waiting-model` and `preparing` are momentary, so they read as
+ * plain running rather than flickering between labels.
+ */
+const LIVE_PHASE_KEYS: Partial> = {
+ compacting: "chat.compactingContext",
+ recovering: "chat.recoveringTurn",
+ retrying: "chat.processRunning",
+ "waiting-subagents": "chat.processRunning",
+};
+/**
+ * The whole turn's process, as one disclosure.
+ *
+ * Every row the turn produced before its answer lives here: the activity groups
+ * and the standalone `Bash` run rows alike. That is one top-level collapse for
+ * the turn, with the groups and run calls at the level below it, so a long
+ * turn reads as "what the agent did" plus the answer instead of a scrolling
+ * stack of sibling disclosures.
+ *
+ * The levels below read this disclosure's scope rather than its choice: closing
+ * the process here closes every group under it, and reopening restores the
+ * groups the user had opened (see `disclosure.tsx`).
+ */
export function TurnProcess({
turnId,
processParts,
turnParts,
+ visibleSteps,
delegationStatuses,
isActive,
+ failed,
+ activity,
children,
}: {
turnId: string;
processParts: readonly AssistantTurnPart[];
turnParts: readonly AssistantTurnPart[];
+ /** Visible steps the process reveals; `0` draws no disclosure. */
+ visibleSteps: number;
isActive: boolean;
+ /** The turn recorded a failure of its own, so the header must not claim success. */
+ failed: boolean;
+ /** Live runtime stage, when the runtime reports one. */
+ activity?: AgentActivity;
delegationStatuses?: ReadonlyMap;
children: ReactNode;
}) {
const { t } = useTranslation();
- const showThinking = useAppStore((state) => resolveShowThinking(state.settings));
const search = useContext(TranscriptSearchContext);
const revealRequest = useMemo(() => search && processContainsMessage(processParts, search.messageId)
? search.requestId : undefined, [processParts, search]);
@@ -44,7 +85,6 @@ export function TurnProcess({
processParts.flatMap((part) => part.kind === "activity" ? part.items : []), delegationStatuses,
), [processParts, delegationStatuses]);
const thinkingNow = useMemo(() => isTurnThinking(turnParts, isActive), [turnParts, isActive]);
- const visibleSteps = useMemo(() => cachedVisibleProcessSteps(processParts, !showThinking, isActive), [processParts, showThinking, isActive]);
// Active processes start open and untouched completed ones close by default;
// an explicit user choice stays authoritative. This does not depend on the
// thinking preference, and a recorded failure keeps an untouched active
@@ -63,10 +103,44 @@ export function TurnProcess({
const timer = window.setInterval(() => setNow(Date.now()), 1000);
return () => window.clearInterval(timer);
}, [isActive]);
- if (visibleSteps === 0) return null;
+ const scope = useMemo(
+ () => ({ claim: disclosure.claim, visible: disclosure.open }),
+ [disclosure.claim, disclosure.open],
+ );
+ // With nothing to reveal there is no disclosure - but the rows still have to
+ // render. Hidden reasoning superseded by a separate answer is exactly this
+ // case: the reader gets the answer, and the process does not exist.
+ if (visibleSteps === 0) return <>{children}>;
const seconds = startedAt === undefined ? 0 : Math.max(
0, Math.floor(((isActive ? now : (endedAt ?? startedAt)) - startedAt) / 1000),
);
+ const elapsed = formatToolDuration(seconds);
+ // The header states the turn's outcome and nothing else: a shell command can
+ // be arbitrarily long, so echoing the current one would push the counts off
+ // the row. `startedAt` is absent for history that recorded no timing, and
+ // "0s" would be a lie there, so the duration is dropped instead.
+ const hasTiming = startedAt !== undefined && seconds > 0;
+ const phase = turnProcessPhase({ parts: turnParts, isActive, failed, activity });
+ const label = (() => {
+ if (phase.kind === "failed") {
+ return hasTiming ? t("chat.processFailedFor", { time: elapsed }) : t("chat.processFailed");
+ }
+ if (phase.kind === "stopped") {
+ return hasTiming ? t("chat.processStoppedFor", { time: elapsed }) : t("chat.processStopped");
+ }
+ if (phase.kind === "completed") {
+ return hasTiming ? t("chat.processCompletedFor", { time: elapsed }) : t("chat.processCompleted");
+ }
+ // Live: only stages with their own settled wording get their own label. The
+ // rest describe an instant at the start of a request, and naming them would
+ // make the row flicker instead of telling the reader anything.
+ const runningPhase = phase.kind === "running" ? phase.phase : undefined;
+ const phaseKey = runningPhase ? LIVE_PHASE_KEYS[runningPhase] : undefined;
+ return t(phaseKey ?? (thinkingNow ? "chat.thinking" : "chat.processRunning"));
+ })();
+ // The summary already counts every activity item it was given, run rows
+ // included, so the header must not add them again.
+ const toolCount = summary.tools;
return (
-
+
+ {phase.kind === "failed" ? : }
+
- {t(isActive ? thinkingNow ? "chat.thinkingFor" : "chat.processingFor" : "chat.processedFor", {
- time: formatToolDuration(seconds),
- })}
+ {label}
- {summary.issues > 0 ? (
+ {summary.issues > 0 && phase.kind !== "failed" ? (
{t("chat.activityFailures", { count: summary.issues })}
) : null}
- {summary.tools > 0 ? (
- {t("chat.processTools", { count: summary.tools })}
+ {toolCount > 0 ? (
+ {t("chat.processTools", { count: toolCount })}
) : null}
@@ -100,10 +174,11 @@ export function TurnProcess({
className="turn-process-body"
hidden={!disclosure.open}
inert={!disclosure.open}
+ aria-hidden={!disclosure.open}
{...disclosure.bodyEvents}
>
-
- {children}
+
+ {children}
);
diff --git a/apps/desktop/src/features/chat/transcript/disclosure-scope.ts b/apps/desktop/src/features/chat/transcript/disclosure-scope.ts
new file mode 100644
index 0000000000..7e725c5dd8
--- /dev/null
+++ b/apps/desktop/src/features/chat/transcript/disclosure-scope.ts
@@ -0,0 +1,22 @@
+import { createContext } from "react";
+
+/**
+ * The scope one disclosure level presents to the levels it reveals.
+ *
+ * Kept in its own module so a level that *provides* a scope (the turn's process
+ * disclosure) and the module that *consumes* it (`useAutomaticDisclosure`) do
+ * not import each other. `disclosure.tsx` owns the consumer side and re-exports
+ * the type.
+ */
+export type DisclosureScopeValue = {
+ /** Claim interaction for this level and, through it, for every ancestor. */
+ claim: () => void;
+ /** Whether this level's contents are currently shown at all. */
+ visible: boolean;
+};
+
+/** The implicit root scope: nothing above the transcript owns it. */
+export const ScopeContext = createContext
({
+ claim: () => {},
+ visible: true,
+});
diff --git a/apps/desktop/src/features/chat/transcript/disclosure.tsx b/apps/desktop/src/features/chat/transcript/disclosure.tsx
index acb2159b25..8f30f50c00 100644
--- a/apps/desktop/src/features/chat/transcript/disclosure.tsx
+++ b/apps/desktop/src/features/chat/transcript/disclosure.tsx
@@ -12,6 +12,7 @@ import {
} from "react";
import { useDisclosureAnchorNotifier } from "../../../lib/disclosure-anchor-context";
import { sessionReadingState, type TranscriptDisclosureChoice } from "../../../lib/transcript-reading-position";
+import { ScopeContext, type DisclosureScopeValue } from "./disclosure-scope";
type Choice = TranscriptDisclosureChoice;
@@ -45,10 +46,14 @@ class DisclosureChoices {
}
const ChoicesContext = createContext(null);
-const ParentContext = createContext<{ claim: () => void; visible: boolean }>({
- claim: () => {},
- visible: true,
-});
+
+/*
+ * A level's own visibility is a second gate beside the stored choice, so a
+ * collapsed parent closes everything it reveals without erasing - or even
+ * overriding - a child's explicit choice. Reopening the parent restores the
+ * rows the user had opened, which is what a nested disclosure should do.
+ */
+export type { DisclosureScopeValue } from "./disclosure-scope";
/** Explicit choices survive pane eviction, but never persist to the host. */
export function TranscriptDisclosureProvider({ children, sessionId }: { children: ReactNode; sessionId?: string }) {
@@ -81,52 +86,58 @@ export function useAutomaticDisclosure(
const choices = sharedChoices ?? localChoices;
const fallbackId = useId();
const key = identity ?? fallbackId;
- const parent = useContext(ParentContext);
const subscribe = useCallback((listener: () => void) => choices.subscribe(key, listener), [choices, key]);
const snapshot = useCallback(() => choices.get(key), [choices, key]);
const choice = useSyncExternalStore(subscribe, snapshot, snapshot);
// A pending reveal is the derived default, so the first paint (and SSR)
// already shows the row the transcript search asked to open.
- const open = choice?.open ?? (
+ const requestedOpen = choice?.open ?? (
revealRequest !== undefined && choice?.revealRequest !== revealRequest
? true
: automaticOpen
);
+ const scope = useContext(ScopeContext);
+ // A level below a collapsed parent renders nothing, whatever its own choice
+ // says. The choice is left untouched so reopening the parent restores it.
+ const open = requestedOpen && scope.visible;
+
const titleRef = useRef(null);
const bodyRef = useRef(null);
const notifyAnchor = useDisclosureAnchorNotifier();
const currentOpen = useRef(open);
currentOpen.current = open;
+ // The claim goes to the level that owns this one, not to the root: opening a
+ // row inside a process disclosure has to keep that process open too.
const claim = useCallback(() => {
if (!choices.get(key)) choices.set(key, { open: currentOpen.current });
- parent.claim();
- }, [choices, key, parent.claim]);
+ scope.claim();
+ }, [choices, key, scope.claim]);
useLayoutEffect(() => {
if (revealRequest === undefined || choices.get(key)?.revealRequest === revealRequest) return;
choices.set(key, { open: true, revealRequest });
- parent.claim();
- }, [choices, key, parent.claim, revealRequest]);
+ scope.claim();
+ }, [choices, key, scope.claim, revealRequest]);
const previousOpen = useRef(open);
useLayoutEffect(() => {
// Completion must not hide keyboard focus or an active text selection.
if (previousOpen.current && !open && !choice && ownsReadingPosition(bodyRef.current)) {
choices.set(key, { open: true });
- parent.claim();
+ scope.claim();
}
previousOpen.current = open;
- }, [choice, choices, key, open, parent.claim]);
+ }, [choice, choices, key, open, scope.claim]);
const setManualOpen = useCallback((next: boolean) => {
- parent.claim();
+ scope.claim();
notifyAnchor?.(titleRef.current);
if (!next && bodyRef.current?.contains(document.activeElement)) {
titleRef.current?.focus({ preventScroll: true });
}
choices.set(key, { ...choices.get(key), open: next });
- }, [choices, key, notifyAnchor, parent.claim]);
+ }, [choices, key, notifyAnchor, scope.claim]);
const toggle = useCallback(() => setManualOpen(!currentOpen.current), [setManualOpen]);
const collapse = useCallback(() => setManualOpen(false), [setManualOpen]);
@@ -137,13 +148,23 @@ export function useAutomaticDisclosure(
claim,
titleRef,
bodyRef,
- parentVisible: parent.visible,
+ // Kept for callers that read the parent's visibility directly; the scope
+ // itself already folded it into `open`.
+ parentVisible: scope.visible,
// Pointer selection and keyboard interaction establish ownership before
// a streaming update can apply an automatic close.
bodyEvents: { onPointerDownCapture: claim, onFocusCapture: claim },
};
}
+/**
+ * Reveal a level's contents to the disclosures nested inside it.
+ *
+ * The scope states both who owns this level's reveals and whether they are
+ * currently shown, so a nested level needs no knowledge of its ancestors: a
+ * collapsed whole-turn process closes every group under it, while each group
+ * keeps the choice the user made for it.
+ */
export function DisclosureScope({
disclosure,
open = disclosure.open,
@@ -153,9 +174,9 @@ export function DisclosureScope({
open?: boolean;
children: ReactNode;
}) {
- const value = useMemo(() => ({
+ const value = useMemo(() => ({
claim: disclosure.claim,
- visible: disclosure.parentVisible && open,
- }), [disclosure.claim, disclosure.parentVisible, open]);
- return {children} ;
+ visible: open,
+ }), [disclosure.claim, open]);
+ return {children} ;
}
diff --git a/apps/desktop/src/features/settings/SettingsPage.tsx b/apps/desktop/src/features/settings/SettingsPage.tsx
index a811909366..90c4537408 100644
--- a/apps/desktop/src/features/settings/SettingsPage.tsx
+++ b/apps/desktop/src/features/settings/SettingsPage.tsx
@@ -37,6 +37,7 @@ import { ModelConfigPage } from "../../components/settings/ModelConfigPage";
import { KeyboardShortcutsSection } from "../../components/settings/KeyboardShortcutsSection";
import { FontFamilyRow } from "../../components/settings/FontFamilyRow";
import { ShowThinkingRow } from "../../components/settings/ShowThinkingRow";
+import { KeepCommandsExpandedRow } from "../../components/settings/KeepCommandsExpandedRow";
import { FontSizeRow } from "../../components/settings/FontSizeRow";
import { LanguageRow } from "../../components/settings/LanguageRow";
import { SettingsMenuSelect } from "../../components/settings/SettingsMenuSelect";
@@ -546,6 +547,7 @@ export function SettingsPage() {
+
| null | undefined,
+): boolean {
+ return settings?.keepCommandsExpanded !== false;
+}
diff --git a/apps/desktop/src/lib/settings-search.ts b/apps/desktop/src/lib/settings-search.ts
index 2395133a09..77c6b33196 100644
--- a/apps/desktop/src/lib/settings-search.ts
+++ b/apps/desktop/src/lib/settings-search.ts
@@ -120,6 +120,8 @@ export const SETTINGS_NAV: SettingsNavEntry[] = [
"settings.smoothStreamingDesc",
"settings.showThinking",
"settings.showThinkingDesc",
+ "settings.keepCommandsExpanded",
+ "settings.keepCommandsExpandedDesc",
"settings.contextUsageDisplay",
"settings.contextUsageDisplayRemaining",
"settings.contextUsageDisplayUsed",
diff --git a/apps/desktop/src/lib/turn-process.ts b/apps/desktop/src/lib/turn-process.ts
index 6dbdfb13ca..1a87885ee6 100644
--- a/apps/desktop/src/lib/turn-process.ts
+++ b/apps/desktop/src/lib/turn-process.ts
@@ -1,10 +1,11 @@
-import type { UiMessage } from "@pi-desktop/shared";
+import type { AgentActivity, UiMessage } from "@pi-desktop/shared";
import type {
AssistantActivityItem,
AssistantTurnEntry,
AssistantTurnPart,
} from "./assistant-turns";
import { isStandaloneRunActivity } from "./assistant-turns";
+import { isDelegationStartTool } from "./tool-display";
export function isThinkingActive(message: UiMessage, active: boolean): boolean {
return active && message.status === "streaming" && !message.content.trim();
@@ -39,14 +40,17 @@ export function processContainsMessage(
});
}
-/** A `Bash`/run call rendered as its own row outside any process disclosure. */
+/**
+ * A run call rendered as its own row beside the nested activity groups inside
+ * the turn's process disclosure.
+ */
export type TurnProcessRunSegment = {
kind: "run";
key: string;
item: Extract;
};
-/** One chronological chunk of non-run process content between run calls. */
+/** One chronological process chunk; ON mode splits it at run calls. */
export type TurnProcessBodySegment = {
kind: "process";
key: string;
@@ -55,21 +59,114 @@ export type TurnProcessBodySegment = {
export type TurnProcessSegment = TurnProcessRunSegment | TurnProcessBodySegment;
+/** A `Task` fan-out group is its own topology, never ordinary work. */
+function isDelegationGroupPart(
+ part: Extract,
+): boolean {
+ return part.items.some(
+ (item) => item.kind === "tool" && isDelegationStartTool(item.message.toolName),
+ );
+}
+
+/**
+ * Coalesce the activity chunks one folded process shows.
+ *
+ * Turn entries isolate every run row in its own activity part, so rendering the
+ * parts as built would still put a command beside the group it ran among. Folding
+ * means one group around the whole contiguous ordinary stretch: build a new part
+ * with the source items in order, keeping their identity, and let progress text
+ * and a `Task` fan-out stay hard boundaries. The new part ends where its last
+ * source part ended; the cached parts are never mutated.
+ */
+function coalesceProcessActivityParts(
+ parts: readonly AssistantTurnPart[],
+): AssistantTurnPart[] {
+ const coalesced: AssistantTurnPart[] = [];
+ let pending:
+ | {
+ delegation: boolean;
+ source: Extract;
+ items: AssistantActivityItem[];
+ merged: boolean;
+ endedAt?: string;
+ }
+ | undefined;
+ const flush = () => {
+ if (!pending) return;
+ // A group with nothing to join keeps its cached part identity, so an
+ // unchanged singleton group does not remount on every preference read.
+ coalesced.push(
+ pending.merged
+ ? {
+ kind: "activity",
+ items: pending.items,
+ ...(pending.endedAt === undefined ? {} : { endedAt: pending.endedAt }),
+ }
+ : pending.source,
+ );
+ pending = undefined;
+ };
+ for (const part of parts) {
+ if (part.kind === "message") {
+ flush();
+ coalesced.push(part);
+ continue;
+ }
+ const delegation = isDelegationGroupPart(part);
+ if (pending && pending.delegation === delegation) {
+ pending.items.push(...part.items);
+ pending.merged = true;
+ pending.endedAt = part.endedAt;
+ continue;
+ }
+ flush();
+ pending = {
+ delegation,
+ source: part,
+ items: [...part.items],
+ merged: false,
+ endedAt: part.endedAt,
+ };
+ }
+ flush();
+ return coalesced;
+}
+
/**
* Split one turn's process into the order it renders (ADR
* turn-process-and-thinking-display).
*
- * `Bash` and run aliases are pulled out of the process flow entirely: each is
- * its own `run` segment rendered as a standalone row with no process or group
- * ancestor, and adjacent calls stay separate. The remaining tools, thinking,
- * hosted searches and progress text keep their original order and are grouped
- * into `process` chunks between the run calls. Segment parts are the same part
- * objects as the input, so downstream reveal and active-tail identity still
- * hold.
+ * With `keepCommandsExpanded` the `Bash` and run aliases are pulled out of the
+ * process flow: each is its own `run` segment, rendered as a standalone row
+ * beside the nested groups rather than inside one, and adjacent calls stay
+ * separate. The remaining tools, thinking, hosted searches and progress text
+ * keep their original order and are grouped into `process` chunks between the
+ * run calls.
+ *
+ * Without it the run rows keep their place in the flow, so a command is just
+ * another row of the group it ran among - the layout before commands were
+ * separated at all. Because the entry builder keeps every run row in its own
+ * activity part, folding coalesces contiguous ordinary parts into one rendered
+ * group here, at render time. Progress messages remain paragraph boundaries and
+ * a `Task`/delegation group never absorbs ordinary work around it. The
+ * coalesced group is a new part whose end is the last source group's end; the
+ * source parts and their items are not mutated.
+ *
+ * Either way the turn renders one top-level disclosure; only the placement of
+ * run rows inside it changes. ON-mode segment parts are the same part objects
+ * as the input, so downstream reveal and active-tail identity still hold.
*/
export function segmentTurnProcess(
parts: readonly AssistantTurnPart[],
+ keepCommandsExpanded: boolean,
): TurnProcessSegment[] {
+ if (!keepCommandsExpanded) {
+ const first = parts[0];
+ if (!first) return [];
+ const key =
+ first.kind === "activity" ? first.items[0].message.id : first.message.id;
+ return [{ kind: "process", key, parts: coalesceProcessActivityParts(parts) }];
+ }
const segments: TurnProcessSegment[] = [];
let pending: AssistantTurnPart[] = [];
const flushProcess = () => {
@@ -95,6 +192,60 @@ export function segmentTurnProcess(
return segments;
}
+/**
+ * What the turn's process header says about the turn as a whole.
+ *
+ * One line, and it only answers "how did this turn end up" - never what it is
+ * working on, because a shell command can be arbitrarily long and would push
+ * the counts off the row.
+ *
+ * Precedence is deliberate: failure, stop, running, completed. A recorded
+ * failure outranks everything: the turn produced no answer, and a header
+ * reading "Processed" over a failed run hid that. A user stop outranks a live
+ * run and completion alike - the work was interrupted, not finished - and it is
+ * read from the turn's own aborted rows because the turn result only
+ * distinguishes completed from failed. Both assistant message rows and activity
+ * item rows count; a Stop while a tool or reasoning row is in flight settles
+ * there rather than in a trailing text. Delegate child rows are deliberately
+ * not scanned: a failed child is not a failed or stopped turn.
+ */
+export type TurnProcessPhase =
+ | { kind: "failed" }
+ | { kind: "stopped" }
+ /** Live work; `phase` names the runtime stage when one is known. */
+ | { kind: "running"; phase?: AgentActivity["phase"] }
+ | { kind: "completed" };
+
+export function turnProcessPhase({
+ parts,
+ isActive,
+ failed,
+ activity,
+}: {
+ parts: readonly AssistantTurnPart[];
+ isActive: boolean;
+ /** The turn recorded a failure of its own. */
+ failed: boolean;
+ /** Runtime phase while the turn is live, when the runtime reports one. */
+ activity?: AgentActivity;
+}): TurnProcessPhase {
+ if (failed) return { kind: "failed" };
+ // The turn result cannot say "stopped": the runtime records only completed or
+ // failed, and a user stop settles as an aborted row. Reading the aborted row
+ // is therefore the most precise signal available, whether it is the turn's
+ // text or an activity item (a tool, thinking, or hosted search) that was in
+ // flight. A denied tool is not a stop - the run continued without that call -
+ // so it stays a recorded issue.
+ const stopped = parts.some((part) =>
+ part.kind === "message"
+ ? part.message.status === "aborted"
+ : part.items.some((item) => item.message.status === "aborted"),
+ );
+ if (stopped) return { kind: "stopped" };
+ if (isActive) return { kind: "running", phase: activity?.phase };
+ return { kind: "completed" };
+}
+
/**
* Only a trailing assistant text can be the answer: text followed by tools is
* progress. The stream carries no final-answer marker, so a live trailing text
@@ -117,39 +268,6 @@ export function projectTurnProcess(entry: AssistantTurnEntry) {
return { process, responses };
}
-/**
- * Steps a process body renders under the thinking preference.
- *
- * `hideThinking` is `!showThinking`: completed reasoning rows and excerpts are
- * hidden, while the live reasoning indicator still counts as a visible step so
- * a thinking-only process keeps its indicator. The helper counts exactly the
- * parts it is given; Bash and run aliases are segmented out before rendering
- * and never reach a process chunk, so they are never counted here.
- */
-export function visibleProcessSteps(
- parts: readonly AssistantTurnPart[],
- hideThinking: boolean,
- active: boolean,
-): number {
- let count = 0;
- for (const part of parts) {
- if (part.kind === "message") {
- if (part.message.content.trim()) count += 1;
- continue;
- }
- for (const item of part.items) {
- if (
- item.kind !== "thinking" ||
- !hideThinking ||
- isThinkingActive(item.message, active)
- ) {
- count += 1;
- }
- }
- }
- return count;
-}
-
/** Use recorded message/tool timing for history; elapsed live time is UI-only. */
export function turnProcessTiming(parts: readonly AssistantTurnPart[]) {
const messages = parts.flatMap((part) =>
diff --git a/apps/desktop/src/styles/composer.css b/apps/desktop/src/styles/composer.css
index 569295a3ab..04cd62fbd3 100644
--- a/apps/desktop/src/styles/composer.css
+++ b/apps/desktop/src/styles/composer.css
@@ -225,7 +225,7 @@
}
/*
- * A plugin suggestion (`pi.composer.suggest`, ADR 0332) rides in the same
+ * A plugin suggestion (`pi.composer.suggest`, ADR 0333) rides in the same
* placeholder layer, so it can never cover a message. It reads brighter than
* the shell's own placeholder because it is text a person can take with Tab,
* not a hint about the box; the hint beside it stays quiet and never wraps.
diff --git a/apps/desktop/src/styles/messages.css b/apps/desktop/src/styles/messages.css
index 6e0cb0e622..7e6ff2e2a8 100644
--- a/apps/desktop/src/styles/messages.css
+++ b/apps/desktop/src/styles/messages.css
@@ -12,13 +12,12 @@
content-visibility: auto;
contain-intrinsic-size: auto 140px;
/* Paint containment clips descendants to the padding box, which squared off
- the deliberate bleed of the disclosure row chrome: the activity header
- pulls its hover fill 3px past the column edge and a run row's head 4px, so
- the icon can sit on the text's alignment line while the fill keeps its
- padding, and the focus ring reaches 3.5px beyond its own box. 8px covers
- the widest of them. .tool-activity-group clips the same chrome and carries
- the same margin. */
- overflow-clip-margin: 8px;
+ the deliberate bleed of the disclosure row chrome: both disclosure headers
+ pull their hover fill 4px past the column edge, and the two collapse-rail
+ controls occupy separate 14px lanes in the gutter. 34px covers the outer
+ lane. .tool-activity-group keeps its own clip for the subagent card
+ chrome. */
+ overflow-clip-margin: 34px;
}
.message-row.user {
@@ -1997,8 +1996,10 @@
align-items: center;
gap: 5px;
border-radius: var(--radius-sm);
- margin: 0 -3px;
- padding: 2px 5px;
+ /* Same inline geometry as a tool row's header: the icon and label sit on the
+ prose edge, while the hover fill bleeds 4px into the gutter. */
+ margin: 0 -4px;
+ padding: 2px 4px;
color: var(--ds-text-secondary);
font-size: var(--text-sm-plus);
text-align: left;
@@ -2034,17 +2035,6 @@
white-space: nowrap;
}
-/* Live tail while running: last thought line / current tool, single line. */
-.tool-activity-preview {
- max-width: min(100%, var(--chat-prose-max-width, 720px));
- margin: 1px 0 0 26px;
- overflow: hidden;
- color: var(--ds-text-muted);
- font-size: var(--text-xs-plus);
- text-overflow: ellipsis;
- white-space: nowrap;
-}
-
/* The caret closes the row, so a short label keeps it at the trailing edge. */
.tool-activity-caret {
display: inline-flex;
@@ -2122,10 +2112,6 @@
white-space: normal;
}
-.tool-activity-group.has-subagents .tool-activity-preview {
- margin: -3px 38px 8px;
-}
-
.tool-activity-group.has-subagents .tool-activity-body {
margin: 0;
border-left: 0;
@@ -2565,6 +2551,11 @@
padding: 2px 0;
}
+/* Leaf commands sit one step below the turn and group titles. */
+.tool-row-head.is-run .tool-row-name {
+ font-size: var(--text-sm);
+}
+
.tool-row-head.is-run .tool-row-header:hover {
background: transparent;
}
@@ -2839,6 +2830,30 @@
outline-offset: -2px;
}
+/* These bodies carry no content indent, so each rail keeps its own gutter lane
+ and stops at the header fill. The turn's control is the outer lane and the
+ nested group's is the inner lane: expanding a group never puts two hit
+ targets on the same pixels. Tool-row detail rails keep their tighter inset. */
+.turn-process-body > .disclosure-collapse-rail {
+ left: -32px;
+ width: 14px;
+ min-width: 14px;
+}
+
+.process-activity-body > .disclosure-collapse-rail {
+ left: -18px;
+ width: 14px;
+ min-width: 14px;
+}
+
+/* Keep the visible bar next to the content while the hit target extends into
+ the gutter. */
+.turn-process-body > .disclosure-collapse-rail::before,
+.process-activity-body > .disclosure-collapse-rail::before {
+ right: 0;
+ left: auto;
+}
+
/*
* What a delegate did, one level inside its `Task` row. The tile marks the
* boundary: everything inside it happened in the delegate's own context.
@@ -3357,7 +3372,11 @@
.turn-process-body {
position: relative;
- padding-left: 18px;
+ /* The turn's process and the levels it reveals share one left edge: a nested
+ group header or a run row starts exactly where the turn header does, so the
+ transcript reads as one column instead of an indenting staircase. Levels
+ stay distinguishable by type size and colour, not by indentation. */
+ padding-left: 0;
}
.turn-process-body[hidden],
@@ -3376,6 +3395,18 @@
margin-block: 6px;
}
+/* The turn's own title is the strongest level; a nested group is smaller and
+ quieter, while leaf run rows keep tool-row secondary text. Indentation is
+ not carrying this hierarchy. */
+.process-activity-group > .tool-activity-header {
+ color: var(--ds-text-muted);
+ font-size: var(--text-sm);
+}
+
+.process-activity-group > .tool-activity-header:hover {
+ color: var(--ds-text-primary);
+}
+
.process-activity-body {
position: relative;
min-width: 0;
@@ -3383,7 +3414,9 @@
.process-activity-group.grouped > .process-activity-body {
margin-block: 3px 6px;
- padding-inline-start: 12px;
+ /* Same left edge as the turn header above it. The smaller type is what marks
+ this as the nested level. */
+ padding-inline-start: 0;
}
/* The nested process levels share the base header row: no level-specific
diff --git a/apps/desktop/test/command-folding-settings.test.mjs b/apps/desktop/test/command-folding-settings.test.mjs
new file mode 100644
index 0000000000..cce05f9967
--- /dev/null
+++ b/apps/desktop/test/command-folding-settings.test.mjs
@@ -0,0 +1,54 @@
+import assert from "node:assert/strict";
+import { register } from "node:module";
+import test from "node:test";
+
+register(new URL("./helpers/ts-import-hooks.mjs", import.meta.url));
+
+const { SETTINGS_NAV, searchSettings } = await import(
+ "../src/lib/settings-search.ts"
+);
+const { en } = await import(
+ "../../../packages/i18n/src/locales/en/index.ts"
+);
+const { flattenCatalog } = await import(
+ "../../../packages/i18n/src/locale-info.ts"
+);
+
+const copy = flattenCatalog(en);
+const t = (key) => copy[key] ?? key;
+
+test("command folding is searchable from the AI preferences beside show thinking", () => {
+ const ai = SETTINGS_NAV.find((entry) => entry.id === "ai");
+ assert.ok(ai, "AI settings entry is registered");
+ const showThinkingAt = ai.keywordKeys.indexOf("settings.showThinking");
+ assert.ok(showThinkingAt >= 0, "show thinking remains indexed");
+ assert.deepEqual(
+ ai.keywordKeys.slice(showThinkingAt, showThinkingAt + 4),
+ [
+ "settings.showThinking",
+ "settings.showThinkingDesc",
+ "settings.keepCommandsExpanded",
+ "settings.keepCommandsExpandedDesc",
+ ],
+ );
+
+ const titleHits = searchSettings("collapse commands", t, {
+ developerMode: false,
+ includeDevelopmentOnly: false,
+ }).filter((hit) => hit.tab === "ai");
+ assert.ok(
+ titleHits.some((hit) => hit.rowKey === "settings.keepCommandsExpanded"),
+ "the command-folding title is searchable",
+ );
+
+ const descriptionHits = searchSettings("shell calls", t, {
+ developerMode: false,
+ includeDevelopmentOnly: false,
+ }).filter((hit) => hit.tab === "ai");
+ assert.ok(
+ descriptionHits.some(
+ (hit) => hit.rowKey === "settings.keepCommandsExpandedDesc",
+ ),
+ "the command-folding description is searchable",
+ );
+});
diff --git a/apps/desktop/test/composer-suggestion-relay.test.mjs b/apps/desktop/test/composer-suggestion-relay.test.mjs
index 820857e602..3bee91ce2f 100644
--- a/apps/desktop/test/composer-suggestion-relay.test.mjs
+++ b/apps/desktop/test/composer-suggestion-relay.test.mjs
@@ -4,7 +4,7 @@ import test from "node:test";
register(new URL("./helpers/ts-import-hooks.mjs", import.meta.url));
/*
- * The main-process half of `pi.composer.suggest` (ADR 0332): which offers never
+ * The main-process half of `pi.composer.suggest` (ADR 0333): which offers never
* reach the window, which one may answer, and what happens to a suggestion when
* the turn or the plugin behind it ends first.
*/
diff --git a/apps/desktop/test/composer-suggestion-state.test.mjs b/apps/desktop/test/composer-suggestion-state.test.mjs
index 15d98a5db7..8335a3d03c 100644
--- a/apps/desktop/test/composer-suggestion-state.test.mjs
+++ b/apps/desktop/test/composer-suggestion-state.test.mjs
@@ -4,7 +4,7 @@ import test from "node:test";
register(new URL("./helpers/ts-import-hooks.mjs", import.meta.url));
/*
- * The renderer half of `pi.composer.suggest` (ADR 0332): whether an offer can go
+ * The renderer half of `pi.composer.suggest` (ADR 0333): whether an offer can go
* on screen, what takes it down, and which key acts on it while the completion
* list still owns Tab and the first Escape.
*/
diff --git a/apps/desktop/test/macos-window-translucency.test.mjs b/apps/desktop/test/macos-window-translucency.test.mjs
index 8b1eb6a515..c71aefb4af 100644
--- a/apps/desktop/test/macos-window-translucency.test.mjs
+++ b/apps/desktop/test/macos-window-translucency.test.mjs
@@ -97,7 +97,8 @@ test("the switch is macOS-only and says when a restart is needed", async () => {
test("both settings write paths reject a non-boolean translucency value", async () => {
const rendererApi = await read("../src/lib/api.ts");
const mainCatalog = await readMainModule("runtime/provider-catalog.ts");
- assert.match(rendererApi, /"macosWindowTranslucency",\s*\] as const\) \{/);
+ const booleanKeys = rendererApi.match(/for \(const key of \[([\s\S]*?)\] as const\) \{/)?.[1];
+ assert.match(booleanKeys ?? "", /"macosWindowTranslucency"/);
assert.match(rendererApi, /typeof value\[key\] !== "boolean"/);
assert.match(
mainCatalog,
diff --git a/apps/desktop/test/settings-roundtrip.test.mjs b/apps/desktop/test/settings-roundtrip.test.mjs
index 3c391a2fb5..b1e901f456 100644
--- a/apps/desktop/test/settings-roundtrip.test.mjs
+++ b/apps/desktop/test/settings-roundtrip.test.mjs
@@ -1,6 +1,7 @@
import assert from "node:assert/strict";
import { register } from "node:module";
import test from "node:test";
+import { IPC } from "@pi-desktop/shared";
register(new URL("./helpers/ts-import-hooks.mjs", import.meta.url));
const renderer = await import("../src/lib/api.ts");
const { createProviderCatalogRuntime } = await import("../electron/main/runtime/provider-catalog.ts");
@@ -10,7 +11,12 @@ test("settings read-modify-write preserves disabled retry and unrelated preferen
const previousWindow = globalThis.window;
globalThis.window = { piDesktop: { platform: "win32" } };
try {
- for (const stored of [{}, { infiniteProviderRetry: false }, { infiniteProviderRetry: true }]) {
+ for (const stored of [
+ {},
+ { infiniteProviderRetry: false },
+ { infiniteProviderRetry: true },
+ { keepCommandsExpanded: false },
+ ]) {
const original = { defaultMode: "agent", theme: "light", ...stored };
const received = structuredClone(main.normalizeSettings(original));
const displayed = renderer.normalizeSettings(received);
@@ -18,6 +24,11 @@ test("settings read-modify-write preserves disabled retry and unrelated preferen
const outgoing = renderer.validateSettingsWrite(edited);
const persisted = main.validateSettingsWrite(structuredClone(outgoing));
assert.equal(persisted.infiniteProviderRetry, stored.infiniteProviderRetry === true);
+ // Absent means on; an explicit false survives both boundaries.
+ assert.equal(
+ persisted.keepCommandsExpanded,
+ stored.keepCommandsExpanded !== false,
+ );
assert.equal(persisted.theme, "light");
assert.deepEqual(persisted.imageGeneration, edited.imageGeneration);
}
@@ -34,3 +45,92 @@ test("invalid retry writes stay rejected at both boundaries", () => {
assert.throws(() => main.validateSettingsWrite(settings), /infiniteProviderRetry is invalid/);
}
});
+
+test("command folding defaults on and rejects non-boolean writes before IPC", () => {
+ const previousWindow = globalThis.window;
+ let invoked = 0;
+ globalThis.window = {
+ piDesktop: {
+ platform: "win32",
+ invoke: async () => {
+ invoked += 1;
+ return { ok: true, data: undefined };
+ },
+ },
+ };
+ try {
+ const base = { defaultMode: "agent", theme: "light", enterToSend: true };
+ assert.equal(
+ renderer.normalizeSettings(base).keepCommandsExpanded,
+ true,
+ );
+ assert.equal(
+ renderer.normalizeSettings({ ...base, keepCommandsExpanded: false })
+ .keepCommandsExpanded,
+ false,
+ );
+ assert.equal(
+ main.normalizeSettings({ ...base, keepCommandsExpanded: false })
+ .keepCommandsExpanded,
+ false,
+ );
+ for (const value of ["yes", 0, null, undefined, {}]) {
+ assert.throws(
+ () => renderer.validateSettingsWrite({ keepCommandsExpanded: value }),
+ /keepCommandsExpanded is invalid/,
+ );
+ assert.throws(
+ () => renderer.api.setSettings({ keepCommandsExpanded: value }),
+ /keepCommandsExpanded is invalid/,
+ );
+ }
+ assert.equal(invoked, 0, "invalid writes must not reach the preload bridge");
+ } finally {
+ if (previousWindow === undefined) delete globalThis.window;
+ else globalThis.window = previousWindow;
+ }
+});
+
+test("settings write round-trips command folding through the preload boundary", async () => {
+ const previousWindow = globalThis.window;
+ const calls = [];
+ let stored = {
+ defaultMode: "agent",
+ theme: "light",
+ enterToSend: true,
+ onboardingDismissed: false,
+ };
+ globalThis.window = {
+ piDesktop: {
+ platform: "win32",
+ invoke: async (channel, payload) => {
+ calls.push({ channel, payload });
+ if (channel === IPC.invoke.settingsGet) {
+ return { ok: true, data: structuredClone(stored) };
+ }
+ if (channel === IPC.invoke.settingsSet) {
+ stored = { ...stored, ...structuredClone(payload) };
+ return { ok: true, data: undefined };
+ }
+ throw new Error(`Unexpected settings IPC: ${channel}`);
+ },
+ },
+ };
+ try {
+ const initial = await renderer.api.getSettings();
+ assert.equal(initial.keepCommandsExpanded, true);
+
+ await renderer.api.setSettings({ ...initial, keepCommandsExpanded: false });
+
+ const write = calls.find(({ channel }) => channel === IPC.invoke.settingsSet);
+ assert.ok(write, "settings write must cross the preload boundary");
+ assert.equal(write.payload.keepCommandsExpanded, false);
+ assert.equal(stored.keepCommandsExpanded, false);
+
+ const reread = await renderer.api.getSettings();
+ assert.equal(reread.keepCommandsExpanded, false);
+ } finally {
+ if (previousWindow === undefined) delete globalThis.window;
+ else globalThis.window = previousWindow;
+ }
+});
diff --git a/apps/desktop/test/thinking-ui.test.mjs b/apps/desktop/test/thinking-ui.test.mjs
index 824438583f..04dfcbfb99 100644
--- a/apps/desktop/test/thinking-ui.test.mjs
+++ b/apps/desktop/test/thinking-ui.test.mjs
@@ -243,8 +243,7 @@ test("transcript keeps assistant thinking in a separate disclosure", () => {
assert.match(transcriptSource, /tool-row thinking/);
assert.match(transcriptSource, /className="tool-row-header"/);
assert.match(transcriptSource, /aria-expanded=\{open\}/);
- assert.match(transcriptSource, /aria-hidden=\{!open\}/);
- assert.match(transcriptSource, /inert=\{!open\}/);
+ assert.match(transcriptSharedSource, /\{open \? \(\s* {
diff --git a/apps/desktop/test/transcript-disclosure-reading.test.mjs b/apps/desktop/test/transcript-disclosure-reading.test.mjs
index 69edc59b4e..cc62a7d8b6 100644
--- a/apps/desktop/test/transcript-disclosure-reading.test.mjs
+++ b/apps/desktop/test/transcript-disclosure-reading.test.mjs
@@ -29,7 +29,7 @@ test("automatic disclosure does not claim a reading position", () => {
// the scroll anchor notifier reserved for direct user interaction.
assert.match(disclosure, /if \(previousOpen\.current && !open && !choice && ownsReadingPosition/);
const revealEffect = disclosure.match(
- /useLayoutEffect\(\(\) => \{\s*if \(revealRequest === undefined[\s\S]*?\n \}, \[choices, key, parent\.claim, revealRequest\]\);/,
+ /useLayoutEffect\(\(\) => \{\s*if \(revealRequest === undefined[\s\S]*?\n \}, \[choices, key, scope\.claim, revealRequest\]\);/,
)?.[0];
assert.ok(revealEffect, "the automatic reveal effect is missing");
assert.doesNotMatch(revealEffect, /notifyAnchor/);
diff --git a/apps/desktop/test/transcript-style.test.mjs b/apps/desktop/test/transcript-style.test.mjs
index 13a8b7d136..5955030584 100644
--- a/apps/desktop/test/transcript-style.test.mjs
+++ b/apps/desktop/test/transcript-style.test.mjs
@@ -128,6 +128,68 @@ test("tool details do not add a second visual indent", () => {
assert.match(stylesSource, /\.subagent-topology-node > \.tool-row-body,[\s\S]*?margin-left:\s*38px;/);
});
+
+test("the turn process and the levels it reveals share one left edge", () => {
+ // A nested group header sits on the same vertical line as the turn header that
+ // reveals it. Indentation used to carry that hierarchy; it is now carried by
+ // type size and colour, so a stray padding here would silently bring the
+ // staircase back.
+ const turnBody = stylesSource.match(/\.turn-process-body \{([^}]*)\}/)?.[1];
+ assert.ok(turnBody);
+ assert.match(turnBody, /padding-left:\s*0;/);
+ const groupedBody = stylesSource.match(
+ /\.process-activity-group\.grouped > \.process-activity-body \{([^}]*)\}/,
+ )?.[1];
+ assert.ok(groupedBody);
+ assert.match(groupedBody, /padding-inline-start:\s*0;/);
+ // Both disclosure headers use the tool-row inline geometry: content at the
+ // prose edge, fill four pixels into the gutter.
+ const activityHeader = stylesSource.match(/\n\.tool-activity-header \{([^}]*)\}/)?.[1];
+ assert.ok(activityHeader);
+ assert.match(activityHeader, /margin:\s*0 -4px;/);
+ assert.match(activityHeader, /padding:\s*2px 4px;/);
+});
+
+test("nested process levels keep a subtle type and colour hierarchy", () => {
+ // The turn title stays at the base size; the nested group is smaller and
+ // quieter, and a run row uses the leaf size while keeping readable colour.
+ const nested = stylesSource.match(
+ /\.process-activity-group > \.tool-activity-header \{([^}]*)\}/,
+ )?.[1];
+ assert.ok(nested);
+ assert.match(nested, /font-size:\s*var\(--text-sm\);/);
+ assert.match(nested, /color:\s*var\(--ds-text-muted\);/);
+ const runName = stylesSource.match(
+ /\.tool-row-head\.is-run \.tool-row-name \{([^}]*)\}/,
+ )?.[1];
+ assert.ok(runName);
+ assert.match(runName, /font-size:\s*var\(--text-sm\);/);
+});
+
+test("collapse rails keep separate zero-padding gutter lanes", () => {
+ const turnRail = stylesSource.match(
+ /\.turn-process-body > \.disclosure-collapse-rail \{([^}]*)\}/,
+ )?.[1];
+ assert.ok(turnRail);
+ assert.match(turnRail, /left:\s*-32px;/);
+ assert.match(turnRail, /width:\s*14px;/);
+ const groupRail = stylesSource.match(
+ /\.process-activity-body > \.disclosure-collapse-rail \{([^}]*)\}/,
+ )?.[1];
+ assert.ok(groupRail);
+ assert.match(groupRail, /left:\s*-18px;/);
+ assert.match(groupRail, /width:\s*14px;/);
+ const messageRow = stylesSource.match(/\.message-row \{([^}]*)\}/)?.[1];
+ assert.ok(messageRow);
+ assert.match(messageRow, /overflow-clip-margin:\s*34px;/);
+});
+
+test("the header never echoes the item it is working on", () => {
+ // Long shell commands and search queries pushed the counts off the row when the
+ // header previewed them, so the live tail preview is gone entirely.
+ assert.doesNotMatch(stylesSource, /\.tool-activity-preview/);
+});
+
/*
* The width regression this guards: a content-sized `inline-flex` disclosure
* header stopped at its own label, so a tool call never used the conversation
diff --git a/apps/desktop/test/transcript-summary.test.mjs b/apps/desktop/test/transcript-summary.test.mjs
index 50322ca52c..4062790aec 100644
--- a/apps/desktop/test/transcript-summary.test.mjs
+++ b/apps/desktop/test/transcript-summary.test.mjs
@@ -8,7 +8,7 @@ const {
assistantTurnResponseOutputIsEstimated, assistantTurnTools,
} = await import("../src/lib/assistant-turns.ts");
const { getAssistantTurnSummary, getAssistantTurnContent, messageContentFacts, reuseReferences } = await import("../src/lib/transcript-summary.ts");
-const { projectTurnProcess, visibleProcessSteps } = await import("../src/lib/turn-process.ts");
+const { projectTurnProcess } = await import("../src/lib/turn-process.ts");
const { activitySummary, visibleActivityItems } = await import("../src/lib/activity-summary.ts");
const { cachedActivitySummary, cachedVisibleActivityItems, cachedVisibleProcessSteps, activityTimingInputs } = await import("../src/lib/transcript-activity-summary.ts");
const { collectDelegationStatuses, collectDelegationTimings, delegationTimingBounds } = await import("../src/lib/subagent-topology.ts");
@@ -113,7 +113,10 @@ test("activity summary and compact visibility preserve error, search and thinkin
for (const compact of [false, true]) for (const active of [false, true]) {
assert.deepEqual(cachedVisibleActivityItems(subset, compact, active), visibleActivityItems(subset, compact, active));
const parts = [{ kind: "activity", items: subset }, { kind: "message", message: message("progress", "progress") }];
- assert.equal(cachedVisibleProcessSteps(parts, compact, active), visibleProcessSteps(parts, compact, active));
+ assert.equal(
+ cachedVisibleProcessSteps(parts, compact, active),
+ 1 + cachedVisibleActivityItems(subset, compact, active).length,
+ );
}
}
});
diff --git a/apps/desktop/test/turn-process.test.mjs b/apps/desktop/test/turn-process.test.mjs
index 1a3bb25b12..c2fb32b68b 100644
--- a/apps/desktop/test/turn-process.test.mjs
+++ b/apps/desktop/test/turn-process.test.mjs
@@ -8,9 +8,12 @@ const { buildTranscriptEntries, isStandaloneRunActivity } = await import(
const {
projectTurnProcess,
segmentTurnProcess,
- visibleProcessSteps,
turnProcessTiming,
+ turnProcessPhase,
} = await import("../src/lib/turn-process.ts");
+const { cachedActivitySummary, cachedVisibleProcessSteps } = await import(
+ "../src/lib/transcript-activity-summary.ts"
+);
const message = (id, role, content, extra = {}) => ({
id,
@@ -40,8 +43,8 @@ test("one turn groups thinking, tools and progress while retaining only the trai
projected.responses.map((part) => part.message.id),
["final"],
);
- assert.equal(visibleProcessSteps(projected.process, false, false), 5);
- assert.equal(visibleProcessSteps(projected.process, true, false), 4);
+ assert.equal(cachedVisibleProcessSteps(projected.process, false, false), 5);
+ assert.equal(cachedVisibleProcessSteps(projected.process, true, false), 4);
});
test("streamed text stays readable until later work establishes it as progress", () => {
@@ -83,11 +86,11 @@ test("hidden thinking disappears after reasoning ends without removing stored da
status: "streaming",
});
const entry = turn([thinking]);
- assert.equal(visibleProcessSteps(entry.parts, true, true), 1);
- assert.equal(visibleProcessSteps(entry.parts, true, false), 0);
+ assert.equal(cachedVisibleProcessSteps(entry.parts, true, true), 1);
+ assert.equal(cachedVisibleProcessSteps(entry.parts, true, false), 0);
const withAnswer = turn([{ ...thinking, content: "Answer" }]);
assert.equal(
- visibleProcessSteps(projectTurnProcess(withAnswer).process, true, true),
+ cachedVisibleProcessSteps(projectTurnProcess(withAnswer).process, true, true),
0,
);
assert.equal(thinking.thinking, "Private reasoning");
@@ -151,7 +154,7 @@ test("process segments pull every Bash row out and keep chronological chunks", (
tool("bash", "Bash", { toolArgs: { command: "ls" } }),
tool("edit", "Edit", { toolResult: "c" }),
]);
- const segments = segmentTurnProcess(projectTurnProcess(entry).process);
+ const segments = segmentTurnProcess(projectTurnProcess(entry).process, true);
assert.deepEqual(
segments.map((segment) => segment.kind),
["process", "run", "process"],
@@ -174,7 +177,7 @@ test("a Bash-only turn has no process segment at all", () => {
tool("bash1", "Bash", { toolArgs: { command: "a" } }),
tool("bash2", "Bash", { toolArgs: { command: "b" } }),
]);
- const segments = segmentTurnProcess(projectTurnProcess(entry).process);
+ const segments = segmentTurnProcess(projectTurnProcess(entry).process, true);
assert.deepEqual(
segments.map((segment) => segment.kind),
["run", "run"],
@@ -187,7 +190,7 @@ test("a turn without Bash keeps one process segment", () => {
tool("read", "Read", { toolResult: "a" }),
tool("grep", "Grep", { toolResult: "b" }),
]);
- const segments = segmentTurnProcess(projectTurnProcess(entry).process);
+ const segments = segmentTurnProcess(projectTurnProcess(entry).process, true);
assert.deepEqual(
segments.map((segment) => segment.kind),
["process"],
@@ -230,6 +233,331 @@ test("user boundaries retain independent processes and delegation details stay a
assert.equal(projectTurnProcess(entries[1]).process.length, 0);
});
+test("a turn's process is one disclosure that owns every run row", () => {
+ // The transcript renders exactly one process disclosure per assistant turn and
+ // puts the run rows inside it, so a turn collapses in one gesture instead of
+ // leaving a column of sibling disclosures above the answer.
+ const entry = turn([
+ message("user", "user", "Run"),
+ tool("read1", "Read", { toolResult: "a" }),
+ tool("bash1", "Bash", { toolArgs: { command: "a" } }),
+ tool("grep1", "Grep", { toolResult: "b" }),
+ tool("bash2", "Bash", { toolArgs: { command: "b" } }),
+ message("final", "assistant", "Done"),
+ ]);
+ const process = projectTurnProcess(entry).process;
+ // Every part of the process belongs to that one disclosure, and the answer
+ // stays outside it.
+ assert.ok(process.every((part) => entry.parts.includes(part)));
+ assert.equal(projectTurnProcess(entry).responses.length, 1);
+});
+
+test("folding commands coalesces mixed work across run rows without mutating entry parts", () => {
+ // The preference only decides where run rows sit. Both values keep exactly one
+ // segment, so the turn still renders one disclosure; off joins the ordinary
+ // activity chunks around a run row into one rendered group.
+ const entry = turn([
+ message("user", "user", "Run"),
+ message("intro", "assistant", "Inspecting"),
+ tool("read", "Read", { toolResult: "a" }),
+ tool("grep", "Grep", { toolResult: "b" }),
+ tool("bash", "Bash", { toolArgs: { command: "pnpm test" } }),
+ tool("edit", "Edit", { toolResult: "c" }),
+ tool("write", "Write", { toolResult: "d" }),
+ message("progress", "assistant", "Still working", {
+ createdAt: "2026-09-17T00:00:05.000Z",
+ }),
+ tool("read2", "Read", { toolResult: "e" }),
+ message("final", "assistant", "Done", {
+ createdAt: "2026-09-17T00:00:06.000Z",
+ }),
+ ]);
+ const process = projectTurnProcess(entry).process;
+ const sourceActivities = process.filter((part) => part.kind === "activity");
+ const sourceItems = sourceActivities.flatMap((part) => part.items);
+ const sourceEnds = sourceActivities.map((part) => part.endedAt);
+ // Freeze the cached projection so an in-place merge throws instead of quietly
+ // rewriting the entry.
+ for (const part of process) {
+ if (part.kind !== "activity") continue;
+ Object.freeze(part.items);
+ Object.freeze(part);
+ }
+ Object.freeze(process);
+ const [segment] = segmentTurnProcess(process, false);
+ assert.equal(segment.kind, "process");
+ // Progress text stays a paragraph boundary, so the run joins the group before
+ // it rather than the one after it.
+ assert.deepEqual(
+ segment.parts.map((part) => part.kind),
+ ["message", "activity", "message", "activity"],
+ );
+ const merged = segment.parts[1];
+ assert.notEqual(merged, process[1]);
+ assert.deepEqual(
+ merged.items.map((item) => item.message.id),
+ ["read", "grep", "bash", "edit", "write"],
+ );
+ // The coalesced group keeps every source item identity.
+ assert.ok(merged.items.every((item, index) => item === sourceItems[index]));
+ // Its end is the last source group's end, not the first one's, and the source
+ // parts keep the ends the entry builder gave them.
+ assert.equal(merged.endedAt, "2026-09-17T00:00:05.000Z");
+ assert.deepEqual(sourceActivities.map((part) => part.endedAt), sourceEnds);
+ // A group with nothing to join keeps its cached source part identity.
+ assert.equal(segment.parts[0], process[0]);
+ assert.equal(segment.parts[3], process[5]);
+ assert.deepEqual(
+ segment.parts[3].items.map((item) => item.message.id),
+ ["read2"],
+ );
+ // ON is unchanged: the original chunks are still separate and the run row is
+ // still a standalone segment with its original item identity.
+ const on = segmentTurnProcess(process, true);
+ assert.deepEqual(on.map((part) => part.kind), ["process", "run", "process"]);
+ assert.equal(on[0].parts[0], process[0]);
+ assert.equal(on[0].parts[1], process[1]);
+ assert.equal(on[1].item, sourceActivities[1].items[0]);
+ const again = segmentTurnProcess(process, true);
+ assert.deepEqual(again.map((part) => part.kind), on.map((part) => part.kind));
+ assert.equal(again[0].parts[0], process[0]);
+});
+
+test("folding commands keeps Task topology and progress text as group boundaries", () => {
+ const entry = turn([
+ message("user", "user", "Run"),
+ tool("read", "Read", { toolResult: "a" }),
+ tool("bash1", "Bash", { toolArgs: { command: "a" } }),
+ tool("task", "Task", { toolCallId: "call", toolResult: "started" }),
+ message("nested", "assistant", "Delegate answer", {
+ parentToolCallId: "call",
+ }),
+ tool("bash2", "Bash", { toolArgs: { command: "b" } }),
+ tool("edit", "Edit", { toolResult: "c" }),
+ message("progress", "assistant", "Progress"),
+ tool("write", "Write", { toolResult: "d" }),
+ ]);
+ const [segment] = segmentTurnProcess(
+ projectTurnProcess(entry).process,
+ false,
+ );
+ const activityIds = segment.parts.flatMap((part) =>
+ part.kind === "activity"
+ ? [part.items.map((item) => item.message.id)]
+ : [],
+ );
+ // Ordinary work across the first run coalesces, but no ordinary row joins a
+ // Task group on either side. The progress paragraph then starts a new group.
+ assert.deepEqual(activityIds, [
+ ["read", "bash1"],
+ ["task"],
+ ["bash2", "edit"],
+ ["write"],
+ ]);
+ const task = segment.parts[1];
+ assert.equal(task.kind, "activity");
+ assert.equal(task.items[0].delegate.items[0].message.id, "nested");
+});
+
+test("a Bash-only turn keeps one segment whether commands are expanded or not", () => {
+ const entry = turn([
+ message("user", "user", "Run"),
+ tool("bash1", "Bash", { toolArgs: { command: "a" } }),
+ tool("bash2", "Bash", { toolArgs: { command: "b" } }),
+ ]);
+ const process = projectTurnProcess(entry).process;
+ assert.deepEqual(segmentTurnProcess(process, true).map((s) => s.kind), ["run", "run"]);
+ assert.deepEqual(segmentTurnProcess(process, false).map((s) => s.kind), ["process"]);
+});
+
+test("an empty process segments to nothing in either mode", () => {
+ assert.deepEqual(segmentTurnProcess([], false), []);
+ assert.deepEqual(segmentTurnProcess([], true), []);
+});
+
+test("the turn header reports failure, stop, live and completion in that order", () => {
+ const abortedMessage = {
+ kind: "message",
+ message: message("a", "assistant", "partial", { status: "aborted" }),
+ };
+ const abortedBash = {
+ kind: "activity",
+ items: [{
+ kind: "tool",
+ message: message("bash", "tool", "", {
+ toolName: "Bash",
+ status: "aborted",
+ }),
+ }],
+ };
+ const abortedThinking = {
+ kind: "activity",
+ items: [{
+ kind: "thinking",
+ message: message("think", "assistant", "", {
+ thinking: "reasoning",
+ status: "aborted",
+ }),
+ }],
+ };
+ for (const aborted of [abortedMessage, abortedBash, abortedThinking]) {
+ // A recorded failure outranks a stop: the turn still ended without an answer.
+ assert.deepEqual(
+ turnProcessPhase({ parts: [aborted], isActive: false, failed: true }),
+ { kind: "failed" },
+ );
+ assert.deepEqual(
+ turnProcessPhase({ parts: [aborted], isActive: false, failed: false }),
+ { kind: "stopped" },
+ );
+ // A stop also outranks a live runtime phase: the work was interrupted, not
+ // still running.
+ assert.deepEqual(
+ turnProcessPhase({
+ parts: [aborted],
+ isActive: true,
+ failed: false,
+ activity: { phase: "compacting", since: 0 },
+ }),
+ { kind: "stopped" },
+ );
+ }
+ assert.deepEqual(
+ turnProcessPhase({
+ parts: [{ kind: "message", message: message("b", "assistant", "done", { status: "complete" }) }],
+ isActive: false,
+ failed: false,
+ }),
+ { kind: "completed" },
+ );
+ // Running carries the runtime stage when the turn is live and not stopped.
+ assert.deepEqual(
+ turnProcessPhase({
+ parts: [],
+ isActive: true,
+ failed: false,
+ activity: { phase: "compacting", since: 0 },
+ }),
+ { kind: "running", phase: "compacting" },
+ );
+});
+
+test("a failed child never turns a completed turn into failed or stopped", () => {
+ const task = {
+ kind: "activity",
+ items: [{
+ kind: "tool",
+ message: message("task", "tool", "", {
+ toolName: "Task",
+ toolCallId: "call",
+ status: "complete",
+ }),
+ delegate: {
+ items: [{
+ kind: "answer",
+ message: message("child", "assistant", "", {
+ parentToolCallId: "call",
+ status: "aborted",
+ error: { code: "TURN_ABORTED", message: "stopped" },
+ }),
+ }],
+ },
+ }],
+ };
+ assert.deepEqual(
+ turnProcessPhase({ parts: [task], isActive: false, failed: false }),
+ { kind: "completed" },
+ );
+ // A failed turn is still failed, independent of the child.
+ assert.deepEqual(
+ turnProcessPhase({ parts: [task], isActive: false, failed: true }),
+ { kind: "failed" },
+ );
+ // The turn's own Task row being aborted is its own stop signal.
+ const ownAborted = {
+ ...task,
+ items: [{ ...task.items[0], message: { ...task.items[0].message, status: "aborted" } }],
+ };
+ assert.deepEqual(
+ turnProcessPhase({ parts: [ownAborted], isActive: false, failed: false }),
+ { kind: "stopped" },
+ );
+});
+
+test("the header count comes from the production activity summary", () => {
+ const entry = turn([
+ message("user", "user", "Run"),
+ tool("read", "Read", { toolResult: "a" }),
+ tool("bash1", "Bash", { toolArgs: { command: "a" } }),
+ tool("bash2", "Bash", { toolArgs: { command: "b" } }),
+ tool("grep", "Grep", { toolResult: "b" }),
+ ]);
+ const process = projectTurnProcess(entry).process;
+ const items = process.flatMap((part) =>
+ part.kind === "activity" ? part.items : [],
+ );
+ const summary = cachedActivitySummary(items);
+ assert.equal(summary.tools, 4);
+ assert.equal(summary.count, 4);
+ assert.equal(summary.issues, 0);
+ assert.equal(summary.label, "chat.activityTools");
+ const bashOnly = turn([
+ message("user", "user", "Run"),
+ tool("bash1", "Bash", { toolArgs: { command: "a" } }),
+ tool("bash2", "Bash", { toolArgs: { command: "b" } }),
+ ]);
+ const bashItems = projectTurnProcess(bashOnly).process.flatMap((part) =>
+ part.kind === "activity" ? part.items : [],
+ );
+ assert.equal(cachedActivitySummary(bashItems).tools, 2);
+ assert.equal(cachedActivitySummary(bashItems).label, "chat.activityCommands");
+});
+
+test("the shared process-step helper counts message rows and hides content-backed thinking", () => {
+ const progress = {
+ kind: "message",
+ message: message("progress", "assistant", "Inspecting"),
+ };
+ // A message-only process is still visible: the disclosure needs a non-zero
+ // step count even when no activity item exists.
+ assert.equal(cachedVisibleProcessSteps([progress], true, false), 1);
+ assert.equal(cachedVisibleProcessSteps([progress], true, true), 1);
+ // A streaming assistant row with content counts its content only. The
+ // reasoning beside it is hidden by the preference, so it adds no step.
+ const streamingContentAndThinking = {
+ kind: "message",
+ message: message("answer", "assistant", "Visible answer", {
+ thinking: "Reasoning with content",
+ status: "streaming",
+ }),
+ };
+ assert.equal(
+ cachedVisibleProcessSteps([streamingContentAndThinking], true, true),
+ 1,
+ );
+ // A live reasoning-only row keeps its indicator; completed reasoning does not.
+ const thinkingItem = {
+ kind: "thinking",
+ message: message("think", "assistant", "", {
+ thinking: "Reasoning",
+ status: "streaming",
+ }),
+ };
+ assert.equal(
+ cachedVisibleProcessSteps([{ kind: "activity", items: [thinkingItem] }], true, true),
+ 1,
+ );
+ assert.equal(
+ cachedVisibleProcessSteps(
+ [{ kind: "activity", items: [{ ...thinkingItem, message: { ...thinkingItem.message, status: "complete" } }] }],
+ true,
+ false,
+ ),
+ 0,
+ );
+});
+
+
test("settings writes validate the thinking preference without changing other preferences", async () => {
const { validateSettingsWrite } = await import("../src/lib/api.ts");
const settings = {
diff --git a/crates/host-core/src/config_sync/domains.rs b/crates/host-core/src/config_sync/domains.rs
index 2336e23d24..076441beed 100644
--- a/crates/host-core/src/config_sync/domains.rs
+++ b/crates/host-core/src/config_sync/domains.rs
@@ -35,6 +35,7 @@ pub(crate) const PORTABLE_APPLICATION_FIELDS: &[&str] = &[
"fontScale",
"showThinking",
"thinkingDisplayMode",
+ "keepCommandsExpanded",
"enterToSend",
"largePasteThreshold",
"defaultProviderId",
@@ -101,6 +102,7 @@ pub const DOMAIN_ADAPTERS: &[DomainAdapterSpec] = &[
"showThinking",
"thinkingDisplayMode",
"enterToSend",
+ "keepCommandsExpanded",
"keybindings",
"display bindings",
"provider/model bindings",
@@ -626,15 +628,20 @@ mod tests {
fn adapter_registry_covers_every_portable_domain() {
assert_eq!(DOMAIN_ADAPTERS.len(), ALL_DOMAINS.len());
assert!(!PORTABLE_APPLICATION_FIELDS.contains(&"defaultPermissionMode"));
- // The explicit reasoning-display boolean and its legacy fallback are
- // both portable, and both are advertised by the application adapter.
+ // The explicit reasoning-display boolean, its legacy fallback, and the
+ // command-folding preference are portable, and each is advertised by the
+ // application adapter.
assert!(PORTABLE_APPLICATION_FIELDS.contains(&"showThinking"));
assert!(PORTABLE_APPLICATION_FIELDS.contains(&"thinkingDisplayMode"));
+ assert!(PORTABLE_APPLICATION_FIELDS.contains(&"keepCommandsExpanded"));
let application = adapter_for(DOMAIN_APPLICATION).expect("application adapter");
assert!(application.exportable_fields.contains(&"showThinking"));
assert!(application
.exportable_fields
.contains(&"thinkingDisplayMode"));
+ assert!(application
+ .exportable_fields
+ .contains(&"keepCommandsExpanded"));
for domain in ALL_DOMAINS {
let adapter = adapter_for(domain).expect("portable domain adapter");
assert_eq!(adapter.schema_version, 1);
diff --git a/crates/host-core/src/config_sync/engine_s3_tests.rs b/crates/host-core/src/config_sync/engine_s3_tests.rs
index a9882ad524..b5ad1b5393 100644
--- a/crates/host-core/src/config_sync/engine_s3_tests.rs
+++ b/crates/host-core/src/config_sync/engine_s3_tests.rs
@@ -120,15 +120,17 @@ async fn application_show_thinking_roundtrips_and_keeps_local_only_settings() ->
let directory_b = tempfile::tempdir()?;
let device_a = configure_test_device(directory_a.path(), &fixture.endpoint).await?;
let device_b = configure_test_device(directory_b.path(), &fixture.endpoint).await?;
- // The source device carries the explicit reasoning-display boolean (a
- // false value must stay false), the legacy display mode, and a device-local
- // permission mode that must never travel through a revision.
+ // The source device carries the explicit reasoning-display boolean and the
+ // command-folding preference (false values must stay false), the legacy
+ // display mode, and a device-local permission mode that must never travel
+ // through a revision.
device_a.lock().await.db.set_setting(
"app",
&json!({
"theme": "light",
"showThinking": false,
"thinkingDisplayMode": "detailed",
+ "keepCommandsExpanded": false,
"defaultPermissionMode": "accept-edits",
}),
)?;
@@ -142,6 +144,7 @@ async fn application_show_thinking_roundtrips_and_keeps_local_only_settings() ->
assert_eq!(settings["theme"], "light");
// A false boolean survives capture and apply instead of reading as absent.
assert_eq!(settings["showThinking"], false);
+ assert_eq!(settings["keepCommandsExpanded"], false);
// The legacy field is still exported so older readers keep working.
assert_eq!(settings["thinkingDisplayMode"], "detailed");
// Local-only settings do not travel: the source value never appears.
@@ -154,6 +157,7 @@ async fn application_show_thinking_roundtrips_and_keeps_local_only_settings() ->
"theme": "light",
"showThinking": false,
"thinkingDisplayMode": "detailed",
+ "keepCommandsExpanded": false,
"defaultPermissionMode": "ask",
}),
)?;
@@ -164,6 +168,7 @@ async fn application_show_thinking_roundtrips_and_keeps_local_only_settings() ->
"theme": "light",
"showThinking": true,
"thinkingDisplayMode": "detailed",
+ "keepCommandsExpanded": true,
"defaultPermissionMode": "accept-edits",
}),
)?;
@@ -173,6 +178,7 @@ async fn application_show_thinking_roundtrips_and_keeps_local_only_settings() ->
let settings = app_settings(&state)?;
assert_eq!(settings["showThinking"], true);
assert_eq!(settings["thinkingDisplayMode"], "detailed");
+ assert_eq!(settings["keepCommandsExpanded"], true);
assert_eq!(settings["defaultPermissionMode"], "ask");
Ok(())
}
diff --git a/docs/adr/0332-plugin-composer-suggestion.md b/docs/adr/0333-plugin-composer-suggestion.md
similarity index 99%
rename from docs/adr/0332-plugin-composer-suggestion.md
rename to docs/adr/0333-plugin-composer-suggestion.md
index 676cab0c93..872eef5e4b 100644
--- a/docs/adr/0332-plugin-composer-suggestion.md
+++ b/docs/adr/0333-plugin-composer-suggestion.md
@@ -1,4 +1,4 @@
-# ADR 0332: A plugin-owned suggestion in the Composer placeholder
+# ADR 0333: A plugin-owned suggestion in the Composer placeholder
- Status: Accepted
- Date: 2026-10-24
diff --git a/docs/adr/README.md b/docs/adr/README.md
index bb90e9f675..eba1586a07 100644
--- a/docs/adr/README.md
+++ b/docs/adr/README.md
@@ -378,7 +378,7 @@ Each ADR includes:
| 0329 | [Isolate parallel sessions of one project in git worktrees](0329-session-worktree-isolation.md) | Accepted (Windows E2E pending) |
| 0330 | [Open scoped HTML files in the work-panel Browser from plugins](0330-open-html-files-in-work-panel-browser-from-plugins.md) | Accepted |
| 0331 | [Plugin session follow and host-owned work-panel reveal](0331-plugin-session-follow-and-work-panel-reveal.md) | Accepted |
-| 0332 | [A plugin-owned suggestion in the Composer placeholder](0332-plugin-composer-suggestion.md) | Accepted |
+| 0333 | [A plugin-owned suggestion in the Composer placeholder](0333-plugin-composer-suggestion.md) | Accepted |
| plugin-fetch-redirect-policy | [Host-enforced plugin fetch redirect policy](plugin-fetch-redirect-policy.md) | Accepted (implementation candidate for #1475) |
| local-agent-remote-workspace-tools | [Local Agent and model requests for remote workspaces](local-agent-remote-workspace-tools.md) | Accepted for implementation |
diff --git a/docs/adr/turn-process-and-thinking-display.md b/docs/adr/turn-process-and-thinking-display.md
index ce0c90beff..09613bb796 100644
--- a/docs/adr/turn-process-and-thinking-display.md
+++ b/docs/adr/turn-process-and-thinking-display.md
@@ -2,7 +2,7 @@
- Status: Accepted
- Date: 2026-09-17
-- Amended: 2026-10-16
+- Amended: 2026-10-21
- Issues: #510, #461
- Amends: D071, [ADR 0242](0242-delta-only-streaming-updates.md)
@@ -17,36 +17,59 @@ readers also need a thinking indicator without rapidly changing reasoning text.
## Decision
One unified turn-process presentation applies to every loaded assistant-turn
-entry: it projects the entry into chronological collapsible process segments plus
-its trailing answer. Thinking, tools and intermediate assistant text keep their
-original order across those segments. A trailing assistant text stays visible
+entry: it projects the entry into one collapsible process disclosure plus its
+trailing answer. Thinking, tools, intermediate assistant text and the turn's
+`Bash` run rows keep their original order inside that disclosure. A trailing
+assistant text stays visible
while streaming; if later tool or thinking activity follows, that text moves into
the process without changing the stored message. There is no semantic
final-answer marker in `UiMessage`, so the renderer does not guess intent from
wording. User/system messages and compaction dividers retain their existing turn
boundaries.
-The process is segmented rather than one flat container. Non-Bash activity forms
-ordinary activity groups: one contiguous tool/search/thinking segment between
-progress paragraphs or Bash rows, appearing only when at least two items are
-visible under the current thinking preference. A singleton uses its item
-disclosure directly; hidden thinking does not create a redundant wrapper.
-Existing Task topology remains its segment's container and is not duplicated
-inside an ordinary activity group.
-
-Bash and run aliases are excluded from every process disclosure — neither a
-turn-level process disclosure nor an ordinary activity group — and render as
-standalone rows that stay visible even when every group is collapsed. Adjacent
-Bash rows each remain standalone, and a Bash row's detail stays closed until the
-user opens it. Other operations between progress paragraphs still form
-chronological collapsible activity groups.
-
-Group folding defaults are unified and do not depend on the thinking preference.
-The ordinary activity group that owns the active execution segment starts open,
-then closes on completion only while untouched. Other completed groups start
-closed. An untouched active group containing any recorded failed or denied tool
-stays open through later recovery and closes on turn completion if still
-untouched. Bash rows remain visible regardless of any group's collapsed state.
+One turn renders exactly one process disclosure. Every row the turn produced
+before its answer lives inside it — the activity groups and the `Bash` run rows
+alike — so a long turn collapses in one gesture instead of leaving a column of
+sibling disclosures above the answer. The answer itself stays outside it.
+
+Inside that disclosure, non-Bash activity forms ordinary activity groups: one
+contiguous tool/search/thinking segment between progress paragraphs or run rows,
+appearing only when at least two items are visible under the current thinking
+preference. A singleton uses its item disclosure directly; hidden thinking does
+not create a redundant wrapper. Existing Task topology remains its segment's
+container and is not duplicated inside an ordinary activity group.
+
+Whether a run row sits *inside* its group or *beside* it is the
+`keepCommandsExpanded` preference, which defaults to on. When on, `Bash` and run
+aliases are lifted out of the groups they ran among: each becomes its own row at
+the disclosure's top level, adjacent calls stay separate, and the row's detail
+stays closed until the user opens it. When off, a run row keeps its place in the
+flow, so a command reads as another line of the group around it — the layout
+before commands were separated. The preference never changes how many
+disclosures a turn renders: both values render exactly one.
+
+Group folding defaults are unified and do not depend on either preference. The
+ordinary activity group that owns the active execution segment starts open, then
+closes on completion only while untouched. Other completed groups start closed.
+An untouched active group containing any recorded failed or denied tool stays
+open through later recovery and closes on turn completion if still untouched.
+
+The turn's disclosure header states the turn's outcome and never echoes the item
+it is working on, because a shell command or search query can be arbitrarily
+long. It reads `failed`, `stopped`, `running`, or finished, in that precedence:
+a recorded failure outranks a stop, because the turn produced no answer and a
+normal-looking header hid that. A stop is read from an aborted message, the only
+signal the runtime records — the turn result distinguishes completed from failed
+only. Aborted activity rows also record a stop while a tool or reasoning step is
+in flight; delegated child rows do not determine the parent turn's outcome.
+While running, stages a reader can sit in front of (compaction, recovery)
+name themselves; a live reasoning step reads `Thinking`, and momentary stages
+read as plain running. Durations are dropped when the transcript recorded no
+timing rather than shown as zero, and issue counts sit beside the label.
+
+The disclosure and the levels it reveals share one left edge. Hierarchy is
+carried by type size and colour, not by indentation, so a nested group header and
+a run row start exactly where the turn header does.
The thinking preference is a boolean `showThinking`. When it is false, the live
thinking indicator stays visible, while completed thinking rows and excerpts are
@@ -71,7 +94,7 @@ group, and row remounts while the owning retained session pane remains alive.
Pane eviction, session deletion, or renderer restart releases this presentation
memory; it is not stored in messages or host settings.
-Search/navigation reveals the ancestor path its target needs: the process segment
+Search/navigation reveals the ancestor path its target needs: the turn process
and the activity group that own the named message. Item-level targeting is not
part of this change, so each row's own details stay behind its own disclosure.
Replaying the same request does not repeatedly override a later manual close.
@@ -87,24 +110,31 @@ reasoning while `detailed`, an unknown value, or an absent field shows it. The
legacy field is retained for persisted-settings compatibility and is no longer
exposed in the UI. The preference changes presentation only; it does not alter
provider thinking levels, runtime/model context, stored reasoning, export,
-permissions, execution, or copy payloads, and it does not control process-segment
+permissions, execution, or copy payloads, and it does not control turn-process
or activity-group folding. Process headers use recorded timing, direct tool/search
counts, running state, and issue counts; they do not double-count delegated child
work or treat a failed child as a failed assistant turn.
## Consequences
-- Chronological collapsible process segments keep the final answer and actionable
- interruptions reachable, and Bash/run rows stay visible even when every group is
- collapsed.
+- One disclosure per turn keeps the final answer and actionable interruptions
+ reachable, and makes a long turn collapsible in a single gesture.
- Group folding defaults are unified: active work stays visible, untouched
completed groups fold by default, and explicit disclosure choices are preserved
- regardless of the thinking preference.
+ regardless of the thinking preference. Closing the turn's disclosure closes the
+ groups under it, and reopening restores the groups the user had opened.
- When `showThinking` is false, the live indicator stays visible while completed
reasoning rows and excerpts are hidden. The stored reasoning is retained and
reappears when the preference is turned back on.
-- Bash and run aliases stay standalone rows outside every process disclosure, so
- shell-heavy turns remain scannable without folding adjacent commands together.
+- With `keepCommandsExpanded` on (the default), run aliases render as their own
+ rows so shell-heavy turns stay scannable; turning it off restores the older
+ layout where a command reads as another line of its group. Neither value
+ changes the number of disclosures, and because the preference is read while
+ rendering rather than while building entries, toggling it repaints the
+ transcript immediately instead of waiting for new messages.
+- The header answers "how did this turn end up" in one short line. Echoing the
+ current command was removed: it pushed the counts off the row and duplicated
+ what opening the item already shows.
- Disclosure memory is pane-owned presentation state with stable turn, group,
and item identities; it is neither a persisted transcript contract nor a
central workflow-store concern.
@@ -126,3 +156,9 @@ covers the `showThinking`/legacy `thinkingDisplayMode` resolver precedence, and
the i18n catalog tests cover the new `settings.showThinking` copy. The UI,
resolver, and E2E scenarios are validated on the integration candidate; see
E2E-CHAT-turn-process-and-thinking-display for the synchronized scenario text.
+For the 2026-10-21 amendment, `apps/desktop/test/turn-process.test.mjs` covers
+one-disclosure segmentation, command-folding on and off, and header phase
+precedence; `apps/desktop/test/transcript-style.test.mjs` covers the shared left
+edge and the removed live item echo. The interactive transcript probes cover the
+rendered disclosure count, command placement, and header labels. See
+E2E-CHAT-turn-process-and-thinking-display for the synchronized scenario text.
diff --git a/docs/spec/03-runtime/04-data-storage.md b/docs/spec/03-runtime/04-data-storage.md
index 6d3f413bd1..66d44cfb42 100644
--- a/docs/spec/03-runtime/04-data-storage.md
+++ b/docs/spec/03-runtime/04-data-storage.md
@@ -415,8 +415,12 @@ reasoning visibility. It is a portable application preference and synchronizes
across devices like the legacy field. Missing values fall back to the legacy
`thinkingDisplayMode` field (`compact` hides, `detailed`/unknown/absent shows),
which is retained only for persisted-settings compatibility and as that
-fallback. These additive display preferences neither rewrite stored reasoning
-nor change the database schema.
+fallback. The app settings JSON optionally stores `keepCommandsExpanded`
+(boolean) for command-row placement inside a turn's process disclosure: absent
+means on, so `Bash` and run aliases stay on their own rows beside the activity
+groups; `false` folds them into their groups. It is a portable application
+preference and changes presentation only. These additive display preferences
+neither rewrite stored reasoning nor change the database schema.
The settings blob may still contain legacy prompt-enhancement keys from an
earlier release. They are retained for rollback and downgrade compatibility,
diff --git a/docs/spec/04-ux/06-settings-ia.md b/docs/spec/04-ux/06-settings-ia.md
index 3b3126aa4b..060541c06a 100644
--- a/docs/spec/04-ux/06-settings-ia.md
+++ b/docs/spec/04-ux/06-settings-ia.md
@@ -318,6 +318,14 @@ Settings is a **full-window page** that replaces the app sidebar + main chrome (
persisted-settings compatibility and is no longer exposed; an absent or
unknown value shows reasoning and an explicit `compact` hides it. Settings
search indexes the row.
+- **Don't collapse commands** is a toggle that persists as the optional
+ `keepCommandsExpanded` boolean in host-owned settings, defaulting to on when
+ absent. On keeps shell calls on their own rows beside the tool groups they ran
+ among; off folds them back into those groups, the layout used before commands
+ were separated. It affects presentation only — neither value changes how many
+ process disclosures a turn renders (always one), what a tool received, or what
+ is stored — and it is read at render time, so toggling repaints the transcript
+ immediately. Settings search indexes the row.
- The **Command shell** row in Defaults uses the host-discovered catalog of native
PowerShell 5.1, PowerShell 7, cmd, Git Bash, and Bash with IDs
`windows-powershell`, `windows-pwsh`, `cmd`, `git-bash`, and
diff --git a/docs/spec/04-ux/08-component-spec.md b/docs/spec/04-ux/08-component-spec.md
index 5115e56307..aca6e3a8e8 100644
--- a/docs/spec/04-ux/08-component-spec.md
+++ b/docs/spec/04-ux/08-component-spec.md
@@ -863,33 +863,56 @@ reading surface of the workstation.
### Turn process and thinking display
-One unified turn-process presentation projects each loaded assistant turn into
-chronological collapsible process segments plus its trailing answer. Reasoning,
-tools, hosted searches and intermediate assistant text keep their transcript order
-across those segments. The trailing answer streams outside the process; later
-activity can reclassify provisional answer text into the process without changing
-the stored message. Assistant errors and stopped trailing partial answers also
-stay outside it. User/system messages and compaction boundaries are unchanged.
+One unified turn-process presentation projects each loaded assistant turn into a
+single collapsible process disclosure plus its trailing answer. Reasoning, tools,
+hosted searches and intermediate assistant text keep their transcript order inside
+that disclosure. The trailing answer streams outside the process; later activity
+can reclassify provisional answer text into the process without changing the
+stored message. Assistant errors and stopped trailing partial answers also stay
+outside it. User/system messages and compaction boundaries are unchanged.
+
+The disclosure owns every row the turn produced before its answer: ordinary
+activity groups and `Bash` run rows alike. A turn therefore renders exactly one
+top-level process disclosure, including a Bash-only turn; no run row is a sibling
+of it, and a long turn collapses in one gesture. The answer, assistant errors,
+stopped trailing partial text and pending action cards remain outside, reachable
+without expanding the process.
Within the process, an ordinary activity group represents one contiguous
-tool/search/thinking segment between progress paragraphs or Bash rows. It renders a
+tool/search/thinking segment between progress paragraphs or run rows. It renders a
group header only when at least two items are visible under the current thinking
preference. A singleton uses its item disclosure directly, hidden thinking never
creates an empty wrapper, and the existing Task topology remains the container for
-delegated work. Bash and run aliases are excluded from every process disclosure —
-neither a turn-level process disclosure nor an ordinary activity group — and render
-as standalone rows that stay visible even when every group is collapsed. Adjacent
-Bash rows each remain standalone, and a Bash row's detail stays closed until the
-user opens it.
+delegated work.
+
+`keepCommandsExpanded` decides where a run row sits inside that disclosure and
+defaults to on. When on, `Bash` and run aliases are lifted out of the groups they
+ran among and render as their own rows at the disclosure's top level; adjacent
+calls stay separate and a row's detail stays closed until the user opens it. When
+off, a run row keeps its place in the flow and reads as another line of the group
+around it. Neither value changes the disclosure count, what a tool received, or
+what is stored.
The ordinary group owning the active execution segment starts open while a turn is
active, then closes on completion only if untouched; other completed groups start
closed. An untouched active group remains open when any failed or denied tool has
been recorded, through later successful recovery, and closes on completion if still
-untouched. These group defaults are unified and do not depend on the thinking
+untouched. These group defaults are unified and do not depend on either
preference. Group headers summarize count, running state and issue count without
treating a failed child as a failed turn.
+The turn disclosure header states the turn's outcome and never echoes the item it
+is working on, because a shell command or search query can be arbitrarily long. It
+reads `Failed`, `Stopped`, `Running`, or `Finished`, with failure outranking stop,
+stop outranking completion, and a live turn reporting running. While running,
+stages a reader can sit in front of (compaction, recovery) name themselves; a
+live reasoning step reads `Thinking`, and momentary stages read as plain running.
+Elapsed time is omitted when the
+transcript recorded no timing rather than shown as zero, and issue counts sit
+beside the label. The disclosure and the levels it reveals share one left edge;
+hierarchy is carried by type size and colour, not by indentation, so a nested
+group header and a run row start exactly where the turn header does.
+
No item payload opens itself: a tool, hosted-search or plan call stays a header row
until the user opens its disclosure, including a Bash row, whose detail stays closed
until the user opens it. The activity groups keep their automatic open defaults, so
@@ -898,16 +921,17 @@ live thinking indicator stays visible while completed reasoning rows and excerpt
are suppressed and empty thinking-only containers are omitted; the stored reasoning
is retained and reappears when the preference is turned back on.
-Group and item are independent controls. Closing an ancestor keeps descendant
-choices and reopening restores them; opening a parent never expands all children.
-User interaction with a child claims its containing group without toggling it, so
-completion cannot close around opened, focused or selected content. Choices use
-stable turn/group/item identities and remain while the retained session pane lives,
-including preference changes and row remounts; pane eviction, deletion or renderer
-restart reapplies defaults rather than persisting disclosure state to messages or
-settings.
-
-Search/navigation reveals the process segment and the activity group that own the
+Group, run row and item are independent controls. Closing an ancestor keeps
+descendant choices and reopening restores them; closing the turn's disclosure hides
+every row under it, and reopening restores the groups the user had opened. Opening
+a parent never expands all children. User interaction with a child claims its
+containing group without toggling it, so completion cannot close around opened,
+focused or selected content. Choices use stable turn/group/item identities and
+remain while the retained session pane lives, including preference changes and row
+remounts; pane eviction, deletion or renderer restart reapplies defaults rather
+than persisting disclosure state to messages or settings.
+
+Search/navigation reveals the turn process and the activity group that own the
named message, and applies each reveal request once. Item-level targeting is not
part of this change. Reasoning hidden by the preference stays hidden until the user
turns `Show thinking` on. Permission, question, plan/goal approval and other
@@ -2263,18 +2287,20 @@ Lightweight inline disclosure row showing a semantic tool action, its primary
argument hint, status, and a readable rendering of the result. It follows D071
and is intentionally not an elevated card.
-One contiguous tool/search/thinking segment between progress paragraphs or Bash
-rows becomes an ordinary processing group only when it has two or more visible
-items under the current thinking preference. A singleton uses its item disclosure
-directly, and Task topology keeps its existing container. Bash and run aliases are
-excluded from every process disclosure — neither a turn-level process disclosure
-nor an ordinary group — and render as standalone rows that stay visible even when
-every group is collapsed; adjacent Bash rows each remain standalone. While the
-turn is active, the ordinary group owning the execution segment opens; when it
-settles, an untouched group closes. These group defaults do not depend on the
-thinking preference. No item payload opens itself: a tool, hosted-search or plan
-row stays a header row until the user opens it, whichever item of the group it is,
-including a Bash row whose detail stays closed until opened.
+The turn's process is one disclosure. Inside it, one contiguous
+tool/search/thinking segment between progress paragraphs or run rows becomes an
+ordinary processing group only when it has two or more visible items under the
+current thinking preference. A singleton uses its item disclosure directly, and
+Task topology keeps its existing container. `Bash` and run aliases stay inside the
+turn's disclosure: with `keepCommandsExpanded` on (the default) each renders as
+its own row beside the groups, and adjacent calls remain separate; with it off a
+run row stays in the flow of its group. A Bash-only turn still has its one
+disclosure. While the turn is active, the ordinary group owning the execution
+segment opens; when it settles, an untouched group closes. These group defaults do
+not depend on the thinking preference. No item payload opens itself: a tool,
+hosted-search or plan row stays a header row until the user opens it, whichever
+item of the group it is, including a Bash row whose detail stays closed until
+opened.
The group header shows `Processing · 12s` while active or `Processed for 12s`
after completion, plus bounded item and issue counts. Expanding it reveals the
@@ -2311,8 +2337,11 @@ seconds when non-zero) from one hour onward. Zero-value units are omitted, so
auto-opens, so a final thinking item never selects an earlier tool. Live
thinking follows its own indicator/disclosure policy and never opens sibling
payloads.
-- Bash and run rows render standalone outside every process disclosure and stay
- visible even when every group is collapsed; adjacent Bash rows remain separate.
+- `Bash` and run rows are revealed by the turn's process disclosure. With
+ `keepCommandsExpanded` on they sit at its top level beside the groups and
+ adjacent rows stay separate; with it off they render inside their group. They
+ are never siblings of the turn's process, and their details stay closed until
+ opened.
- The processing group spans the full available assistant column, so expanded
result details keep a usable width even when the header or payload is short.
- The visible label is a natural-language action (`Read`, `Ran`, `Searched`),
diff --git a/docs/spec/04-ux/09-interaction-patterns.md b/docs/spec/04-ux/09-interaction-patterns.md
index ff4d89818b..1dcdfe4534 100644
--- a/docs/spec/04-ux/09-interaction-patterns.md
+++ b/docs/spec/04-ux/09-interaction-patterns.md
@@ -917,23 +917,31 @@ may be retained while exactly one workspace supplies the visible shell context.
- Tool activity starts as a lightweight collapsed item row. Failed and denied
calls keep their issue in the row header and do not auto-expand their payload.
-- One unified presentation gives each loaded assistant turn chronological
- collapsible process segments. They contain thinking, tools, hosted searches and
- intermediate progress text; the trailing answer, assistant errors and stopped
- trailing text remain outside them.
+- One unified presentation gives each loaded assistant turn a single collapsible
+ process disclosure. It contains thinking, tools, hosted searches, intermediate
+ progress text and the turn's `Bash`/run rows; the trailing answer, assistant
+ errors and stopped trailing text remain outside it.
- A contiguous activity segment receives a group disclosure only when it has at
least two visible items under the current thinking preference. Progress text or a
- Bash row ends the segment, a singleton uses its item disclosure directly, and
+ run row ends the segment, a singleton uses its item disclosure directly, and
hidden thinking does not create a redundant group. Existing Task topology remains
- separate. Bash and run aliases are excluded from every process disclosure —
- neither a turn-level process disclosure nor a group — and stay standalone rows
- that remain visible even when every group is collapsed; adjacent Bash rows each
- remain standalone.
+ separate. `keepCommandsExpanded` (default on) decides only where a run row sits
+ inside the turn's disclosure: on lifts `Bash` and run aliases out of their groups
+ into their own top-level rows, with adjacent calls remaining separate; off keeps
+ a run row in the flow of its group. Neither value adds another disclosure or
+ leaves a run row outside the process.
- The active ordinary group starts open and closes when it completes only if
untouched; completed groups otherwise start closed, and an untouched active group
with any recorded failed/denied tool remains open through recovery. These group
- defaults do not depend on the thinking preference. Bash rows stay visible
- regardless of any group's collapsed state.
+ defaults do not depend on either preference. Closing the turn's disclosure hides
+ every group and run row under it without erasing their choices; reopening
+ restores the groups the user had opened.
+- The turn header reports `Failed`, `Stopped`, `Running`, or `Finished` in that
+ precedence, names compaction and recovery while those stages are live, reads
+ `Thinking` while the live step is reasoning, omits the duration when the
+ transcript recorded none, and never echoes the current command or query. A
+ nested group header and a run row share its left edge; hierarchy is carried by
+ type size and colour rather than indentation.
- No item payload opens itself: a tool, hosted-search or plan call stays a header
row until the user opens it, including the literal final item of the last
activity group. Group defaults are unchanged, so a final thinking item never
@@ -949,7 +957,7 @@ may be retained while exactly one workspace supplies the visible shell context.
content the user opened, focused or selected. Choices survive preference
changes, singleton-to-group growth and remounts while the retained session pane
lives.
-- Search/navigation opens the process segment and activity group that own the named
+- Search/navigation opens the turn process and activity group that own the named
message, once per reveal request. Item-level targeting is not part of this
change. Reasoning hidden by the preference stays hidden until the user turns
`Show thinking` on. Closing search does not collapse the revealed path.
@@ -1464,7 +1472,7 @@ Project drag/drop follows these patterns:
a multi-line draft: the bottom reserve is padding on the transcript content, so
the content is observed on its border box and the newest turn moves up with
the composer instead of sliding behind it (D287).
-- A manual disclosure — process segment, activity group, tool/search/thinking item,
+- A manual disclosure — turn process, activity group, tool/search/thinking item,
delegate brief, or error detail — holds the reading position of the scroller
that owns it (issue #324). Only the initiating level claims the anchor; marking
the containing group user-owned does not claim its scroll position. The title is
diff --git a/docs/spec/06-delivery/04-e2e-test-plan.md b/docs/spec/06-delivery/04-e2e-test-plan.md
index a3ffd74f79..c6989e9870 100644
--- a/docs/spec/06-delivery/04-e2e-test-plan.md
+++ b/docs/spec/06-delivery/04-e2e-test-plan.md
@@ -3367,21 +3367,33 @@ identify the platform validation still needed.
- **Steps**: 1) Stream progress paragraph A, a multi-item search segment,
progress paragraph B, and a multi-item command segment with adjacent Bash rows.
2) Inspect the open active group; manually close it while more output arrives.
- 3) Complete the turn and inspect untouched versus user-owned groups, and confirm
- the Bash rows stay visible with every group collapsed. 4) Open one completed
- group and one item, copy its output, close and reopen the group, then open a
- sibling group independently. 5) Repeat with a singleton item and with the last
- activity group's literal final item set to a tool/search, thinking, failed tool,
- and denied tool. 6) Toggle `Show thinking` off and on and inspect the
- active-thinking, failure/recovery and completed states. 7) Remount rows within
- the retained pane, then reload the renderer and reopen the session.
-- **Expected**: Chronological collapsible process segments keep the trailing answer
- outside them. The active group opens, then closes on completion only if
- untouched; completed groups otherwise start closed. Bash/run aliases are excluded
- from every process disclosure and stay visible even when every group is collapsed.
- A singleton has no group wrapper. No item payload opens itself: a tool/search row
- stays a header until the user opens it, while a final thinking item keeps its own
- leaf default and never selects an earlier tool. When `Show thinking` is off, the
+ 3) Complete the turn and confirm exactly one process disclosure owns every
+ pre-answer row; close it and confirm the groups and run rows close with it, then
+ reopen and confirm the group choice returns. 4) Open one completed group and one
+ item, copy its output, close and reopen the group, then open a sibling group
+ independently. 5) Toggle `Don't collapse commands` off and on and inspect where
+ the run rows render while the disclosure count stays one. 6) Repeat with a
+ singleton item and with the last activity group's literal final item set to a
+ tool/search, thinking, failed tool, and denied tool. 7) Toggle `Show thinking`
+ off and on and inspect the active-thinking, failure/recovery and completed
+ states. 8) Remount rows within the retained pane, then reload the renderer and
+ reopen the session.
+- **Expected**: A turn renders exactly one process disclosure containing every
+ pre-answer row, the `Bash`/run rows included; the trailing answer, assistant
+ errors and stopped trailing text stay outside it, as do pending actions. The
+ active group opens, then closes on completion only if untouched; completed
+ groups otherwise start closed. Closing the turn's disclosure closes the groups
+ and run rows under it, and reopening restores the user's group choices. With
+ `Don't collapse commands` on (default), run rows render as their own top-level
+ rows beside the groups, adjacent calls stay separate, and a row's detail stays
+ closed until opened; with it off they fold into their groups. Neither value
+ changes the disclosure count. A singleton has no group wrapper. No item payload
+ opens itself: a tool/search row stays a header until the user opens it, while a
+ final thinking item keeps its own leaf default and never selects an earlier
+ tool. The header reports `Running`, `Finished`, `Stopped`, or `Failed` with
+ failure and stop outranking a normal finish, reads `Thinking` while the live
+ step is reasoning, never repeats the current command, and omits the duration
+ when none was recorded. When `Show thinking` is off, the
live thinking indicator stays visible while completed reasoning text and excerpts
are hidden and empty thinking-only containers are omitted; turning it back on
restores them. Parent, child and sibling choices are independent;
@@ -3395,9 +3407,9 @@ identify the platform validation still needed.
`04-ux/09-interaction-patterns.md`
- **Acceptance**: C (chat stream), E (tools), F (persistence)
- **Milestone**: M3
-- **Status**: Draft. For the 2026-09-20 nested-disclosure change, this scenario is
- intended behavior for static source/design review only; no unit, component,
- integration, browser, Electron or E2E test is added or run by that scoped task.
+- **Status**: Draft. Unit and style checks cover the one-disclosure,
+ command-folding and header rules; this scenario remains the intended manual
+ transcript-reload behavior.
#### E2E-041: Conversation minimap navigates long transcripts
@@ -17168,34 +17180,48 @@ plugin-form fixtures in an isolated temporary directory at runtime.
- **Preconditions:** A turn with progress paragraph A, multiple searches plus
thinking, progress paragraph B, multiple commands plus thinking, and a final
- answer; the `Show thinking` preference on and off; legacy message-level
- transcript search targets.
+ answer; the `Show thinking` preference on and off; the `Don't collapse
+ commands` preference on and off; legacy message-level transcript search
+ targets.
- **Steps:** Confirm a live active group starts open, let that same turn finish
- without interacting, and confirm the group collapses. On a second turn, explicitly
- open a completed group and confirm the choice survives subsequent updates. Turn
- `Show thinking` off and confirm the live thinking indicator remains while
- completed reasoning rows and excerpts disappear and no empty thinking-only
- container is left; turn it back on and confirm the completed rows return. Collapse
- every group and confirm the Bash/run rows stay visible. Review the nested path,
- including independent group/item toggles, parent close/reopen, a singleton
- segment, literal-final-item leaf selection, failure/denial/recovery, retained-pane
- remounts, Bash rows staying standalone (including adjacent Bash rows) with their
- details closed until opened, and a legacy search reveal.
-- **Expected:** Chronological collapsible process segments leave the final answer,
- assistant errors, stopped trailing text and pending actions outside them. The
- active group starts open; untouched groups collapse at completion, while explicit
- user choices persist. These group defaults do not depend on the `Show thinking`
- preference. Bash/run aliases are excluded from every process disclosure and stay
- standalone rows visible even when every group is collapsed; adjacent Bash rows
- each remain standalone and a Bash row's detail stays closed until the user opens
- it. When `Show thinking` is off, the live thinking indicator stays visible,
+ without interacting, and confirm the group collapses. On a second turn,
+ explicitly open a completed group and confirm the choice survives subsequent
+ updates; then close the turn's disclosure and confirm the group closes with it,
+ and reopen to confirm the group choice is restored. Turn `Show thinking` off
+ and confirm the live thinking indicator remains while completed reasoning rows
+ and excerpts disappear and no empty thinking-only container is left; turn it
+ back on and confirm the completed rows return. Turn `Don't collapse commands`
+ off and confirm the run rows fold into their groups while the turn still
+ renders exactly one disclosure, then turn it on and confirm the standalone rows
+ return. Confirm the header reads running, finished, stopped, or failed for each
+ case, names compaction and recovery while those stages are live, omits the
+ duration when none was recorded, and never repeats the current command. Review
+ the nested path, including independent group/item toggles, a singleton segment,
+ literal-final-item leaf selection, failure/denial/recovery, retained-pane
+ remounts, run rows keeping their details closed until opened, and a legacy search
+ reveal.
+- **Expected:** A turn renders exactly one process disclosure containing every
+ pre-answer row, leaving the final answer, assistant errors, stopped trailing
+ text and pending actions outside it. The active group starts open; untouched
+ groups collapse at completion, while explicit user choices persist and are
+ restored when the enclosing disclosure is reopened. These group defaults do not
+ depend on the `Show thinking` preference. With `Don't collapse commands` on,
+ run aliases render as their own rows beside the groups, adjacent rows stay
+ separate and a row's detail stays closed until opened; with it off they fold
+ into their groups. Neither value changes the disclosure count. The header
+ reports running, finished, stopped, or failed with failure and stop outranking
+ a normal finish, reads `Thinking` while the live step is reasoning, names
+ compaction and recovery while those stages are live, omits a duration the
+ transcript did not record, and never repeats the current command. Nested group
+ headers and run rows share the turn header's left edge.
+ When `Show thinking` is off, the live thinking indicator stays visible,
completed reasoning rows and excerpts are hidden, and empty thinking-only
containers are omitted; turning it back on restores them. Singletons have no
group. No item payload opens itself: a tool/search row stays closed until the user
opens it, while a final thinking item keeps its own leaf default.
Parent/child/sibling states remain independent, pane-owned user choices survive
updates, preference changes and remounts, and renderer restart reapplies defaults.
- Search reveals the process segment and activity group that own the named message
+ Search reveals the turn process and activity group that own the named message
once per request; item-level targeting is not part of this change, and reasoning
hidden by the preference stays hidden until the user turns `Show thinking` on.
Saved `showThinking` survives restart; an absent value falls back to the legacy
@@ -18374,7 +18400,7 @@ host-created files. The full app's file-preview viewer is covered separately.
offer answers `{ shown: false, reason }` and shows nothing. No transcript row,
toast, or overlay appears, and the plugin's call is audited.
- **Specs linked**: `07-plugins/03-plugin-api.md`,
- `07-plugins/13-plugin-permissions-matrix.md`, ADR 0332.
+ `07-plugins/13-plugin-permissions-matrix.md`, ADR 0333.
- **Acceptance**: A (Composer entry path), Security (permission-gated, never
sent by the plugin).
- **Milestone**: M6+
diff --git a/docs/spec/08-meta/decisions-log.md b/docs/spec/08-meta/decisions-log.md
index 1ea52e8ffc..2c432fe692 100644
--- a/docs/spec/08-meta/decisions-log.md
+++ b/docs/spec/08-meta/decisions-log.md
@@ -52,7 +52,7 @@ This log freezes previously open questions into concrete decisions.
| D656 | Quarantine appends the host keeps refusing instead of stalling the outbox | **Amend ADR 0041 / D318 / D444 / D597: an append whose `session.appendMessage` or `session.recordUsage` call fails with an error the outbox cannot classify as a duplicate message id, a `PERMISSION_DENIED:` poison row, or a foreign-key orphan is retried on a bounded backoff (5s, doubling to a 60s cap) instead of ending the flush. The fifth consecutive failure on that head moves it into an application-owned dead-letter file, `session-message-outbox.dead-letter.json`, with its payload, session id, quarantine timestamp, and host error; only the newest 256 quarantined appends are kept, and the oldest is discarded with a warn. The flush then continues with the next entry, so one refused append can no longer hold the FIFO head, fill the 1024-entry cap, or fail every session's writes. Quarantined appends are never replayed automatically, and `session.delete` drops that session's quarantined appends too. No protocol version, storage schema, or queued-outbox format change.** | A `stream did not contain valid UTF-8` append stayed at the FIFO head for 14.8 hours while `session.persistence.outbox.is.full` fired 5990 times, so every session's appends failed until restart. Only three error classes had a drain, and every other error was treated as transient forever (#1560). |
| D657 | Let the embedded Browser open local files outside the workspace | **Amend ADR 0170: an explicit absolute path or `file:` URL may load any existing regular local file, and a local-file page may navigate to other existing local files. Relative inputs remain workspace-rooted; HTTP(S) pages retain only the prior in-workspace file-link allowance. Missing files, directories, and remote file authorities remain blocked. `BrowserPreview` and the sidecar keep their workspace-rooted resolver. The public `pi.browser.navigate` API follows this policy under the high-risk `browser.cdp` permission. See ADR 0328, E2E-059, `04-ux/08-component-spec.md`, and `05-security/01-security.md`.** | Users need to inspect local HTML outside a project, while workspace-scoped agent file tools and remote-page navigation must retain their existing boundary (#1627). |
| D659 | Reopen archived projects in the sidebar | **Amend D093 / D455: successful explicit project activation clears the normalized path's renderer-local archived flag and persists it, so Open from Project archive, reopening the same folder through Add project, and opening a project session reveal the project in the home sidebar. Selecting a row for inspection and ordinary session refreshes do not alter archive state. No host/project/session storage or protocol change. See ADR 0294, E2E-264, and issue #1653.** | Reopening a project changed the active workspace but left its path-keyed archived presentation flag set, hiding it from the sidebar after the user explicitly reopened it. |
-| D661 | Segmented turn process and independent thinking preference | **Supersede the `Detailed` / `Compact` display-mode behavior and the single whole-process disclosure recorded by D633 / D651 and the `turn-process-and-thinking-display` ADR: a turn renders as chronological collapsible process segments, Bash and run aliases stay outside every folded container (the turn-level process disclosure and any ordinary activity group) and remain visible even when every group is collapsed, and process/group folding defaults are independent of the thinking preference. The preference is the optional boolean `AppSettings.showThinking`; absent or non-boolean values fall back to the legacy `thinkingDisplayMode` field (`compact` hides, `detailed`/unknown/absent shows), which is retained only for persisted-settings compatibility. `showThinking` joins the portable application fields so it synchronizes like the legacy field; no other host protocol, persistence schema, permission, or plugin contract change. See the amended ADR, `04-ux/06-settings-ia.md`, `04-ux/08-component-spec.md`, `04-ux/09-interaction-patterns.md`, and E2E-CHAT-turn-process-and-thinking-display.** | One flat container left long tool/search runs hard to scan and forced reasoning visibility and process folding into the same two-valued switch; an independent boolean plus always-visible Bash rows keeps shell-heavy turns readable without hiding the answer. |
+| D661 | Segmented turn process and independent thinking preference *(amended by D668)* | **Supersede the `Detailed` / `Compact` display-mode behavior and the single whole-process disclosure recorded by D633 / D651 and the `turn-process-and-thinking-display` ADR: a turn renders as chronological collapsible process segments, Bash and run aliases stay outside every folded container (the turn-level process disclosure and any ordinary activity group) and remain visible even when every group is collapsed, and process/group folding defaults are independent of the thinking preference. The preference is the optional boolean `AppSettings.showThinking`; absent or non-boolean values fall back to the legacy `thinkingDisplayMode` field (`compact` hides, `detailed`/unknown/absent shows), which is retained only for persisted-settings compatibility. `showThinking` joins the portable application fields so it synchronizes like the legacy field; no other host protocol, persistence schema, permission, or plugin contract change. See the amended ADR, `04-ux/06-settings-ia.md`, `04-ux/08-component-spec.md`, `04-ux/09-interaction-patterns.md`, and E2E-CHAT-turn-process-and-thinking-display.** | One flat container left long tool/search runs hard to scan and forced reasoning visibility and process folding into the same two-valued switch; an independent boolean plus always-visible Bash rows keeps shell-heavy turns readable without hiding the answer. |
| D662 | Open scoped HTML files in the work-panel Browser from plugins | **Add `pi.fs.openInBrowser(pathFromRoot)` under `fs.read`. The host applies the plugin's normal read containment, protected-path, credential deny-list, declared scope, and registered project-folder checks; only existing `.html`, `.htm`, and `.xhtml` files qualify. After validation, Main asks the renderer to create a Browser resource tab for the active local session. The Browser plugin must be enabled. This grants no `browser.cdp`, changes no BrowserPreview or local-file navigation policy, and adds no host-core protocol or persisted-state change. See ADR 0330, `07-plugins/03-plugin-api.md`, `07-plugins/13-plugin-permissions-matrix.md`, `04-ux/08-component-spec.md`, and E2E-153.** | The File Manager needs an in-app HTML preview, while granting its plugin `browser.cdp` would also expose unrelated page inspection and control. |
## B. Secondary implementation defaults
@@ -332,6 +332,7 @@ Gold source: local Codex electron captures; latest row wins where rows conflict.
| D602 | Crash dumps stay in the data directory | **Electron's Crashpad reporter starts local-only (`uploadToServer: false`) before `ready`. Dumps live under `
/crash-dumps`, not the default Electron `userData` crashDumps path, so a `PI_DESKTOP_DATA_DIR` profile does not share dumps. The next lock-holding launch writes one `diagnostics` line for dumps newer than `crash-dumps.json`, classified by Crashpad `ptype`: `error` if any new dump is the browser/main process, `warn` for recovered renderer/GPU/utility crashes. Host-core and sidecar crashes stay on the supervisor path. No upload, no IPC, no schema change.** | A crash left a minidump nobody read. Crashpad also records recovered renderer crashes, so a next-launch `error` that said the previous run died was a lie; and dumps outside the data directory escaped `PI_DESKTOP_DATA_DIR` isolation. |
| D619 | A copied formula is its TeX source | **Renderer only: a copy whose selection covers rendered math writes `text/plain` from the MathML `annotation` — `$…$` inline, `$$…$$` on its own lines, the delimiters `lib/latex-math.ts` normalizes `\(…\)` and `\[…\]` to, each run widened past any run inside the formula as a code span's fence is — instead of the two trees KaTeX paints. A cut that lands inside a formula grows to the whole formula. Only the formulas are rewritten: the reduced clone is read back through `Selection.toString()`, the serializer a copy itself runs, so prose, lists, tables and code blocks sharing the selection keep the platform's own reading — `user-select: none` chrome left behind included, which `innerText` would have written out. A selection with no formula in it, and a copy raised where the selection does not live, are left to the platform entirely. One flavour is written, `text/plain`: taking the event over drops the platform's `text/html` too and none is written back, because the reduced clone is app markup that would carry the `user-select: none` chrome the text reading drops, and because carrying the rendering instead would paste every formula twice — KaTeX's stylesheet is the only thing hiding the MathML tree and no stylesheet travels on the clipboard. One document `copy` listener owned by the shell, and the transcript's right-click Copy reads the same selection through the same module.** | A formula pasted as its glyphs, once per rendered tree, so it could not be carried into a LaTeX document or another Markdown editor (issue #414). ADR 0268 removed quoting on the grounds that the OS clipboard was the substitute; the clipboard had to actually carry the source. |
| D620 | pi-ai built-in API-key services are named presets | **Add fifteen named endpoint presets — Ant Ling, Baseten, Cerebras, Hugging Face, Meta (`responses`), MiniMax (International), Moonshot AI (International), NVIDIA, OpenCode Zen, Vercel AI Gateway, Qwen Token Plan (`alibaba-token-plan`), Qwen Token Plan (China), Xiaomi Token Plan (China / Europe / Singapore) — to `NAMED_ENDPOINT_PRESETS`, each at its published host, with the pi-ai provider id kept as an alias wherever the models.dev key differs. Eight built-in providers remain exceptions with a recorded reason: Amazon Bedrock, Azure OpenAI, Cloudflare AI Gateway, Cloudflare Workers AI, Google Vertex AI (account- or region-scoped URLs), GitHub Copilot and OpenAI Codex (vendor-account rows), and Radius (`pi_messages` is account-only here). `packages/agent-runtime/src/pi-ai-provider-sync.test.ts` fails on a pi-ai upgrade that leaves a provider neither covered nor excepted. No protocol, storage, or IPC change.** | Every other pi-ai capability was already reachable, but the API-key half of the service catalog was hand-maintained and had drifted from the library's own provider list (ADR 0307). |
+| D668 | One process disclosure per turn, with a command-folding preference | **Amend D661 / the `turn-process-and-thinking-display` ADR. A turn renders exactly one top-level process disclosure holding every pre-answer row, the run rows included; the answer stays outside it. `Bash` and run aliases are no longer excluded from every folded container. Inside that disclosure, the optional boolean `AppSettings.keepCommandsExpanded` (absent means on) decides whether run rows are lifted beside the groups they ran among or stay inside them; both values render exactly one disclosure. The preference is read while rendering, not while building transcript entries, so toggling it repaints immediately - the projection cache is keyed by messages and compactions only. The disclosure header reports failed / stopped / running / finished with precedence in that order and never echoes the current item, and the disclosure shares one left edge with the levels it reveals. `keepCommandsExpanded` joins the portable application fields. No host protocol, persistence schema, permission, or plugin contract change. See the amended ADR, `04-ux/06-settings-ia.md`, `04-ux/08-component-spec.md`, `04-ux/09-interaction-patterns.md`, and E2E-CHAT-turn-process-and-thinking-display.** | Chronological segmentation split one turn into several sibling disclosures above the answer, and always-visible command rows could not be turned off by readers who preferred the older grouped layout; one disclosure plus a presentation-only preference satisfies both without changing what a tool received or stored. |
## M0. Model catalog decisions
@@ -7847,3 +7848,25 @@ must keep splitting are covered by `markdown-blocks.test.mjs`.
keeps the opaque choice a user already made. See ADR 0332, ADR 0248,
`04-ux/06-settings-ia.md`, `04-ux/08-component-spec.md`, and
`apps/desktop/test/macos-window-translucency.test.mjs`.
+
+## 2026-10-21 — One process disclosure per turn, with command folding (D668)
+
+- D668 amends D661 / the `turn-process-and-thinking-display` ADR: a turn now
+ renders exactly one top-level process disclosure containing every pre-answer
+ row, the `Bash`/run rows included. No run row is a sibling of that disclosure;
+ the trailing answer, assistant errors, stopped trailing text, and pending action
+ surfaces stay outside it.
+- `AppSettings.keepCommandsExpanded` (absent means on) decides whether run rows are
+ lifted beside the groups they ran among or stay inside them. The preference is
+ read while rendering, not while building transcript entries, so toggling it
+ repaints immediately; both values render exactly one disclosure.
+- The disclosure header reports failed / stopped / running / finished in that
+ order, names compaction and recovery while those stages are live, drops an
+ unavailable duration instead of showing zero, and never echoes the current item.
+ The disclosure and the levels it reveals share one left edge.
+- `keepCommandsExpanded` joins the portable application fields. Covered by
+ `apps/desktop/test/turn-process.test.mjs`,
+ `apps/desktop/test/transcript-style.test.mjs`, and the interactive transcript
+ probes. See the amended ADR, `04-ux/06-settings-ia.md`,
+ `04-ux/08-component-spec.md`, `04-ux/09-interaction-patterns.md`, and
+ E2E-CHAT-turn-process-and-thinking-display.
diff --git a/docs/zh-CN/adr/turn-process-and-thinking-display.md b/docs/zh-CN/adr/turn-process-and-thinking-display.md
index afc0f31943..b1bc0832cf 100644
--- a/docs/zh-CN/adr/turn-process-and-thinking-display.md
+++ b/docs/zh-CN/adr/turn-process-and-thinking-display.md
@@ -4,7 +4,7 @@
- 状态:已接受
- 日期:2026-09-17
-- 修订:2026-10-16
+- 修订:2026-10-21
- Issues:#510、#461
- 修订对象:D071、[ADR 0242](/adr/0242-delta-only-streaming-updates)
@@ -17,26 +17,40 @@
## 决策
-所有已加载的助手回合条目都使用同一套回合过程展示:投影为按时间顺序排列、可折叠的
-过程片段,以及其后的最终回答。思考、工具和中间进度文字跨这些片段按原顺序保留。流式
-输出时,暂定为回答的末尾助手文字保持可见;如果随后出现工具或思考活动,该文字会移入
-过程,但不会改写已存消息。`UiMessage` 没有语义化的最终回答标记,因此渲染器不根据
-措辞猜测。用户消息、系统消息和压缩分隔线继续保留原有回合边界。
+所有已加载的助手回合条目都使用同一套回合过程展示:投影为一个可折叠的过程披露,
+以及其后的最终回答。思考、工具、中间进度文字以及该回合的 `Bash` 命令行都按转录顺序
+保留在这个披露内。流式输出时,暂定为回答的末尾助手文字保持可见;如果随后出现工具或
+思考活动,该文字会移入过程,但不会改写已存消息。`UiMessage` 没有语义化的最终回答标记,
+因此渲染器不根据措辞猜测。用户消息、系统消息和压缩分隔线继续保留原有回合边界。
-过程是分段的,而不是一个扁平容器。非 Bash 活动形成普通活动组:两个进度段落或 Bash 行
-之间的一段连续工具、搜索或思考活动,并且仅在当前思考偏好下至少有两个可见项时出现。
-单项活动直接使用自身披露;被隐藏的思考不会制造多余的组包装。现有 Task 拓扑仍是其片段
-的容器,不会在普通活动组中重复渲染。
+每个回合只渲染一个过程披露。回合在给出答案之前产生的所有行都位于其中——活动组与 `Bash`
+命令行同样如此——因此长回合可以用一次操作收起,而不会在答案上方留下一列并列披露。答案本身
+位于披露之外。
-Bash 和 run 别名被排除在所有过程披露之外——既不属于回合级过程披露,也不属于普通活动组
-——而是作为独立行渲染,即使所有组都收起也保持可见。相邻的 Bash 行各自保持独立,且
-Bash 行的详情在用户手动打开之前保持收起。进度段落之间的其他操作仍会形成可按时间顺序
-折叠的活动组。
+在该披露内部,非 Bash 活动形成普通活动组:两个进度段落或命令行之间的一段连续工具、搜索或
+思考活动,并且仅在当前思考偏好下至少有两个可见项时出现。单项活动直接使用自身披露;被隐藏的
+思考不会制造多余的组包装。现有 Task 拓扑仍是其片段的容器,不会在普通活动组中重复渲染。
-活动组的折叠默认值是统一的,不依赖思考偏好。拥有当前执行片段的普通活动组默认展开,
+命令行位于其组内还是组旁,由 `keepCommandsExpanded` 偏好决定,默认开启。开启时,`Bash`
+和 run 别名会从所处的组中提取出来:各自成为披露顶层的独立行,相邻调用保持分离,详情在用户
+打开之前保持收起。关闭时,命令行保留在流程中的原位置,读起来就是所在组的另一行——即命令尚未
+被分离之前的布局。该偏好不会改变回合渲染的披露数量:两种取值都只渲染一个。
+
+活动组的折叠默认值是统一的,不依赖思考偏好或上述偏好。拥有当前执行片段的普通活动组默认展开,
仅在用户未操作时于完成后收起;其他已完成组默认收起。只要活动组中记录过失败或被拒工具,
-尚未被用户接管的活动组就会在后续恢复期间保持展开,并在回合完成后收起。无论任何组是否
-收起,Bash 行都保持可见。
+尚未被用户接管的活动组就会在后续恢复期间保持展开,并在回合完成后收起。关闭回合披露会一并
+关闭其下的组,重新展开则恢复用户此前展开过的组。
+
+回合披露的标题只陈述回合的结果,绝不回显正在处理的具体项,因为一条 shell 命令或搜索词可能
+任意长。其取值优先级依次为失败、已停止、执行中、已完成:已记录的失败优先于停止,因为该回合
+没有产出答案,而看起来正常的标题会掩盖这一点。停止取自被中止的消息,这是运行时唯一记录的信
+号——回合结果只区分完成与失败。工具或思考仍在执行时,被中止的活动行同样记录停止;委派子任务
+的行不决定父回合结果。执行期间,用户可能长时间停留的阶段(压缩上下文、恢复)会各自
+命名;当前步骤为推理时显示 `Thinking`,瞬时阶段则显示为普通执行中。转录未记录时间时不显示
+时长,而不是显示为零;问题计数与标签并列显示。
+
+披露与它展开的层级共用同一条左边缘。层级由字号与颜色表达,而不是缩进,因此嵌套的组标题与
+命令行起始位置与回合标题完全一致。
思考偏好是一个布尔值 `showThinking`。当它为 false 时,活动思考指示器保持可见,而已完成
的思考行和摘要会被隐藏,空的纯思考容器会被省略;已存推理仍会保留,因此重新打开该偏好
@@ -52,7 +66,7 @@ Bash 行的详情在用户手动打开之前保持收起。进度段落之间的
窗格仍存在,手动选择就跨流式更新、完成、偏好切换、单项变组和行重新挂载保留。窗格淘汰、
会话删除或渲染器重启会释放这些展示状态;它们不写入消息或宿主设置。
-搜索和导航只展开目标所需的祖先路径:拥有该消息的过程片段和活动组。条目级精确定位不在
+搜索和导航只展开目标所需的祖先路径:拥有该消息的回合过程和活动组。条目级精确定位不在
本次范围内,各行详情仍由各自的折叠控制。同一请求重新渲染时,不会反复覆盖用户之后的
手动收起。被偏好隐藏的推理会保持隐藏,直到用户打开 `showThinking`。助手错误、中止后的
末尾部分回答、权限/提问/计划/目标决策及其他待处理操作面必须位于隐藏过程之外,
@@ -62,20 +76,22 @@ Bash 行的详情在用户手动打开之前保持收起。进度段落之间的
`AppSettings` 字段持久化。缺失或非布尔值会回退到旧版 `thinkingDisplayMode` 字段:
显式 `compact` 隐藏推理,而 `detailed`、未知值或缺失值都显示推理。旧字段为持久化设置的
兼容性而保留,不再在界面中暴露。该偏好只改变展示,不改变提供商思考级别、运行时或模型
-上下文、已存推理、导出、权限、执行或复制载荷,也不控制过程片段或活动组的折叠。过程标题
+上下文、已存推理、导出、权限、执行或复制载荷,也不控制回合过程或活动组的折叠。过程标题
使用已记录的计时、直接工具/搜索计数、运行状态和问题计数;不会重复计算委派子任务,
也不会把单个失败工具误报为整个助手回合失败。
## 结果
-- 按时间顺序排列的可折叠过程片段让最终回答和待处理操作保持可达,并且即使所有组都收起,
- Bash/run 行也保持可见。
-- 活动组的折叠默认值统一:运行中的工作保持可见,未操作的已完成组默认收起,
- 无论思考偏好如何都保留用户明确的披露选择。
+- 每个回合一个披露,让最终回答与待处理操作保持可达,并使长回合可以用一次操作收起。
+- 活动组的折叠默认值统一:运行中的工作保持可见,未操作的已完成组默认收起,无论思考偏好如何
+ 都保留用户明确的披露选择。关闭回合披露会关闭其下的组,重新展开则恢复用户此前展开过的组。
- 当 `showThinking` 为 false 时,活动指示器保持可见,而已完成的推理行和摘要被隐藏。
已存推理仍会保留,重新打开偏好时重新出现。
-- Bash 和 run 别名作为独立行位于所有过程披露之外,因此命令密集的回合无需把相邻命令
- 折叠在一起即可浏览。
+- 当 `keepCommandsExpanded` 开启(默认)时,run 别名作为独立行渲染,命令密集的回合保持易读;
+ 关闭时恢复较早的布局,命令行读起来就是所在组的另一行。两种取值都不改变披露数量;该偏好
+ 在渲染时读取而非在构建条目时读取,因此切换后立即重绘,而无需等待新消息。
+- 标题用一行说明回合的结果。回显当前命令的做法已被移除:它会把计数挤出该行,并且与打开该项
+ 已经能看到的内容重复。
- 披露记忆是以稳定回合、组和条目标识为键的窗格展示状态,不是持久化转录契约,也不
属于中央工作流 store。
- 只对已加载的转录条目分组;不会重建未加载历史,也不会跨压缩边界合并回合。
@@ -92,3 +108,7 @@ Bash 行的详情在用户手动打开之前保持收起。进度段落之间的
`showThinking`/旧版 `thinkingDisplayMode` 的解析优先级,并由 i18n 目录测试覆盖新增的
`settings.showThinking` 文案。界面、解析器与 E2E 场景在集成候选上验证;同步后的场景文本见
E2E-CHAT-turn-process-and-thinking-display。
+2026-10-21 修订由 `apps/desktop/test/turn-process.test.mjs` 覆盖单披露分段、
+命令折叠开关与标题阶段优先级,由 `apps/desktop/test/transcript-style.test.mjs` 覆盖共享
+左边缘与已移除的实时条目回显;交互式转录探针覆盖实际渲染的披露数量、命令行位置和标题
+文案。同步后的场景文本见 E2E-CHAT-turn-process-and-thinking-display。
diff --git a/docs/zh-CN/spec/03-runtime/04-data-storage.md b/docs/zh-CN/spec/03-runtime/04-data-storage.md
index 5b8bc49f74..98cab02961 100644
--- a/docs/zh-CN/spec/03-runtime/04-data-storage.md
+++ b/docs/zh-CN/spec/03-runtime/04-data-storage.md
@@ -1232,7 +1232,10 @@ outbox 排空。渲染器侧的停止绝不重写已有已开始回复的转录
应用设置 JSON 还可选存储布尔值 `showThinking`,用于转录中的推理可见性。它是可移植的
应用偏好,会像旧字段一样跨设备同步。缺失值回退到旧版 `thinkingDisplayMode` 字段
(`compact` 隐藏,`detailed`/未知/缺失显示);该旧字段仅为持久化设置兼容性保留,
-并作为该回退来源。这些新增展示偏好既不重写已存推理,也不改变数据库 schema。
+并作为该回退来源。应用设置 JSON 还可选存储布尔值 `keepCommandsExpanded`,用于回合
+过程披露中的命令行位置:缺失即开启,`Bash` 与 run 别名保留在活动组旁的独立行;
+`false` 折回所属组。它是可移植的应用偏好,只改变展示。这些新增展示偏好既不重写
+已存推理,也不改变数据库 schema。
应用设置 JSON 可能仍包含旧版本写入的提示词增强键。为支持回退和降级,宿主保留这些值,
但不会再把它们作为有效偏好读取或写入。用户安装并授权独立的
diff --git a/docs/zh-CN/spec/04-ux/06-settings-ia.md b/docs/zh-CN/spec/04-ux/06-settings-ia.md
index 39a02e805f..9e903d2724 100644
--- a/docs/zh-CN/spec/04-ux/06-settings-ia.md
+++ b/docs/zh-CN/spec/04-ux/06-settings-ia.md
@@ -129,6 +129,11 @@
`thinkingDisplayMode` 字段(`detailed` / `compact`)仅为持久化设置兼容性保留,
不再在界面暴露;缺失或未知值显示推理,显式 `compact` 隐藏推理。设置搜索会索引
该行。
+- **不折叠命令**是一个开关,以可选的 `keepCommandsExpanded` 布尔值持久化到宿主设置,
+ 缺失时默认开启。开启时,shell 调用保留在它们所运行的工具组旁,作为独立行;关闭时
+ 折回这些组,即命令被分离之前的布局。它只影响展示——两种取值都不改变回合渲染的过程
+ 披露数量(始终为一个),也不改变工具收到的内容或持久化内容——并且在渲染时读取,
+ 因此切换后会立即重绘转录。设置搜索会索引该行。
- 语音绑定(`AppSettings.speech`)**不属于设置页面**(ADR 0291)。宿主仍保留语音能力与
`speech/*` IPC,供插件和已存绑定使用;这里不再提供转写/朗读的服务、协议、模型或音色
选择,设置搜索也不再索引语音相关键。
diff --git a/docs/zh-CN/spec/04-ux/08-component-spec.md b/docs/zh-CN/spec/04-ux/08-component-spec.md
index 07d75aa4ea..d6d89adcaa 100644
--- a/docs/zh-CN/spec/04-ux/08-component-spec.md
+++ b/docs/zh-CN/spec/04-ux/08-component-spec.md
@@ -1057,22 +1057,38 @@ SESSIONS [msg+][↕]
### 回合过程与思考展示
-所有已加载的助手回合都使用同一套回合过程展示,投影为按时间顺序排列、可折叠的过程片段,
-以及其后的最终回答。推理、工具、托管搜索和中间进度文字跨这些片段按转录顺序保留。末尾
-回答在过程之外流式显示;后续活动可以把暂定回答重新归入过程,但不会改写已存消息。助手
-错误和中止后的末尾部分回答也留在过程之外。用户/系统消息及压缩边界不变。
-
-过程内的普通活动组表示两个进度段落或 Bash 行之间的一段连续工具、搜索或思考活动。只有在
-当前思考偏好下至少有两个可见项时才显示组标题。单项活动直接使用自身披露,被隐藏的思考
-不会制造空包装,委派工作继续使用现有 Task 拓扑作为容器。Bash 和 run 别名被排除在所有
-过程披露之外——既不属于回合级过程披露,也不属于普通活动组——而是作为独立行渲染,即使
-所有组都收起也保持可见;相邻的 Bash 行各自保持独立,其详情在用户打开之前保持收起。
-
-拥有当前执行片段的普通活动组在回合运行时默认展开,完成时仅在用户未操作的情况下收起;
-其他已完成组默认收起。若活动组记录过失败或被拒工具,尚未被用户接管的活动组会在后续成功
-恢复期间保持展开,并在回合完成后收起。这些组默认值统一,不依赖思考偏好。无论任何组是否
-收起,Bash 行都保持可见。组标题显示计数、运行状态和问题计数,但不会把失败子项当作整个
-回合失败。
+所有已加载的助手回合都使用同一套回合过程展示:投影为一个可折叠的过程披露,以及其后的
+最终回答。推理、工具、托管搜索和中间进度文字按转录顺序保留在该披露内。末尾回答在过程
+之外流式显示;后续活动可以把暂定回答重新归入过程,但不会改写已存消息。助手错误和中止
+后的末尾部分回答也留在披露之外。用户/系统消息及压缩边界不变。
+
+该披露包含回合在给出回答之前产生的所有行:普通活动组与 `Bash` 命令行都在其中。因此
+每个回合只渲染一个顶层过程披露,只有 Bash 调用的回合也一样;任何命令行都不是该披露的
+同级,长回合可以用一次操作收起。末尾回答、助手错误、中止后的末尾部分文字和待处理操作
+卡留在披露之外,无需展开过程即可访问。
+
+在披露内部,普通活动组表示两个进度段落或命令行之间的一段连续工具、搜索或思考活动。
+只有在当前思考偏好下至少有两个可见项时才显示组标题。单项活动直接使用自身披露,被隐藏
+的思考不会制造空包装,委派工作继续使用现有 Task 拓扑作为容器。
+
+`keepCommandsExpanded` 决定命令行在该披露内的位置,默认开启。开启时,`Bash` 和 run
+别名会从所处的组中提取出来,作为披露顶层的独立行渲染;相邻调用保持分离,详情在用户
+打开之前保持收起。关闭时,命令行保留在流程中的原位置,读起来就是所在组的另一行。两种
+取值都不改变披露数量、工具实际收到的内容或持久化内容。
+
+活动组的折叠默认值统一,不依赖任一偏好。拥有当前执行片段的普通活动组在回合运行时默认
+展开,完成时仅在用户未操作的情况下收起;其他已完成组默认收起。若活动组记录过失败或被
+拒工具,尚未被用户接管的活动组会在后续成功恢复期间保持展开,并在回合完成后收起。组
+标题汇总计数、运行状态和问题计数,但不会把失败子项当作整个回合失败。
+
+回合披露的标题只陈述回合结果,绝不回显正在处理的具体项,因为 shell 命令或搜索词可能
+任意长。它显示 `Failed`、`Stopped`、`Running` 或 `Finished`,优先级依次为失败、停止、
+运行中、已完成:已记录的失败优先于停止,停止优先于正常完成,运行中的回合显示为执行中。
+执行期间,用户可能长时间停留的阶段(压缩上下文、恢复)会各自命名;当前步骤为推理时显示
+`Thinking`,瞬时阶段显示为普通执行中。转录未记录时间时不显示时长,而不是显示为零;问题
+计数与标签并列显示。披露与它
+展开的层级共用同一条左边缘;层级由字号与颜色表达,而不是缩进,因此嵌套组标题与命令行
+起始位置与回合标题完全一致。
条目载荷都不会自动展开:工具调用、托管搜索或计划卡片行在用户打开其披露之前始终只是
标题行,包括 Bash 行——其详情在用户打开之前保持收起。活动组保留各自的自动展开默认值,
@@ -1080,14 +1096,15 @@ SESSIONS [msg+][↕]
可见,而已完成的推理行和摘要被隐藏,空的纯思考容器被省略;已存推理仍会保留,重新打开
偏好时重新出现。
-活动组和条目是相互独立的控件。收起祖先会保留下级选择,重新展开时恢复;展开父级不会
-展开所有后代。用户操作子项时会接管其所属组但不切换该组,因此完成事件不能收起包含已
-展开、聚焦或选中内容的容器。选择以稳定回合/组/条目标识保存在会话窗格内,跨偏好切换
-和行重新挂载保留;窗格淘汰、会话删除或渲染器重启后重新应用默认值,不会写入消息或设置。
+活动组、命令行和条目是相互独立的控件。收起祖先会保留下级选择,重新展开时恢复;收起
+回合披露会隐藏其下所有行,重新展开时恢复用户此前展开的组。展开父级不会展开所有后代。
+用户操作子项时会接管其所属组但不切换该组,因此完成事件不能收起包含已展开、聚焦或选中
+内容的容器。选择以稳定回合/组/条目标识保存在会话窗格内,跨偏好切换和行重新挂载保留;
+窗格淘汰、会话删除或渲染器重启后重新应用默认值,不会写入消息或设置。
-搜索和导航只展开拥有目标消息的过程片段和活动组,并且每个显示请求只应用一次。条目级精确
-定位不在本次范围内。被偏好隐藏的推理会保持隐藏,直到用户打开 `Show thinking`。权限、
-提问、计划/目标审批及其他待处理操作卡位于隐藏过程之外,始终可达。参见
+搜索和导航只展开拥有目标消息的回合过程与活动组,并且每个显示请求只应用一次。条目级
+精确定位不在本次范围内。被偏好隐藏的推理会保持隐藏,直到用户打开 `Show thinking`。
+权限、提问、计划/目标审批及其他待处理操作卡位于隐藏过程之外,始终可达。参见
[ADR turn-process-and-thinking-display](/zh-CN/adr/turn-process-and-thinking-display)。
### 7.2 解剖学
@@ -1523,13 +1540,14 @@ sorting, new settings, persistence, or host protocol is introduced.
参数提示、状态和结果的可读呈现。遵循D071
并且故意不是一张高级卡。
-两个进度段落或 Bash 行之间的一段连续工具、搜索或思考活动,仅在当前思考偏好下有两个及
-以上可见项时成为普通处理组。单项活动直接使用自身披露,Task 拓扑继续使用原有容器。
-Bash 和 run 别名被排除在所有过程披露之外——既不属于回合级过程披露,也不属于普通组——
-而是作为独立行渲染,即使所有组都收起也保持可见;相邻的 Bash 行各自保持独立。回合活动
-期间,拥有当前执行片段的普通组默认展开;未操作的组在完成时自动收起。这些组默认值不依赖
-思考偏好。条目载荷都不会自动展开:工具调用、托管搜索或计划行在用户打开之前始终只是
-标题行,无论它位于活动组的哪一项,包括详情在打开前保持收起的 Bash 行。
+回合过程是一个披露。在该披露内部,两个进度段落或命令行之间的一段连续工具、搜索或思考
+活动,仅在当前思考偏好下有两个及以上可见项时成为普通处理组。单项活动直接使用自身披露,
+Task 拓扑继续使用原有容器。`Bash` 和 run 别名保留在回合披露内:`keepCommandsExpanded`
+开启(默认)时,每一项作为组旁的独立行渲染,相邻调用保持分离;关闭时,命令行留在所在组
+的流程中。只有 Bash 调用的回合仍保留其唯一披露。回合活动期间,拥有当前执行片段的普通组
+默认展开;未操作的组在完成时自动收起。这些组默认值不依赖思考偏好。条目载荷都不会自动
+展开:工具调用、托管搜索或计划行在用户打开之前始终只是标题行,无论它位于活动组的哪一项,
+包括详情在打开前保持收起的 Bash 行。
组标题在活动时显示 `Processing · 12s`,完成后显示 `Processed for 12s`,并提供有界
条目与问题计数。展开后显示有序活动行及其相互独立的结果披露。失败子项仍在自己的
@@ -1559,8 +1577,9 @@ ToolCallRow 上显示错误,但不会让组或整个回合成为终端失败
活动没有组标题。
- 工具/搜索载荷保持收起,直到用户打开;没有任何行会自动展开,因此
最后一项为思考时绝不会选择更早的工具。活动思考遵循自身披露策略,绝不会展开同级载荷。
-- Bash 和 run 行作为独立行渲染,位于所有过程披露之外,即使所有组都收起也保持可见;
- 相邻的 Bash 行保持独立。
+- `Bash` 和 run 行由回合过程披露展开。`keepCommandsExpanded` 开启时,它们位于披露顶层、
+ 组旁,相邻行保持独立;关闭时,它们渲染在所属组内。它们绝不是回合过程的同级,详情在
+ 用户打开之前保持收起。
- 处理组跨越完整可用的辅助列,因此扩展
即使标头或有效负载很短,结果详细信息也会保持可用宽度。
- 可见标签是自然语言操作(`Read`、`Ran`、`Searched`),
diff --git a/docs/zh-CN/spec/04-ux/09-interaction-patterns.md b/docs/zh-CN/spec/04-ux/09-interaction-patterns.md
index 4ddf2fee89..29f46e1f75 100644
--- a/docs/zh-CN/spec/04-ux/09-interaction-patterns.md
+++ b/docs/zh-CN/spec/04-ux/09-interaction-patterns.md
@@ -701,15 +701,22 @@
- 工具活动以轻量的收起条目开始。失败和被拒调用在行标题中保留问题状态,载荷不会
自动展开。
-- 统一的展示为每个已加载的助手回合提供按时间顺序排列的可折叠过程片段,其中包含思考、
- 工具、托管搜索和中间进度文字;末尾回答、助手错误和中止后的末尾文字位于过程之外。
-- 连续活动片段仅在当前思考偏好下至少有两个可见项时获得组披露。进度文字或 Bash 行结束
+- 统一的展示为每个已加载的助手回合提供一个可折叠的过程披露。它包含思考、工具、托管搜索、
+ 中间进度文字以及该回合的 `Bash`/run 行;末尾回答、助手错误和中止后的末尾文字留在
+ 披露之外。
+- 连续活动片段仅在当前思考偏好下至少有两个可见项时获得组披露。进度文字或命令行结束
该片段,单项活动直接使用自身披露,被隐藏的思考不会制造多余组;Task 拓扑保持独立。
- Bash 和 run 别名被排除在所有过程披露之外——既不属于回合级过程披露,也不属于组——
- 而是作为独立行渲染,即使所有组都收起也保持可见;相邻的 Bash 行各自保持独立。
+ `keepCommandsExpanded`(默认开启)只决定命令行在该披露内的位置:开启时把 `Bash` 和
+ run 别名从组中提取为顶层独立行,相邻调用保持分离;关闭时命令行留在所在组的流程中。
+ 两种取值都不会增加披露,也不会让命令行落在回合过程之外。
- 活动普通组默认展开,完成时仅在用户未操作的情况下收起;其他已完成组默认收起,而记录过
- 失败或被拒工具的未接管活动组会在恢复期间保持展开。这些组默认值不依赖思考偏好。无论
- 任何组是否收起,Bash 行都保持可见。
+ 失败或被拒工具的未接管活动组会在恢复期间保持展开。这些组默认值不依赖任一偏好。收起
+ 回合披露会隐藏其下所有组与命令行,但不会清除它们的选择;重新展开时恢复用户此前展开
+ 的组。
+- 回合标题按失败、停止、执行中、已完成的优先级显示 `Failed`、`Stopped`、`Running` 或
+ `Finished`;执行期间压缩上下文与恢复会各自命名,当前步骤为推理时显示 `Thinking`;
+ 转录未记录时长时不显示时长;标题绝不回显当前命令或查询。嵌套组标题与命令行共用它的
+ 左边缘,层级由字号和颜色而不是缩进表达。
- 条目载荷都不会自动展开:工具调用、托管搜索或计划卡片行在用户打开之前始终只是标题行,
包括最后一个活动组的字面最后一项。组的默认展开不变,因此最后一项为思考时
绝不会向前回扫。当 `Show thinking` 关闭时,所有条目载荷保持关闭,已完成的推理正文与
@@ -719,7 +726,7 @@
- 手动操作条目会把所属组标记为用户接管,但不会切换该组。流式更新和完成不会
重新打开手动收起,也不会收起包含用户已展开、聚焦或选中内容的容器。只要保留会话
窗格仍存在,选择就跨偏好切换、单项变组和重新挂载保留。
-- 搜索和导航只打开拥有目标消息的过程片段与活动组,每个显示请求仅应用一次;条目级精确定位不在本次范围内。被偏好隐藏的推理会保持隐藏,直到用户打开 `Show thinking`;关闭搜索不会收起已显示路径。
+- 搜索和导航只打开拥有目标消息的回合过程与活动组,每个显示请求仅应用一次;条目级精确定位不在本次范围内。被偏好隐藏的推理会保持隐藏,直到用户打开 `Show thinking`;关闭搜索不会收起已显示路径。
- 待处理权限、提问、计划/目标审批及其他操作卡位于隐藏过程之外,始终可达。
- 每个披露使用独立按钮、`aria-expanded` 和 `aria-controls`;收起的后代离开 Tab 与
无障碍遍历顺序。减少动态效果会禁用非必要标记和 V 形动画。
diff --git a/docs/zh-CN/spec/06-delivery/04-e2e-test-plan.md b/docs/zh-CN/spec/06-delivery/04-e2e-test-plan.md
index 1bf5205a08..20fdd2d13e 100644
--- a/docs/zh-CN/spec/06-delivery/04-e2e-test-plan.md
+++ b/docs/zh-CN/spec/06-delivery/04-e2e-test-plan.md
@@ -1355,27 +1355,35 @@ task-candidate E2E 从请求工作树运行,但使用主工作区已经准备
- **先决条件**:已配置提供商并打开项目;回合可以包含进度文字、多个搜索/工具/思考
条目,以及失败或被拒工具。
- **步骤**:1) 流式输出进度段落 A、多项搜索片段、进度段落 B,以及带相邻 Bash 行的
- 多项命令片段。2) 检查已展开的活动组;在更多输出到达时手动收起该组。3) 完成回合并
- 比较未操作与用户接管的组,确认所有组都收起时 Bash 行仍保持可见。4) 展开一个已完成组
- 和其中一个条目,复制输出,收起并重新展开该组,再独立打开同级组。5) 分别检查单项片段,
- 以及最后一个活动组的字面最后一项为工具/搜索、思考、失败工具和被拒工具。6) 关闭并重新
- 打开 `Show thinking`,检查活动思考、失败后恢复及完成状态。7) 在保留窗格内重新挂载行,
+ 多项命令片段。2) 检查已展开的活动组;在更多输出到达时手动收起该组。3) 完成回合,
+ 确认恰好一个过程披露拥有全部回答前的行;收起它并确认其下的组与命令行一并收起,再
+ 重新展开并确认组选择恢复。4) 展开一个已完成组和其中一个条目,复制输出,收起并重新
+ 展开该组,再独立打开同级组。5) 切换 `Don't collapse commands` 关闭与开启,检查命令行
+ 的渲染位置,同时确认披露数量始终为一个。6) 分别检查单项片段,以及最后一个活动组的
+ 字面最后一项为工具/搜索、思考、失败工具和被拒工具。7) 关闭并重新打开
+ `Show thinking`,检查活动思考、失败后恢复及完成状态。8) 在保留窗格内重新挂载行,
然后重载渲染器并重新打开会话。
-- **预期**:按时间顺序排列的可折叠过程片段把末尾回答留在其外。活动组展开,并且只在用户
- 未操作时于完成后收起;其他已完成组默认收起。Bash/run 别名被排除在所有过程披露之外,
- 即使所有组都收起也保持可见。单项没有组包装。没有任何条目载荷会自动展开:工具/搜索行
- 在用户打开之前保持标题行,最后一个活动组的字面最后一项也不例外,而思考项保留自身的
- 叶子默认值。当 `Show thinking` 关闭时,活动思考指示器保持可见,已完成的推理正文与摘要
- 被隐藏,空的纯思考容器被省略;重新打开时恢复。父级、子级和同级选择彼此独立;
- 收起/重新展开父级会保留后代,流式更新和完成不会覆盖用户接管的选择。保留窗格中的重新
- 挂载保留选择;渲染器重启重新应用默认值,但工具名称、参数、结果和状态仍会恢复。组标题
- 显示有界运行和问题摘要,不会把整个回合标记为失败。
+- **预期**:一个回合只渲染一个过程披露,其中包含全部回答前的行,`Bash`/run 行也不例外;
+ 末尾回答、助手错误和中止后的末尾文字留在披露之外,待处理操作也一样。活动组默认展开,
+ 并且只在用户未操作时于完成后收起;其他已完成组默认收起。收起回合披露会一并收起其下
+ 的组与命令行,重新展开则恢复用户的组选择。`Don't collapse commands` 开启(默认)时,
+ 命令行作为组旁的顶层独立行渲染,相邻调用保持分离,详情在打开前保持收起;关闭时它们
+ 折回所属组。两种取值都不改变披露数量。单项没有组包装。没有任何条目载荷会自动展开:
+ 工具/搜索行在用户打开之前保持标题行,最后一个活动组的字面最后一项也不例外,而思考项
+ 保留自身的叶子默认值。回合标题按 `Running`、`Finished`、`Stopped` 或 `Failed` 报告
+ 结果,失败与停止优先于正常完成,当前步骤为推理时显示 `Thinking`,绝不回显当前命令;
+ 转录未记录时长时不显示时长。当 `Show thinking` 关闭时,活动思考指示器保持可见,已完成的
+ 推理正文与摘要被隐藏,空的
+ 纯思考容器被省略;重新打开时恢复。父级、子级和同级选择彼此独立;收起/重新展开父级
+ 会保留后代,流式更新和完成不会覆盖用户接管的选择。保留窗格中的重新挂载保留选择;
+ 渲染器重启重新应用默认值,但工具名称、参数、结果和状态仍会恢复。组标题显示有界运行
+ 和问题摘要,不会把整个回合标记为失败。
- **链接规格**:`04-ux/01-ui-ia.md`、`04-ux/07-ui-design-system.md`、
`04-ux/08-component-spec.md`、`04-ux/09-interaction-patterns.md`
- **验收**:C(聊天流)、E(工具)、F(持久性)
- **里程碑**:M3
-- **状态**:草案。2026-09-20 的嵌套披露变更仅把本场景作为静态源码/设计审查的
- 预期行为;该范围不新增或运行单元、组件、集成、浏览器、Electron 或 E2E 测试。
+- **状态**:草案。单元与样式检查覆盖单披露、命令折叠和标题规则;本场景仍是转录重新加载
+ 的预期人工行为。
#### E2E-TRANSCRIPT-invalid-utf8-window-remains-readable
@@ -9196,26 +9204,33 @@ Follow the [current S3 acceptance scenario](/spec/06-delivery/04-e2e-test-plan#e
### E2E-CHAT-turn-process-and-thinking-display
- **先决条件:** 一个回合包含进度段落 A、多次搜索及思考、进度段落 B、多条命令及
- 思考和最终回答;`Show thinking` 偏好开启与关闭两种状态;旧版消息级转录搜索目标。
+ 思考和最终回答;`Show thinking` 偏好开启与关闭两种状态;`Don't collapse commands`
+ 偏好开启与关闭两种状态;旧版消息级转录搜索目标。
- **步骤:** 确认活动组默认展开,让同一回合在无人操作时完成,并确认组收起。另一个
- 回合中,明确展开已完成组,并确认后续更新仍保留该选择。关闭 `Show thinking`,确认
- 活动思考指示器仍然可见、已完成的推理行和摘要消失且不残留空的纯思考容器;再重新打开,
- 确认已完成的推理行恢复。收起所有组,确认 Bash/run 行仍保持可见。检查嵌套路径,包括
- 相互独立的组/条目切换、父级收起与恢复、单项片段、字面最后一项选择、失败/被拒/恢复、
- 保留窗格重新挂载、Bash 行保持独立(包括相邻 Bash 行)且其详情在打开前保持收起,以及
- 旧版搜索定位。
-- **预期:** 按时间顺序排列的可折叠过程片段把最终回答、助手错误、中止后的末尾文字和待处理
- 操作留在过程之外。活动组默认展开;未操作的组在回合完成时收起,用户明确选择的状态继续
- 保留。这些组默认值不依赖 `Show thinking` 偏好。Bash/run 别名被排除在所有过程披露之外,
- 作为独立行渲染,即使所有组都收起也保持可见;相邻 Bash 行各自独立,Bash 行的详情在用户
- 打开前保持收起。`Show thinking` 关闭时,活动思考指示器保持可见,已完成的推理行和摘要
- 被隐藏,空的纯思考容器被省略;重新打开时恢复。单项没有组。没有任何条目载荷会自动展开:
- 工具/搜索行在用户打开之前保持收起,而思考项保留自身的叶子默认值。父级、子级和同级
- 状态相互独立;窗格拥有的用户选择跨更新、偏好切换和重新挂载保留,渲染器重启后重新应用
- 默认值。搜索只展开拥有目标消息的过程片段和活动组,每个请求应用一次;条目级精确定位不在
- 本次范围内,被偏好隐藏的推理会保持隐藏,直到用户打开 `Show thinking`。已保存的
- `showThinking` 跨重启保留;缺失值回退到旧版 `thinkingDisplayMode`(`compact` 隐藏,
- `detailed`/未知/缺失显示)。
+ 回合中,明确展开已完成组,并确认后续更新仍保留该选择;随后收起回合披露并确认组随之
+ 收起,再重新展开并确认组选择恢复。关闭 `Show thinking`,确认活动思考指示器仍然可见、
+ 已完成的推理行和摘要消失且不残留空的纯思考容器;再重新打开,确认已完成的推理行恢复。
+ 关闭 `Don't collapse commands`,确认命令行折回所属组且回合仍只渲染一个披露;再开启,
+ 确认独立行恢复。确认标题分别显示执行中、已完成、已停止或失败,执行期间压缩上下文与
+ 恢复会各自命名,未记录时长时不显示时长,且绝不回显当前命令。检查嵌套路径,包括相互
+ 独立的组/条目切换、父级收起与恢复、单项片段、字面最后一项选择、失败/被拒/恢复、
+ 保留窗格重新挂载、命令行详情在打开前保持收起,以及旧版搜索定位。
+- **预期:** 一个回合只渲染一个过程披露,包含全部回答前的行,命令行也不例外;最终回答、
+ 助手错误、中止后的末尾文字和待处理操作留在披露之外。活动组默认展开;未操作的组在回合
+ 完成时收起,用户明确选择的状态继续保留,并在外层披露重新展开时恢复。这些组默认值不
+ 依赖 `Show thinking` 偏好。`Don't collapse commands` 开启时,命令行作为组旁的顶层独立
+ 行渲染,相邻行保持独立,详情在用户打开前保持收起;关闭时它们折回所属组。两种取值都
+ 不改变披露数量。回合标题按执行中、已完成、已停止、失败的顺序报告,失败与停止优先于
+ 正常完成,当前步骤为推理时显示 `Thinking`,执行期间压缩上下文和恢复会各自命名,未记录
+ 时长时不显示时长,且绝不回显当前命令。嵌套组标题与命令行共用回合标题的左边缘。
+ `Show thinking` 关闭时,活动思考指示器
+ 保持可见,已完成的推理行和摘要被隐藏,空的纯思考容器被省略;重新打开时恢复。单项没有
+ 组。没有任何条目载荷会自动展开:工具/搜索行在用户打开之前保持收起,而思考项保留自身
+ 的叶子默认值。父级、子级和同级状态相互独立;窗格拥有的用户选择跨更新、偏好切换和重新
+ 挂载保留,渲染器重启后重新应用默认值。搜索只展开拥有目标消息的回合过程和活动组,每个
+ 请求应用一次;条目级精确定位不在本次范围内,被偏好隐藏的推理会保持隐藏,直到用户打开
+ `Show thinking`。已保存的 `showThinking` 跨重启保留;缺失值回退到旧版
+ `thinkingDisplayMode`(`compact` 隐藏,`detailed`/未知/缺失显示)。
- **2026-09-20 变更的验证范围:** 本次变更只包含多级折叠与活动组呈现;精确转录搜索
定位不在本次范围内,保持原有搜索行为。
- **自动化:** `pnpm test:e2e:transcript` 覆盖默认及运行中到完成时的过程披露行为;
diff --git a/docs/zh-CN/spec/08-meta/decisions-log.md b/docs/zh-CN/spec/08-meta/decisions-log.md
index c5792d5581..ab5cdb1f4c 100644
--- a/docs/zh-CN/spec/08-meta/decisions-log.md
+++ b/docs/zh-CN/spec/08-meta/decisions-log.md
@@ -54,7 +54,7 @@
| D656 | 隔离宿主持续拒绝的 outbox 追加,避免整队停摆 | **修订 ADR 0041 / D318 / D444 / D597:当 `session.appendMessage` 或 `session.recordUsage` 返回的错误无法归类为重复消息 ID、`PERMISSION_DENIED:` 毒行或外键孤立行时,不再结束本次 flush,而是在同一 Host 代内按有界退避重试(5 秒起、翻倍、上限 60 秒)。同一队头连续第五次失败后,该追加被移入应用自有的死信文件 `session-message-outbox.dead-letter.json`(保留载荷、sessionId、隔离时间与宿主错误;只保留最新 256 条,超出丢弃最旧并记 warn),随后继续排空后续条目,因此单条被拒追加不再长期占用 FIFO 队头、填满 1024 条上限或导致所有会话写入失败。Host 重启属于新代,会立即重试该队头。隔离条目永不自动重放,`session.delete` 会连同该会话的隔离条目一起删除。协议版本、存储架构与队列文件格式均不变。** | 一条 `stream did not contain valid UTF-8` 追加在队头滞留 14.8 小时,期间 `session.persistence.outbox.is.full` 触发 5990 次,导致所有会话的写入直到重启前全部失败;此前只有三类错误有排空出口,其余错误被永久当作瞬时错误(#1560)。 |
| D657 | 让内置浏览器打开工作区外的本地文件 | **修订 ADR 0170:通过绝对路径或 `file:` URL 可打开任意已存在的本地普通文件,本地文件页面也可导航到其他已存在的本地文件。相对输入仍以工作区为根;HTTP(S) 页面只保留此前工作区内文件链接的权限。缺失文件、目录与远程文件 authority 仍被阻止。`BrowserPreview` 与 sidecar 继续使用工作区根解析。公开的 `pi.browser.navigate` API 在高风险 `browser.cdp` 权限下采用相同策略。见 ADR 0328、E2E-059、`04-ux/08-component-spec.md` 与 `05-security/01-security.md`。** | 用户需要检查项目外的本地 HTML,而工作区范围内的 Agent 文件工具和远程页面导航仍须保留原有边界(#1627)。 |
| D659 | 重新打开归档项目后恢复侧栏显示 | **修订 D093 / D455:成功明确激活项目时,清除该规范化路径的渲染层归档标记并持久化,使用户从「项目归档」点击「打开」、通过「添加项目」再次选择同一目录,或打开项目会话后,都能在主页侧边栏看到该项目。仅选择归档详情行而未激活,以及普通会话刷新,都不改变归档状态。不更改 Host/项目/会话存储或协议。见 ADR 0294、E2E-264 与 issue #1653。** | 用户明确重新打开项目后,活动工作区虽已切换,但按路径存储的归档展示标记仍在,导致项目从侧栏隐藏。 |
-| D661 | 分段回合过程与独立的思考偏好 | **取代 D633 / D651 与 `turn-process-and-thinking-display` ADR 中记录的 `Detailed` / `Compact` 显示模式行为与单一整体过程披露:回合渲染为按时间顺序排列的可折叠过程片段,Bash 与 run 别名位于所有折叠容器之外(回合级过程披露与任何普通活动组),即使所有组都收起也保持可见,且过程/组折叠默认值不依赖思考偏好。偏好为可选的布尔值 `AppSettings.showThinking`;缺失或非布尔值回退到旧版 `thinkingDisplayMode` 字段(`compact` 隐藏,`detailed`/未知/缺失显示),该旧字段仅为持久化设置兼容性保留。`showThinking` 加入可移植应用字段,因此会像旧字段一样同步;其余 Host 协议、持久化 schema、权限或插件契约不变。见修订后的 ADR、`04-ux/06-settings-ia.md`、`04-ux/08-component-spec.md`、`04-ux/09-interaction-patterns.md` 与 E2E-CHAT-turn-process-and-thinking-display。** | 单一扁平容器让较长的工具/搜索序列难以浏览,并把推理可见性与过程折叠挤进同一个二值开关;独立布尔值加上始终可见的 Bash 行,让命令密集的回合保持可读又不遮挡回答。 |
+| D661 | 分段回合过程与独立的思考偏好 *(由 D668 修订)* | **取代 D633 / D651 与 `turn-process-and-thinking-display` ADR 中记录的 `Detailed` / `Compact` 显示模式行为与单一整体过程披露:回合渲染为按时间顺序排列的可折叠过程片段,Bash 与 run 别名位于所有折叠容器之外(回合级过程披露与任何普通活动组),即使所有组都收起也保持可见,且过程/组折叠默认值不依赖思考偏好。偏好为可选的布尔值 `AppSettings.showThinking`;缺失或非布尔值回退到旧版 `thinkingDisplayMode` 字段(`compact` 隐藏,`detailed`/未知/缺失显示),该旧字段仅为持久化设置兼容性保留。`showThinking` 加入可移植应用字段,因此会像旧字段一样同步;其余 Host 协议、持久化 schema、权限或插件契约不变。见修订后的 ADR、`04-ux/06-settings-ia.md`、`04-ux/08-component-spec.md`、`04-ux/09-interaction-patterns.md` 与 E2E-CHAT-turn-process-and-thinking-display。** | 单一扁平容器让较长的工具/搜索序列难以浏览,并把推理可见性与过程折叠挤进同一个二值开关;独立布尔值加上始终可见的 Bash 行,让命令密集的回合保持可读又不遮挡回答。 |
| D662 | 插件在工作面板 Browser 中打开受范围限制的 HTML | **在 `fs.read` 下新增 `pi.fs.openInBrowser(pathFromRoot)`。宿主执行插件常规的读取路径包含、受保护路径、凭据拒绝名单、声明范围与项目注册文件夹检查;仅接受已存在的 `.html`、`.htm`、`.xhtml` 文件。验证后,Main 请求渲染进程为当前本地会话创建 Browser 资源标签页。Browser 插件必须启用。此操作不授予 `browser.cdp`,不改变 BrowserPreview 或本地文件导航策略,也不新增 host-core 协议或持久化状态。见 ADR 0330、`07-plugins/03-plugin-api.md`、`07-plugins/13-plugin-permissions-matrix.md`、`04-ux/08-component-spec.md` 与 E2E-153。** | 文件管理器需要在应用内预览 HTML;如果授予插件 `browser.cdp`,也会暴露无关的页面检查与控制能力。 |
## B. 辅助实现默认值
@@ -335,6 +335,7 @@
| D602 | 崩溃转储留在数据目录 | **Electron 的 Crashpad 报告器在 `ready` 之前以本地模式启动(`uploadToServer: false`)。转储放在 `/crash-dumps`,而不是 Electron 默认的 `userData` crashDumps 路径,因此 `PI_DESKTOP_DATA_DIR` profile 不会与其它安装共用转储。下一次持有单实例锁的启动会为新于 `crash-dumps.json` 的转储写一条 `diagnostics` 记录,按 Crashpad `ptype` 分类:任一新转储属于 browser/main 进程则为 `error`,已恢复的 renderer/GPU/utility 崩溃为 `warn`。host-core 与 sidecar 崩溃仍走监督器路径。不上传,不改 IPC,不改 schema。** | 崩溃留下的 minidump 无人读取。Crashpad 也会记录已恢复的渲染进程崩溃,因此下次启动用 `error` 声称上次运行已死是错的;而数据目录之外的转储会逃出 `PI_DESKTOP_DATA_DIR` 隔离。 |
| D619 | 复制公式得到的是它的 TeX 源码 | **仅渲染层:当选区覆盖到渲染出来的公式时,`text/plain` 从 MathML `annotation` 写出——行内 `$…$`,块级 `$$…$$` 独占行,也就是 `lib/latex-math.ts` 把 `\(…\)` 和 `\[…\]` 归一到的那组定界符,且每组定界符都像代码段的围栏那样加长到盖过公式内部出现的最长同字符串——而不是 KaTeX 画的那两棵树。落在公式内部的切口会扩展成整个公式。只有公式被改写:归约后的克隆经由 `Selection.toString()`——复制自己跑的那个序列化器——读回,因此同处一个选区的正文、列表、表格和代码块保留平台自己的读法,包括 `innerText` 会写出、而复制本就会略过的 `user-select: none` 界面零件。不含公式的选区,以及在选区所在位置之外触发的复制,整份交回平台。只写一种 flavour:`text/plain`。接管事件同时丢掉了平台的 `text/html`,且不再写回——归约后的克隆是应用自己的标记,写回去会带上文本读法已略过的 `user-select: none` 界面零件;而改为携带渲染结果则会把每个公式粘贴两遍,因为隐藏 MathML 树的只有 KaTeX 自己的样式表,样式表不会随剪贴板一起走。只有一个由外壳持有的文档级 `copy` 监听器,记录区的右键复制经由同一个模块读取同一个选区。** | 公式粘出来是它的字形,而且每棵渲染树各一份,无法带进 LaTeX 文档或别的 Markdown 编辑器(issue #414)。ADR 0268 当年移除「引用」的理由正是 OS 剪贴板可以替代,那剪贴板就得真的装着源码。 |
| D620 | pi-ai 内置的 API-key 服务成为命名预设 | **向 `NAMED_ENDPOINT_PRESETS` 新增十五条命名预设——Ant Ling、Baseten、Cerebras、Hugging Face、Meta(`responses`)、MiniMax(国际)、Moonshot AI(国际)、NVIDIA、OpenCode Zen、Vercel AI Gateway、Qwen Token 套餐(`alibaba-token-plan`)、Qwen Token 套餐(中国)、小米 Token 套餐(中国/欧洲/新加坡)——各自使用官方主机名;models.dev 键与 pi-ai 提供方 id 不同的那几条,把 pi-ai id 保留为别名。八个内置提供方仍作例外并写明原因:Amazon Bedrock、Azure OpenAI、Cloudflare AI Gateway、Cloudflare Workers AI、Google Vertex AI(URL 里带账户或区域),GitHub Copilot 与 OpenAI Codex(以厂商账号行提供),以及 Radius(这里的 `pi_messages` 仅限账号)。pi-ai 升级后若某提供方既未被覆盖也不在例外中,`packages/agent-runtime/src/pi-ai-provider-sync.test.ts` 会失败。不改协议、存储或 IPC。** | pi-ai 其他能力本就可达,但服务目录的 API-key 一半靠手工维护,已经跟库自带的提供方列表脱节(ADR 0307)。 |
+| D668 | 每回合一个过程披露,并提供命令折叠偏好 | **修订 D661 / `turn-process-and-thinking-display` ADR:每个回合渲染一个顶层过程披露,包含回答前的全部行,`Bash`/run 行也不例外;回答留在披露之外。`Bash` 与 run 别名不再被排除在所有折叠容器之外。可选的布尔值 `AppSettings.keepCommandsExpanded`(缺失即开启)决定命令行是放在其运行所在的组旁,还是留在组内;两种取值都只渲染一个披露。该偏好在渲染时读取,而不是在构建转录条目时读取,因此切换后立即重绘——投影缓存只以消息和压缩为键。披露标题按失败/停止/执行中/已完成的优先级报告,且绝不回显当前条目;披露与它展开的层级共用一条左边缘。`keepCommandsExpanded` 加入可移植应用字段。无 Host 协议、持久化 schema、权限或插件契约变更。见修订后的 ADR、`04-ux/06-settings-ia.md`、`04-ux/08-component-spec.md`、`04-ux/09-interaction-patterns.md` 与 E2E-CHAT-turn-process-and-thinking-display。** | 按时间顺序的分段把同一回合拆成答案上方多个并列披露,而始终可见的命令行也无法被偏好旧分组布局的读者关闭;一个披露加上仅影响展示的偏好同时满足两种需求,且不改变工具收到的内容或持久化内容。 |
## M0. 模型目录决策
@@ -5488,3 +5489,18 @@ Markdown 源码,不是 `text/html` 负载;对禁用行内 HTML 的外部编
- 数量徽标保留运行状态的可发现性,同时避免动画轨道成为默认界面。不需要更改持久化
schema 或迁移。设置读取通过渲染层 API 规范化应用这些默认值。见
`04-ux/01-ui-ia.md`、`04-ux/06-settings-ia.md` 与 E2E-266。
+
+## 2026-10-21 —— 每回合一个过程披露与命令折叠偏好(D668)
+
+- D668 修订 D661 / `turn-process-and-thinking-display` ADR:每个回合现在渲染一个顶层
+ 过程披露,包含回答前的全部行,`Bash`/run 行也不例外。命令行不再是披露的同级;末尾
+ 回答、助手错误、中止后的末尾文字和待处理操作面留在披露之外。
+- `AppSettings.keepCommandsExpanded`(缺失即开启)决定命令行是提取到其运行所在的组旁,
+ 还是留在组内。该偏好在渲染时读取,而不是在构建转录条目时读取,因此切换后立即重绘;
+ 两种取值都只渲染一个披露。
+- 披露标题按失败/停止/执行中/已完成的优先级报告,执行期间压缩上下文与恢复会各自
+ 命名,未记录时长时不显示为零,且绝不回显当前条目。披露与它展开的层级共用一条左边缘。
+- `keepCommandsExpanded` 加入可移植应用字段。已由 `apps/desktop/test/turn-process.test.mjs`、
+ `apps/desktop/test/transcript-style.test.mjs` 与交互式转录探针覆盖。见修订后的 ADR、
+ `04-ux/06-settings-ia.md`、`04-ux/08-component-spec.md`、
+ `04-ux/09-interaction-patterns.md` 与 E2E-CHAT-turn-process-and-thinking-display。
diff --git a/packages/i18n/src/locales/de/index.ts b/packages/i18n/src/locales/de/index.ts
index a65c322712..a8de529887 100644
--- a/packages/i18n/src/locales/de/index.ts
+++ b/packages/i18n/src/locales/de/index.ts
@@ -604,6 +604,14 @@ export const de = {
"processedFor": "Verarbeitet für {{time}}",
"thinkingFor": "Nachdenken · {{time}}",
"thoughtFor": "Nachgedacht für {{time}}",
+ "processRunning": "Läuft",
+ "processRunningFor": "Läuft · {{time}}",
+ "processCompleted": "Abgeschlossen",
+ "processCompletedFor": "Abgeschlossen in {{time}}",
+ "processStopped": "Gestoppt",
+ "processStoppedFor": "Gestoppt nach {{time}}",
+ "processFailed": "Fehlgeschlagen",
+ "processFailedFor": "Fehlgeschlagen nach {{time}}",
"waitingForModel": "Warten auf Modell",
"startingTurn": "Wird gestartet…",
"preparingNextRequest": "Nächste Anfrage wird vorbereitet…",
@@ -628,6 +636,7 @@ export const de = {
"activityIncludesThinking": "Enthält Denken",
"activityFailures": "{{count}} Problem",
"activityFailures_other": "{{count}} Probleme",
+ "collapseTurnProcess": "Gesamten Turn-Prozess einklappen",
"collapseProcess": "Prozess einklappen",
"collapseActivityGroup": "Aktivitätsgruppe einklappen",
"collapseToolOutput": "Tool-Ausgabe einklappen",
@@ -1446,6 +1455,8 @@ sklm: {
"thinkingDisplayCompact": "Kompakt",
"showThinking": "Denkprozess anzeigen",
"showThinkingDesc": "Zeigt den Denkprozess des Modells. Wenn aus, bleibt die Live-Denk-Anzeige sichtbar und abgeschlossene Denkzeilen und Auszüge werden ausgeblendet.",
+ "keepCommandsExpanded": "Befehle nicht einklappen",
+ "keepCommandsExpandedDesc": "Shell-Aufrufe bleiben in eigenen Zeilen, statt in die umgebende Werkzeuggruppe eingeklappt zu werden.",
"contextUsageDisplay": "Kontextnutzung-Anzeige",
"contextUsageDisplayRemaining": "Verbleibend",
"contextUsageDisplayUsed": "Verwendet",
diff --git a/packages/i18n/src/locales/en/index.ts b/packages/i18n/src/locales/en/index.ts
index c909a95c21..4cd59d3c29 100644
--- a/packages/i18n/src/locales/en/index.ts
+++ b/packages/i18n/src/locales/en/index.ts
@@ -616,6 +616,14 @@ export const en = {
processedFor: "Processed for {{time}}",
thinkingFor: "Thinking · {{time}}",
thoughtFor: "Thought for {{time}}",
+ processRunning: "Running",
+ processRunningFor: "Running · {{time}}",
+ processCompleted: "Finished",
+ processCompletedFor: "Finished in {{time}}",
+ processStopped: "Stopped",
+ processStoppedFor: "Stopped after {{time}}",
+ processFailed: "Failed",
+ processFailedFor: "Failed after {{time}}",
waitingForModel: "Waiting for model",
startingTurn: "Starting…",
preparingNextRequest: "Preparing next request…",
@@ -640,6 +648,7 @@ export const en = {
activityIncludesThinking: "Includes thinking",
activityFailures: "{{count}} issue",
activityFailures_other: "{{count}} issues",
+ collapseTurnProcess: "Collapse the whole turn's process",
collapseProcess: "Collapse process",
collapseActivityGroup: "Collapse activity group",
collapseToolOutput: "Collapse tool output",
@@ -1460,6 +1469,8 @@ sklm: {
thinkingDisplayCompact: "Compact",
showThinking: "Show thinking",
showThinkingDesc: "Show the model's reasoning. Off keeps the live thinking indicator visible and hides completed reasoning rows and excerpts.",
+ keepCommandsExpanded: "Don't collapse commands",
+ keepCommandsExpandedDesc: "Keep shell calls on their own rows instead of folding them into the surrounding tool group.",
contextUsageDisplay: "Context usage readout",
contextUsageDisplayRemaining: "Remaining",
contextUsageDisplayUsed: "Used",
diff --git a/packages/i18n/src/locales/es/index.ts b/packages/i18n/src/locales/es/index.ts
index 7d64be7d7f..e36c4cf05d 100644
--- a/packages/i18n/src/locales/es/index.ts
+++ b/packages/i18n/src/locales/es/index.ts
@@ -604,6 +604,14 @@ export const es = {
"processedFor": "Procesado durante {{time}}",
"thinkingFor": "Pensando · {{time}}",
"thoughtFor": "Pensado durante {{time}}",
+ "processRunning": "Ejecutando",
+ "processRunningFor": "Ejecutando · {{time}}",
+ "processCompleted": "Completado",
+ "processCompletedFor": "Completado en {{time}}",
+ "processStopped": "Detenido",
+ "processStoppedFor": "Detenido tras {{time}}",
+ "processFailed": "Fallido",
+ "processFailedFor": "Fallido tras {{time}}",
"waitingForModel": "Esperando modelo",
"startingTurn": "Iniciando…",
"preparingNextRequest": "Preparando la siguiente solicitud…",
@@ -628,6 +636,7 @@ export const es = {
"activityIncludesThinking": "Incluye razonamiento",
"activityFailures": "{{count}} problema",
"activityFailures_other": "{{count}} problemas",
+ "collapseTurnProcess": "Contraer el proceso del turno completo",
"collapseProcess": "Contraer proceso",
"collapseActivityGroup": "Contraer grupo de actividad",
"collapseToolOutput": "Contraer salida de herramienta",
@@ -1446,6 +1455,8 @@ sklm: {
"thinkingDisplayCompact": "Compacto",
"showThinking": "Mostrar razonamiento",
"showThinkingDesc": "Muestra el razonamiento del modelo. Desactivado, el indicador de razonamiento en vivo sigue visible y las filas y extractos de razonamiento completados quedan ocultos.",
+ "keepCommandsExpanded": "No plegar los comandos",
+ "keepCommandsExpandedDesc": "Las llamadas de shell se mantienen en filas propias en lugar de plegarse en el grupo de herramientas contiguo.",
"contextUsageDisplay": "Lectura del uso del contexto",
"contextUsageDisplayRemaining": "Restante",
"contextUsageDisplayUsed": "Usado",
diff --git a/packages/i18n/src/locales/fr/index.ts b/packages/i18n/src/locales/fr/index.ts
index 2b6e2056fd..c3f39ca019 100644
--- a/packages/i18n/src/locales/fr/index.ts
+++ b/packages/i18n/src/locales/fr/index.ts
@@ -604,6 +604,14 @@ export const fr = {
"processedFor": "Traité pendant {{time}}",
"thinkingFor": "Réflexion · {{time}}",
"thoughtFor": "Pensé pendant {{time}}",
+ "processRunning": "En cours",
+ "processRunningFor": "En cours · {{time}}",
+ "processCompleted": "Terminé",
+ "processCompletedFor": "Terminé en {{time}}",
+ "processStopped": "Arrêté",
+ "processStoppedFor": "Arrêté après {{time}}",
+ "processFailed": "Échec",
+ "processFailedFor": "Échec après {{time}}",
"waitingForModel": "En attente du modèle",
"startingTurn": "Démarrage…",
"preparingNextRequest": "Préparation de la prochaine requête…",
@@ -628,6 +636,7 @@ export const fr = {
"activityIncludesThinking": "Inclut le raisonnement",
"activityFailures": "{{count}} problème",
"activityFailures_other": "{{count}} problèmes",
+ "collapseTurnProcess": "Réduire le processus du tour complet",
"collapseProcess": "Réduire le processus",
"collapseActivityGroup": "Réduire le groupe d'activité",
"collapseToolOutput": "Réduire la sortie de l'outil",
@@ -1446,6 +1455,8 @@ sklm: {
"thinkingDisplayCompact": "Compact",
"showThinking": "Afficher le raisonnement",
"showThinkingDesc": "Affiche le raisonnement du modèle. Désactivé, l'indicateur de raisonnement en direct reste visible et les lignes et extraits de raisonnement terminés sont masqués.",
+ "keepCommandsExpanded": "Ne pas replier les commandes",
+ "keepCommandsExpandedDesc": "Les appels shell restent sur leurs propres lignes au lieu d'être repliés dans le groupe d'outils voisin.",
"contextUsageDisplay": "Affichage de l'usage du contexte",
"contextUsageDisplayRemaining": "Restant",
"contextUsageDisplayUsed": "Utilisé",
diff --git a/packages/i18n/src/locales/ko/index.ts b/packages/i18n/src/locales/ko/index.ts
index 6c9edfcb8b..4834527621 100644
--- a/packages/i18n/src/locales/ko/index.ts
+++ b/packages/i18n/src/locales/ko/index.ts
@@ -613,6 +613,14 @@ export const ko = {
processedFor: "{{time}} 동안 처리됨",
thinkingFor: "생각 중 · {{time}}",
thoughtFor: "{{time}} 동안 생각함",
+ processRunning: "실행 중",
+ processRunningFor: "실행 중 · {{time}}",
+ processCompleted: "실행 완료",
+ processCompletedFor: "실행 완료, {{time}}",
+ processStopped: "중지됨",
+ processStoppedFor: "중지됨, {{time}}",
+ processFailed: "실패",
+ processFailedFor: "실패, {{time}}",
waitingForModel: "모델 대기 중",
startingTurn: "시작하는 중…",
preparingNextRequest: "다음 요청 준비 중…",
@@ -637,6 +645,7 @@ export const ko = {
activityIncludesThinking: "생각 포함",
activityFailures: "문제 {{count}}개",
activityFailures_other: "문제 {{count}}개",
+ collapseTurnProcess: "전체 턴 처리 과정 접기",
collapseProcess: "처리 과정 접기",
collapseActivityGroup: "활동 그룹 접기",
collapseToolOutput: "도구 출력 접기",
@@ -1456,6 +1465,8 @@ sklm: {
thinkingDisplayCompact: "간결",
showThinking: "사고 과정 표시",
showThinkingDesc: "모델의 사고 과정을 표시합니다. 끄면 실시간 사고 표시기는 계속 보이고 완료된 사고 행과 발췌는 숨겨집니다.",
+ keepCommandsExpanded: "명령 접지 않기",
+ keepCommandsExpandedDesc: "셸 호출을 주변 도구 그룹에 접지 않고 자체 행으로 유지합니다.",
contextUsageDisplay: "컨텍스트 사용량 표시",
contextUsageDisplayRemaining: "남음",
contextUsageDisplayUsed: "사용됨",
diff --git a/packages/i18n/src/locales/pt-BR/index.ts b/packages/i18n/src/locales/pt-BR/index.ts
index e02ec85b1b..e4d19e8e14 100644
--- a/packages/i18n/src/locales/pt-BR/index.ts
+++ b/packages/i18n/src/locales/pt-BR/index.ts
@@ -603,6 +603,14 @@ export const ptBR = {
processedFor: "Processado durante {{time}}",
thinkingFor: "Pensando · {{time}}",
thoughtFor: "Pensado durante {{time}}",
+ processRunning: "Executando",
+ processRunningFor: "Executando · {{time}}",
+ processCompleted: "Concluído",
+ processCompletedFor: "Concluído em {{time}}",
+ processStopped: "Interrompido",
+ processStoppedFor: "Interrompido após {{time}}",
+ processFailed: "Falhou",
+ processFailedFor: "Falhou após {{time}}",
waitingForModel: "Aguardando o modelo…",
startingTurn: "Iniciando…",
preparingNextRequest: "Preparando próxima solicitação…",
@@ -627,6 +635,7 @@ export const ptBR = {
activityIncludesThinking: "Inclui raciocínio",
activityFailures: "{{count}} problema",
activityFailures_other: "{{count}} problemas",
+ collapseTurnProcess: "Recolher o processo do turno inteiro",
collapseProcess: "Recolher processo",
collapseActivityGroup: "Recolher grupo de atividades",
collapseToolOutput: "Recolher saída da ferramenta",
@@ -1419,6 +1428,8 @@ export const ptBR = {
thinkingDisplayCompact: "Compacto",
showThinking: "Mostrar raciocínio",
showThinkingDesc: "Mostra o raciocínio do modelo. Quando desativado, o indicador de raciocínio ao vivo continua visível e as linhas e trechos de raciocínio concluídos ficam ocultos.",
+ keepCommandsExpanded: "Não recolher comandos",
+ keepCommandsExpandedDesc: "As chamadas de shell ficam em linhas próprias em vez de serem recolhidas no grupo de ferramentas ao redor.",
contextUsageDisplay: "Indicador de uso do contexto",
contextUsageDisplayRemaining: "Restante",
contextUsageDisplayUsed: "Usado",
diff --git a/packages/i18n/src/locales/tr/index.ts b/packages/i18n/src/locales/tr/index.ts
index 8b2d02e326..4f3ef83640 100644
--- a/packages/i18n/src/locales/tr/index.ts
+++ b/packages/i18n/src/locales/tr/index.ts
@@ -613,6 +613,14 @@ export const tr = {
processedFor: "{{time}} işlendi",
thinkingFor: "Düşünülüyor · {{time}}",
thoughtFor: "{{time}} düşünüldü",
+ processRunning: "Çalışıyor",
+ processRunningFor: "Çalışıyor · {{time}}",
+ processCompleted: "Tamamlandı",
+ processCompletedFor: "{{time}} içinde tamamlandı",
+ processStopped: "Durduruldu",
+ processStoppedFor: "{{time}} sonra durduruldu",
+ processFailed: "Başarısız",
+ processFailedFor: "{{time}} sonra başarısız",
waitingForModel: "Model bekleniyor",
startingTurn: "Başlatılıyor…",
preparingNextRequest: "Sonraki istek hazırlanıyor…",
@@ -637,6 +645,7 @@ export const tr = {
activityIncludesThinking: "Düşünmeyi içerir",
activityFailures: "{{count}} sorun",
activityFailures_other: "{{count}} sorun",
+ collapseTurnProcess: "Tüm tur işlemini daralt",
collapseProcess: "İşlemi daralt",
collapseActivityGroup: "Etkinlik grubunu daralt",
collapseToolOutput: "Araç çıktısını daralt",
@@ -1450,6 +1459,8 @@ sklm: {
thinkingDisplayCompact: "Sade",
showThinking: "Düşünmeyi göster",
showThinkingDesc: "Modelin düşünmesini gösterir. Kapalıyken canlı düşünme göstergesi görünür kalır; tamamlanan düşünme satırları ve alıntılar gizlenir.",
+ keepCommandsExpanded: "Komutları katlama",
+ keepCommandsExpandedDesc: "Kabuk çağrıları, çevresindeki araç grubuna katlanmak yerine kendi satırlarında kalır.",
contextUsageDisplay: "Bağlam kullanımı göstergesi",
contextUsageDisplayRemaining: "Kalan",
contextUsageDisplayUsed: "Kullanılan",
diff --git a/packages/i18n/src/locales/zh-CN/index.ts b/packages/i18n/src/locales/zh-CN/index.ts
index cf25670f77..fe9dd50d87 100644
--- a/packages/i18n/src/locales/zh-CN/index.ts
+++ b/packages/i18n/src/locales/zh-CN/index.ts
@@ -609,6 +609,14 @@ export const zhCN = {
processedFor: "已处理 {{time}}",
thinkingFor: "思考中 · {{time}}",
thoughtFor: "已思考 {{time}}",
+ processRunning: "执行中",
+ processRunningFor: "执行中 · {{time}}",
+ processCompleted: "运行完成",
+ processCompletedFor: "运行完成,{{time}}",
+ processStopped: "已停止",
+ processStoppedFor: "已停止,{{time}}",
+ processFailed: "失败",
+ processFailedFor: "失败,{{time}}",
waitingForModel: "等待模型响应",
startingTurn: "正在开始…",
preparingNextRequest: "正在准备下一次请求…",
@@ -633,6 +641,7 @@ export const zhCN = {
activityIncludesThinking: "包含思考",
activityFailures: "{{count}} 个问题",
activityFailures_other: "{{count}} 个问题",
+ collapseTurnProcess: "折叠整轮处理过程",
collapseProcess: "折叠处理过程",
collapseActivityGroup: "折叠活动分组",
collapseToolOutput: "折叠工具输出",
@@ -1440,6 +1449,8 @@ sklm: {
thinkingDisplayCompact: "精简",
showThinking: "显示思考",
showThinkingDesc: "显示模型的推理内容。关闭后仍显示实时思考指示器,并隐藏已完成的推理行和摘要。",
+ keepCommandsExpanded: "命令不折叠",
+ keepCommandsExpandedDesc: "命令行单独成行显示,不并入上下文的工具分组。",
contextUsageDisplay: "上下文用量读数",
contextUsageDisplayRemaining: "剩余",
contextUsageDisplayUsed: "已用",
diff --git a/packages/i18n/src/locales/zh-TW/index.ts b/packages/i18n/src/locales/zh-TW/index.ts
index bd3286669a..1f13023ed9 100644
--- a/packages/i18n/src/locales/zh-TW/index.ts
+++ b/packages/i18n/src/locales/zh-TW/index.ts
@@ -609,6 +609,14 @@ export const zhTW = {
processedFor: "已處理 {{time}}",
thinkingFor: "思考中 · {{time}}",
thoughtFor: "已思考 {{time}}",
+ processRunning: "執行中",
+ processRunningFor: "執行中 · {{time}}",
+ processCompleted: "執行完成",
+ processCompletedFor: "執行完成,{{time}}",
+ processStopped: "已停止",
+ processStoppedFor: "已停止,{{time}}",
+ processFailed: "失敗",
+ processFailedFor: "失敗,{{time}}",
waitingForModel: "等待模型響應",
startingTurn: "正在開始…",
preparingNextRequest: "正在準備下一次請求…",
@@ -633,6 +641,7 @@ export const zhTW = {
activityIncludesThinking: "包含思考",
activityFailures: "{{count}} 個問題",
activityFailures_other: "{{count}} 個問題",
+ collapseTurnProcess: "摺疊整輪處理過程",
collapseProcess: "摺疊處理過程",
collapseActivityGroup: "摺疊活動群組",
collapseToolOutput: "摺疊工具輸出",
@@ -1440,6 +1449,8 @@ sklm: {
thinkingDisplayCompact: "精簡",
showThinking: "顯示思考",
showThinkingDesc: "顯示模型的推理內容。關閉後仍顯示即時思考指示器,並隱藏已完成的推理列和摘要。",
+ keepCommandsExpanded: "指令不折疊",
+ keepCommandsExpandedDesc: "指令列單獨成列顯示,不併入上下文的工具分組。",
contextUsageDisplay: "上下文用量讀數",
contextUsageDisplayRemaining: "剩餘",
contextUsageDisplayUsed: "已用",
diff --git a/packages/shared/src/types/settings.ts b/packages/shared/src/types/settings.ts
index 133d214826..ce2f9040d2 100644
--- a/packages/shared/src/types/settings.ts
+++ b/packages/shared/src/types/settings.ts
@@ -106,6 +106,16 @@ export type AppSettings = {
* export, or execution, and it does not control turn-process folding.
*/
showThinking?: boolean;
+ /**
+ * Keep shell calls (`Bash`, `exec`, `shell`, …) as their own rows instead of
+ * folding them into the surrounding tool group. Absent means `true`, so an
+ * existing install keeps today's scannable command rows.
+ *
+ * The turn's process disclosure itself is not affected: both values render
+ * exactly one top-level disclosure per turn. This preference only decides
+ * whether a run row sits inside a group or beside it.
+ */
+ keepCommandsExpanded?: boolean;
/**
* @deprecated Retained for persisted-settings compatibility. New writes use
* `showThinking`; this field is read only as a fallback when `showThinking`
diff --git a/scripts/e2e/transcript-disclosure-anchor.tsx b/scripts/e2e/transcript-disclosure-anchor.tsx
index 3aeed2de35..813e13e233 100644
--- a/scripts/e2e/transcript-disclosure-anchor.tsx
+++ b/scripts/e2e/transcript-disclosure-anchor.tsx
@@ -69,11 +69,190 @@ function geometry(scroller: HTMLElement, title: HTMLElement): Geometry {
};
}
-/** Two ticks: one for the observer-driven layout, one for the follow frame. */
-async function settle() {
- for (let tick = 0; tick < 3; tick += 1) {
- await new Promise((resolve) => setTimeout(resolve, 40));
- }
+type LayoutDirection = "initial" | "grow" | "shrink" | "change";
+
+type LayoutHistoryEntry = {
+ phase: "baseline" | "resize" | "frame";
+ at: number;
+ contentHeight: number;
+ expected: boolean;
+ geometry: Geometry;
+};
+
+function contentHeight(content: HTMLElement): number {
+ return content.getBoundingClientRect().height;
+}
+
+function observedBorderBoxHeight(entry: ResizeObserverEntry): number {
+ const borderBox = entry.borderBoxSize?.[0];
+ return borderBox ? borderBox.blockSize : entry.contentRect.height;
+}
+
+function geometrySnapshot(sample: Geometry): string {
+ return [
+ sample.scrollTop,
+ sample.scrollHeight,
+ sample.clientHeight,
+ sample.titleTop,
+ sample.distanceFromBottom,
+ ]
+ .map((value) => Math.round(value * 1000) / 1000)
+ .join(",");
+}
+
+function layoutTransitioned(
+ direction: LayoutDirection,
+ baselineHeight: number,
+ observedHeight: number,
+): boolean {
+ const delta = observedHeight - baselineHeight;
+ if (direction === "initial") return observedHeight > 0;
+ if (direction === "grow") return delta > 0.5;
+ if (direction === "shrink") return delta < -0.5;
+ return Math.abs(delta) > 0.5;
+}
+
+/**
+ * A real layout barrier for one fixture action.
+ *
+ * It is armed before `trigger`, on the owning content's border box: the same
+ * element the product observes. Once the delivered content resize matches the
+ * expected disclosure state and direction, geometry is sampled in an animation
+ * frame scheduled from that delivery, and must hold for two consecutive frames.
+ * Any later resize cancels that window. The watchdog only bounds a hung
+ * fixture; it never retries the product assertion, so a mismatch reported after
+ * this returns is witnessed after the layout correction, not before it.
+ */
+async function waitForLayout({
+ label,
+ scroller,
+ content,
+ title,
+ expected,
+ direction,
+ trigger,
+ timeoutMs = 10_000,
+}: {
+ label: string;
+ scroller: HTMLElement;
+ content: HTMLElement;
+ title: HTMLElement;
+ expected: () => boolean;
+ direction: LayoutDirection;
+ trigger?: () => void;
+ timeoutMs?: number;
+}): Promise {
+ const baselineHeight = contentHeight(content);
+ const history: LayoutHistoryEntry[] = [];
+ const record = (phase: LayoutHistoryEntry["phase"], height: number) => {
+ history.push({
+ phase,
+ at: Math.round(performance.now()),
+ contentHeight: Math.round(height * 100) / 100,
+ expected: expected(),
+ geometry: geometry(scroller, title),
+ });
+ if (history.length > 48) history.splice(0, history.length - 48);
+ };
+ record("baseline", baselineHeight);
+
+ let targetSeen = false;
+ let stableFrames = 0;
+ let lastSignature = "";
+ let frame = 0;
+ let watchdog = 0;
+ let finished = false;
+ let observer: ResizeObserver | null = null;
+
+ const cleanup = () => {
+ if (watchdog !== 0) window.clearTimeout(watchdog);
+ watchdog = 0;
+ cancelAnimationFrame(frame);
+ frame = 0;
+ observer?.disconnect();
+ observer = null;
+ };
+
+ await new Promise((resolve, reject) => {
+ const fail = (reason: string) => {
+ if (finished) return;
+ finished = true;
+ cleanup();
+ let current: { contentHeight: number; geometry: Geometry } | null = null;
+ try {
+ current = {
+ contentHeight: Math.round(contentHeight(content) * 100) / 100,
+ geometry: geometry(scroller, title),
+ };
+ } catch {
+ // Keep the history from before the owning elements disappeared.
+ }
+ reject(new Error(
+ `${label}: ${reason}; ${JSON.stringify({
+ direction,
+ baselineHeight,
+ targetSeen,
+ expected: expected(),
+ current,
+ history,
+ })}`,
+ ));
+ };
+
+ const sample = () => {
+ frame = 0;
+ if (finished) return;
+ const height = contentHeight(content);
+ record("frame", height);
+ const signature = geometrySnapshot(geometry(scroller, title));
+ if (signature === lastSignature) {
+ stableFrames += 1;
+ } else {
+ lastSignature = signature;
+ stableFrames = 1;
+ }
+ if (stableFrames >= 2) {
+ finished = true;
+ cleanup();
+ resolve();
+ return;
+ }
+ frame = requestAnimationFrame(sample);
+ };
+
+ const instance = new ResizeObserver((entries) => {
+ if (finished) return;
+ const entry = entries[entries.length - 1];
+ const height = observedBorderBoxHeight(entry);
+ record("resize", height);
+ stableFrames = 0;
+ lastSignature = "";
+ if (
+ !targetSeen &&
+ expected() &&
+ layoutTransitioned(direction, baselineHeight, height)
+ ) {
+ targetSeen = true;
+ }
+ if (targetSeen && frame === 0) frame = requestAnimationFrame(sample);
+ });
+ observer = instance;
+
+ watchdog = window.setTimeout(() => {
+ fail(targetSeen
+ ? "geometry did not hold for two consecutive frames after the resize"
+ : `no ${direction} content resize was delivered`);
+ }, timeoutMs);
+
+ instance.observe(content, { box: "border-box" });
+ try {
+ trigger?.();
+ } catch (error) {
+ finished = true;
+ cleanup();
+ reject(error);
+ }
+ });
}
/**
@@ -82,7 +261,17 @@ async function settle() {
* viewport. Only the app's stylesheet is left out, so the geometry comes from
* inline sizes and the real components' intrinsic height.
*/
-function TranscriptFixture({ messages, process = false, isActive = false }: { messages: UiMessage[]; process?: boolean; isActive?: boolean }) {
+function TranscriptFixture({
+ messages,
+ process = false,
+ isActive = false,
+ sessionId = "fixture",
+}: {
+ messages: UiMessage[];
+ process?: boolean;
+ isActive?: boolean;
+ sessionId?: string;
+}) {
const entry = process ? buildTranscriptEntries(messages).entries.find((item) => item.kind === "assistant-turn") : undefined;
const {
scrollRef,
@@ -91,7 +280,7 @@ function TranscriptFixture({ messages, process = false, isActive = false }: { me
handleScroll,
disclosureAnchorNotifier,
} = useTranscriptScroll({
- sessionId: "fixture",
+ sessionId,
messages,
hasMoreBefore: false,
isRunning: false,
@@ -113,7 +302,7 @@ function TranscriptFixture({ messages, process = false, isActive = false }: { me
className="thread-scroll"
data-scroll-owner="transcript"
onScroll={handleScroll}
- style={{ height: "100%", overflowY: "auto" }}
+ style={{ height: "100%", overflowY: "auto", overflowAnchor: "none" }}
>
@@ -139,9 +328,9 @@ function FollowFixture({ tool }: { tool: UiMessage }) {
className="subagent-run-rows"
data-scroll-owner="follow"
onScroll={handleScroll}
- style={{ height: "300px", overflowY: "auto" }}
+ style={{ height: "300px", overflowY: "auto", overflowAnchor: "none" }}
>
-
+
@@ -192,11 +381,20 @@ globalThis.transcriptDisclosureProbe = async () => {
/>,
);
const scroller = container.querySelector
(".thread-scroll");
+ const content = container.querySelector(".thread-content");
const title = container.querySelector(".tool-row-header");
assert(scroller, "the transcript scroller did not render");
+ assert(content, "the transcript content did not render");
assert(title, "the tool title did not render");
- await settle();
+ await waitForLayout({
+ label: "transcript mount",
+ scroller,
+ content,
+ title,
+ expected: () => title.isConnected,
+ direction: "initial",
+ });
const before = geometry(scroller, title);
assert(
Math.abs(before.distanceFromBottom) < 1,
@@ -208,8 +406,15 @@ globalThis.transcriptDisclosureProbe = async () => {
);
// A plain click on the title, exactly as a reader expands a tool row.
- title.click();
- await settle();
+ await waitForLayout({
+ label: "transcript tool expansion",
+ scroller,
+ content,
+ title,
+ expected: () => title.getAttribute("aria-expanded") === "true",
+ direction: "grow",
+ trigger: () => title.click(),
+ });
const expanded = geometry(scroller, title);
assert(
expanded.scrollHeight > before.scrollHeight + 100,
@@ -224,8 +429,15 @@ globalThis.transcriptDisclosureProbe = async () => {
`expanding the tool re-bottomed the transcript: ${JSON.stringify({ before, expanded })}`,
);
- title.click();
- await settle();
+ await waitForLayout({
+ label: "transcript tool collapse",
+ scroller,
+ content,
+ title,
+ expected: () => title.getAttribute("aria-expanded") === "false",
+ direction: "shrink",
+ trigger: () => title.click(),
+ });
const collapsed = geometry(scroller, title);
assert(
Math.abs(collapsed.titleTop - before.titleTop) < 2,
@@ -243,16 +455,34 @@ globalThis.transcriptDisclosureProbe = async () => {
const dockTitle = dockContainer.querySelector(
".tool-row-header",
);
+ const dockContent = dockContainer.querySelector(
+ "[data-layout-content='dock']",
+ );
assert(dockScroller, "the dock scroller did not render");
+ assert(dockContent, "the dock content did not render");
assert(dockTitle, "the dock tool title did not render");
- await settle();
+ await waitForLayout({
+ label: "dock mount",
+ scroller: dockScroller,
+ content: dockContent,
+ title: dockTitle,
+ expected: () => dockTitle.isConnected,
+ direction: "initial",
+ });
const dockBefore = geometry(dockScroller, dockTitle);
assert(
Math.abs(dockBefore.distanceFromBottom) < 1,
`the dock did not start pinned to the bottom: ${JSON.stringify(dockBefore)}`,
);
- dockTitle.click();
- await settle();
+ await waitForLayout({
+ label: "dock tool expansion",
+ scroller: dockScroller,
+ content: dockContent,
+ title: dockTitle,
+ expected: () => dockTitle.getAttribute("aria-expanded") === "true",
+ direction: "grow",
+ trigger: () => dockTitle.click(),
+ });
const dockExpanded = geometry(dockScroller, dockTitle);
assert(
dockExpanded.scrollHeight > dockBefore.scrollHeight + 100,
@@ -282,23 +512,51 @@ globalThis.transcriptDisclosureProbe = async () => {
const renderProcess = (isActive: boolean) => flushSync(() =>
processRoot.render(
-
+
,
),
);
renderProcess(true);
const processScroller = processContainer.querySelector(".thread-scroll");
+ const processContent = processContainer.querySelector(".thread-content");
const processTitle = processContainer.querySelector(".turn-process > button");
- assert(processScroller && processTitle, "process fixture did not render");
- await settle();
+ assert(processScroller && processContent && processTitle, "process fixture did not render");
+ await waitForLayout({
+ label: "process mount",
+ scroller: processScroller,
+ content: processContent,
+ title: processTitle,
+ expected: () => processTitle.getAttribute("aria-expanded") === "true",
+ direction: "initial",
+ });
const processBefore = geometry(processScroller, processTitle);
assert(
processTitle.getAttribute("aria-expanded") === "true",
"an active detailed process should start open",
);
- renderProcess(false);
- await settle();
+ assert(
+ Math.abs(processBefore.distanceFromBottom) < 1,
+ `the process fixture did not start pinned to the bottom: ${JSON.stringify(processBefore)}`,
+ );
+ await waitForLayout({
+ label: "process automatic collapse",
+ scroller: processScroller,
+ content: processContent,
+ title: processTitle,
+ expected: () => processTitle.getAttribute("aria-expanded") === "false",
+ direction: "shrink",
+ trigger: () => renderProcess(false),
+ });
const processCollapsed = geometry(processScroller, processTitle);
+ assert(
+ processCollapsed.titleTop >= 0 && processCollapsed.titleTop < 600,
+ `the process title is not on screen for the expansion test: ${JSON.stringify(processCollapsed)}`,
+ );
assert(
processTitle.getAttribute("aria-expanded") === "false",
`an untouched process should collapse when its turn completes (expanded=${processTitle.getAttribute("aria-expanded")}, active=${processContainer.querySelector(".turn-process")?.classList.contains("active") ?? false}, bodyHidden=${processContainer.querySelector(".turn-process-body")?.hidden ?? true}, focusInside=${processContainer.querySelector(".turn-process-body")?.contains(document.activeElement) ?? false}, selected=${window.getSelection()?.isCollapsed === false})`,
@@ -307,8 +565,15 @@ globalThis.transcriptDisclosureProbe = async () => {
processCollapsed.scrollHeight < processBefore.scrollHeight - 100,
"completed process content remained visible",
);
- processTitle.click();
- await settle();
+ await waitForLayout({
+ label: "process manual expansion",
+ scroller: processScroller,
+ content: processContent,
+ title: processTitle,
+ expected: () => processTitle.getAttribute("aria-expanded") === "true",
+ direction: "grow",
+ trigger: () => processTitle.click(),
+ });
const processExpanded = geometry(processScroller, processTitle);
assert(
processTitle.getAttribute("aria-expanded") === "true",
@@ -322,19 +587,96 @@ globalThis.transcriptDisclosureProbe = async () => {
// anchor has to compensate; the automatic collapse above may legitimately clamp.
assert(
Math.abs(processExpanded.titleTop - processCollapsed.titleTop) < 2,
- "process expansion moved its title",
+ `process expansion moved its title by ${processExpanded.titleTop - processCollapsed.titleTop}px: ${JSON.stringify({ processBefore, processCollapsed, processExpanded })}`,
);
+ // Both renders are flushSync commits and this check reads state only, so it
+ // needs no layout barrier.
renderProcess(true);
renderProcess(false);
- await settle();
assert(
processTitle.getAttribute("aria-expanded") === "true",
"a user-expanded process should stay open after completion",
);
+
+ // A fresh process starts active. Its automatic collapse and the reader's
+ // immediate manual expansion commit in the same task, so the pending
+ // collapse layout and follow work must not drag the clicked title away.
+ const rapidContainer = document.createElement("div");
+ rapidContainer.style.height = "600px";
+ rapidContainer.style.width = "640px";
+ host.append(rapidContainer);
+ const rapidRoot = createRoot(rapidContainer, {
+ onUncaughtError: (error) => renderErrors.push(error),
+ });
+ roots.push(rapidRoot);
+ const renderRapid = (isActive: boolean) => flushSync(() =>
+ rapidRoot.render(
+
+
+ ,
+ ),
+ );
+ renderRapid(true);
+ const rapidScroller = rapidContainer.querySelector(".thread-scroll");
+ const rapidContent = rapidContainer.querySelector(".thread-content");
+ const rapidTitle = rapidContainer.querySelector(".turn-process > button");
+ assert(rapidScroller && rapidContent && rapidTitle, "rapid process fixture did not render");
+ await waitForLayout({
+ label: "rapid process mount",
+ scroller: rapidScroller,
+ content: rapidContent,
+ title: rapidTitle,
+ expected: () => rapidTitle.getAttribute("aria-expanded") === "true",
+ direction: "initial",
+ });
+ const rapidBefore = geometry(rapidScroller, rapidTitle);
+ assert(
+ Math.abs(rapidBefore.distanceFromBottom) < 1,
+ `the rapid process did not start pinned to the bottom: ${JSON.stringify(rapidBefore)}`,
+ );
+ const rapid = {
+ collapsedHeight: 0,
+ atExpansion: null as Geometry | null,
+ };
+ await waitForLayout({
+ label: "rapid automatic collapse then immediate manual expansion",
+ scroller: rapidScroller,
+ content: rapidContent,
+ title: rapidTitle,
+ expected: () => rapidTitle.getAttribute("aria-expanded") === "true",
+ direction: "change",
+ trigger: () => {
+ renderRapid(false);
+ rapid.collapsedHeight = rapidScroller.scrollHeight;
+ rapidTitle.click();
+ rapid.atExpansion = geometry(rapidScroller, rapidTitle);
+ },
+ });
+ const rapidExpanded = geometry(rapidScroller, rapidTitle);
+ assert(
+ rapidTitle.getAttribute("aria-expanded") === "true",
+ "the immediate manual expansion should win over the automatic collapse",
+ );
+ assert(
+ rapid.collapsedHeight > 0 && rapidExpanded.scrollHeight > rapid.collapsedHeight + 100,
+ `the rapid manual expansion did not restore the process height: ${JSON.stringify({ rapidBefore, rapidExpanded, collapsedHeight: rapid.collapsedHeight })}`,
+ );
+ assert(rapid.atExpansion, "the rapid expansion did not record its click geometry");
+ assert(
+ Math.abs(rapidExpanded.titleTop - rapid.atExpansion.titleTop) < 2,
+ `pending collapse work moved the rapidly expanded title by ${rapidExpanded.titleTop - rapid.atExpansion.titleTop}px: ${JSON.stringify({ rapidBefore, atExpansion: rapid.atExpansion, rapidExpanded })}`,
+ );
+
assert(renderErrors.length === 0, `React render errors: ${renderErrors.map(String).join("; ")}`);
return {
ok: true,
process: { before: processBefore, collapsed: processCollapsed, expanded: processExpanded },
+ rapid: { before: rapidBefore, expanded: rapidExpanded },
transcript: { before, expanded, collapsed },
dock: { before: dockBefore, expanded: dockExpanded },
};
diff --git a/scripts/e2e/transcript-render.tsx b/scripts/e2e/transcript-render.tsx
index af9a818c90..d3ce4d7d84 100644
--- a/scripts/e2e/transcript-render.tsx
+++ b/scripts/e2e/transcript-render.tsx
@@ -511,7 +511,7 @@ globalThis.transcriptRenderProbe = async () => {
);
// A standalone Bash row is not an activity group: it updates through its own
- // rendered command, outside every process disclosure.
+ // rendered command, as a row of the turn's single process disclosure.
const bashMessages = (command: string): UiMessage[] => [
message("bash-user", "user", "Run"),
message("bash-row", "tool", "", {
@@ -526,8 +526,11 @@ globalThis.transcriptRenderProbe = async () => {
const bashRow = container.querySelector('[data-message-id="bash-row"]');
assert(bashRow, "the standalone Bash row did not render");
assert(
- bashRow.closest(".turn-process") === null,
- "the Bash row must render outside every process disclosure",
+ bashRow.closest(".turn-process") !== null &&
+ bashRow.closest(".turn-process") ===
+ container.querySelector(".turn-process") &&
+ bashRow.closest(".process-activity-group") === null,
+ "the Bash row must render inside the turn's one process, outside every group",
);
assert(container.textContent?.includes("printf before"), "the Bash command did not render");
globalThis.__activityGroupRenders = [];
diff --git a/scripts/e2e/turn-process.tsx b/scripts/e2e/turn-process.tsx
index 81ac6af8da..98c5b10ddb 100644
--- a/scripts/e2e/turn-process.tsx
+++ b/scripts/e2e/turn-process.tsx
@@ -6,6 +6,7 @@ import { en } from "@pi-desktop/i18n";
import type { AppSettings, UiMessage } from "@pi-desktop/shared";
import { AssistantTurn } from "../../apps/desktop/src/features/chat/transcript/AssistantTurn";
import { ShowThinkingRow } from "../../apps/desktop/src/components/settings/ShowThinkingRow";
+import { KeepCommandsExpandedRow } from "../../apps/desktop/src/components/settings/KeepCommandsExpandedRow";
import { buildTranscriptEntries } from "../../apps/desktop/src/lib/assistant-turns";
import { TranscriptSearchContext } from "../../apps/desktop/src/lib/transcript-search-context";
import type { TranscriptSearchTarget } from "../../apps/desktop/src/lib/transcript-reading";
@@ -55,6 +56,10 @@ export async function turnProcessProbe() {
interpolation: { escapeValue: false },
});
const container = document.createElement("div");
+ // Keep the collapse rail's gutter inside the viewport, like the real
+ // .thread-content padding does, so hit testing can address it.
+ container.style.cssText =
+ "width: 800px; max-width: 100%; padding-left: 32px; box-sizing: border-box;";
document.body.append(container);
const initialSettings = useAppStore.getState().settings;
const baseSettings: AppSettings = {
@@ -71,6 +76,7 @@ export async function turnProcessProbe() {
onUncaughtError: (error) => errors.push(error),
});
const notes: string[] = [];
+ const metrics: Record = {};
const check = (value: unknown, name: string) => {
assert(value, name);
notes.push(name);
@@ -101,6 +107,44 @@ export async function turnProcessProbe() {
const firstProcess = () => container.querySelector(".turn-process-body");
const visible = (element: Element | null) =>
Boolean(element?.getBoundingClientRect().height);
+ const leftOf = (element: Element | null) =>
+ element?.getBoundingClientRect().left;
+ const nearLeft = (left: number | undefined, right: number | undefined) =>
+ typeof left === "number" && typeof right === "number" &&
+ Math.abs(left - right) < 0.75;
+ const pointIn = (element: Element | null) => {
+ if (!element) return null;
+ const rect = element.getBoundingClientRect();
+ return document.elementFromPoint(
+ rect.left + Math.min(6, rect.width / 2),
+ rect.top + rect.height / 2,
+ );
+ };
+ const owns = (header: Element | null, target: Element | null) =>
+ Boolean(header && target && header.contains(target));
+ const railHit = (rail: Element | null) => {
+ if (!rail) return null;
+ const rect = rail.getBoundingClientRect();
+ return document.elementFromPoint(
+ rect.left + rect.width / 2,
+ rect.top + rect.height / 2,
+ );
+ };
+ const rectOf = (element: Element | null) => {
+ if (!element) return null;
+ const rect = element.getBoundingClientRect();
+ return {
+ left: rect.left,
+ right: rect.right,
+ width: rect.width,
+ top: rect.top,
+ bottom: rect.bottom,
+ };
+ };
+ const fontSize = (element: Element | null) =>
+ element ? Number.parseFloat(getComputedStyle(element).fontSize) : NaN;
+ const color = (element: Element | null) =>
+ element ? getComputedStyle(element).color : "";
const click = (element: HTMLElement | null) => {
assert(element, "missing click target");
flushSync(() => element.click());
@@ -136,18 +180,25 @@ export async function turnProcessProbe() {
responseDurationMs: 1000,
});
const mixed = [intro, read, grep, bash1, bash2, edit, answer];
+ // No progress paragraph between these rows: the folded group must be one
+ // contiguous ordinary stretch around both run rows.
+ const contiguous = [read, grep, bash1, bash2, edit, answer];
try {
- // Bash has no process ancestor and stays visible with every disclosure
- // collapsed, even across adjacent calls.
+ // One disclosure per turn: the Bash rows are rows inside the turn's process,
+ // not siblings of it, so a long turn collapses in one gesture.
render(mixed);
const bash1Row = row("bash1");
const bash2Row = row("bash2");
check(Boolean(bash1Row) && Boolean(bash2Row), "both adjacent Bash rows render");
check(
- bash1Row?.closest(".turn-process") === null &&
- bash2Row?.closest(".turn-process") === null,
- "no Bash row is inside any turn-process disclosure",
+ container.querySelectorAll(".turn-process").length === 1,
+ "a turn renders exactly one process disclosure",
+ );
+ check(
+ bash1Row?.closest(".turn-process") !== null &&
+ bash2Row?.closest(".turn-process") !== null,
+ "every Bash row lives inside that one disclosure",
);
check(
bash1Row?.closest(".turn-run-row") !== null &&
@@ -159,15 +210,116 @@ export async function turnProcessProbe() {
bash1Row?.closest(".tool-activity-group") === null,
"Bash rows are not folded into an activity group",
);
+ check(
+ processHeaders()[0]?.querySelector(".tool-activity-count")?.textContent ===
+ i18n.t("chat.processTools", { count: 5 }),
+ "the process header counts every tool once",
+ );
check(allCollapsed(), "the completed process starts fully collapsed");
check(
- visible(bash1Row) && visible(bash2Row),
- "Bash rows stay visible with every disclosure collapsed",
+ !visible(bash1Row) && !visible(bash2Row),
+ "Bash rows are revealed by the turn's process, not left outside it",
);
check(
!visible(row("read")) && !visible(row("grep")),
"non-run work stays inside its collapsed process",
);
+ // Opening the one top-level disclosure reveals the whole run: the groups and
+ // the standalone Bash rows alike.
+ click(processHeaders()[0] ?? null);
+ check(
+ visible(bash1Row) && visible(bash2Row),
+ "opening the process reveals the Bash rows",
+ );
+
+ // Real geometry and hit testing: the turn title, a nested group title and a
+ // Bash row share one left edge, and the collapse rail owns its gutter.
+ const topHeader = processHeaders()[0] ?? null;
+ const nestedHeader = container.querySelector(
+ ".process-activity-group.grouped > .tool-activity-header",
+ );
+ const bashHeader = bash1Row?.querySelector(".tool-row-header") ?? null;
+ const bashHead = bash1Row?.querySelector(".tool-row-head.is-run") ?? null;
+ const topIcon = topHeader?.querySelector(".tool-activity-icon") ?? null;
+ const nestedIcon = nestedHeader?.querySelector(".tool-activity-icon") ?? null;
+ const bashIcon = bashHeader?.querySelector(".tool-row-icon") ?? null;
+ const topLabel = topHeader?.querySelector(".tool-activity-label") ?? null;
+ const nestedLabel = nestedHeader?.querySelector(".tool-activity-label") ?? null;
+ const bashLabel = bashHeader?.querySelector(".tool-row-name") ?? null;
+ check(
+ nearLeft(leftOf(topIcon), leftOf(nestedIcon)) &&
+ nearLeft(leftOf(nestedIcon), leftOf(bashIcon)),
+ "turn, group and run icons share one left edge",
+ );
+ check(
+ nearLeft(leftOf(topLabel), leftOf(nestedLabel)) &&
+ nearLeft(leftOf(nestedLabel), leftOf(bashLabel)),
+ "turn, group and run titles share one text line",
+ );
+ check(
+ nearLeft(leftOf(topHeader), leftOf(nestedHeader)) &&
+ nearLeft(leftOf(nestedHeader), leftOf(bashHead)),
+ "turn, group and run header fills share one left edge",
+ );
+ check(
+ owns(topHeader, pointIn(topIcon)) &&
+ owns(nestedHeader, pointIn(nestedIcon)) &&
+ owns(bashHeader, pointIn(bashIcon)),
+ "each disclosure header owns its content hit target",
+ );
+ check(
+ fontSize(topLabel) > fontSize(nestedLabel) &&
+ fontSize(nestedLabel) === fontSize(bashLabel),
+ "the nested group title is smaller than the turn title and matches run-row type",
+ );
+ check(
+ color(topLabel) !== color(nestedLabel) &&
+ color(nestedLabel) !== color(bashLabel),
+ "the nested group title uses a quieter colour than the turn and run rows",
+ );
+ const topRail = firstProcess()?.querySelector(
+ ":scope > .disclosure-collapse-rail",
+ ) ?? null;
+ check(
+ topRail !== null && railHit(topRail) === topRail,
+ "the turn collapse rail owns its gutter hit target",
+ );
+ click(nestedHeader);
+ const nestedBody = nestedHeader?.parentElement?.querySelector(
+ ":scope > .process-activity-body",
+ ) ?? null;
+ const nestedRail = nestedBody?.querySelector(
+ ":scope > .disclosure-collapse-rail",
+ ) ?? null;
+ check(
+ nestedRail !== null && railHit(nestedRail) === nestedRail,
+ "the nested group collapse rail owns its gutter hit target",
+ );
+ metrics.desktop = {
+ icons: [leftOf(topIcon), leftOf(nestedIcon), leftOf(bashIcon)],
+ labels: [leftOf(topLabel), leftOf(nestedLabel), leftOf(bashLabel)],
+ headers: [leftOf(topHeader), leftOf(nestedHeader), leftOf(bashHead)],
+ turnRail: rectOf(topRail),
+ groupRail: rectOf(nestedRail),
+ };
+ container.style.width = "420px";
+ check(
+ nearLeft(leftOf(topIcon), leftOf(nestedIcon)) &&
+ nearLeft(leftOf(nestedIcon), leftOf(bashIcon)),
+ "the shared left edge survives a narrow transcript",
+ );
+ check(
+ topRail !== null && railHit(topRail) === topRail &&
+ nestedRail !== null && railHit(nestedRail) === nestedRail,
+ "both collapse rails stay usable in a narrow transcript",
+ );
+ metrics.narrow = {
+ icons: [leftOf(topIcon), leftOf(nestedIcon), leftOf(bashIcon)],
+ turnRail: rectOf(topRail),
+ groupRail: rectOf(nestedRail),
+ };
+ container.style.width = "800px";
+
check(
bash1Row?.classList.contains("open") !== true,
"a Bash row keeps its detail closed until opened",
@@ -178,15 +330,44 @@ export async function turnProcessProbe() {
"a Bash row opens its own detail on request",
);
- // A turn of only Bash calls has no process disclosure at all.
+ // A turn of only Bash calls still has its single process disclosure: the run
+ // rows are what it reveals.
render([run("only1", "echo 1"), run("only2", "echo 2")], false, null, "only-bash");
check(
- container.querySelectorAll(".turn-process").length === 0,
- "a Bash-only turn renders no process disclosure",
+ container.querySelectorAll(".turn-process").length === 1,
+ "a Bash-only turn keeps its one process disclosure",
+ );
+ check(
+ processHeaders()[0]?.getAttribute("aria-expanded") === "false",
+ "a completed Bash-only process starts collapsed",
+ );
+ check(
+ processHeaders()[0]?.querySelector(".tool-activity-count")?.textContent ===
+ i18n.t("chat.processTools", { count: 2 }),
+ "a Bash-only header counts its commands once",
);
+ click(processHeaders()[0] ?? null);
check(
visible(row("only1")) && visible(row("only2")),
- "both Bash-only rows stay visible",
+ "opening it reveals both Bash rows",
+ );
+
+ // Progress text without a tool still owns the turn's one process.
+ const progressOnly = [
+ message("progress-only", "assistant", "Inspecting the workspace", {
+ status: "streaming",
+ }),
+ message("progress-final", "assistant", "Done", { status: "complete" }),
+ ];
+ render(progressOnly, false, null, "progress-only");
+ check(
+ container.querySelectorAll(".turn-process").length === 1,
+ "a progress-only process keeps its one disclosure",
+ );
+ click(processHeaders()[0] ?? null);
+ check(
+ visible(row("progress-only")),
+ "opening the progress-only disclosure reveals its text",
);
// Active process content opens while the turn runs and closes when it stops.
@@ -212,12 +393,12 @@ export async function turnProcessProbe() {
status: "streaming",
});
const bashLive = run("bash-live", "pnpm test");
- const thinkingLabel = i18n.t("chat.thinkingFor", { time: "" });
+ const thinkingLabel = i18n.t("chat.thinking");
render([supersededThought, bashLive], true, null, "thinking-to-bash");
check(
- row("bash-live")?.closest(".turn-process") === null &&
- visible(row("bash-live")),
- "a Bash row that supersedes thinking stays standalone and visible",
+ row("bash-live")?.closest(".turn-run-row") !== null &&
+ row("bash-live")?.closest(".process-activity-group") === null,
+ "a Bash row that supersedes thinking renders as a standalone run row",
);
check(
!processHeaders().some((header) =>
@@ -230,9 +411,9 @@ export async function turnProcessProbe() {
setSettings({ showThinking: false });
render([supersededThought, bashLive], true, null, "thinking-to-bash-hidden");
check(
- container.querySelectorAll(".turn-process").length === 0 &&
+ container.querySelectorAll(".turn-process").length === 1 &&
visible(row("bash-live")),
- "hidden superseded thinking leaves no empty process and keeps the Bash row",
+ "hidden superseded thinking leaves the run row in the live process",
);
setSettings();
@@ -260,11 +441,15 @@ export async function turnProcessProbe() {
);
setSettings({ showThinking: false });
render([supersededThought2, separateAnswer], true, null, "thinking-to-answer-hidden");
+ // The live reasoning indicator is still a visible step of the turn's one
+ // disclosure (that is what keeps the indicator), so the disclosure stays.
+ // What must not happen is the answer being swallowed or hidden reasoning
+ // leaving a row behind.
check(
- container.querySelectorAll(".turn-process").length === 0 &&
+ container.querySelectorAll(".turn-process").length <= 1 &&
!container.querySelector(".thinking") &&
Boolean(row("stream-answer")),
- "hidden thinking superseded by a separate answer leaves no empty process",
+ "hidden thinking superseded by a separate answer stays out of the answer row",
);
setSettings();
@@ -277,10 +462,13 @@ export async function turnProcessProbe() {
setSettings({ showThinking: false });
render([liveThought], true, null, "thought-off-live");
const liveHeader = processHeaders()[0];
+ // A live turn whose only row is reasoning still says so, even with completed
+ // reasoning hidden: the header answers "what is happening", and hiding the
+ // finished rows must not hide that the model is thinking right now.
+ const liveLabel = () =>
+ liveHeader?.querySelector(".tool-activity-label")?.textContent ?? "";
check(
- liveHeader?.querySelector(".tool-activity-label")?.textContent?.startsWith(
- i18n.t("chat.thinkingFor", { time: "" }),
- ),
+ liveLabel() === i18n.t("chat.thinking"),
"show thinking off keeps the live thinking indicator in the header",
);
check(
@@ -289,10 +477,7 @@ export async function turnProcessProbe() {
);
click(liveHeader);
check(
- allCollapsed() &&
- liveHeader?.querySelector(".tool-activity-label")?.textContent?.startsWith(
- i18n.t("chat.thinkingFor", { time: "" }),
- ),
+ allCollapsed() && liveLabel() === i18n.t("chat.thinking"),
"the live thinking indicator stays visible with the process closed",
);
render([{ ...liveThought, status: "complete" }], false, null, "thought-off-done");
@@ -304,6 +489,22 @@ export async function turnProcessProbe() {
liveThought.thinking === "Reasoning before the answer",
"hiding thinking never deletes stored reasoning",
);
+ // A streaming reasoning row that already has assistant content is hidden
+ // like any completed reasoning row. It must not leave an empty disclosure
+ // behind, and the answer must stay visible.
+ const hiddenStreamingContent = message(
+ "hidden-streaming-content",
+ "assistant",
+ "Visible answer",
+ { thinking: "Reasoning with content", status: "streaming" },
+ );
+ render([hiddenStreamingContent], true, null, "hidden-streaming-content");
+ check(
+ !container.querySelector(".turn-process") &&
+ !container.querySelector(".thinking") &&
+ visible(row("hidden-streaming-content")),
+ "hidden streaming reasoning with content leaves no empty process shell",
+ );
setSettings({ showThinking: true });
render([{ ...liveThought, status: "complete" }], false, null, "thought-on-done");
check(
@@ -329,6 +530,132 @@ export async function turnProcessProbe() {
"search reveals the process chunk that owns the target",
);
+ // Command folding is read at render time: toggling it on the mounted turn
+ // must regroup the rows without remounting the transcript.
+ setSettings();
+ render(contiguous, false, null, "command-folding-toggle");
+ click(processHeaders()[0] ?? null);
+ check(
+ visible(row("bash1")) &&
+ container.querySelectorAll(".turn-run-row").length === 2,
+ "the mounted turn starts with standalone command rows",
+ );
+ setSettings({ keepCommandsExpanded: false });
+ check(
+ container.querySelectorAll(".turn-process").length === 1 &&
+ container.querySelectorAll(".turn-run-row").length === 0,
+ "toggling command folding keeps one process and removes standalone rows",
+ );
+ const foldedBash1 = row("bash1");
+ const foldedBash2 = row("bash2");
+ const foldedGroup = foldedBash1?.closest(".process-activity-group.grouped");
+ check(
+ foldedGroup !== null &&
+ foldedGroup === foldedBash2?.closest(".process-activity-group.grouped"),
+ "folded commands share one grouped activity ancestor",
+ );
+ check(
+ foldedGroup?.contains(row("read") ?? null) === true &&
+ foldedGroup?.contains(row("edit") ?? null) === true,
+ "the shared group contains the surrounding tools",
+ );
+ check(
+ foldedGroup?.querySelector(".tool-activity-header") !== null,
+ "the shared group keeps its group header",
+ );
+ check(
+ processHeaders()[0]?.querySelector(".tool-activity-count")?.textContent ===
+ i18n.t("chat.processTools", { count: 5 }),
+ "folding commands does not change the header tool count",
+ );
+ setSettings();
+ check(
+ container.querySelectorAll(".turn-run-row").length === 2 &&
+ row("bash1")?.closest(".process-activity-group") === null,
+ "toggling command folding back restores standalone rows without a remount",
+ );
+
+ // The active tail may be wrapped in a merged off-mode part; the merged group
+ // must still receive the live disclosure defaults.
+ setSettings({ keepCommandsExpanded: false });
+ render(
+ [read, grep, run("live-folded-bash", "pnpm test")],
+ true,
+ null,
+ "live-folded",
+ );
+ check(
+ visible(row("live-folded-bash")) &&
+ container.querySelector(".process-activity-group.grouped.open") !== null,
+ "the merged group keeps its live disclosure default",
+ );
+ setSettings();
+
+ // The header reports the turn's outcome, never the item it is working on.
+ render(mixed, false, null, "completed-header");
+ const completedLabel = i18n.t("chat.processCompleted");
+ const completedText = processHeaders()[0]
+ ?.querySelector(".tool-activity-label")
+ ?.textContent ?? "";
+ check(
+ completedText.startsWith(completedLabel) &&
+ !completedText.includes("pnpm test") &&
+ !completedText.includes("pnpm build"),
+ "a settled turn header reports completion without echoing a command",
+ );
+ render([intro, read, grep], true, null, "live-header");
+ check(
+ processHeaders()[0]
+ ?.querySelector(".tool-activity-label")
+ ?.textContent === i18n.t("chat.processRunning"),
+ "a live turn header reports running",
+ );
+
+ // The store settles a Stop on the tool row itself: an aborted assistant row
+ // is not written. The header must read the aborted activity row rather than
+ // falling back to the tool's running/error state.
+ const stoppedBash = [
+ message("stopped-user", "user", "Run"),
+ tool("stopped-bash", "Bash", {
+ toolArgs: { command: "pnpm test" },
+ status: "aborted",
+ toolStatus: "error",
+ }),
+ ];
+ render(stoppedBash, false, null, "stopped-bash");
+ check(
+ processHeaders()[0]
+ ?.querySelector(".tool-activity-label")
+ ?.textContent === i18n.t("chat.processStopped"),
+ "an aborted running Bash row reports the turn stopped",
+ );
+
+ // The Settings row is a boolean command-folding toggle, defaulting to on.
+ let foldSaved: Partial | undefined;
+ flushSync(() =>
+ root.render(
+
+ {
+ foldSaved = patch;
+ }}
+ />
+ ,
+ ),
+ );
+ const foldToggle = container.querySelector('[role="switch"]');
+ check(
+ foldToggle?.getAttribute("aria-checked") === "true",
+ "the command-folding row defaults to keeping commands expanded",
+ );
+ click(foldToggle);
+ check(
+ foldSaved?.keepCommandsExpanded === false,
+ "the command-folding row saves the boolean preference",
+ );
+
+
// The Settings row is a boolean Show thinking toggle.
let saved: Partial | undefined;
const settings: AppSettings = { ...baseSettings, showThinking: false };
@@ -355,7 +682,7 @@ export async function turnProcessProbe() {
"the Show thinking row saves the boolean preference",
);
- return { ok: true, checks: notes };
+ return { ok: true, checks: notes, metrics };
} finally {
flushSync(() => root.unmount());
useAppStore.setState({ settings: initialSettings });
From 434e06f5d2382482bcc6bf065474b221d657a968 Mon Sep 17 00:00:00 2001
From: muzimu217
Date: Tue, 20 Oct 2026 17:02:14 -0700
Subject: [PATCH 11/44] fix(e2e): escalate to SIGKILL when the certificate
probe hangs
#1751's Electron E2E job ran 30m18s and was cancelled by the job budget with
no failing step to read. The cause is this runner's only timeout:
const timer = setTimeout(() => child.kill(), 60_000);
SIGTERM is a request. An Electron child still initialising its renderer can
ignore it, and the 'close' event this script awaits then never arrives, so the
step holds the job until GitHub cancels it. The runner's own 60s budget is
never enforced.
Escalate: SIGTERM at 60s, SIGKILL at 65s, and report which one fired. A probe
that cannot start now fails this step in about a minute with its output
attached, instead of burning the job budget.
Verified: normal path still passes ("provider client certificate E2E
passed"); with a child that ignores SIGTERM the escalation force-kills it at
~800ms in an isolated harness, so the timeout path terminates rather than
hanging.
---
scripts/e2e-provider-client-certificate.mjs | 25 +++++++++++++++++++--
1 file changed, 23 insertions(+), 2 deletions(-)
diff --git a/scripts/e2e-provider-client-certificate.mjs b/scripts/e2e-provider-client-certificate.mjs
index 2876c74792..f29cb14846 100644
--- a/scripts/e2e-provider-client-certificate.mjs
+++ b/scripts/e2e-provider-client-certificate.mjs
@@ -29,13 +29,34 @@ try {
output += chunk;
process.stdout.write(chunk);
});
- const timer = setTimeout(() => child.kill(), 60_000);
+ // A probe that cannot start must fail this step, not hold the job open.
+ // SIGTERM alone is not enough: Electron can ignore it while a renderer is
+ // mid-init, and the `close` event then never arrives, so the step waits out
+ // the job's 30-minute budget and is cancelled with no failing step to read
+ // (#1751 hit exactly this). Escalate to SIGKILL after a short grace period.
+ let killedBy = null;
+ const termTimer = setTimeout(() => {
+ killedBy = "SIGTERM";
+ child.kill("SIGTERM");
+ }, 60_000);
+ const killTimer = setTimeout(() => {
+ killedBy = "SIGKILL";
+ child.kill("SIGKILL");
+ }, 65_000);
try {
const code = await new Promise((resolve, reject) => {
child.once("error", reject);
child.once("close", resolve);
});
+ assert.equal(
+ killedBy,
+ null,
+ `provider client certificate E2E hung and was killed by ${killedBy} after ${killedBy === "SIGKILL" ? 65 : 60}s: ${output}`,
+ );
assert.equal(code, 0, output);
assert.match(output, /provider client certificate E2E passed/);
- } finally { clearTimeout(timer); }
+ } finally {
+ clearTimeout(termTimer);
+ clearTimeout(killTimer);
+ }
} finally { await rm(temp, { recursive: true, force: true }); }
From c82490ce7e6ff0967fa768273d838d1cc1c4675f Mon Sep 17 00:00:00 2001
From: spacker-343 <67576022+spacker-343@users.noreply.github.com>
Date: Wed, 21 Oct 2026 17:03:34 +0800
Subject: [PATCH 12/44] fix(runtime): size the output cap from the folded
request transcript
Long sessions accumulate one system-transcript snapshot per instruction
change. Unless a model declares mid-conversation system support, every
adapter folds them into a single leading message, but the output-cap
estimate charged each superseded snapshot again. The clamp collapsed to
1 and the provider floor (16) went on the wire while the request was far
from the window, so reasoning models were cut off and the turn ended as
EMPTY_MODEL_RESPONSE without compaction ever triggering.
The parent and subagent stream paths now fold the transcript the way
the adapter will before clamping, and hand that same transcript to
pi-ai so its own streamSimple clamp agrees. Context calibration and the
compaction budget keep their existing basis.
---
docs/spec/03-runtime/02-agent-runtime.md | 8 +-
docs/spec/06-delivery/04-e2e-test-plan.md | 14 +-
.../src/output-cap-request.test.ts | 171 ++++++++++++++++++
packages/agent-runtime/src/output-cap.test.ts | 29 +++
packages/agent-runtime/src/output-cap.ts | 31 +++-
packages/agent-runtime/src/runtime.ts | 12 +-
.../src/subagent-model-binding.ts | 11 +-
packages/agent-runtime/src/subagent.test.ts | 2 +-
8 files changed, 263 insertions(+), 15 deletions(-)
create mode 100644 packages/agent-runtime/src/output-cap-request.test.ts
diff --git a/docs/spec/03-runtime/02-agent-runtime.md b/docs/spec/03-runtime/02-agent-runtime.md
index 34f3a0a7e3..a5d4dff28c 100644
--- a/docs/spec/03-runtime/02-agent-runtime.md
+++ b/docs/spec/03-runtime/02-agent-runtime.md
@@ -577,7 +577,13 @@ the pi-ai chars/4 baseline plus a CJK correction, then reserves the larger of
4,096 tokens or 1% of the effective window. The effective window is the smaller
of the configured value and the published catalog window when both are known;
this prevents an oversized user override from bypassing compaction and output
-protection. Unknown windows preserve the configured output budget.
+protection. Unknown windows preserve the configured output budget. The estimate
+measures the transcript the adapter sends: unless the bound model declares
+mid-conversation system support, later system-transcript updates are folded
+into one leading message carrying the current instructions and tools, and the
+parent and subagent paths hand that folded transcript to pi-ai as well, so its
+own `streamSimple` clamp agrees. Superseded instruction snapshots are never
+charged against the output budget.
The incoming user prompt participates in budgeting before the first provider
request. The automatic summary request retries transient provider failures
diff --git a/docs/spec/06-delivery/04-e2e-test-plan.md b/docs/spec/06-delivery/04-e2e-test-plan.md
index c6989e9870..56c8fcc82f 100644
--- a/docs/spec/06-delivery/04-e2e-test-plan.md
+++ b/docs/spec/06-delivery/04-e2e-test-plan.md
@@ -17416,16 +17416,24 @@ the latest destination. These assertions measure work counts, not device FPS.
window, supports parent and subagent requests, and records request payloads.
- **Steps:** Configure a user context override larger than the published window;
send a CJK-heavy parent prompt, invoke a subagent, and run a one-shot
- completion. Repeat the parent request with `thinkingLevel: "omit"`.
+ completion. Repeat the parent request with `thinkingLevel: "omit"`. Restore a
+ session whose transcript holds many large instruction updates on a Responses
+ gateway without mid-conversation system support, then continue it and run a
+ subagent whose updates follow its last usage report.
- **Expected:** Each request carries a concrete output budget no larger than the
remaining published window after input estimation and safety reserve. The
runtime compacts against the published safety ceiling, and no request is sent
with `input + output` beyond that ceiling. Small ASCII requests retain the
- configured budget when it fits.
+ configured budget when it fits. The restored session and the subagent send one
+ folded instruction message and keep the configured output budget instead of
+ the provider's minimum.
- **Specs linked:** `03-runtime/02-agent-runtime.md`,
`03-runtime/13-model-catalog-and-selection.md`
- **Acceptance:** F (runtime provider requests), C (chat and stream)
-- **Status:** Unit-covered; deterministic provider fixture pending
+- **Automation:** `packages/agent-runtime/src/output-cap-request.test.ts` drives
+ the restored-session and subagent steps through a loopback Responses gateway.
+- **Status:** Unit-covered; folded-instruction steps covered by a loopback
+ gateway; remaining deterministic provider fixture pending
### E2E-PROVIDER-certificate-trust-and-terminal-errors
diff --git a/packages/agent-runtime/src/output-cap-request.test.ts b/packages/agent-runtime/src/output-cap-request.test.ts
new file mode 100644
index 0000000000..f8b41a0983
--- /dev/null
+++ b/packages/agent-runtime/src/output-cap-request.test.ts
@@ -0,0 +1,171 @@
+import { createServer, type ServerResponse } from "node:http";
+import { afterEach, describe, expect, it } from "vitest";
+import { normalizeContext, type Message } from "@earendil-works/pi-ai";
+import type { UiMessage } from "@pi-desktop/shared";
+import { DesktopAgentRuntime } from "./runtime.js";
+import type { RuntimeProviderConfig } from "./provider-binding.js";
+import { subagentModelBinding } from "./subagent-model-binding.js";
+
+/**
+ * A long session rewrites a large instruction section many times. A gateway
+ * without mid-conversation system support receives only the current
+ * instructions, so the output budget must be measured against that request,
+ * not against every superseded snapshot kept in the transcript.
+ */
+
+const WINDOW = 128_000;
+const OUTPUT = 8_192;
+const UPDATES = 20;
+/** Each snapshot alone is ~6k tokens; all of them together exceed the window. */
+const SECTION_CHARS = 25_000;
+
+type WireItem = { role?: string; type?: string; content?: unknown };
+type WireRequest = { max_output_tokens?: number; input: WireItem[] };
+
+const cleanups: Array<() => Promise> = [];
+afterEach(async () => {
+ for (const cleanup of cleanups.splice(0).reverse()) await cleanup();
+});
+
+function section(index: number): string {
+ return `update-${index}:`.padEnd(SECTION_CHARS, "x");
+}
+
+function respond(res: ServerResponse): void {
+ res.writeHead(200, { "content-type": "text/event-stream" });
+ const send = (data: { type: string; [key: string]: unknown }) =>
+ res.write(`event: ${data.type}\ndata: ${JSON.stringify(data)}\n\n`);
+ const item = {
+ id: "msg_fixture", type: "message", role: "assistant", status: "completed",
+ content: [{ type: "output_text", text: "Continuing.", annotations: [] }],
+ };
+ send({ type: "response.created", response: { id: "resp_fixture" } });
+ send({ type: "response.output_item.added", output_index: 0, item: { ...item, content: [], status: "in_progress" } });
+ send({ type: "response.output_text.delta", output_index: 0, content_index: 0, delta: "Continuing." });
+ send({ type: "response.output_item.done", output_index: 0, item });
+ send({
+ type: "response.completed",
+ response: {
+ id: "resp_fixture", status: "completed", output: [item],
+ usage: {
+ input_tokens: 10, output_tokens: 2, total_tokens: 12,
+ input_tokens_details: { cached_tokens: 0 }, output_tokens_details: { reasoning_tokens: 0 },
+ },
+ },
+ });
+ res.end();
+}
+
+async function gateway(): Promise<{ baseUrl: string; requests: WireRequest[] }> {
+ const requests: WireRequest[] = [];
+ const server = createServer(async (req, res) => {
+ let raw = "";
+ for await (const part of req) raw += part;
+ requests.push(JSON.parse(raw) as WireRequest);
+ respond(res);
+ });
+ await new Promise((resolve) => server.listen(0, "127.0.0.1", resolve));
+ cleanups.push(async () => {
+ server.closeAllConnections();
+ await new Promise((resolve) => server.close(() => resolve()));
+ });
+ const address = server.address();
+ if (!address || typeof address === "string") throw new Error("fixture address missing");
+ return { baseUrl: `http://127.0.0.1:${address.port}/v1`, requests };
+}
+
+/** A user-configured Responses gateway: mid-conversation system support is unverified. */
+function gatewayProvider(baseUrl: string): RuntimeProviderConfig {
+ return {
+ id: "gateway", name: "Gateway", baseUrl, modelId: "gateway-model", apiKey: "fixture-not-real",
+ apiStyle: "responses", supportsReasoning: false, supportedThinkingLevels: ["off"],
+ modelConfig: {
+ source: "generic", name: "Gateway model", baseUrl, reasoning: false, input: ["text"],
+ cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
+ contextWindow: WINDOW, maxTokens: OUTPUT,
+ },
+ };
+}
+
+function instructionItems(request: WireRequest): WireItem[] {
+ return request.input.filter((item) => item.role === "system" || item.role === "developer");
+}
+
+describe("output budget with superseded instruction snapshots", () => {
+ it("keeps the configured output budget when a restored long session continues", async () => {
+ const { baseUrl, requests } = await gateway();
+ const createdAt = "2026-10-20T10:00:00.000Z";
+ const history: UiMessage[] = [];
+ let previous: string | undefined;
+ for (let index = 0; index < UPDATES; index++) {
+ const update = { role: "system", content: "", sections: { context: section(index) }, timestamp: 1_000 + index };
+ history.push({
+ id: `update-${index}`, role: "system", content: "", createdAt,
+ modelSystem: {
+ version: 1, messageJson: JSON.stringify(update),
+ ...(previous ? { afterMessageId: previous } : {}),
+ },
+ });
+ history.push({ id: `user-${index}`, role: "user", content: `Step ${index}`, createdAt, status: "complete" });
+ history.push({
+ id: `assistant-${index}`, role: "assistant", content: `Done ${index}.`, createdAt, status: "complete",
+ // The provider measured the folded request, not the unfolded history.
+ usage: { inputTokens: 12_000, outputTokens: 100, totalTokens: 12_100 },
+ });
+ previous = `assistant-${index}`;
+ }
+ const runtime = new DesktopAgentRuntime({
+ sessionId: "long-session", mode: "agent", provider: gatewayProvider(baseUrl), history, thinkingLevel: "off",
+ commandShell: { id: "bash", label: "Bash", dialect: "posix", available: true, isDefault: true },
+ host: {
+ call: async (method: string): Promise => {
+ if (method === "session.appendMessage") return undefined as T;
+ throw new Error(`Unexpected host method: ${method}`);
+ },
+ onNotification: () => () => {},
+ },
+ onEvent: () => {},
+ });
+ cleanups.push(async () => { await runtime.dispose(); });
+
+ await runtime.prompt("Continue");
+
+ expect(requests).toHaveLength(1);
+ const [request] = requests;
+ expect(request.max_output_tokens).toBe(OUTPUT);
+ expect(instructionItems(request)).toHaveLength(1);
+ expect(JSON.stringify(request.input)).not.toContain("update-0:");
+ });
+
+ it("keeps a delegate's output budget when instruction updates follow its usage anchor", async () => {
+ const { baseUrl, requests } = await gateway();
+ const binding = subagentModelBinding(
+ { provider: gatewayProvider(baseUrl), thinkingLevel: "off", sessionId: "long-session" },
+ { claim: () => undefined },
+ );
+ const messages: Message[] = [
+ { role: "system", content: "Delegate instructions.", timestamp: 1 },
+ { role: "user", content: "Review the change.", timestamp: 2 },
+ {
+ role: "assistant", content: [{ type: "text", text: "Reviewing." }],
+ api: "openai-responses", provider: binding.model.provider, model: binding.model.id,
+ usage: {
+ input: 12_000, output: 100, cacheRead: 0, cacheWrite: 0, totalTokens: 12_100,
+ cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
+ },
+ stopReason: "stop", timestamp: 3,
+ },
+ ...Array.from({ length: UPDATES }, (_, index): Message => ({
+ role: "system", content: "", sections: { context: section(index) }, timestamp: 4 + index,
+ })),
+ { role: "user", content: "Continue.", timestamp: 100 },
+ ];
+
+ const result = await binding.streamFn(binding.model, normalizeContext({ messages }), {}).result();
+
+ expect(result.stopReason).toBe("stop");
+ expect(requests).toHaveLength(1);
+ expect(requests[0].max_output_tokens).toBe(OUTPUT);
+ expect(instructionItems(requests[0])).toHaveLength(1);
+ });
+});
diff --git a/packages/agent-runtime/src/output-cap.test.ts b/packages/agent-runtime/src/output-cap.test.ts
index 234a118a54..c36e3726eb 100644
--- a/packages/agent-runtime/src/output-cap.test.ts
+++ b/packages/agent-runtime/src/output-cap.test.ts
@@ -1,7 +1,9 @@
import { describe, expect, it } from "vitest";
+import { getCurrentSystemPrompt, normalizeContext, type Message } from "@earendil-works/pi-ai";
import {
clampOutputToContext,
estimateOutputCapInputTokens,
+ requestTranscript,
type OutputCapContext,
} from "./output-cap.js";
@@ -353,6 +355,33 @@ describe("clampOutputToContext", () => {
});
});
+describe("requestTranscript", () => {
+ const updates = (count: number): Message[] => [
+ { role: "system", content: "Base instructions.", timestamp: 1 },
+ ...Array.from({ length: count }, (_, index): Message => ({
+ role: "system", content: "", sections: { context: `${index}`.padEnd(40_000, "x") }, timestamp: 2 + index,
+ })),
+ { role: "user", content: "Continue.", timestamp: 100 },
+ ];
+ const model = { contextWindow: 128_000, maxTokens: 8_192, compat: { supportsMidConvoSystemMessages: false } };
+
+ it("charges only the current instructions when the adapter folds system updates", () => {
+ const context = normalizeContext({ messages: updates(16) });
+ const request = requestTranscript(model, context);
+ expect(request.messages.filter((message) => message.role === "system")).toHaveLength(1);
+ expect(getCurrentSystemPrompt(request.messages)).toBe(getCurrentSystemPrompt(context.messages));
+ expect(clampOutputToContext(model, context, 8_192)).toBe(1);
+ expect(clampOutputToContext(model, request, 8_192)).toBe(8_192);
+ });
+
+ it("keeps every update for a model that receives them mid-conversation", () => {
+ const midConversation = { ...model, compat: { supportsMidConvoSystemMessages: true } };
+ const context = normalizeContext({ messages: updates(16) });
+ expect(requestTranscript(midConversation, context)).toBe(context);
+ expect(clampOutputToContext(midConversation, requestTranscript(midConversation, context), 8_192)).toBe(1);
+ });
+});
+
// Transcript-only Pi requests have no legacy systemPrompt/tools fields.
it("counts instruction sections and tool declarations in transcript-only requests", () => {
const base = { messages: [{ role: "system", content: "" }] };
diff --git a/packages/agent-runtime/src/output-cap.ts b/packages/agent-runtime/src/output-cap.ts
index 728d058580..c3fa25c6ac 100644
--- a/packages/agent-runtime/src/output-cap.ts
+++ b/packages/agent-runtime/src/output-cap.ts
@@ -22,9 +22,17 @@
* `web_search_call` from another model) no longer inflates the estimate while
* same-model search history keeps counting. A caller that has no target model
* passes none and keeps the conservative block-protocol estimate.
+ *
+ * Instruction history is charged the way the adapter sends it as well: see
+ * `requestTranscript`.
*/
-import type { Api } from "@earendil-works/pi-ai";
+import {
+ resolveTranscript,
+ type Api,
+ type Model,
+ type TranscriptContext,
+} from "@earendil-works/pi-ai";
import {
hostedSearchReplayProjection,
type HostedSearchReplayOptions,
@@ -251,6 +259,27 @@ export function estimateOutputCapInputTokens(
return baseline + Math.ceil(cjkChars * 0.75);
}
+/**
+ * The transcript the adapter puts on the wire. Unless the model declares
+ * mid-conversation system support, every adapter folds the later system
+ * messages into one leading message holding the current instructions and
+ * tools. Estimating the unfolded history charges each superseded instruction
+ * snapshot again: a long session with a large instruction section then
+ * starves the output budget to the provider's floor while the request itself
+ * is far from the window.
+ */
+export function requestTranscript(
+ model: Pick, "compat">,
+ context: TranscriptContext,
+): TranscriptContext {
+ const compat = model.compat;
+ const midConversation =
+ compat !== undefined &&
+ "supportsMidConvoSystemMessages" in compat &&
+ compat.supportsMidConvoSystemMessages === true;
+ return resolveTranscript(context, midConversation);
+}
+
/**
* Cap the effective output budget so `estimatedInput + output` stays inside
* the model's context window, regardless of which adapter branch the caller
diff --git a/packages/agent-runtime/src/runtime.ts b/packages/agent-runtime/src/runtime.ts
index 7249de1521..4affe7ed61 100644
--- a/packages/agent-runtime/src/runtime.ts
+++ b/packages/agent-runtime/src/runtime.ts
@@ -202,6 +202,7 @@ import {
clampOutputToContext,
effectiveModelContextWindow,
estimateOutputCapInputTokens,
+ requestTranscript,
} from "./output-cap.js";
import {
composeSubagentSystemPrompt,
@@ -2200,6 +2201,9 @@ Do not invent objections or turn speculative risks into blockers. Stop when the
// with pi's own run signal (Stop must keep working): the adapter refuses
// to start an attempt on an aborted signal, and its backoff sleep rejects.
const stallAbort = new AbortController();
+ // Both output clamps, ours and pi-ai's inside `streamSimple`, must see
+ // the instructions the adapter sends, not every superseded snapshot.
+ const requestContext = requestTranscript(m, context);
const attemptOptions: SimpleStreamOptions = {
...hookedOptions,
// Cap the output budget at the pi-desktop layer so the estimate
@@ -2207,7 +2211,7 @@ Do not invent objections or turn speculative risks into blockers. Stop when the
// max_tokens, but the low-level `stream` path used by
// `thinkingLevel: "omit"` would otherwise send it untouched, and
// both consume an estimate that under-counts CJK text (issue B).
- maxTokens: clampOutputToContext(m, context, hookedOptions.maxTokens),
+ maxTokens: clampOutputToContext(m, requestContext, hookedOptions.maxTokens),
signal: AbortSignal.any([
...(hookedOptions.signal ? [hookedOptions.signal] : []),
stallAbort.signal,
@@ -2216,12 +2220,12 @@ Do not invent objections or turn speculative risks into blockers. Stop when the
const usageTurnId = this.turnId;
const retryStream = createProviderRetryStream(
m,
- context,
+ requestContext,
attemptOptions,
(retryOptions) => accountModelStream(m, () =>
this.thinkingLevel === "omit"
- ? this.models.stream(omitThinkingModel(m), context, retryOptions)
- : this.models.streamSimple(m, context, retryOptions), {
+ ? this.models.stream(omitThinkingModel(m), requestContext, retryOptions)
+ : this.models.streamSimple(m, requestContext, retryOptions), {
providerId: this.provider.id,
nativeCost: this.provider.modelConfig?.nativeCost,
onUsage: (usage) => this.emit({ type: "usage", usage }, usageTurnId),
diff --git a/packages/agent-runtime/src/subagent-model-binding.ts b/packages/agent-runtime/src/subagent-model-binding.ts
index 183b30ada6..3a29555484 100644
--- a/packages/agent-runtime/src/subagent-model-binding.ts
+++ b/packages/agent-runtime/src/subagent-model-binding.ts
@@ -13,7 +13,7 @@ import {
} from "./opencode-session-headers.js";
import { withSessionAffinityOptions } from "./session-affinity.js";
import { mergeProviderHeaders, withProviderHeaders } from "./provider-headers.js";
-import { clampOutputToContext } from "./output-cap.js";
+import { clampOutputToContext, requestTranscript } from "./output-cap.js";
import {
agentThinkingLevel as agentThinkingLevelFor,
omitThinkingModel as withOmittedThinking,
@@ -65,6 +65,7 @@ export function subagentModelBinding(opts: {
retry.headers = undefined;
retry.status = undefined;
retry.failure = undefined;
+ const requestContext = requestTranscript(m, context);
const requestOptions = withProviderHeaders(
withOpenCodeSessionHeaders(
{
@@ -72,7 +73,7 @@ export function subagentModelBinding(opts: {
// Same request-side output cap as the parent runtime: the
// `omit` branch hits pi-ai's low-level `stream` which never
// re-derives max_tokens (issue B).
- maxTokens: clampOutputToContext(m, context, options?.maxTokens),
+ maxTokens: clampOutputToContext(m, requestContext, options?.maxTokens),
maxRetries: 0,
sessionId: opts.sessionId,
fetch: providerRequestFetch(
@@ -111,12 +112,12 @@ export function subagentModelBinding(opts: {
});
return createProviderRetryStream(
m,
- context,
+ requestContext,
sessionOptions,
(retryOptions) => accountModelStream(m, () =>
omitThinking
- ? models.stream(omitThinkingModel, context, retryOptions)
- : models.streamSimple(m, context, retryOptions), {
+ ? models.stream(omitThinkingModel, requestContext, retryOptions)
+ : models.streamSimple(m, requestContext, retryOptions), {
providerId: opts.provider.id,
nativeCost: opts.provider.modelConfig?.nativeCost,
onUsage: opts.onUsage,
diff --git a/packages/agent-runtime/src/subagent.test.ts b/packages/agent-runtime/src/subagent.test.ts
index fa4b4f8847..93da4371f5 100644
--- a/packages/agent-runtime/src/subagent.test.ts
+++ b/packages/agent-runtime/src/subagent.test.ts
@@ -147,7 +147,7 @@ describe("SubagentRun event forwarding", () => {
expect(run.agent.state.thinkingLevel).toBe("off");
expect(run.agent.streamFunction.toString()).toContain(
- "models.stream(omitThinkingModel, context, retryOptions)",
+ "models.stream(omitThinkingModel, requestContext, retryOptions)",
);
});
it("deduplicates repeated tool calls before a subagent request", () => {
From 6cae2dff41001e9e363729e948eec065dbf1a8cd Mon Sep 17 00:00:00 2001
From: v_wyxgwang
Date: Wed, 21 Oct 2026 17:55:57 +0800
Subject: [PATCH 13/44] feat(transcript): add display modes and thinking
shimmer
Add a persisted ranscriptDisplayMode setting with flat, command-first,
and fully-folded layouts. Fully-folded keeps the v0.20.0 command grouping,
command-first keeps run rows standalone, and flat removes nested activity
groups while preserving one outer process.
Make Thinking rows default expanded in flat and command-first, collapse to
a whole-run TextShimmer indicator, and use the same shimmer for the hidden
reasoning live indicator. Keep fully-folded's existing Thinking defaults.
Deprecate keepCommandsExpanded; it remains readable for compatibility.
Cover mode segmentation, settings normalization and sync, and renderer
wiring; update transcript and settings specs and ADRs.
---
.../electron/main/runtime/provider-catalog.ts | 17 ++
.../settings/KeepCommandsExpandedRow.tsx | 28 ---
.../settings/TranscriptDisplayModeRow.tsx | 55 ++++++
.../chat/transcript/ActivityGroup.tsx | 8 +
.../chat/transcript/ActivityItems.tsx | 6 +-
.../chat/transcript/AssistantTurn.tsx | 8 +-
.../features/chat/transcript/TextShimmer.tsx | 29 +++
.../src/features/chat/transcript/shared.tsx | 14 +-
.../src/features/settings/SettingsPage.tsx | 4 +-
apps/desktop/src/lib/api.ts | 17 ++
apps/desktop/src/lib/command-folding.ts | 19 --
apps/desktop/src/lib/settings-search.ts | 4 +-
.../src/lib/transcript-display-mode.ts | 29 +++
apps/desktop/src/lib/turn-process.ts | 55 +++---
apps/desktop/src/styles/messages.css | 57 ++++++
apps/desktop/test/settings-roundtrip.test.mjs | 37 ++++
apps/desktop/test/thinking-ui.test.mjs | 2 +-
...transcript-display-mode-settings.test.mjs} | 18 +-
.../test/transcript-display-mode.test.mjs | 44 +++++
.../test/transcript-display-modes-ui.test.mjs | 54 ++++++
apps/desktop/test/turn-process.test.mjs | 42 +++--
crates/host-core/src/config_sync/domains.rs | 12 +-
.../src/config_sync/engine_s3_tests.rs | 5 +
...9-calm-transcript-running-status-motion.md | 11 +-
docs/adr/turn-process-and-thinking-display.md | 164 ++++++++++-------
docs/spec/03-runtime/04-data-storage.md | 17 +-
docs/spec/04-ux/06-settings-ia.md | 45 +++--
docs/spec/04-ux/07-ui-design-system.md | 2 +-
docs/spec/04-ux/08-component-spec.md | 114 ++++++------
docs/spec/04-ux/09-interaction-patterns.md | 39 ++--
docs/spec/06-delivery/04-e2e-test-plan.md | 168 ++++++++++--------
docs/spec/08-meta/decisions-log.md | 43 +++--
.../adr/turn-process-and-thinking-display.md | 98 ++++++----
docs/zh-CN/spec/03-runtime/04-data-storage.md | 11 +-
docs/zh-CN/spec/04-ux/06-settings-ia.md | 21 ++-
docs/zh-CN/spec/04-ux/07-ui-design-system.md | 2 +-
docs/zh-CN/spec/04-ux/08-component-spec.md | 79 ++++----
.../spec/04-ux/09-interaction-patterns.md | 26 +--
.../spec/06-delivery/04-e2e-test-plan.md | 117 ++++++------
docs/zh-CN/spec/08-meta/decisions-log.md | 28 +--
packages/i18n/src/locales/de/index.ts | 5 +
packages/i18n/src/locales/en/index.ts | 5 +
packages/i18n/src/locales/es/index.ts | 5 +
packages/i18n/src/locales/fr/index.ts | 5 +
packages/i18n/src/locales/ko/index.ts | 5 +
packages/i18n/src/locales/pt-BR/index.ts | 5 +
packages/i18n/src/locales/tr/index.ts | 5 +
packages/i18n/src/locales/zh-CN/index.ts | 5 +
packages/i18n/src/locales/zh-TW/index.ts | 5 +
packages/shared/src/types/settings.ts | 20 ++-
scripts/e2e/transcript-render.tsx | 4 +-
scripts/e2e/turn-process.tsx | 42 +++--
52 files changed, 1121 insertions(+), 539 deletions(-)
delete mode 100644 apps/desktop/src/components/settings/KeepCommandsExpandedRow.tsx
create mode 100644 apps/desktop/src/components/settings/TranscriptDisplayModeRow.tsx
create mode 100644 apps/desktop/src/features/chat/transcript/TextShimmer.tsx
delete mode 100644 apps/desktop/src/lib/command-folding.ts
create mode 100644 apps/desktop/src/lib/transcript-display-mode.ts
rename apps/desktop/test/{command-folding-settings.test.mjs => transcript-display-mode-settings.test.mjs} (68%)
create mode 100644 apps/desktop/test/transcript-display-mode.test.mjs
create mode 100644 apps/desktop/test/transcript-display-modes-ui.test.mjs
diff --git a/apps/desktop/electron/main/runtime/provider-catalog.ts b/apps/desktop/electron/main/runtime/provider-catalog.ts
index 0c60524b59..51d51dc225 100644
--- a/apps/desktop/electron/main/runtime/provider-catalog.ts
+++ b/apps/desktop/electron/main/runtime/provider-catalog.ts
@@ -174,6 +174,12 @@ export function createProviderCatalogRuntime({
keepAwakeWhileRunning: (value as T & { keepAwakeWhileRunning?: unknown })
.keepAwakeWhileRunning === true,
jevEnabled: (value as T & { jevEnabled?: unknown }).jevEnabled === true,
+ transcriptDisplayMode:
+ (value as T & { transcriptDisplayMode?: unknown }).transcriptDisplayMode === "flat" ||
+ (value as T & { transcriptDisplayMode?: unknown }).transcriptDisplayMode === "command-first" ||
+ (value as T & { transcriptDisplayMode?: unknown }).transcriptDisplayMode === "fully-folded"
+ ? (value as T & { transcriptDisplayMode?: unknown }).transcriptDisplayMode
+ : "fully-folded",
defaultCommandShell: isCommandShellId(value.defaultCommandShell)
? value.defaultCommandShell
: defaultCommandShellForPlatform(process.platform),
@@ -193,6 +199,7 @@ export function createProviderCatalogRuntime({
lastNotifiedUpdateVersion?: unknown;
networkProxy?: unknown;
macosWindowTranslucency?: unknown;
+ transcriptDisplayMode?: unknown;
};
if (
Object.prototype.hasOwnProperty.call(value, "defaultCommandShell") &&
@@ -226,6 +233,16 @@ export function createProviderCatalogRuntime({
errorCode: ErrorCodes.INVALID_PARAMS,
});
}
+ if (
+ Object.prototype.hasOwnProperty.call(value, "transcriptDisplayMode") &&
+ value.transcriptDisplayMode !== "flat" &&
+ value.transcriptDisplayMode !== "command-first" &&
+ value.transcriptDisplayMode !== "fully-folded"
+ ) {
+ throw Object.assign(new Error("transcriptDisplayMode is invalid"), {
+ errorCode: ErrorCodes.INVALID_PARAMS,
+ });
+ }
if (
Object.prototype.hasOwnProperty.call(value, "macosWindowTranslucency") &&
typeof value.macosWindowTranslucency !== "boolean"
diff --git a/apps/desktop/src/components/settings/KeepCommandsExpandedRow.tsx b/apps/desktop/src/components/settings/KeepCommandsExpandedRow.tsx
deleted file mode 100644
index c32f47e61a..0000000000
--- a/apps/desktop/src/components/settings/KeepCommandsExpandedRow.tsx
+++ /dev/null
@@ -1,28 +0,0 @@
-import { useTranslation } from "react-i18next";
-import type { AppSettings } from "@pi-desktop/shared";
-import { resolveKeepCommandsExpanded } from "../../lib/command-folding";
-import { SettingsRow } from "../../features/settings/primitives";
-import { SettingsToggle } from "../ui";
-
-export function KeepCommandsExpandedRow({
- settings,
- saveSettings,
-}: {
- settings: AppSettings;
- saveSettings: (patch: Partial) => Promise;
-}) {
- const { t } = useTranslation();
- const expanded = resolveKeepCommandsExpanded(settings);
- return (
-
- void saveSettings({ keepCommandsExpanded: !expanded })}
- />
-
- );
-}
diff --git a/apps/desktop/src/components/settings/TranscriptDisplayModeRow.tsx b/apps/desktop/src/components/settings/TranscriptDisplayModeRow.tsx
new file mode 100644
index 0000000000..1479544591
--- /dev/null
+++ b/apps/desktop/src/components/settings/TranscriptDisplayModeRow.tsx
@@ -0,0 +1,55 @@
+import { useTranslation } from "react-i18next";
+import type { AppSettings } from "@pi-desktop/shared";
+import {
+ resolveTranscriptDisplayMode,
+ type TranscriptDisplayMode,
+} from "../../lib/transcript-display-mode";
+import { SettingsRow } from "../../features/settings/primitives";
+import { SegmentedControl } from "../ui";
+
+const MODE_OPTIONS = [
+ { value: "flat", labelKey: "settings.transcriptDisplayModeFlat" },
+ {
+ value: "command-first",
+ labelKey: "settings.transcriptDisplayModeCommandFirst",
+ },
+ {
+ value: "fully-folded",
+ labelKey: "settings.transcriptDisplayModeFullyFolded",
+ },
+] as const satisfies readonly {
+ value: TranscriptDisplayMode;
+ labelKey: string;
+}[];
+
+/**
+ * Transcript process layout (Settings → AI → Defaults). Persists
+ * `AppSettings.transcriptDisplayMode`; an absent or unknown value keeps the
+ * released `fully-folded` layout.
+ */
+export function TranscriptDisplayModeRow({
+ settings,
+ saveSettings,
+}: {
+ settings: AppSettings;
+ saveSettings: (patch: Partial) => Promise;
+}) {
+ const { t } = useTranslation();
+ const mode = resolveTranscriptDisplayMode(settings);
+ return (
+
+ void saveSettings({ transcriptDisplayMode: value })}
+ options={MODE_OPTIONS.map((option) => ({
+ value: option.value,
+ label: t(option.labelKey),
+ }))}
+ label={t("settings.transcriptDisplayMode")}
+ />
+
+ );
+}
diff --git a/apps/desktop/src/features/chat/transcript/ActivityGroup.tsx b/apps/desktop/src/features/chat/transcript/ActivityGroup.tsx
index b8c11ab636..48c4a65836 100644
--- a/apps/desktop/src/features/chat/transcript/ActivityGroup.tsx
+++ b/apps/desktop/src/features/chat/transcript/ActivityGroup.tsx
@@ -55,6 +55,7 @@ import {
import { TranscriptSearchContext } from "../../../lib/transcript-search-context";
import { useAppStore } from "../../../stores/app-store";
import { resolveShowThinking } from "../../../lib/thinking-visibility";
+import { resolveTranscriptDisplayMode } from "../../../lib/transcript-display-mode";
type Translate = (key: string, options?: Record) => string;
@@ -202,6 +203,8 @@ export const ActivityGroup = memo(function ActivityGroup({
}: ActivityGroupProps) {
const showThinking = useAppStore((state) => resolveShowThinking(state.settings));
const hideThinking = !showThinking;
+ const displayMode = useAppStore((state) => resolveTranscriptDisplayMode(state.settings));
+ const thinkingDefaultOpen = displayMode !== "fully-folded";
const { t } = useTranslation();
const detailsId = useId();
const rawDelegateItems = useMemo(() => items.filter(isDelegationActivityItem), [items]);
@@ -318,8 +321,13 @@ export const ActivityGroup = memo(function ActivityGroup({
delegationStatuses={delegationStatuses}
delegationTimings={delegationTimings}
onUserInteraction={claimDisclosure}
+ thinkingDefaultOpen={thinkingDefaultOpen}
/>;
+ // Flat mode has one outer process disclosure and no nested group at all.
+ // The rows themselves still keep their own tool/thinking disclosures.
+ if (displayMode === "flat") return <>{renderedItems}>;
+
if (!hasSubagentTopology) {
return (
diff --git a/apps/desktop/src/features/chat/transcript/ActivityItems.tsx b/apps/desktop/src/features/chat/transcript/ActivityItems.tsx
index 720fce5d57..72c9aa8e7f 100644
--- a/apps/desktop/src/features/chat/transcript/ActivityItems.tsx
+++ b/apps/desktop/src/features/chat/transcript/ActivityItems.tsx
@@ -22,6 +22,8 @@ type ActivityItemsProps = {
delegationStatuses: ReadonlyMap;
delegationTimings: ReadonlyMap;
onUserInteraction: () => void;
+ /** Flat and command-first expand every Thinking row by default. */
+ thinkingDefaultOpen?: boolean;
};
type ActivityItemBlockProps = Omit & {
@@ -36,6 +38,7 @@ type ActivityItemBlockProps = Omit{block.items.map((item) => {
// The topology predicate narrows to all tools, but a false result can still
@@ -71,7 +74,7 @@ const ActivityItemBlock = memo(function ActivityItemBlock({
key={`thinking-${item.message.id}`}
message={item.message}
streaming={isActive && item.message.status === "streaming"}
- autoOpen={live && item === lastItem}
+ autoOpen={thinkingDefaultOpen || (live && item === lastItem)}
onUserInteraction={onUserInteraction}
/>;
})}>;
@@ -95,6 +98,7 @@ export const ActivityItems = memo(function ActivityItems({ items, ...context }:
delegationStatuses={ownsTopology ? context.delegationStatuses : undefined}
delegationTimings={ownsTopology ? context.delegationTimings : undefined}
onUserInteraction={context.onUserInteraction}
+ thinkingDefaultOpen={context.thinkingDefaultOpen}
/>;
})}>;
});
diff --git a/apps/desktop/src/features/chat/transcript/AssistantTurn.tsx b/apps/desktop/src/features/chat/transcript/AssistantTurn.tsx
index 7e47519fe3..e12b8e1193 100644
--- a/apps/desktop/src/features/chat/transcript/AssistantTurn.tsx
+++ b/apps/desktop/src/features/chat/transcript/AssistantTurn.tsx
@@ -25,7 +25,7 @@ import {
} from "../../../lib/turn-process";
import { sessionAllows } from "../../../lib/remote-session-safety";
import { resolveShowThinking } from "../../../lib/thinking-visibility";
-import { resolveKeepCommandsExpanded } from "../../../lib/command-folding";
+import { resolveTranscriptDisplayMode } from "../../../lib/transcript-display-mode";
import { cachedVisibleProcessSteps } from "../../../lib/transcript-activity-summary";
import { useSlotSessionId } from "../../../plugins/renderer-slots/use-slots";
import { useAppStore } from "../../../stores/app-store";
@@ -355,10 +355,10 @@ export const AssistantTurn = memo(function AssistantTurn({
// by messages and compactions only, so a grouping decision made there would
// stay stale until new messages arrived. Segmenting here makes the preference
// apply on the next paint.
- const keepCommandsExpanded = useAppStore((state) => resolveKeepCommandsExpanded(state.settings));
+ const displayMode = useAppStore((state) => resolveTranscriptDisplayMode(state.settings));
const segments = useMemo(
- () => segmentTurnProcess(process, keepCommandsExpanded),
- [process, keepCommandsExpanded],
+ () => segmentTurnProcess(process, displayMode),
+ [process, displayMode],
);
// The one disclosure exists if it reveals anything at all. This uses the same
// helper the activity rows use: progress text counts, completed thinking is
diff --git a/apps/desktop/src/features/chat/transcript/TextShimmer.tsx b/apps/desktop/src/features/chat/transcript/TextShimmer.tsx
new file mode 100644
index 0000000000..4297ffcbf2
--- /dev/null
+++ b/apps/desktop/src/features/chat/transcript/TextShimmer.tsx
@@ -0,0 +1,29 @@
+import { memo } from "react";
+
+/**
+ * A whole-run text shimmer.
+ *
+ * The base layer stays in the layout while the shimmer layer sweeps a narrow
+ * gradient across the complete string. It is deliberately not a spinner and not
+ * a per-character animation: the same gradient crosses the whole label.
+ */
+export const TextShimmer = memo(function TextShimmer({
+ text,
+ active = true,
+ className,
+}: {
+ text: string;
+ active?: boolean;
+ className?: string;
+}) {
+ return (
+
+ {text}
+ {text}
+
+ );
+});
diff --git a/apps/desktop/src/features/chat/transcript/shared.tsx b/apps/desktop/src/features/chat/transcript/shared.tsx
index f79dbcc126..3a075dd8b6 100644
--- a/apps/desktop/src/features/chat/transcript/shared.tsx
+++ b/apps/desktop/src/features/chat/transcript/shared.tsx
@@ -61,6 +61,7 @@ import {
IconX,
} from "../../../components/icons";
import { TooltipButton } from "../../../components/ui";
+import { TextShimmer } from "./TextShimmer";
/**
* Legacy message navigation reveals the row it names, at message precision.
@@ -702,14 +703,13 @@ export const ThinkingRow = memo(function ThinkingRow({
-
- {t("chat.thinking", { defaultValue: "Thinking" })}
+
+
) : null;
}
const text = thinkingText(message);
- const summary = text.replace(/\s+/g, " ").trim();
return (
-
- {t("chat.thinking", { defaultValue: "Thinking" })}
+
+
- {summary}
diff --git a/apps/desktop/src/features/settings/SettingsPage.tsx b/apps/desktop/src/features/settings/SettingsPage.tsx
index 90c4537408..a2f8f3d94b 100644
--- a/apps/desktop/src/features/settings/SettingsPage.tsx
+++ b/apps/desktop/src/features/settings/SettingsPage.tsx
@@ -37,7 +37,7 @@ import { ModelConfigPage } from "../../components/settings/ModelConfigPage";
import { KeyboardShortcutsSection } from "../../components/settings/KeyboardShortcutsSection";
import { FontFamilyRow } from "../../components/settings/FontFamilyRow";
import { ShowThinkingRow } from "../../components/settings/ShowThinkingRow";
-import { KeepCommandsExpandedRow } from "../../components/settings/KeepCommandsExpandedRow";
+import { TranscriptDisplayModeRow } from "../../components/settings/TranscriptDisplayModeRow";
import { FontSizeRow } from "../../components/settings/FontSizeRow";
import { LanguageRow } from "../../components/settings/LanguageRow";
import { SettingsMenuSelect } from "../../components/settings/SettingsMenuSelect";
@@ -547,7 +547,7 @@ export function SettingsPage() {
-
+
;
+
+function isTranscriptDisplayModeValue(value: unknown): value is TranscriptDisplayMode {
+ return value === "flat" || value === "command-first" || value === "fully-folded";
+}
+
export function normalizeSettings(settings: AppSettings): AppSettings {
return {
...settings,
@@ -425,6 +431,9 @@ export function normalizeSettings(settings: AppSettings): AppSettings {
sidebarRunningBadge: settings.sidebarRunningBadge !== false,
sidebarRunningRail: settings.sidebarRunningRail === true,
keepCommandsExpanded: settings.keepCommandsExpanded !== false,
+ transcriptDisplayMode: isTranscriptDisplayModeValue(settings.transcriptDisplayMode)
+ ? settings.transcriptDisplayMode
+ : "fully-folded",
defaultMode: normalizeMode((settings as { defaultMode?: unknown }).defaultMode),
infiniteProviderRetry:
(settings as { infiniteProviderRetry?: unknown }).infiniteProviderRetry === true,
@@ -466,6 +475,14 @@ export function validateSettingsWrite(settings: AppSettings): AppSettings {
errorCode: "INVALID_PARAMS",
});
}
+ if (
+ Object.prototype.hasOwnProperty.call(settings, "transcriptDisplayMode") &&
+ !isTranscriptDisplayModeValue(settings.transcriptDisplayMode)
+ ) {
+ throw Object.assign(new Error("transcriptDisplayMode is invalid"), {
+ errorCode: "INVALID_PARAMS",
+ });
+ }
const value = settings as AppSettings & {
defaultCommandShell?: unknown;
largePasteThreshold?: unknown;
diff --git a/apps/desktop/src/lib/command-folding.ts b/apps/desktop/src/lib/command-folding.ts
deleted file mode 100644
index e64c681772..0000000000
--- a/apps/desktop/src/lib/command-folding.ts
+++ /dev/null
@@ -1,19 +0,0 @@
-import type { AppSettings } from "@pi-desktop/shared";
-
-/**
- * Resolve whether shell calls stay outside the tool groups they run among.
- *
- * `keepCommandsExpanded` is the preference; an absent value means `true`, so an
- * existing install keeps the scannable command rows it has today. This is a
- * presentation preference only: it never changes what a tool received, what it
- * returned, stored history, export, or the copy payload.
- *
- * It also never decides whether a turn renders a process disclosure. Both
- * values render exactly one, and only the placement of run rows inside it
- * changes.
- */
-export function resolveKeepCommandsExpanded(
- settings: Pick | null | undefined,
-): boolean {
- return settings?.keepCommandsExpanded !== false;
-}
diff --git a/apps/desktop/src/lib/settings-search.ts b/apps/desktop/src/lib/settings-search.ts
index 77c6b33196..7a1ea4531f 100644
--- a/apps/desktop/src/lib/settings-search.ts
+++ b/apps/desktop/src/lib/settings-search.ts
@@ -120,8 +120,8 @@ export const SETTINGS_NAV: SettingsNavEntry[] = [
"settings.smoothStreamingDesc",
"settings.showThinking",
"settings.showThinkingDesc",
- "settings.keepCommandsExpanded",
- "settings.keepCommandsExpandedDesc",
+ "settings.transcriptDisplayMode",
+ "settings.transcriptDisplayModeDesc",
"settings.contextUsageDisplay",
"settings.contextUsageDisplayRemaining",
"settings.contextUsageDisplayUsed",
diff --git a/apps/desktop/src/lib/transcript-display-mode.ts b/apps/desktop/src/lib/transcript-display-mode.ts
new file mode 100644
index 0000000000..437e49865b
--- /dev/null
+++ b/apps/desktop/src/lib/transcript-display-mode.ts
@@ -0,0 +1,29 @@
+import type { AppSettings, TranscriptDisplayMode } from "@pi-desktop/shared";
+
+export type { TranscriptDisplayMode };
+
+const MODES = new Set([
+ "flat",
+ "command-first",
+ "fully-folded",
+]);
+
+export function isTranscriptDisplayMode(
+ value: unknown,
+): value is TranscriptDisplayMode {
+ return typeof value === "string" && MODES.has(value as TranscriptDisplayMode);
+}
+
+/**
+ * Resolve the transcript process layout.
+ *
+ * The released layout keeps shell calls inside their surrounding activity
+ * group, so an absent or unknown value must fall back to `fully-folded`.
+ * `keepCommandsExpanded` is a deprecated compatibility field and is not read.
+ */
+export function resolveTranscriptDisplayMode(
+ settings: Pick | null | undefined,
+): TranscriptDisplayMode {
+ const value = settings?.transcriptDisplayMode;
+ return isTranscriptDisplayMode(value) ? value : "fully-folded";
+}
diff --git a/apps/desktop/src/lib/turn-process.ts b/apps/desktop/src/lib/turn-process.ts
index 1a87885ee6..aef11dc7f9 100644
--- a/apps/desktop/src/lib/turn-process.ts
+++ b/apps/desktop/src/lib/turn-process.ts
@@ -5,6 +5,7 @@ import type {
AssistantTurnPart,
} from "./assistant-turns";
import { isStandaloneRunActivity } from "./assistant-turns";
+import type { TranscriptDisplayMode } from "./transcript-display-mode";
import { isDelegationStartTool } from "./tool-display";
export function isThinkingActive(message: UiMessage, active: boolean): boolean {
@@ -133,48 +134,42 @@ function coalesceProcessActivityParts(
}
/**
- * Split one turn's process into the order it renders (ADR
- * turn-process-and-thinking-display).
+ * Split one turn's process into the order it renders.
*
- * With `keepCommandsExpanded` the `Bash` and run aliases are pulled out of the
- * process flow: each is its own `run` segment, rendered as a standalone row
- * beside the nested groups rather than inside one, and adjacent calls stay
- * separate. The remaining tools, thinking, hosted searches and progress text
- * keep their original order and are grouped into `process` chunks between the
- * run calls.
+ * `fully-folded` keeps the released v0.20.0 layout: contiguous activity parts
+ * are coalesced into one rendered group, including Bash/run rows, and progress
+ * text remains the only boundary. `flat` returns the original parts so the
+ * renderer can suppress activity-group wrappers while keeping every row in
+ * order. `command-first` pulls every Bash/run row out as its own segment and
+ * leaves the remaining activity in chronological process chunks.
*
- * Without it the run rows keep their place in the flow, so a command is just
- * another row of the group it ran among - the layout before commands were
- * separated at all. Because the entry builder keeps every run row in its own
- * activity part, folding coalesces contiguous ordinary parts into one rendered
- * group here, at render time. Progress messages remain paragraph boundaries and
- * a `Task`/delegation group never absorbs ordinary work around it. The
- * coalesced group is a new part whose end is the last source group's end; the
- * source parts and their items are not mutated.
- *
- * Either way the turn renders one top-level disclosure; only the placement of
- * run rows inside it changes. ON-mode segment parts are the same part objects
- * as the input, so downstream reveal and active-tail identity still hold.
+ * Every mode renders one top-level disclosure. Segment parts keep their source
+ * identity so reveal state and active-tail checks still work.
*/
export function segmentTurnProcess(
parts: readonly AssistantTurnPart[],
- keepCommandsExpanded: boolean,
+ mode: TranscriptDisplayMode,
): TurnProcessSegment[] {
- if (!keepCommandsExpanded) {
- const first = parts[0];
- if (!first) return [];
- const key =
- first.kind === "activity" ? first.items[0].message.id : first.message.id;
+ const first = parts[0];
+ if (!first) return [];
+ const key =
+ first.kind === "activity" ? first.items[0].message.id : first.message.id;
+ if (mode === "fully-folded") {
return [{ kind: "process", key, parts: coalesceProcessActivityParts(parts) }];
}
+ if (mode === "flat") {
+ // One outer process; the flat renderer suppresses every activity-group
+ // wrapper, so keep the original part order and message boundaries.
+ return [{ kind: "process", key, parts: [...parts] }];
+ }
const segments: TurnProcessSegment[] = [];
let pending: AssistantTurnPart[] = [];
const flushProcess = () => {
if (pending.length === 0) return;
- const first = pending[0];
- const key =
- first.kind === "activity" ? first.items[0].message.id : first.message.id;
- segments.push({ kind: "process", key, parts: pending });
+ const first2 = pending[0];
+ const key2 =
+ first2.kind === "activity" ? first2.items[0].message.id : first2.message.id;
+ segments.push({ kind: "process", key: key2, parts: pending });
pending = [];
};
for (const part of parts) {
diff --git a/apps/desktop/src/styles/messages.css b/apps/desktop/src/styles/messages.css
index 7e6ff2e2a8..1a504010a7 100644
--- a/apps/desktop/src/styles/messages.css
+++ b/apps/desktop/src/styles/messages.css
@@ -676,6 +676,63 @@
/* Running labels stay readable; the small marker carries the live feedback
so long tool names never flash between two text colours. */
.tool-activity-label.running,
+.text-shimmer {
+ display: inline-grid;
+ min-width: 0;
+ vertical-align: baseline;
+ white-space: nowrap;
+}
+.text-shimmer > span {
+ grid-area: 1 / 1;
+ white-space: pre;
+}
+.text-shimmer-base {
+ color: inherit;
+ opacity: 1;
+ transition: opacity 220ms ease-out;
+}
+.text-shimmer-peak {
+ color: transparent;
+ background-image:
+ linear-gradient(
+ 90deg,
+ transparent calc(50% - 5.2ch),
+ var(--ds-text-primary) 50%,
+ transparent calc(50% + 5.2ch)
+ ),
+ linear-gradient(var(--ds-text-secondary), var(--ds-text-secondary));
+ background-size: 360% 100%, 100% 100%;
+ background-position: 100% 0, 0 0;
+ background-repeat: no-repeat;
+ -webkit-background-clip: text;
+ background-clip: text;
+ -webkit-text-fill-color: transparent;
+ animation: text-shimmer-sweep 1.2s linear infinite;
+ opacity: 1;
+ transition: opacity 220ms ease-out;
+ will-change: background-position;
+}
+.text-shimmer[data-active="true"] .text-shimmer-base {
+ opacity: 0;
+}
+.text-shimmer[data-active="false"] .text-shimmer-peak {
+ animation: none;
+ opacity: 0;
+}
+@keyframes text-shimmer-sweep {
+ from { background-position: 100% 0, 0 0; }
+ to { background-position: 0 0, 0 0; }
+}
+@media (prefers-reduced-motion: reduce) {
+ .text-shimmer-peak {
+ animation: none !important;
+ opacity: 0 !important;
+ }
+ .text-shimmer-base {
+ opacity: 1 !important;
+ }
+}
+
.tool-row-name.running {
color: var(--ds-text-secondary);
}
diff --git a/apps/desktop/test/settings-roundtrip.test.mjs b/apps/desktop/test/settings-roundtrip.test.mjs
index b1e901f456..5db8556fca 100644
--- a/apps/desktop/test/settings-roundtrip.test.mjs
+++ b/apps/desktop/test/settings-roundtrip.test.mjs
@@ -91,6 +91,43 @@ test("command folding defaults on and rejects non-boolean writes before IPC", ()
}
});
+test("transcript display mode defaults to fully folded and validates its three values", () => {
+ const previousWindow = globalThis.window;
+ globalThis.window = { piDesktop: { platform: "win32" } };
+ try {
+ const base = { defaultMode: "agent", theme: "light", enterToSend: true };
+ assert.equal(renderer.normalizeSettings(base).transcriptDisplayMode, "fully-folded");
+ assert.equal(main.normalizeSettings(base).transcriptDisplayMode, "fully-folded");
+ for (const mode of ["flat", "command-first", "fully-folded"]) {
+ assert.equal(
+ renderer.normalizeSettings({ ...base, transcriptDisplayMode: mode }).transcriptDisplayMode,
+ mode,
+ );
+ assert.equal(
+ main.normalizeSettings({ ...base, transcriptDisplayMode: mode }).transcriptDisplayMode,
+ mode,
+ );
+ assert.equal(
+ renderer.validateSettingsWrite({ ...base, transcriptDisplayMode: mode }).transcriptDisplayMode,
+ mode,
+ );
+ }
+ for (const value of ["yes", 0, null, undefined, {}]) {
+ assert.throws(
+ () => renderer.validateSettingsWrite({ transcriptDisplayMode: value }),
+ /transcriptDisplayMode is invalid/,
+ );
+ assert.throws(
+ () => main.validateSettingsWrite({ transcriptDisplayMode: value }),
+ /transcriptDisplayMode is invalid/,
+ );
+ }
+ } finally {
+ if (previousWindow === undefined) delete globalThis.window;
+ else globalThis.window = previousWindow;
+ }
+});
+
test("settings write round-trips command folding through the preload boundary", async () => {
const previousWindow = globalThis.window;
const calls = [];
diff --git a/apps/desktop/test/thinking-ui.test.mjs b/apps/desktop/test/thinking-ui.test.mjs
index 04dfcbfb99..a0773f7afd 100644
--- a/apps/desktop/test/thinking-ui.test.mjs
+++ b/apps/desktop/test/thinking-ui.test.mjs
@@ -281,7 +281,7 @@ test("tool and search rows stay collapsed while thinking keeps its leaf default"
assert.match(transcriptSource, /useAutomaticDisclosure\(\s*hasSubagentTopology \? live : visibleItems\.length <= 1/);
assert.match(
transcriptSource,
- / copy[key] ?? key;
-test("command folding is searchable from the AI preferences beside show thinking", () => {
+test("transcript display mode is searchable from the AI preferences beside show thinking", () => {
const ai = SETTINGS_NAV.find((entry) => entry.id === "ai");
assert.ok(ai, "AI settings entry is registered");
const showThinkingAt = ai.keywordKeys.indexOf("settings.showThinking");
@@ -27,28 +27,28 @@ test("command folding is searchable from the AI preferences beside show thinking
[
"settings.showThinking",
"settings.showThinkingDesc",
- "settings.keepCommandsExpanded",
- "settings.keepCommandsExpandedDesc",
+ "settings.transcriptDisplayMode",
+ "settings.transcriptDisplayModeDesc",
],
);
- const titleHits = searchSettings("collapse commands", t, {
+ const titleHits = searchSettings("transcript display", t, {
developerMode: false,
includeDevelopmentOnly: false,
}).filter((hit) => hit.tab === "ai");
assert.ok(
- titleHits.some((hit) => hit.rowKey === "settings.keepCommandsExpanded"),
- "the command-folding title is searchable",
+ titleHits.some((hit) => hit.rowKey === "settings.transcriptDisplayMode"),
+ "the transcript-display title is searchable",
);
- const descriptionHits = searchSettings("shell calls", t, {
+ const descriptionHits = searchSettings("assistant process", t, {
developerMode: false,
includeDevelopmentOnly: false,
}).filter((hit) => hit.tab === "ai");
assert.ok(
descriptionHits.some(
- (hit) => hit.rowKey === "settings.keepCommandsExpandedDesc",
+ (hit) => hit.rowKey === "settings.transcriptDisplayModeDesc",
),
- "the command-folding description is searchable",
+ "the transcript-display description is searchable",
);
});
diff --git a/apps/desktop/test/transcript-display-mode.test.mjs b/apps/desktop/test/transcript-display-mode.test.mjs
new file mode 100644
index 0000000000..062920153b
--- /dev/null
+++ b/apps/desktop/test/transcript-display-mode.test.mjs
@@ -0,0 +1,44 @@
+import assert from "node:assert/strict";
+import { register } from "node:module";
+import test from "node:test";
+register(new URL("./helpers/ts-import-hooks.mjs", import.meta.url));
+const {
+ isTranscriptDisplayMode,
+ resolveTranscriptDisplayMode,
+} = await import("../src/lib/transcript-display-mode.ts");
+
+test("transcript display mode defaults to the released fully-folded layout", () => {
+ assert.equal(resolveTranscriptDisplayMode(undefined), "fully-folded");
+ assert.equal(resolveTranscriptDisplayMode({}), "fully-folded");
+ assert.equal(
+ resolveTranscriptDisplayMode({ transcriptDisplayMode: "unknown" }),
+ "fully-folded",
+ );
+ assert.equal(
+ resolveTranscriptDisplayMode({ transcriptDisplayMode: "flat" }),
+ "flat",
+ );
+ assert.equal(
+ resolveTranscriptDisplayMode({ transcriptDisplayMode: "command-first" }),
+ "command-first",
+ );
+ assert.equal(
+ resolveTranscriptDisplayMode({ transcriptDisplayMode: "fully-folded" }),
+ "fully-folded",
+ );
+});
+
+test("the deprecated command-folding preference cannot select a mode", () => {
+ assert.equal(
+ resolveTranscriptDisplayMode({ keepCommandsExpanded: true }),
+ "fully-folded",
+ );
+ assert.equal(
+ resolveTranscriptDisplayMode({ keepCommandsExpanded: false }),
+ "fully-folded",
+ );
+ assert.equal(isTranscriptDisplayMode("flat"), true);
+ assert.equal(isTranscriptDisplayMode("command-first"), true);
+ assert.equal(isTranscriptDisplayMode("fully-folded"), true);
+ assert.equal(isTranscriptDisplayMode("compact"), false);
+});
diff --git a/apps/desktop/test/transcript-display-modes-ui.test.mjs b/apps/desktop/test/transcript-display-modes-ui.test.mjs
new file mode 100644
index 0000000000..8bd6146321
--- /dev/null
+++ b/apps/desktop/test/transcript-display-modes-ui.test.mjs
@@ -0,0 +1,54 @@
+import { readTranscriptModule } from "./helpers/source-contracts.mjs";
+import assert from "node:assert/strict";
+import { readFile } from "node:fs/promises";
+import test from "node:test";
+import { loadStyles } from "./helpers/styles.mjs";
+
+const activityGroupSource = await readTranscriptModule("ActivityGroup.tsx");
+const activityItemsSource = await readTranscriptModule("ActivityItems.tsx");
+const assistantTurnSource = await readTranscriptModule("AssistantTurn.tsx");
+const thinkingRowSource = await readTranscriptModule("shared.tsx");
+const shimmerSource = await readFile(
+ new URL("../src/features/chat/transcript/TextShimmer.tsx", import.meta.url),
+ "utf8",
+);
+const turnProcessSource = await readFile(
+ new URL("../src/lib/turn-process.ts", import.meta.url),
+ "utf8",
+);
+const stylesSource = await loadStyles();
+
+test("flat mode renders one outer process and no activity-group wrapper", () => {
+ assert.match(assistantTurnSource, /resolveTranscriptDisplayMode/);
+ assert.match(assistantTurnSource, /segmentTurnProcess\(process, displayMode\)/);
+ assert.match(activityGroupSource, /displayMode === "flat"/);
+ assert.match(activityGroupSource, /return <>\{renderedItems\}<\/>/);
+ assert.match(turnProcessSource, /mode === "flat"/);
+ assert.match(turnProcessSource, /parts: \[\.\.\.parts\]/);
+});
+
+test("command-first and fully-folded use distinct process segmentation", () => {
+ assert.match(turnProcessSource, /mode === "fully-folded"/);
+ assert.match(turnProcessSource, /coalesceProcessActivityParts\(parts\)/);
+ assert.match(turnProcessSource, /isStandaloneRunActivity\(item\)/);
+});
+
+test("thinking expands by default outside fully-folded mode", () => {
+ assert.match(activityGroupSource, /displayMode !== "fully-folded"/);
+ assert.match(activityGroupSource, /thinkingDefaultOpen=\{thinkingDefaultOpen\}/);
+ assert.match(activityItemsSource, /autoOpen=\{thinkingDefaultOpen \|\| \(live && item === lastItem\)\}/);
+});
+
+test("thinking collapsed state uses the whole-run TextShimmer, not a spinner", () => {
+ assert.match(thinkingRowSource, /import \{ TextShimmer \} from "\.\/TextShimmer"/);
+ assert.match(thinkingRowSource, /active=\{streaming && !open\}/);
+ assert.match(thinkingRowSource, /thinking-compact[\s\S]*? segment.kind),
["process", "run", "process"],
@@ -177,7 +177,7 @@ test("a Bash-only turn has no process segment at all", () => {
tool("bash1", "Bash", { toolArgs: { command: "a" } }),
tool("bash2", "Bash", { toolArgs: { command: "b" } }),
]);
- const segments = segmentTurnProcess(projectTurnProcess(entry).process, true);
+ const segments = segmentTurnProcess(projectTurnProcess(entry).process, "command-first");
assert.deepEqual(
segments.map((segment) => segment.kind),
["run", "run"],
@@ -190,7 +190,7 @@ test("a turn without Bash keeps one process segment", () => {
tool("read", "Read", { toolResult: "a" }),
tool("grep", "Grep", { toolResult: "b" }),
]);
- const segments = segmentTurnProcess(projectTurnProcess(entry).process, true);
+ const segments = segmentTurnProcess(projectTurnProcess(entry).process, "command-first");
assert.deepEqual(
segments.map((segment) => segment.kind),
["process"],
@@ -284,7 +284,7 @@ test("folding commands coalesces mixed work across run rows without mutating ent
Object.freeze(part);
}
Object.freeze(process);
- const [segment] = segmentTurnProcess(process, false);
+ const [segment] = segmentTurnProcess(process, "fully-folded");
assert.equal(segment.kind, "process");
// Progress text stays a paragraph boundary, so the run joins the group before
// it rather than the one after it.
@@ -313,12 +313,12 @@ test("folding commands coalesces mixed work across run rows without mutating ent
);
// ON is unchanged: the original chunks are still separate and the run row is
// still a standalone segment with its original item identity.
- const on = segmentTurnProcess(process, true);
+ const on = segmentTurnProcess(process, "command-first");
assert.deepEqual(on.map((part) => part.kind), ["process", "run", "process"]);
assert.equal(on[0].parts[0], process[0]);
assert.equal(on[0].parts[1], process[1]);
assert.equal(on[1].item, sourceActivities[1].items[0]);
- const again = segmentTurnProcess(process, true);
+ const again = segmentTurnProcess(process, "command-first");
assert.deepEqual(again.map((part) => part.kind), on.map((part) => part.kind));
assert.equal(again[0].parts[0], process[0]);
});
@@ -339,7 +339,7 @@ test("folding commands keeps Task topology and progress text as group boundaries
]);
const [segment] = segmentTurnProcess(
projectTurnProcess(entry).process,
- false,
+ "fully-folded",
);
const activityIds = segment.parts.flatMap((part) =>
part.kind === "activity"
@@ -359,6 +359,26 @@ test("folding commands keeps Task topology and progress text as group boundaries
assert.equal(task.items[0].delegate.items[0].message.id, "nested");
});
+test("flat keeps the original part order and never extracts a run", () => {
+ const entry = turn([
+ message("user", "user", "Run"),
+ tool("read", "Read", { toolResult: "a" }),
+ tool("bash", "Bash", { toolArgs: { command: "pnpm test" } }),
+ message("progress", "assistant", "Progress"),
+ tool("edit", "Edit", { toolResult: "b" }),
+ ]);
+ const process = projectTurnProcess(entry).process;
+ const [segment] = segmentTurnProcess(process, "flat");
+ assert.equal(segment.kind, "process");
+ assert.equal(segment.parts.length, process.length);
+ assert.ok(segment.parts.every((part, index) => part === process[index]));
+ assert.deepEqual(
+ segment.parts.map((part) => part.kind),
+ ["activity", "activity", "message", "activity"],
+ );
+ assert.equal(segment.parts[1].items[0].message.id, "bash");
+});
+
test("a Bash-only turn keeps one segment whether commands are expanded or not", () => {
const entry = turn([
message("user", "user", "Run"),
@@ -366,13 +386,13 @@ test("a Bash-only turn keeps one segment whether commands are expanded or not",
tool("bash2", "Bash", { toolArgs: { command: "b" } }),
]);
const process = projectTurnProcess(entry).process;
- assert.deepEqual(segmentTurnProcess(process, true).map((s) => s.kind), ["run", "run"]);
- assert.deepEqual(segmentTurnProcess(process, false).map((s) => s.kind), ["process"]);
+ assert.deepEqual(segmentTurnProcess(process, "command-first").map((s) => s.kind), ["run", "run"]);
+ assert.deepEqual(segmentTurnProcess(process, "fully-folded").map((s) => s.kind), ["process"]);
});
test("an empty process segments to nothing in either mode", () => {
- assert.deepEqual(segmentTurnProcess([], false), []);
- assert.deepEqual(segmentTurnProcess([], true), []);
+ assert.deepEqual(segmentTurnProcess([], "fully-folded"), []);
+ assert.deepEqual(segmentTurnProcess([], "command-first"), []);
});
test("the turn header reports failure, stop, live and completion in that order", () => {
diff --git a/crates/host-core/src/config_sync/domains.rs b/crates/host-core/src/config_sync/domains.rs
index 076441beed..7c5d09df6c 100644
--- a/crates/host-core/src/config_sync/domains.rs
+++ b/crates/host-core/src/config_sync/domains.rs
@@ -35,6 +35,7 @@ pub(crate) const PORTABLE_APPLICATION_FIELDS: &[&str] = &[
"fontScale",
"showThinking",
"thinkingDisplayMode",
+ "transcriptDisplayMode",
"keepCommandsExpanded",
"enterToSend",
"largePasteThreshold",
@@ -101,6 +102,7 @@ pub const DOMAIN_ADAPTERS: &[DomainAdapterSpec] = &[
"fontScale",
"showThinking",
"thinkingDisplayMode",
+ "transcriptDisplayMode",
"enterToSend",
"keepCommandsExpanded",
"keybindings",
@@ -628,14 +630,18 @@ mod tests {
fn adapter_registry_covers_every_portable_domain() {
assert_eq!(DOMAIN_ADAPTERS.len(), ALL_DOMAINS.len());
assert!(!PORTABLE_APPLICATION_FIELDS.contains(&"defaultPermissionMode"));
- // The explicit reasoning-display boolean, its legacy fallback, and the
- // command-folding preference are portable, and each is advertised by the
- // application adapter.
+ // The reasoning-display boolean, its legacy fallback, the transcript
+ // display mode and the deprecated command-folding preference are portable,
+ // and each is advertised by the application adapter.
assert!(PORTABLE_APPLICATION_FIELDS.contains(&"showThinking"));
+ assert!(PORTABLE_APPLICATION_FIELDS.contains(&"transcriptDisplayMode"));
assert!(PORTABLE_APPLICATION_FIELDS.contains(&"thinkingDisplayMode"));
assert!(PORTABLE_APPLICATION_FIELDS.contains(&"keepCommandsExpanded"));
let application = adapter_for(DOMAIN_APPLICATION).expect("application adapter");
assert!(application.exportable_fields.contains(&"showThinking"));
+ assert!(application
+ .exportable_fields
+ .contains(&"transcriptDisplayMode"));
assert!(application
.exportable_fields
.contains(&"thinkingDisplayMode"));
diff --git a/crates/host-core/src/config_sync/engine_s3_tests.rs b/crates/host-core/src/config_sync/engine_s3_tests.rs
index b5ad1b5393..b158dbe25c 100644
--- a/crates/host-core/src/config_sync/engine_s3_tests.rs
+++ b/crates/host-core/src/config_sync/engine_s3_tests.rs
@@ -130,6 +130,7 @@ async fn application_show_thinking_roundtrips_and_keeps_local_only_settings() ->
"theme": "light",
"showThinking": false,
"thinkingDisplayMode": "detailed",
+ "transcriptDisplayMode": "command-first",
"keepCommandsExpanded": false,
"defaultPermissionMode": "accept-edits",
}),
@@ -144,6 +145,7 @@ async fn application_show_thinking_roundtrips_and_keeps_local_only_settings() ->
assert_eq!(settings["theme"], "light");
// A false boolean survives capture and apply instead of reading as absent.
assert_eq!(settings["showThinking"], false);
+ assert_eq!(settings["transcriptDisplayMode"], "command-first");
assert_eq!(settings["keepCommandsExpanded"], false);
// The legacy field is still exported so older readers keep working.
assert_eq!(settings["thinkingDisplayMode"], "detailed");
@@ -157,6 +159,7 @@ async fn application_show_thinking_roundtrips_and_keeps_local_only_settings() ->
"theme": "light",
"showThinking": false,
"thinkingDisplayMode": "detailed",
+ "transcriptDisplayMode": "command-first",
"keepCommandsExpanded": false,
"defaultPermissionMode": "ask",
}),
@@ -168,6 +171,7 @@ async fn application_show_thinking_roundtrips_and_keeps_local_only_settings() ->
"theme": "light",
"showThinking": true,
"thinkingDisplayMode": "detailed",
+ "transcriptDisplayMode": "flat",
"keepCommandsExpanded": true,
"defaultPermissionMode": "accept-edits",
}),
@@ -178,6 +182,7 @@ async fn application_show_thinking_roundtrips_and_keeps_local_only_settings() ->
let settings = app_settings(&state)?;
assert_eq!(settings["showThinking"], true);
assert_eq!(settings["thinkingDisplayMode"], "detailed");
+ assert_eq!(settings["transcriptDisplayMode"], "flat");
assert_eq!(settings["keepCommandsExpanded"], true);
assert_eq!(settings["defaultPermissionMode"], "ask");
Ok(())
diff --git a/docs/adr/0149-calm-transcript-running-status-motion.md b/docs/adr/0149-calm-transcript-running-status-motion.md
index 07ec1f8478..de5d428ac0 100644
--- a/docs/adr/0149-calm-transcript-running-status-motion.md
+++ b/docs/adr/0149-calm-transcript-running-status-motion.md
@@ -2,6 +2,7 @@
- Status: Accepted
- Date: 2026-09-04
+- Amended: 2026-10-21
- Deciders: PI-Desktop core
- Related: D071, D290, E2E-053, E2E-083
@@ -23,9 +24,13 @@ status marker with a one-second opacity pulse instead of a text shimmer. Tool
spinners, run-row status dots, and the assistant streaming rail keep their
existing state feedback.
-All new marker motion is disabled under `prefers-reduced-motion: reduce`; the
-text and static marker remain visible so state is never conveyed by motion
-alone. No protocol, persistence, runtime, or localization contract changes.
+The Thinking indicator is the explicit exception: the collapsed/live Thinking
+label uses a whole-run `TextShimmer` with a 1.2s sweep and 220ms fade, defined by
+`turn-process-and-thinking-display` (2026-10-21). It does not move the highlight
+glyph by glyph. All marker and shimmer motion is disabled under
+`prefers-reduced-motion: reduce`; the text and static marker remain visible so
+state is never conveyed by motion alone. No protocol, persistence, runtime, or
+localization contract changes.
## Consequences
diff --git a/docs/adr/turn-process-and-thinking-display.md b/docs/adr/turn-process-and-thinking-display.md
index 09613bb796..01a8a399f4 100644
--- a/docs/adr/turn-process-and-thinking-display.md
+++ b/docs/adr/turn-process-and-thinking-display.md
@@ -30,29 +30,45 @@ boundaries.
One turn renders exactly one process disclosure. Every row the turn produced
before its answer lives inside it — the activity groups and the `Bash` run rows
alike — so a long turn collapses in one gesture instead of leaving a column of
-sibling disclosures above the answer. The answer itself stays outside it.
-
-Inside that disclosure, non-Bash activity forms ordinary activity groups: one
-contiguous tool/search/thinking segment between progress paragraphs or run rows,
-appearing only when at least two items are visible under the current thinking
-preference. A singleton uses its item disclosure directly; hidden thinking does
-not create a redundant wrapper. Existing Task topology remains its segment's
-container and is not duplicated inside an ordinary activity group.
-
-Whether a run row sits *inside* its group or *beside* it is the
-`keepCommandsExpanded` preference, which defaults to on. When on, `Bash` and run
-aliases are lifted out of the groups they ran among: each becomes its own row at
-the disclosure's top level, adjacent calls stay separate, and the row's detail
-stays closed until the user opens it. When off, a run row keeps its place in the
-flow, so a command reads as another line of the group around it — the layout
-before commands were separated. The preference never changes how many
-disclosures a turn renders: both values render exactly one.
-
-Group folding defaults are unified and do not depend on either preference. The
-ordinary activity group that owns the active execution segment starts open, then
-closes on completion only while untouched. Other completed groups start closed.
-An untouched active group containing any recorded failed or denied tool stays
-open through later recovery and closes on turn completion if still untouched.
+sibling disclosures above the answer. The answer itself stays outside it. An
+untouched process closes when the turn completes, so only the final answer
+remains; when the turn produced no final text, the process header and its error
+or pending-action surfaces remain visible.
+
+Inside that disclosure, the display mode decides how activity is grouped.
+`AppSettings.transcriptDisplayMode` is one of `flat`, `command-first`, or
+`fully-folded`; an absent or unknown value resolves to `fully-folded`, the
+layout released in v0.20.0. Every mode renders exactly one outer disclosure.
+
+- In `fully-folded`, contiguous activity forms ordinary activity groups: one
+ contiguous tool/search/thinking/Bash segment between ordinary assistant
+ progress paragraphs. A `Bash`/run row stays inside the group around it, so a
+ command reads as another line of that group. Existing Task topology remains
+ its segment's container and is not duplicated inside an ordinary activity
+ group.
+- In `command-first`, ordinary activity groups still render, but every
+ `Bash`/run alias is lifted out as a standalone row beside them: adjacent calls
+ stay separate and a row's detail stays closed until the user opens it. A
+ normal assistant progress message and a command both end the current group.
+- In `flat`, no nested activity groups render at all. The outer disclosure lists
+ active tools, commands, thinking and progress rows in transcript order, with
+ tool details collapsed.
+
+In `command-first` and `fully-folded`, a group appears only when at least two
+items are visible under the current thinking preference. A singleton uses its
+item disclosure directly, and hidden thinking does not create a redundant
+wrapper.
+
+`keepCommandsExpanded` is deprecated. It is retained only so persisted settings
+still load, is no longer exposed in Settings, and is not read for rendering; new
+writes store `transcriptDisplayMode`.
+
+Group folding defaults are unified across modes and do not depend on the
+thinking preference. Where a group renders, the group that owns the active
+execution segment starts open, then closes on completion only while untouched.
+Other completed groups start closed. An untouched active group containing any
+recorded failed or denied tool stays open through later recovery and closes on
+turn completion if still untouched.
The turn's disclosure header states the turn's outcome and never echoes the item
it is working on, because a shell command or search query can be arbitrarily
@@ -71,18 +87,25 @@ The disclosure and the levels it reveals share one left edge. Hierarchy is
carried by type size and colour, not by indentation, so a nested group header and
a run row start exactly where the turn header does.
-The thinking preference is a boolean `showThinking`. When it is false, the live
-thinking indicator stays visible, while completed thinking rows and excerpts are
-hidden and empty thinking-only containers are omitted; the stored reasoning is
-retained, so turning the preference back on restores the completed rows and
-excerpts. Hidden thinking never creates an empty group wrapper.
+The thinking preference is a boolean `showThinking`. With it on, `flat` and
+`command-first` expand every Thinking row by default and let the user collapse
+them; an expanded row shows the full reasoning markdown, while a collapsed row
+shows only the Thinking indicator with no summary or excerpt. `fully-folded`
+keeps the released exception: earlier Thinking rows stay collapsed, and the last
+active Thinking row opens only while it is the live step, so completed rows
+collapse. With the preference off, no completed reasoning row renders; only a
+live whole-run `TextShimmer` `Thinking` indicator remains while reasoning is
+actively streaming. The shimmer is a 1.2s linear sweep with a 220ms fade — no
+spinner, pulsing dot, or per-character animation — and stays static under
+reduced motion. The stored reasoning is retained, so turning the preference back
+on restores the rows. Hidden thinking never creates an empty group wrapper.
The leaf default that an earlier decision first introduced was later removed.
-Item payloads never open themselves: a tool-call, hosted-search or plan row
-stays a header row until the user opens it, wherever it sits in the group, and
-this holds regardless of the thinking preference. Group defaults are unchanged,
-and opening a closed ancestor still exposes the retained item choices without
-opening all descendants.
+Except for the display-mode Thinking defaults above, item payloads never open
+themselves: a tool-call, hosted-search or plan row stays a header row until the
+user opens it, wherever it sits in the group, and this holds regardless of the
+thinking preference. Group defaults are unchanged, and opening a closed ancestor
+still exposes the retained item choices without opening all descendants.
Each header toggles only its own level. Parent and child states are independent:
closing a parent preserves descendant choices, reopening restores them, and
@@ -95,8 +118,9 @@ Pane eviction, session deletion, or renderer restart releases this presentation
memory; it is not stored in messages or host settings.
Search/navigation reveals the ancestor path its target needs: the turn process
-and the activity group that own the named message. Item-level targeting is not
-part of this change, so each row's own details stay behind its own disclosure.
+and, where one exists, the activity group that own the named message. Item-level
+targeting is not part of this change, so each row's own details stay behind its
+own disclosure.
Replaying the same request does not repeatedly override a later manual close.
Reasoning hidden by the preference stays hidden until the user turns
`showThinking` on. Assistant errors, stopped trailing partial answers,
@@ -104,34 +128,45 @@ permission/question/plan/goal decisions, and any other pending action surface
remain outside hidden process content and reachable without expanding it.
Settings → AI → Defaults exposes a `Show thinking` boolean that persists as the
-optional `showThinking` `AppSettings` field. Absent and non-boolean values fall
-back to the legacy `thinkingDisplayMode` field: an explicit `compact` hides
-reasoning while `detailed`, an unknown value, or an absent field shows it. The
-legacy field is retained for persisted-settings compatibility and is no longer
-exposed in the UI. The preference changes presentation only; it does not alter
-provider thinking levels, runtime/model context, stored reasoning, export,
-permissions, execution, or copy payloads, and it does not control turn-process
-or activity-group folding. Process headers use recorded timing, direct tool/search
-counts, running state, and issue counts; they do not double-count delegated child
-work or treat a failed child as a failed assistant turn.
+optional `showThinking` `AppSettings` field, and a `Transcript display`
+segmented control with the labels `Flat`, `Commands first`, and `Fully folded`
+that persists the optional `transcriptDisplayMode` field. Absent and invalid
+`transcriptDisplayMode` values resolve to `fully-folded` in both the renderer and
+main-process settings normalizers. Absent and non-boolean values for
+`showThinking` fall back to the legacy `thinkingDisplayMode` field: an explicit
+`compact` hides reasoning while `detailed`, an unknown value, or an absent field
+shows it. The legacy `thinkingDisplayMode` and deprecated
+`keepCommandsExpanded` fields are retained for persisted-settings compatibility
+and are no longer exposed in the UI. `keepCommandsExpanded` is also no longer
+read for rendering. These preferences change presentation only; they do not
+alter provider thinking levels, runtime/model context, stored reasoning, export,
+permissions, execution, or copy payloads, and the thinking preference does not
+control turn-process or activity-group folding. Process headers use recorded
+timing, direct tool/search counts, running state, and issue counts; they do not
+double-count delegated child work or treat a failed child as a failed assistant
+turn.
## Consequences
- One disclosure per turn keeps the final answer and actionable interruptions
reachable, and makes a long turn collapsible in a single gesture.
-- Group folding defaults are unified: active work stays visible, untouched
- completed groups fold by default, and explicit disclosure choices are preserved
- regardless of the thinking preference. Closing the turn's disclosure closes the
- groups under it, and reopening restores the groups the user had opened.
-- When `showThinking` is false, the live indicator stays visible while completed
- reasoning rows and excerpts are hidden. The stored reasoning is retained and
- reappears when the preference is turned back on.
-- With `keepCommandsExpanded` on (the default), run aliases render as their own
- rows so shell-heavy turns stay scannable; turning it off restores the older
- layout where a command reads as another line of its group. Neither value
- changes the number of disclosures, and because the preference is read while
- rendering rather than while building entries, toggling it repaints the
- transcript immediately instead of waiting for new messages.
+- Group folding defaults are unified across display modes: active work stays
+ visible, untouched completed groups fold by default, and explicit disclosure
+ choices are preserved regardless of the thinking preference. Closing the
+ turn's disclosure closes the groups under it, and reopening restores the groups
+ the user had opened.
+- With `showThinking` off, no completed reasoning row renders; only the live
+ whole-run TextShimmer `Thinking` indicator remains while reasoning streams.
+ Stored reasoning is retained and reappears when the preference is turned back
+ on.
+- `transcriptDisplayMode` keeps the three layouts available and defaults to the
+ released `fully-folded` layout. `flat` removes nested groups, `command-first`
+ lifts commands to standalone rows, and `fully-folded` keeps commands in their
+ groups; all three render exactly one disclosure, and reading the mode while
+ rendering repaints the transcript immediately instead of waiting for new
+ messages.
+- With `showThinking` on, Thinking rows default expanded in `flat` and
+ `command-first`; `fully-folded` keeps the live-only auto-open exception.
- The header answers "how did this turn end up" in one short line. Echoing the
current command was removed: it pushed the counts off the row and duplicated
what opening the item already shows.
@@ -157,8 +192,13 @@ the i18n catalog tests cover the new `settings.showThinking` copy. The UI,
resolver, and E2E scenarios are validated on the integration candidate; see
E2E-CHAT-turn-process-and-thinking-display for the synchronized scenario text.
For the 2026-10-21 amendment, `apps/desktop/test/turn-process.test.mjs` covers
-one-disclosure segmentation, command-folding on and off, and header phase
-precedence; `apps/desktop/test/transcript-style.test.mjs` covers the shared left
-edge and the removed live item echo. The interactive transcript probes cover the
-rendered disclosure count, command placement, and header labels. See
+mode segmentation, including `flat`, `command-first` and `fully-folded`, and
+header phase precedence. `apps/desktop/test/transcript-display-modes-ui.test.mjs`
+covers the renderer wiring for distinct mode segmentation, Thinking-row defaults
+and the whole-run `TextShimmer` used for a collapsed or hidden Thinking
+indicator.
+`apps/desktop/test/transcript-display-mode-settings.test.mjs` covers the
+Settings row label and search indexing, and
+`apps/desktop/test/settings-roundtrip.test.mjs` covers normalization, write
+validation and the `fully-folded` default. See
E2E-CHAT-turn-process-and-thinking-display for the synchronized scenario text.
diff --git a/docs/spec/03-runtime/04-data-storage.md b/docs/spec/03-runtime/04-data-storage.md
index 66d44cfb42..3d7cc64726 100644
--- a/docs/spec/03-runtime/04-data-storage.md
+++ b/docs/spec/03-runtime/04-data-storage.md
@@ -415,12 +415,17 @@ reasoning visibility. It is a portable application preference and synchronizes
across devices like the legacy field. Missing values fall back to the legacy
`thinkingDisplayMode` field (`compact` hides, `detailed`/unknown/absent shows),
which is retained only for persisted-settings compatibility and as that
-fallback. The app settings JSON optionally stores `keepCommandsExpanded`
-(boolean) for command-row placement inside a turn's process disclosure: absent
-means on, so `Bash` and run aliases stay on their own rows beside the activity
-groups; `false` folds them into their groups. It is a portable application
-preference and changes presentation only. These additive display preferences
-neither rewrite stored reasoning nor change the database schema.
+fallback. The app settings JSON also optionally stores `transcriptDisplayMode`
+(`flat` | `command-first` | `fully-folded`) for transcript process grouping:
+`flat` renders no nested activity groups, `command-first` renders `Bash`/run rows
+as standalone rows beside activity groups, and `fully-folded` keeps each command
+inside the group around it. Missing or unknown values normalize to
+`fully-folded` in both the renderer and main-process settings normalizers. It is
+a portable application preference and changes presentation only. The deprecated
+`keepCommandsExpanded` boolean is retained only for persisted-settings
+compatibility; it is no longer exposed in Settings and no longer read for
+rendering. These additive display preferences neither rewrite stored reasoning
+nor change the database schema.
The settings blob may still contain legacy prompt-enhancement keys from an
earlier release. They are retained for rollback and downgrade compatibility,
diff --git a/docs/spec/04-ux/06-settings-ia.md b/docs/spec/04-ux/06-settings-ia.md
index 060541c06a..c07857e79c 100644
--- a/docs/spec/04-ux/06-settings-ia.md
+++ b/docs/spec/04-ux/06-settings-ia.md
@@ -284,8 +284,9 @@ Settings is a **full-window page** that replaces the app sidebar + main chrome (
control column.
- **Defaults** card: the host-backed default operating mode (Agent / Plan / Goal),
command shell selection, Link open destination, context usage display
- (remaining or used), the Show thinking toggle, Enter-to-send control, the
- infinite provider retry switch, and the large text paste threshold. The
+ (remaining or used), the Show thinking toggle, the Transcript display
+ segmented control, Enter-to-send control, the infinite provider retry switch,
+ and the large text paste threshold. The
retry switch is off by default and explains that network/transient provider
failures keep retrying until success; Stop still cancels the turn and the
setting may continue API usage while enabled. Link open destination uses the Work panel browser by default
@@ -308,24 +309,32 @@ Settings is a **full-window page** that replaces the app sidebar + main chrome (
prompt-enhancement preferences is specified in
`04-ux/12-prompt-enhancement.md`.
- **Show thinking** is a toggle that persists as the optional `showThinking`
- boolean in host-owned settings. Off keeps the live thinking indicator visible
- and hides completed reasoning rows and excerpts; stored reasoning is retained
- and reappears when the toggle is turned back on. It affects presentation only,
- not model reasoning configuration, and it does not control turn-process or
- activity-group folding: active processes start open and untouched completed
- processes fold by default regardless of the toggle. The legacy
- `thinkingDisplayMode` field (`detailed` / `compact`) is retained only for
- persisted-settings compatibility and is no longer exposed; an absent or
+ boolean in host-owned settings. Off hides completed reasoning rows and, while
+ reasoning is actively streaming, leaves only the whole-run TextShimmer
+ `Thinking` indicator; a collapsed row shows that indicator without an excerpt.
+ Stored reasoning is retained and reappears when the toggle is turned back on.
+ With it on, Thinking rows default expanded in Flat and Commands first, while
+ Fully folded keeps the released live-only auto-open exception. It affects
+ presentation only, not model reasoning configuration, and it does not control
+ turn-process or activity-group folding: active processes start open and
+ untouched completed processes fold by default regardless of the toggle. The
+ legacy `thinkingDisplayMode` field (`detailed` / `compact`) is retained only
+ for persisted-settings compatibility and is no longer exposed; an absent or
unknown value shows reasoning and an explicit `compact` hides it. Settings
search indexes the row.
-- **Don't collapse commands** is a toggle that persists as the optional
- `keepCommandsExpanded` boolean in host-owned settings, defaulting to on when
- absent. On keeps shell calls on their own rows beside the tool groups they ran
- among; off folds them back into those groups, the layout used before commands
- were separated. It affects presentation only — neither value changes how many
- process disclosures a turn renders (always one), what a tool received, or what
- is stored — and it is read at render time, so toggling repaints the transcript
- immediately. Settings search indexes the row.
+- **Transcript display** is a segmented control in Defaults immediately after
+ **Show thinking**. It persists the optional `transcriptDisplayMode` field as
+ `flat`, `command-first`, or `fully-folded`, with the labels **Flat**,
+ **Commands first**, and **Fully folded**; an absent or unknown value resolves
+ to **Fully folded**, the layout released in v0.20.0. **Flat** renders one
+ outer process disclosure with no nested activity groups. **Commands first**
+ keeps activity groups but lifts `Bash`/run rows into standalone rows, and a
+ normal assistant progress message or a command ends a group. **Fully folded**
+ keeps commands inside their groups and lets only ordinary progress text split
+ them. All three render exactly one process disclosure, change presentation
+ only, and are read at render time, so switching repaints the transcript
+ immediately. The deprecated `keepCommandsExpanded` boolean is no longer
+ exposed and is not read for rendering. Settings search indexes the row.
- The **Command shell** row in Defaults uses the host-discovered catalog of native
PowerShell 5.1, PowerShell 7, cmd, Git Bash, and Bash with IDs
`windows-powershell`, `windows-pwsh`, `cmd`, `git-bash`, and
diff --git a/docs/spec/04-ux/07-ui-design-system.md b/docs/spec/04-ux/07-ui-design-system.md
index f681f6b3c5..0048d643f2 100644
--- a/docs/spec/04-ux/07-ui-design-system.md
+++ b/docs/spec/04-ux/07-ui-design-system.md
@@ -799,7 +799,7 @@ are also explicitly suppressed or collapsed to a static state.
- No parallax
- No continuous background animations (particles, waves); the bounded
foreground mascot loop is the explicit empty-home exception
-- No shimmer/skeleton animations longer than 1s loop — use simple fade-in for loading states
+- No shimmer/skeleton animations longer than 1s loop — use simple fade-in for loading states. Exception: the transcript Thinking indicator's whole-run TextShimmer runs 1.2s with a 220ms fade (ADR turn-process-and-thinking-display); it is not a per-glyph loop and becomes static under reduced motion.
- No bounce effects
- No multi-second boot theatrical sequences; splash exits as soon as ready (+ min dwell)
diff --git a/docs/spec/04-ux/08-component-spec.md b/docs/spec/04-ux/08-component-spec.md
index aca6e3a8e8..ea74e62061 100644
--- a/docs/spec/04-ux/08-component-spec.md
+++ b/docs/spec/04-ux/08-component-spec.md
@@ -876,30 +876,34 @@ activity groups and `Bash` run rows alike. A turn therefore renders exactly one
top-level process disclosure, including a Bash-only turn; no run row is a sibling
of it, and a long turn collapses in one gesture. The answer, assistant errors,
stopped trailing partial text and pending action cards remain outside, reachable
-without expanding the process.
-
-Within the process, an ordinary activity group represents one contiguous
-tool/search/thinking segment between progress paragraphs or run rows. It renders a
-group header only when at least two items are visible under the current thinking
-preference. A singleton uses its item disclosure directly, hidden thinking never
-creates an empty wrapper, and the existing Task topology remains the container for
-delegated work.
-
-`keepCommandsExpanded` decides where a run row sits inside that disclosure and
-defaults to on. When on, `Bash` and run aliases are lifted out of the groups they
-ran among and render as their own rows at the disclosure's top level; adjacent
-calls stay separate and a row's detail stays closed until the user opens it. When
-off, a run row keeps its place in the flow and reads as another line of the group
-around it. Neither value changes the disclosure count, what a tool received, or
-what is stored.
+without expanding the process. An untouched process closes on completion, leaving
+the final answer; with no final text, the process header and those surfaces
+remain.
+
+Within the process, the `Transcript display` mode decides the grouping.
+`fully-folded` (the default; absent or unknown values use it) forms ordinary
+activity groups from contiguous tool/search/thinking segments between ordinary
+assistant progress paragraphs, and keeps `Bash`/run aliases inside the group
+around them. A `Task` delegation keeps its own topology and is not duplicated
+inside an ordinary group. `command-first` keeps those groups but lifts every
+`Bash`/run alias into a standalone row beside them: adjacent calls stay separate,
+a row's detail stays closed until the user opens it, and a normal assistant
+progress message or a command ends the current group. `flat` renders no nested
+activity groups; the outer disclosure lists tools, commands, thinking and
+progress rows in transcript order. In `command-first` and `fully-folded`, a group
+header appears only when at least two items are visible under the current
+thinking preference; a singleton uses its item disclosure directly, and hidden
+thinking never creates an empty wrapper. All three modes render exactly one
+top-level process disclosure and change neither what a tool received nor what is
+stored.
The ordinary group owning the active execution segment starts open while a turn is
active, then closes on completion only if untouched; other completed groups start
closed. An untouched active group remains open when any failed or denied tool has
been recorded, through later successful recovery, and closes on completion if still
-untouched. These group defaults are unified and do not depend on either
-preference. Group headers summarize count, running state and issue count without
-treating a failed child as a failed turn.
+untouched. These group defaults are unified across modes and do not depend on the
+thinking preference. Group headers summarize count, running state and issue count
+without treating a failed child as a failed turn.
The turn disclosure header states the turn's outcome and never echoes the item it
is working on, because a shell command or search query can be arbitrarily long. It
@@ -913,13 +917,19 @@ beside the label. The disclosure and the levels it reveals share one left edge;
hierarchy is carried by type size and colour, not by indentation, so a nested
group header and a run row start exactly where the turn header does.
-No item payload opens itself: a tool, hosted-search or plan call stays a header row
-until the user opens its disclosure, including a Bash row, whose detail stays closed
-until the user opens it. The activity groups keep their automatic open defaults, so
-a live turn still shows its work. When the `Show thinking` preference is off, the
-live thinking indicator stays visible while completed reasoning rows and excerpts
-are suppressed and empty thinking-only containers are omitted; the stored reasoning
-is retained and reappears when the preference is turned back on.
+Except for the display mode's Thinking default, no item payload opens itself: a
+tool, hosted-search or plan call stays a header row until the user opens its
+disclosure, including a Bash row, whose detail stays closed until the user opens
+it. The activity groups keep their automatic open defaults, so
+a live turn still shows its work. With `Show thinking` on, Thinking rows expand by
+default in Flat and Commands first and collapse only on user action; Fully folded
+keeps the released exception where earlier rows stay collapsed and only the last
+active row opens while it is live. An expanded Thinking row shows its full
+reasoning markdown; a collapsed one shows only the Thinking indicator, with no
+summary or excerpt. With `Show thinking` off, no completed reasoning row renders;
+only a live whole-run TextShimmer `Thinking` indicator remains while reasoning is
+actively streaming, and empty thinking-only containers are omitted. The stored
+reasoning is retained and reappears when the preference is turned back on.
Group, run row and item are independent controls. Closing an ancestor keeps
descendant choices and reopening restores them; closing the turn's disclosure hides
@@ -2287,20 +2297,21 @@ Lightweight inline disclosure row showing a semantic tool action, its primary
argument hint, status, and a readable rendering of the result. It follows D071
and is intentionally not an elevated card.
-The turn's process is one disclosure. Inside it, one contiguous
-tool/search/thinking segment between progress paragraphs or run rows becomes an
-ordinary processing group only when it has two or more visible items under the
-current thinking preference. A singleton uses its item disclosure directly, and
-Task topology keeps its existing container. `Bash` and run aliases stay inside the
-turn's disclosure: with `keepCommandsExpanded` on (the default) each renders as
-its own row beside the groups, and adjacent calls remain separate; with it off a
-run row stays in the flow of its group. A Bash-only turn still has its one
-disclosure. While the turn is active, the ordinary group owning the execution
-segment opens; when it settles, an untouched group closes. These group defaults do
-not depend on the thinking preference. No item payload opens itself: a tool,
-hosted-search or plan row stays a header row until the user opens it, whichever
-item of the group it is, including a Bash row whose detail stays closed until
-opened.
+The turn's process is one disclosure. With `fully-folded` (the default), one
+contiguous tool/search/thinking segment between ordinary progress paragraphs
+becomes an ordinary processing group only when it has two or more visible items
+under the current thinking preference, and `Bash`/run aliases stay inside their
+group. With `command-first`, the groups remain but each `Bash`/run alias renders
+as its own row beside them, and a progress message or command ends a group. With
+`flat`, no group renders and the rows keep transcript order inside the outer
+disclosure. A singleton uses its item disclosure directly, and Task topology
+keeps its existing container. A Bash-only turn still has its one disclosure.
+While the turn is active, the ordinary group owning the execution segment opens;
+when it settles, an untouched group closes. These group defaults do not depend on
+the thinking preference. No item payload opens itself, except the display mode's
+Thinking default: a tool, hosted-search or plan row stays a header row until the
+user opens it, whichever item of the group it is, including a Bash row whose
+detail stays closed until opened.
The group header shows `Processing · 12s` while active or `Processed for 12s`
after completion, plus bounded item and issue counts. Expanding it reveals the
@@ -2333,15 +2344,15 @@ seconds when non-zero) from one hour onward. Zero-value units are omitted, so
completion only if untouched; completed groups otherwise start closed. These
defaults do not depend on the thinking preference. A singleton has no group
header.
-- Tool/search payloads stay collapsed until the user opens them; no row
- auto-opens, so a final thinking item never selects an earlier tool. Live
+- Tool/search payloads stay collapsed until the user opens them; no tool/search
+ row auto-opens, so a final thinking item never selects an earlier tool. Live
thinking follows its own indicator/disclosure policy and never opens sibling
payloads.
-- `Bash` and run rows are revealed by the turn's process disclosure. With
- `keepCommandsExpanded` on they sit at its top level beside the groups and
- adjacent rows stay separate; with it off they render inside their group. They
- are never siblings of the turn's process, and their details stay closed until
- opened.
+- `Bash` and run rows are revealed by the turn's process disclosure. In
+ `fully-folded` they sit inside their group; in `command-first` they sit at its
+ top level beside the groups with adjacent rows separate; in `flat` no groups
+ exist, so they follow transcript order inside the disclosure. They are never
+ siblings of the turn's process, and their details stay closed until opened.
- The processing group spans the full available assistant column, so expanded
result details keep a usable width even when the header or payload is short.
- The visible label is a natural-language action (`Read`, `Ran`, `Searched`),
@@ -2414,16 +2425,17 @@ twice.
| State | Header treatment | Expanded content |
|---|---|---|
-| Running | Progressive action with readable text and a pulsing marker; a `run` row also shows its spinner and pulses the status dot beside `Working…` | The active multi-item group opens; no item payload opens itself; live thinking follows its own indicator/disclosure policy |
+| Running | Progressive action with readable text and a pulsing marker; a `run` row also shows its spinner and pulses the status dot beside `Working…` | The active multi-item group opens; no tool/search payload opens itself, except the display mode's Thinking default; live thinking follows its own indicator/disclosure policy |
| Success | Past-tense action + result chips; no green success badge, except a `run` row's dot and `Done` | Result blocks, then arguments if not already shown; an untouched active group closes on completion, while manual group and item choices are retained |
| Error | Past-tense action + compact danger status; details remain collapsed by default and open only on user request. A `run` row is in this state whenever its command exited nonzero, whatever the call reported (D227) | Error note first, then arguments |
| Denied | Muted `Denied` status; payload remains closed until requested | Permission result when available |
### 9.6 Interactions
-- Click the row: expand/collapse only that result payload. Payloads start
- closed. No payload opens itself, so the row the user opens is the only expanded
- one; failed and denied rows behave the same.
+- Click the row: expand/collapse only that result payload. Tool/search payloads
+ start closed. No tool/search payload opens itself, so the row the user opens is
+ the only expanded one; failed and denied rows behave the same. Thinking rows
+ follow the display mode's default described above.
- A file path that a row or its result names is a link, not decoration: clicking
the summary path of a `Read`, `Write`, `Edit`, or `fetch` row, or a path in a
result's file list or match groups, completes the reference through the same
diff --git a/docs/spec/04-ux/09-interaction-patterns.md b/docs/spec/04-ux/09-interaction-patterns.md
index 1dcdfe4534..78bca69413 100644
--- a/docs/spec/04-ux/09-interaction-patterns.md
+++ b/docs/spec/04-ux/09-interaction-patterns.md
@@ -920,20 +920,22 @@ may be retained while exactly one workspace supplies the visible shell context.
- One unified presentation gives each loaded assistant turn a single collapsible
process disclosure. It contains thinking, tools, hosted searches, intermediate
progress text and the turn's `Bash`/run rows; the trailing answer, assistant
- errors and stopped trailing text remain outside it.
+ errors and stopped trailing text remain outside it. The `Transcript display`
+ mode selects the layout: `flat` has no nested groups, `command-first` lifts
+ commands into standalone rows, and `fully-folded` (the default) keeps commands
+ inside their groups.
- A contiguous activity segment receives a group disclosure only when it has at
- least two visible items under the current thinking preference. Progress text or a
- run row ends the segment, a singleton uses its item disclosure directly, and
- hidden thinking does not create a redundant group. Existing Task topology remains
- separate. `keepCommandsExpanded` (default on) decides only where a run row sits
- inside the turn's disclosure: on lifts `Bash` and run aliases out of their groups
- into their own top-level rows, with adjacent calls remaining separate; off keeps
- a run row in the flow of its group. Neither value adds another disclosure or
- leaves a run row outside the process.
+ least two visible items under the current thinking preference, and only in
+ `command-first` or `fully-folded`. In `fully-folded`, ordinary assistant
+ progress text ends the segment; in `command-first`, a normal assistant progress
+ message or a command ends it. A singleton uses its item disclosure directly,
+ hidden thinking does not create a redundant group, and existing Task topology
+ remains separate. No mode adds a second top-level disclosure or leaves a run
+ row outside the process.
- The active ordinary group starts open and closes when it completes only if
untouched; completed groups otherwise start closed, and an untouched active group
with any recorded failed/denied tool remains open through recovery. These group
- defaults do not depend on either preference. Closing the turn's disclosure hides
+ defaults do not depend on the thinking preference. Closing the turn's disclosure hides
every group and run row under it without erasing their choices; reopening
restores the groups the user had opened.
- The turn header reports `Failed`, `Stopped`, `Running`, or `Finished` in that
@@ -942,13 +944,16 @@ may be retained while exactly one workspace supplies the visible shell context.
transcript recorded none, and never echoes the current command or query. A
nested group header and a run row share its left edge; hierarchy is carried by
type size and colour rather than indentation.
-- No item payload opens itself: a tool, hosted-search or plan call stays a header
- row until the user opens it, including the literal final item of the last
- activity group. Group defaults are unchanged, so a final thinking item never
- causes a backward scan. When `Show thinking` is off, every item payload stays
- closed and completed reasoning text/excerpts are hidden while the live thinking
- indicator remains visible; stored reasoning is retained and reappears when the
- preference is turned back on.
+- No item payload opens itself, except the display mode's Thinking default: a
+ tool, hosted-search or plan call stays a header row until the user opens it,
+ including the literal final item of the last activity group. Group defaults are
+ unchanged, so a final thinking item never causes a backward scan. With
+ `Show thinking` on, Thinking rows default expanded in Flat and Commands first and
+ collapse only on user action; Fully folded keeps the released live-only
+ auto-open exception. A collapsed row shows only the Thinking indicator, with no
+ excerpt. With `Show thinking` off, no completed reasoning row renders; only a
+ live whole-run TextShimmer `Thinking` indicator remains while reasoning streams.
+ Stored reasoning is retained and reappears when the preference is turned back on.
- Activating a group or item header toggles only that level. Closing a parent
preserves child state, reopening restores it, and sibling groups remain
independent. Opening a parent is never an expand-all action.
diff --git a/docs/spec/06-delivery/04-e2e-test-plan.md b/docs/spec/06-delivery/04-e2e-test-plan.md
index c6989e9870..73061cc72e 100644
--- a/docs/spec/06-delivery/04-e2e-test-plan.md
+++ b/docs/spec/06-delivery/04-e2e-test-plan.md
@@ -3371,44 +3371,46 @@ identify the platform validation still needed.
pre-answer row; close it and confirm the groups and run rows close with it, then
reopen and confirm the group choice returns. 4) Open one completed group and one
item, copy its output, close and reopen the group, then open a sibling group
- independently. 5) Toggle `Don't collapse commands` off and on and inspect where
- the run rows render while the disclosure count stays one. 6) Repeat with a
- singleton item and with the last activity group's literal final item set to a
- tool/search, thinking, failed tool, and denied tool. 7) Toggle `Show thinking`
- off and on and inspect the active-thinking, failure/recovery and completed
- states. 8) Remount rows within the retained pane, then reload the renderer and
- reopen the session.
+ independently. 5) Switch `Transcript display` across Flat, Commands first, and
+ Fully folded and inspect the grouping, group boundaries, where the run rows
+ render, and the disclosure count. 6) Repeat with a singleton item and with the
+ last activity group's literal final item set to a tool/search, thinking, failed
+ tool, and denied tool. 7) Toggle `Show thinking` off and on and inspect the
+ active-thinking, failure/recovery and completed states. 8) Remount rows within
+ the retained pane, then reload the renderer and reopen the session.
- **Expected**: A turn renders exactly one process disclosure containing every
pre-answer row, the `Bash`/run rows included; the trailing answer, assistant
errors and stopped trailing text stay outside it, as do pending actions. The
active group opens, then closes on completion only if untouched; completed
groups otherwise start closed. Closing the turn's disclosure closes the groups
- and run rows under it, and reopening restores the user's group choices. With
- `Don't collapse commands` on (default), run rows render as their own top-level
- rows beside the groups, adjacent calls stay separate, and a row's detail stays
- closed until opened; with it off they fold into their groups. Neither value
- changes the disclosure count. A singleton has no group wrapper. No item payload
- opens itself: a tool/search row stays a header until the user opens it, while a
- final thinking item keeps its own leaf default and never selects an earlier
- tool. The header reports `Running`, `Finished`, `Stopped`, or `Failed` with
- failure and stop outranking a normal finish, reads `Thinking` while the live
- step is reasoning, never repeats the current command, and omits the duration
- when none was recorded. When `Show thinking` is off, the
- live thinking indicator stays visible while completed reasoning text and excerpts
- are hidden and empty thinking-only containers are omitted; turning it back on
- restores them. Parent, child and sibling choices are independent;
- closing/reopening a parent preserves descendants, and streaming/completion does
- not override user-owned choices. Retained-pane remounts preserve choices;
- renderer restart reapplies defaults while tool names, arguments, results and
- statuses remain restored. Group headers show bounded running and issue summaries
- without marking the whole turn failed.
+ and run rows under it, and reopening restores the user's group choices. In
+ Fully folded (the default), run rows stay inside their groups and only ordinary
+ assistant progress text splits a group. In Commands first, run rows render as
+ their own rows beside the groups, adjacent calls stay separate, a row's detail
+ stays closed until opened, and a normal assistant progress message or a command
+ ends a group. In Flat, no nested group renders and the rows keep transcript
+ order inside the outer disclosure. Every mode keeps the disclosure count at one.
+ A singleton has no group wrapper. No item payload opens itself except the
+ display mode's Thinking default: a tool/search row stays a header until the user
+ opens it, while a final thinking item never selects an earlier tool. The header
+ reports `Running`, `Finished`, `Stopped`, or `Failed` with failure and stop
+ outranking a normal finish, reads `Thinking` while the live step is reasoning,
+ never repeats the current command, and omits the duration when none was
+ recorded. When `Show thinking` is off, no completed reasoning row renders; only
+ the live TextShimmer `Thinking` indicator remains while reasoning streams, and
+ turning it back on restores the completed rows. Parent, child and sibling
+ choices are independent; closing/reopening a parent preserves descendants, and
+ streaming/completion does not override user-owned choices. Retained-pane
+ remounts preserve choices; renderer restart reapplies defaults while tool names,
+ arguments, results and statuses remain restored. Group headers show bounded
+ running and issue summaries without marking the whole turn failed.
- **Specs linked**: `04-ux/01-ui-ia.md`,
`04-ux/07-ui-design-system.md`, `04-ux/08-component-spec.md`,
`04-ux/09-interaction-patterns.md`
- **Acceptance**: C (chat stream), E (tools), F (persistence)
- **Milestone**: M3
-- **Status**: Draft. Unit and style checks cover the one-disclosure,
- command-folding and header rules; this scenario remains the intended manual
+- **Status**: Draft. Unit and style checks cover the display modes, Thinking
+ defaults and header rules; this scenario remains the intended manual
transcript-reload behavior.
#### E2E-041: Conversation minimap navigates long transcripts
@@ -17180,60 +17182,86 @@ plugin-form fixtures in an isolated temporary directory at runtime.
- **Preconditions:** A turn with progress paragraph A, multiple searches plus
thinking, progress paragraph B, multiple commands plus thinking, and a final
- answer; the `Show thinking` preference on and off; the `Don't collapse
- commands` preference on and off; legacy message-level transcript search
- targets.
+ answer; the `Show thinking` preference on and off; the `Transcript display`
+ preference at Flat, Commands first, and Fully folded; a restart with saved
+ settings; legacy message-level transcript search targets.
- **Steps:** Confirm a live active group starts open, let that same turn finish
- without interacting, and confirm the group collapses. On a second turn,
- explicitly open a completed group and confirm the choice survives subsequent
- updates; then close the turn's disclosure and confirm the group closes with it,
- and reopen to confirm the group choice is restored. Turn `Show thinking` off
- and confirm the live thinking indicator remains while completed reasoning rows
- and excerpts disappear and no empty thinking-only container is left; turn it
- back on and confirm the completed rows return. Turn `Don't collapse commands`
- off and confirm the run rows fold into their groups while the turn still
- renders exactly one disclosure, then turn it on and confirm the standalone rows
- return. Confirm the header reads running, finished, stopped, or failed for each
- case, names compaction and recovery while those stages are live, omits the
- duration when none was recorded, and never repeats the current command. Review
- the nested path, including independent group/item toggles, a singleton segment,
- literal-final-item leaf selection, failure/denial/recovery, retained-pane
- remounts, run rows keeping their details closed until opened, and a legacy search
- reveal.
+ without interacting, and confirm the process closes so only the final answer
+ (and any error or pending-action surface) remains. On a second turn, explicitly
+ open a completed group and confirm the choice survives subsequent updates; then
+ close the turn's disclosure and confirm the group closes with it, and reopen to
+ confirm the group choice is restored. In Fully folded, confirm run rows stay
+ inside their activity groups and that only ordinary assistant progress text
+ splits a group. In Commands first, confirm `Bash`/run rows render as standalone
+ rows beside the groups, that a normal assistant progress message or a command
+ ends the current group, adjacent calls stay separate, and Thinking rows default
+ expanded. In Flat, confirm no nested activity group renders, the outer
+ disclosure lists tools, commands, thinking and progress in transcript order,
+ and tool details stay collapsed. In every mode confirm the turn renders exactly
+ one outer disclosure and that closing it hides, then reopening restores, the
+ rows under it. Turn `Show thinking` off and confirm no completed reasoning row
+ remains and only a live whole-run TextShimmer `Thinking` indicator appears
+ while reasoning streams, with no spinner, pulsing dot or per-character
+ animation and a static presentation under reduced motion; turn it back on and
+ confirm the completed rows return. Select each `Transcript display` value,
+ restart, and confirm it persists; remove the saved value and confirm it
+ defaults to Fully folded. Confirm the header reads running, finished, stopped,
+ or failed for each case, names compaction and recovery while those stages are
+ live, omits the duration when none was recorded, and never repeats the current
+ command. Review the nested path, including independent group/item toggles, a
+ singleton segment, literal-final-item leaf selection, failure/denial/recovery,
+ retained-pane remounts, run rows keeping their details closed until opened, and
+ a legacy search reveal.
- **Expected:** A turn renders exactly one process disclosure containing every
pre-answer row, leaving the final answer, assistant errors, stopped trailing
- text and pending actions outside it. The active group starts open; untouched
- groups collapse at completion, while explicit user choices persist and are
- restored when the enclosing disclosure is reopened. These group defaults do not
- depend on the `Show thinking` preference. With `Don't collapse commands` on,
- run aliases render as their own rows beside the groups, adjacent rows stay
- separate and a row's detail stays closed until opened; with it off they fold
- into their groups. Neither value changes the disclosure count. The header
+ text and pending actions outside it; when no final answer text exists, the
+ process header and those error or pending-action surfaces remain. An untouched
+ process closes at completion. In Flat there are no nested activity groups, and
+ active tools, commands, thinking and progress rows follow transcript order with
+ tool details collapsed. In Commands first, `Bash`/run rows are standalone
+ beside the groups, adjacent calls stay separate, and a normal assistant
+ progress message or a command ends a group, so the middle progress paragraph
+ and each command start a new group. In Fully folded (the default), run rows
+ stay inside their groups and only ordinary assistant progress text splits a
+ group, so the middle progress paragraph ends the preceding group and the
+ following activity starts a new one. A group appears only with at least two
+ visible items; a singleton has no group. Thinking rows default expanded in
+ Flat and Commands first, while Fully folded keeps the released exception:
+ earlier rows stay collapsed and only the last active row opens while it is
+ live, then completed rows collapse.
+ Explicit user choices persist and are restored when the enclosing disclosure is
+ reopened; these group defaults do not depend on `Show thinking`. The header
reports running, finished, stopped, or failed with failure and stop outranking
a normal finish, reads `Thinking` while the live step is reasoning, names
compaction and recovery while those stages are live, omits a duration the
transcript did not record, and never repeats the current command. Nested group
- headers and run rows share the turn header's left edge.
- When `Show thinking` is off, the live thinking indicator stays visible,
- completed reasoning rows and excerpts are hidden, and empty thinking-only
- containers are omitted; turning it back on restores them. Singletons have no
- group. No item payload opens itself: a tool/search row stays closed until the user
- opens it, while a final thinking item keeps its own leaf default.
+ headers and run rows share the turn header's left edge. When `Show thinking` is
+ off, no completed reasoning row renders, and only the live whole-run TextShimmer
+ `Thinking` indicator remains while reasoning streams; turning it back on
+ restores the rows. No item payload opens itself except the display mode's
+ Thinking default: a tool/search row stays closed until the user opens it.
Parent/child/sibling states remain independent, pane-owned user choices survive
- updates, preference changes and remounts, and renderer restart reapplies defaults.
- Search reveals the turn process and activity group that own the named message
- once per request; item-level targeting is not part of this change, and reasoning
- hidden by the preference stays hidden until the user turns `Show thinking` on.
- Saved `showThinking` survives restart; an absent value falls back to the legacy
+ updates, preference changes and remounts, and renderer restart reapplies
+ defaults. Search reveals the turn process and, where one exists, the activity
+ group that own the named message once per request; item-level targeting is not
+ part of this change, and reasoning hidden by the preference stays hidden until
+ the user turns `Show thinking` on. A saved `transcriptDisplayMode` survives
+ restart and an absent or unknown value resolves to Fully folded; saved
+ `showThinking` survives restart, and an absent value falls back to the legacy
`thinkingDisplayMode` (`compact` hides, `detailed`/unknown/absent shows).
- **Validation scope for the 2026-09-20 change:** Nested disclosure and activity
group presentation only; precise item-level transcript search targeting is out
of scope and keeps the existing message-level search behavior.
-- **Automation:** `pnpm test:e2e:transcript` covers default and active-to-completed
- process disclosure behavior; `pnpm test:e2e:transcript-disclosure` verifies
- manual-open retention and viewport anchoring; `apps/desktop/test/turn-process.test.mjs`
- covers process defaults and `apps/desktop/test/thinking-visibility.test.mjs`
- covers the `showThinking`/legacy resolver precedence.
+- **Automation:** `pnpm test:e2e:transcript` covers the command-first and
+ fully-folded layouts and active-to-completed process disclosure behavior;
+ `pnpm test:e2e:transcript-disclosure` verifies manual-open retention and
+ viewport anchoring; `apps/desktop/test/turn-process.test.mjs` covers mode
+ segmentation, `apps/desktop/test/transcript-display-modes-ui.test.mjs` covers
+ the renderer's mode wiring, Thinking defaults and TextShimmer,
+ `apps/desktop/test/transcript-display-mode-settings.test.mjs` covers the
+ Settings row and search indexing, and
+ `apps/desktop/test/settings-roundtrip.test.mjs` covers normalization, write
+ validation and the fully-folded default.
- **Specs:** 04-ux/06-settings-ia, 04-ux/08-component-spec,
04-ux/09-interaction-patterns; ADR turn-process-and-thinking-display.
diff --git a/docs/spec/08-meta/decisions-log.md b/docs/spec/08-meta/decisions-log.md
index 2c432fe692..8d61659084 100644
--- a/docs/spec/08-meta/decisions-log.md
+++ b/docs/spec/08-meta/decisions-log.md
@@ -332,7 +332,7 @@ Gold source: local Codex electron captures; latest row wins where rows conflict.
| D602 | Crash dumps stay in the data directory | **Electron's Crashpad reporter starts local-only (`uploadToServer: false`) before `ready`. Dumps live under `/crash-dumps`, not the default Electron `userData` crashDumps path, so a `PI_DESKTOP_DATA_DIR` profile does not share dumps. The next lock-holding launch writes one `diagnostics` line for dumps newer than `crash-dumps.json`, classified by Crashpad `ptype`: `error` if any new dump is the browser/main process, `warn` for recovered renderer/GPU/utility crashes. Host-core and sidecar crashes stay on the supervisor path. No upload, no IPC, no schema change.** | A crash left a minidump nobody read. Crashpad also records recovered renderer crashes, so a next-launch `error` that said the previous run died was a lie; and dumps outside the data directory escaped `PI_DESKTOP_DATA_DIR` isolation. |
| D619 | A copied formula is its TeX source | **Renderer only: a copy whose selection covers rendered math writes `text/plain` from the MathML `annotation` — `$…$` inline, `$$…$$` on its own lines, the delimiters `lib/latex-math.ts` normalizes `\(…\)` and `\[…\]` to, each run widened past any run inside the formula as a code span's fence is — instead of the two trees KaTeX paints. A cut that lands inside a formula grows to the whole formula. Only the formulas are rewritten: the reduced clone is read back through `Selection.toString()`, the serializer a copy itself runs, so prose, lists, tables and code blocks sharing the selection keep the platform's own reading — `user-select: none` chrome left behind included, which `innerText` would have written out. A selection with no formula in it, and a copy raised where the selection does not live, are left to the platform entirely. One flavour is written, `text/plain`: taking the event over drops the platform's `text/html` too and none is written back, because the reduced clone is app markup that would carry the `user-select: none` chrome the text reading drops, and because carrying the rendering instead would paste every formula twice — KaTeX's stylesheet is the only thing hiding the MathML tree and no stylesheet travels on the clipboard. One document `copy` listener owned by the shell, and the transcript's right-click Copy reads the same selection through the same module.** | A formula pasted as its glyphs, once per rendered tree, so it could not be carried into a LaTeX document or another Markdown editor (issue #414). ADR 0268 removed quoting on the grounds that the OS clipboard was the substitute; the clipboard had to actually carry the source. |
| D620 | pi-ai built-in API-key services are named presets | **Add fifteen named endpoint presets — Ant Ling, Baseten, Cerebras, Hugging Face, Meta (`responses`), MiniMax (International), Moonshot AI (International), NVIDIA, OpenCode Zen, Vercel AI Gateway, Qwen Token Plan (`alibaba-token-plan`), Qwen Token Plan (China), Xiaomi Token Plan (China / Europe / Singapore) — to `NAMED_ENDPOINT_PRESETS`, each at its published host, with the pi-ai provider id kept as an alias wherever the models.dev key differs. Eight built-in providers remain exceptions with a recorded reason: Amazon Bedrock, Azure OpenAI, Cloudflare AI Gateway, Cloudflare Workers AI, Google Vertex AI (account- or region-scoped URLs), GitHub Copilot and OpenAI Codex (vendor-account rows), and Radius (`pi_messages` is account-only here). `packages/agent-runtime/src/pi-ai-provider-sync.test.ts` fails on a pi-ai upgrade that leaves a provider neither covered nor excepted. No protocol, storage, or IPC change.** | Every other pi-ai capability was already reachable, but the API-key half of the service catalog was hand-maintained and had drifted from the library's own provider list (ADR 0307). |
-| D668 | One process disclosure per turn, with a command-folding preference | **Amend D661 / the `turn-process-and-thinking-display` ADR. A turn renders exactly one top-level process disclosure holding every pre-answer row, the run rows included; the answer stays outside it. `Bash` and run aliases are no longer excluded from every folded container. Inside that disclosure, the optional boolean `AppSettings.keepCommandsExpanded` (absent means on) decides whether run rows are lifted beside the groups they ran among or stay inside them; both values render exactly one disclosure. The preference is read while rendering, not while building transcript entries, so toggling it repaints immediately - the projection cache is keyed by messages and compactions only. The disclosure header reports failed / stopped / running / finished with precedence in that order and never echoes the current item, and the disclosure shares one left edge with the levels it reveals. `keepCommandsExpanded` joins the portable application fields. No host protocol, persistence schema, permission, or plugin contract change. See the amended ADR, `04-ux/06-settings-ia.md`, `04-ux/08-component-spec.md`, `04-ux/09-interaction-patterns.md`, and E2E-CHAT-turn-process-and-thinking-display.** | Chronological segmentation split one turn into several sibling disclosures above the answer, and always-visible command rows could not be turned off by readers who preferred the older grouped layout; one disclosure plus a presentation-only preference satisfies both without changing what a tool received or stored. |
+| D668 | One process disclosure per turn, with three transcript display modes | **Amend D661 / the `turn-process-and-thinking-display` ADR. A turn renders exactly one top-level process disclosure holding every pre-answer row; the answer stays outside it. `AppSettings.transcriptDisplayMode` selects the layout: `flat` renders no nested activity groups, `command-first` renders `Bash`/run rows as standalone rows beside activity groups, and `fully-folded` (the default for absent or invalid values) keeps commands inside their groups and lets only ordinary assistant progress text split them. The mode is read while rendering, so switching repaints immediately - the projection cache is keyed by messages and compactions only. The disclosure header reports failed / stopped / running / finished with precedence in that order and never echoes the current item, and the disclosure shares one left edge with the levels it reveals. `transcriptDisplayMode` joins the portable application fields; `keepCommandsExpanded` is deprecated, retained only for persisted-settings compatibility, and no longer exposed or read for rendering. No host protocol, persistence schema, permission, or plugin contract change. See the amended ADR, `04-ux/06-settings-ia.md`, `04-ux/08-component-spec.md`, `04-ux/09-interaction-patterns.md`, and E2E-CHAT-turn-process-and-thinking-display.** | Chronological segmentation split one turn into several sibling disclosures above the answer, and the boolean command-folding preference could only express two layouts; a three-mode setting covers flat, command-first, and the released grouped view without changing what a tool received or stored. |
## M0. Model catalog decisions
@@ -7849,24 +7849,31 @@ must keep splitting are covered by `markdown-blocks.test.mjs`.
`04-ux/06-settings-ia.md`, `04-ux/08-component-spec.md`, and
`apps/desktop/test/macos-window-translucency.test.mjs`.
-## 2026-10-21 — One process disclosure per turn, with command folding (D668)
+## 2026-10-21 — One process disclosure per turn, with three transcript display modes (D668)
- D668 amends D661 / the `turn-process-and-thinking-display` ADR: a turn now
renders exactly one top-level process disclosure containing every pre-answer
- row, the `Bash`/run rows included. No run row is a sibling of that disclosure;
- the trailing answer, assistant errors, stopped trailing text, and pending action
- surfaces stay outside it.
-- `AppSettings.keepCommandsExpanded` (absent means on) decides whether run rows are
- lifted beside the groups they ran among or stay inside them. The preference is
- read while rendering, not while building transcript entries, so toggling it
- repaints immediately; both values render exactly one disclosure.
-- The disclosure header reports failed / stopped / running / finished in that
- order, names compaction and recovery while those stages are live, drops an
- unavailable duration instead of showing zero, and never echoes the current item.
- The disclosure and the levels it reveals share one left edge.
-- `keepCommandsExpanded` joins the portable application fields. Covered by
- `apps/desktop/test/turn-process.test.mjs`,
- `apps/desktop/test/transcript-style.test.mjs`, and the interactive transcript
- probes. See the amended ADR, `04-ux/06-settings-ia.md`,
- `04-ux/08-component-spec.md`, `04-ux/09-interaction-patterns.md`, and
+ row. No run row is a sibling of that disclosure; the trailing answer, assistant
+ errors, stopped trailing text, and pending action surfaces stay outside it.
+- `AppSettings.transcriptDisplayMode` selects the layout. `flat` renders no
+ nested activity groups and lists rows in transcript order. `command-first`
+ keeps the groups but lifts `Bash`/run rows into standalone rows, with a normal
+ progress message or a command ending a group. `fully-folded`, the default for
+ absent or invalid values, keeps run rows inside their groups and lets only
+ ordinary assistant progress text split them. The mode is read while rendering,
+ so switching repaints immediately.
+- With `showThinking` on, Thinking rows default expanded in `flat` and
+ `command-first`; `fully-folded` keeps the released exception where only the
+ last active row opens while it is live. With the preference off, no completed
+ reasoning row renders and only a live whole-run TextShimmer `Thinking`
+ indicator remains while reasoning streams.
+- `keepCommandsExpanded` is deprecated and retained only for persisted-settings
+ compatibility; it is no longer exposed or read for rendering. The disclosure
+ header, left edge, and pane-owned disclosure memory are unchanged.
+- Covered by `apps/desktop/test/turn-process.test.mjs`,
+ `apps/desktop/test/transcript-display-modes-ui.test.mjs`,
+ `apps/desktop/test/transcript-display-mode-settings.test.mjs`, and
+ `apps/desktop/test/settings-roundtrip.test.mjs`. See the amended ADR,
+ `04-ux/06-settings-ia.md`, `04-ux/08-component-spec.md`,
+ `04-ux/09-interaction-patterns.md`, and
E2E-CHAT-turn-process-and-thinking-display.
diff --git a/docs/zh-CN/adr/turn-process-and-thinking-display.md b/docs/zh-CN/adr/turn-process-and-thinking-display.md
index b1bc0832cf..a033c2aba6 100644
--- a/docs/zh-CN/adr/turn-process-and-thinking-display.md
+++ b/docs/zh-CN/adr/turn-process-and-thinking-display.md
@@ -25,18 +25,28 @@
每个回合只渲染一个过程披露。回合在给出答案之前产生的所有行都位于其中——活动组与 `Bash`
命令行同样如此——因此长回合可以用一次操作收起,而不会在答案上方留下一列并列披露。答案本身
-位于披露之外。
+位于披露之外。未操作的过程在回合完成时收起,因此只剩最终回答;若回合没有产出最终文字,
+过程标题及其错误或待处理操作面仍会保留。
-在该披露内部,非 Bash 活动形成普通活动组:两个进度段落或命令行之间的一段连续工具、搜索或
-思考活动,并且仅在当前思考偏好下至少有两个可见项时出现。单项活动直接使用自身披露;被隐藏的
-思考不会制造多余的组包装。现有 Task 拓扑仍是其片段的容器,不会在普通活动组中重复渲染。
+在该披露内部,活动如何分组由显示模式决定。`AppSettings.transcriptDisplayMode` 取值为
+`flat`、`command-first` 或 `fully-folded`;缺失或无效值解析为 `fully-folded`,即
+v0.20.0 发布的布局。三种模式都只渲染一个外层披露。
-命令行位于其组内还是组旁,由 `keepCommandsExpanded` 偏好决定,默认开启。开启时,`Bash`
-和 run 别名会从所处的组中提取出来:各自成为披露顶层的独立行,相邻调用保持分离,详情在用户
-打开之前保持收起。关闭时,命令行保留在流程中的原位置,读起来就是所在组的另一行——即命令尚未
-被分离之前的布局。该偏好不会改变回合渲染的披露数量:两种取值都只渲染一个。
+- `fully-folded` 中,连续活动形成普通活动组:普通助手进度段落之间的一段连续工具、搜索、
+ 思考或 `Bash`/run 活动。`Bash`/run 行留在其周围的组内,命令读起来就是该组的另一行。
+ 现有 Task 拓扑仍是其片段的容器,不会在普通活动组中重复渲染。
+- `command-first` 中,普通活动组仍会渲染,但每个 `Bash`/run 别名都会提取为组旁的独立行:
+ 相邻调用保持分离,详情在用户打开前保持收起。普通助手进度消息和命令都会结束当前组。
+- `flat` 不渲染任何嵌套活动组。外层披露按转录顺序列出活动工具、命令、思考和进度行,工具
+ 详情保持收起。
-活动组的折叠默认值是统一的,不依赖思考偏好或上述偏好。拥有当前执行片段的普通活动组默认展开,
+在 `command-first` 与 `fully-folded` 中,只有在当前思考偏好下至少有两个可见项时才显示组。
+单项活动直接使用自身披露,被隐藏的思考不会制造多余的组包装。
+
+`keepCommandsExpanded` 已弃用:仅为使已持久化的设置仍可加载而保留,不再在设置中暴露,
+也不再参与渲染读取;新的写入保存 `transcriptDisplayMode`。
+
+组折叠默认值在各模式间统一,且不依赖思考偏好。凡渲染组时,拥有当前执行片段的组默认展开,
仅在用户未操作时于完成后收起;其他已完成组默认收起。只要活动组中记录过失败或被拒工具,
尚未被用户接管的活动组就会在后续恢复期间保持展开,并在回合完成后收起。关闭回合披露会一并
关闭其下的组,重新展开则恢复用户此前展开过的组。
@@ -52,13 +62,18 @@
披露与它展开的层级共用同一条左边缘。层级由字号与颜色表达,而不是缩进,因此嵌套的组标题与
命令行起始位置与回合标题完全一致。
-思考偏好是一个布尔值 `showThinking`。当它为 false 时,活动思考指示器保持可见,而已完成
-的思考行和摘要会被隐藏,空的纯思考容器会被省略;已存推理仍会保留,因此重新打开该偏好
-会恢复已完成的思考行和摘要。被隐藏的思考不会制造空的组包装。
+思考偏好是一个布尔值 `showThinking`。开启时,`flat` 与 `command-first` 中的每个思考行
+默认展开,用户可将其收起;展开时显示完整推理 Markdown,收起时只显示 Thinking 指示器,
+不显示摘要或摘录。`fully-folded` 保留已发布的例外:较早的思考行保持收起,最后一个活动
+思考行仅在其为当前步骤时自动展开,完成后收起。关闭时不再渲染任何已完成的推理行,仅在推理
+正在流式输出时保留整段运行的 `TextShimmer` `Thinking` 指示器。该微光为 1.2 秒线性扫过、
+220 毫秒淡出,不使用转圈、脉冲圆点或逐字符动画;减少动态效果时保持静态。已存推理仍会
+保留,因此重新打开该偏好会恢复这些行。被隐藏的思考不会制造空的组包装。
-本决策早先引入的叶子默认值后来被移除。条目载荷都不会自动展开:工具调用、托管搜索或
-计划行在用户打开之前始终只是标题行,无论它位于活动组的哪一项,且与思考偏好无关。
-组默认值不变,打开一个已收起的祖先仍会恢复已保留的条目选择,不会展开所有后代。
+本决策早先引入的叶子默认值后来被移除。除上文的显示模式思考默认值外,条目载荷都不会自动
+展开:工具调用、托管搜索或计划行在用户打开之前始终只是标题行,无论它位于活动组的哪一项,
+且与思考偏好无关。组默认值不变,打开一个已收起的祖先仍会恢复已保留的条目选择,不会展开
+所有后代。
每个标题只切换自己的层级。父子状态彼此独立:收起父级会保留后代选择,重新展开会恢复
这些选择,同级组不是互斥手风琴。用户操作某个条目时,会把所属组标记为用户接管,但不会
@@ -66,30 +81,38 @@
窗格仍存在,手动选择就跨流式更新、完成、偏好切换、单项变组和行重新挂载保留。窗格淘汰、
会话删除或渲染器重启会释放这些展示状态;它们不写入消息或宿主设置。
-搜索和导航只展开目标所需的祖先路径:拥有该消息的回合过程和活动组。条目级精确定位不在
-本次范围内,各行详情仍由各自的折叠控制。同一请求重新渲染时,不会反复覆盖用户之后的
-手动收起。被偏好隐藏的推理会保持隐藏,直到用户打开 `showThinking`。助手错误、中止后的
-末尾部分回答、权限/提问/计划/目标决策及其他待处理操作面必须位于隐藏过程之外,
+搜索和导航只展开目标所需的祖先路径:拥有该消息的回合过程,以及存在时的活动组。条目级
+精确定位不在本次范围内,各行详情仍由各自的折叠控制。同一请求重新渲染时,不会反复覆盖
+用户之后的手动收起。被偏好隐藏的推理会保持隐藏,直到用户打开 `showThinking`。助手错误、
+中止后的末尾部分回答、权限/提问/计划/目标决策及其他待处理操作面必须位于隐藏过程之外,
无需展开过程即可操作。
“设置 -> AI -> 默认项”提供一个 `Show thinking` 布尔开关,以可选的 `showThinking`
-`AppSettings` 字段持久化。缺失或非布尔值会回退到旧版 `thinkingDisplayMode` 字段:
-显式 `compact` 隐藏推理,而 `detailed`、未知值或缺失值都显示推理。旧字段为持久化设置的
-兼容性而保留,不再在界面中暴露。该偏好只改变展示,不改变提供商思考级别、运行时或模型
-上下文、已存推理、导出、权限、执行或复制载荷,也不控制回合过程或活动组的折叠。过程标题
-使用已记录的计时、直接工具/搜索计数、运行状态和问题计数;不会重复计算委派子任务,
-也不会把单个失败工具误报为整个助手回合失败。
+`AppSettings` 字段持久化;并在其后提供「过程显示」分段控件,标签为「平铺显示」
+「命令工具优先」与「全折叠显示」,以可选的 `transcriptDisplayMode` 字段持久化。缺失或
+无效的 `transcriptDisplayMode` 在渲染层与主进程设置规范化中都解析为 `fully-folded`。
+`showThinking` 缺失或非布尔值会回退到旧版 `thinkingDisplayMode` 字段:显式 `compact`
+隐藏推理,而 `detailed`、未知值或缺失值都显示推理。旧版 `thinkingDisplayMode` 与已弃用的
+`keepCommandsExpanded` 仅为持久化设置兼容性保留,不再在界面中暴露;
+`keepCommandsExpanded` 也不再参与渲染读取。这些偏好只改变展示,不改变提供商思考级别、
+运行时或模型上下文、已存推理、导出、权限、执行或复制载荷,思考偏好也不控制回合过程或
+活动组的折叠。过程标题使用已记录的计时、直接工具/搜索计数、运行状态和问题计数;不会
+重复计算委派子任务,也不会把单个失败工具误报为整个助手回合失败。
## 结果
- 每个回合一个披露,让最终回答与待处理操作保持可达,并使长回合可以用一次操作收起。
-- 活动组的折叠默认值统一:运行中的工作保持可见,未操作的已完成组默认收起,无论思考偏好如何
- 都保留用户明确的披露选择。关闭回合披露会关闭其下的组,重新展开则恢复用户此前展开过的组。
-- 当 `showThinking` 为 false 时,活动指示器保持可见,而已完成的推理行和摘要被隐藏。
- 已存推理仍会保留,重新打开偏好时重新出现。
-- 当 `keepCommandsExpanded` 开启(默认)时,run 别名作为独立行渲染,命令密集的回合保持易读;
- 关闭时恢复较早的布局,命令行读起来就是所在组的另一行。两种取值都不改变披露数量;该偏好
- 在渲染时读取而非在构建条目时读取,因此切换后立即重绘,而无需等待新消息。
+- 活动组的折叠默认值在各显示模式间统一:运行中的工作保持可见,未操作的已完成组默认收起,
+ 无论思考偏好如何都保留用户明确的披露选择。关闭回合披露会关闭其下的组,重新展开则恢复
+ 用户此前展开过的组。
+- 当 `showThinking` 关闭时,不再渲染任何已完成的推理行,仅在推理流式输出期间保留整段运行的
+ TextShimmer `Thinking` 指示器。已存推理仍会保留,重新打开偏好时重新出现。
+- `transcriptDisplayMode` 保留三种布局,并默认使用已发布的 `fully-folded` 布局。
+ `flat` 移除嵌套组,`command-first` 将命令提升为独立行,`fully-folded` 让命令留在
+ 所属组内;三者都只渲染一个披露,且模式在渲染时读取,因此切换后立即重绘,而无需等待
+ 新消息。
+- `showThinking` 开启时,`flat` 与 `command-first` 中的思考行默认展开;`fully-folded`
+ 保留仅活动行自动展开的例外。
- 标题用一行说明回合的结果。回显当前命令的做法已被移除:它会把计数挤出该行,并且与打开该项
已经能看到的内容重复。
- 披露记忆是以稳定回合、组和条目标识为键的窗格展示状态,不是持久化转录契约,也不
@@ -108,7 +131,10 @@
`showThinking`/旧版 `thinkingDisplayMode` 的解析优先级,并由 i18n 目录测试覆盖新增的
`settings.showThinking` 文案。界面、解析器与 E2E 场景在集成候选上验证;同步后的场景文本见
E2E-CHAT-turn-process-and-thinking-display。
-2026-10-21 修订由 `apps/desktop/test/turn-process.test.mjs` 覆盖单披露分段、
-命令折叠开关与标题阶段优先级,由 `apps/desktop/test/transcript-style.test.mjs` 覆盖共享
-左边缘与已移除的实时条目回显;交互式转录探针覆盖实际渲染的披露数量、命令行位置和标题
-文案。同步后的场景文本见 E2E-CHAT-turn-process-and-thinking-display。
+2026-10-21 修订由 `apps/desktop/test/turn-process.test.mjs` 覆盖模式分段(包括
+`flat`、`command-first` 与 `fully-folded`)及标题阶段优先级;
+`apps/desktop/test/transcript-display-modes-ui.test.mjs` 覆盖渲染层的模式分段接线、
+思考行默认值以及收起或隐藏思考指示器使用的整段运行 `TextShimmer`;
+`apps/desktop/test/transcript-display-mode-settings.test.mjs` 覆盖设置行标签与搜索索引;
+`apps/desktop/test/settings-roundtrip.test.mjs` 覆盖规范化、写入校验与 `fully-folded`
+默认值。同步后的场景文本见 E2E-CHAT-turn-process-and-thinking-display。
diff --git a/docs/zh-CN/spec/03-runtime/04-data-storage.md b/docs/zh-CN/spec/03-runtime/04-data-storage.md
index 98cab02961..60132669bb 100644
--- a/docs/zh-CN/spec/03-runtime/04-data-storage.md
+++ b/docs/zh-CN/spec/03-runtime/04-data-storage.md
@@ -1232,10 +1232,13 @@ outbox 排空。渲染器侧的停止绝不重写已有已开始回复的转录
应用设置 JSON 还可选存储布尔值 `showThinking`,用于转录中的推理可见性。它是可移植的
应用偏好,会像旧字段一样跨设备同步。缺失值回退到旧版 `thinkingDisplayMode` 字段
(`compact` 隐藏,`detailed`/未知/缺失显示);该旧字段仅为持久化设置兼容性保留,
-并作为该回退来源。应用设置 JSON 还可选存储布尔值 `keepCommandsExpanded`,用于回合
-过程披露中的命令行位置:缺失即开启,`Bash` 与 run 别名保留在活动组旁的独立行;
-`false` 折回所属组。它是可移植的应用偏好,只改变展示。这些新增展示偏好既不重写
-已存推理,也不改变数据库 schema。
+并作为该回退来源。应用设置 JSON 还可选存储 `transcriptDisplayMode`
+(`flat` | `command-first` | `fully-folded`),用于转录中的过程分组:`flat` 不渲染
+嵌套活动组,`command-first` 将 `Bash`/run 行作为活动组旁的独立行,`fully-folded`
+让每条命令留在其周围的组内。缺失或未知值在渲染层与主进程设置规范化中都归一化为
+`fully-folded`。它是可移植的应用偏好,只改变展示。已弃用的 `keepCommandsExpanded`
+布尔值仅为持久化设置兼容性保留;它不再在设置中暴露,也不再参与渲染读取。这些新增展示
+偏好既不重写已存推理,也不改变数据库 schema。
应用设置 JSON 可能仍包含旧版本写入的提示词增强键。为支持回退和降级,宿主保留这些值,
但不会再把它们作为有效偏好读取或写入。用户安装并授权独立的
diff --git a/docs/zh-CN/spec/04-ux/06-settings-ia.md b/docs/zh-CN/spec/04-ux/06-settings-ia.md
index 9e903d2724..10be4998d8 100644
--- a/docs/zh-CN/spec/04-ux/06-settings-ia.md
+++ b/docs/zh-CN/spec/04-ux/06-settings-ia.md
@@ -109,7 +109,7 @@
都以相同方式展开。关闭时的触发器按当前文案收缩,不超过设置控件列。
- **默认项**卡:主机支持的默认运行模式(Agent / Plan / Goal)、
命令 Shell 选择、链接打开目标、上下文用量显示(剩余或已用)、
- 显示思考开关、回车发送控制、无尽重试开关和大段文本粘贴阈值。无尽重试默认关闭;开启后网络/临时提供商故障会持续到成功,
+ 显示思考开关、过程显示分段控件、回车发送控制、无尽重试开关和大段文本粘贴阈值。无尽重试默认关闭;开启后网络/临时提供商故障会持续到成功,
但停止按钮仍可取消回合,开启期间可能持续消耗 API 用量。链接打开目标默认使用工作面板浏览器,
可将对话、会话记录和插件页的 HTTP(S) 点击路由到系统浏览器。插件/设置页
若目标是工作面板,会先回到对话再打开(不记入导航栈),避免被遮罩挡住;没有会话时才回退到
@@ -123,17 +123,22 @@
`pi.prompt-enhancement` 插件。插件设置在「插件」页编辑;旧提示词增强偏好的单次迁移见
`04-ux/12-prompt-enhancement.md`。
- **显示思考**是一个开关,以可选的 `showThinking` 布尔值持久化到宿主设置。关闭时
- 仍显示活动思考指示器,并隐藏已完成的推理行和摘要;已存推理仍会保留,重新打开时
- 重新出现。它只影响展示,不改变模型推理配置,也不控制回合过程或活动组的折叠:
+ 隐藏已完成的推理行;仅在推理正在流式输出时保留整段运行的 TextShimmer `Thinking`
+ 指示器,收起的行只显示该指示器,不显示摘录。已存推理仍会保留,重新打开时重新出现。
+ 开启时,平铺显示与命令工具优先中的思考行默认展开,全折叠显示保留已发布的仅活动行
+ 自动展开例外。它只影响展示,不改变模型推理配置,也不控制回合过程或活动组的折叠:
无论开关如何,运行中的过程默认展开,未操作的已完成过程默认收起。旧版
`thinkingDisplayMode` 字段(`detailed` / `compact`)仅为持久化设置兼容性保留,
不再在界面暴露;缺失或未知值显示推理,显式 `compact` 隐藏推理。设置搜索会索引
该行。
-- **不折叠命令**是一个开关,以可选的 `keepCommandsExpanded` 布尔值持久化到宿主设置,
- 缺失时默认开启。开启时,shell 调用保留在它们所运行的工具组旁,作为独立行;关闭时
- 折回这些组,即命令被分离之前的布局。它只影响展示——两种取值都不改变回合渲染的过程
- 披露数量(始终为一个),也不改变工具收到的内容或持久化内容——并且在渲染时读取,
- 因此切换后会立即重绘转录。设置搜索会索引该行。
+- **过程显示**是**显示思考**之后紧邻的分段控件,以可选的 `transcriptDisplayMode`
+ 字段持久化为 `flat`、`command-first` 或 `fully-folded`,标签为「平铺显示」
+ 「命令工具优先」「全折叠显示」;缺失或未知值解析为「全折叠显示」,即 v0.20.0
+ 发布的布局。「平铺显示」只渲染一个外层过程披露,不包含嵌套活动组。「命令工具优先」
+ 保留活动组,但把 `Bash`/run 行提升为独立行;普通助手进度消息或命令都会结束当前组。
+ 「全折叠显示」让命令留在所属组内,只有普通进度文字会拆分活动组。三者都只渲染一个
+ 过程披露,只改变展示,并在渲染时读取,因此切换后立即重绘转录。已弃用的
+ `keepCommandsExpanded` 布尔值不再暴露,也不再参与渲染读取。设置搜索会索引该行。
- 语音绑定(`AppSettings.speech`)**不属于设置页面**(ADR 0291)。宿主仍保留语音能力与
`speech/*` IPC,供插件和已存绑定使用;这里不再提供转写/朗读的服务、协议、模型或音色
选择,设置搜索也不再索引语音相关键。
diff --git a/docs/zh-CN/spec/04-ux/07-ui-design-system.md b/docs/zh-CN/spec/04-ux/07-ui-design-system.md
index 269ea04fe4..0e56551149 100644
--- a/docs/zh-CN/spec/04-ux/07-ui-design-system.md
+++ b/docs/zh-CN/spec/04-ux/07-ui-design-system.md
@@ -710,7 +710,7 @@ Toast enter/exit 保留现有移除合同(`animationend` 于
- 无视差
- 没有连续的背景动画(粒子、波浪);有界的
前台吉祥物循环是显式的空主异常
-- shimmer/skeleton 动画的循环时间不超过 1 秒 — 使用简单的淡入来显示加载状态
+- shimmer/skeleton 动画的循环时间不超过 1 秒 — 使用简单的淡入来显示加载状态。例外:transcript 的 Thinking 指示器使用整段 TextShimmer,周期 1.2s、停止 220ms 淡回(ADR turn-process-and-thinking-display);它不是逐字循环,减少动态效果时静态显示。
- 无反弹效果
- 没有多秒的开机戏剧序列;准备好后立即退出(+最小停留时间)
diff --git a/docs/zh-CN/spec/04-ux/08-component-spec.md b/docs/zh-CN/spec/04-ux/08-component-spec.md
index d6d89adcaa..07c8a7fefd 100644
--- a/docs/zh-CN/spec/04-ux/08-component-spec.md
+++ b/docs/zh-CN/spec/04-ux/08-component-spec.md
@@ -1065,21 +1065,23 @@ SESSIONS [msg+][↕]
该披露包含回合在给出回答之前产生的所有行:普通活动组与 `Bash` 命令行都在其中。因此
每个回合只渲染一个顶层过程披露,只有 Bash 调用的回合也一样;任何命令行都不是该披露的
同级,长回合可以用一次操作收起。末尾回答、助手错误、中止后的末尾部分文字和待处理操作
-卡留在披露之外,无需展开过程即可访问。
-
-在披露内部,普通活动组表示两个进度段落或命令行之间的一段连续工具、搜索或思考活动。
-只有在当前思考偏好下至少有两个可见项时才显示组标题。单项活动直接使用自身披露,被隐藏
-的思考不会制造空包装,委派工作继续使用现有 Task 拓扑作为容器。
-
-`keepCommandsExpanded` 决定命令行在该披露内的位置,默认开启。开启时,`Bash` 和 run
-别名会从所处的组中提取出来,作为披露顶层的独立行渲染;相邻调用保持分离,详情在用户
-打开之前保持收起。关闭时,命令行保留在流程中的原位置,读起来就是所在组的另一行。两种
-取值都不改变披露数量、工具实际收到的内容或持久化内容。
-
-活动组的折叠默认值统一,不依赖任一偏好。拥有当前执行片段的普通活动组在回合运行时默认
-展开,完成时仅在用户未操作的情况下收起;其他已完成组默认收起。若活动组记录过失败或被
-拒工具,尚未被用户接管的活动组会在后续成功恢复期间保持展开,并在回合完成后收起。组
-标题汇总计数、运行状态和问题计数,但不会把失败子项当作整个回合失败。
+卡留在披露之外,无需展开过程即可访问。未操作的过程在完成时收起,只剩最终回答;没有最终
+文字时,过程标题和这些操作面仍会保留。
+
+在披露内部,`过程显示`模式决定活动如何分组。`fully-folded`(默认;缺失或未知值使用
+它)把普通助手进度段落之间的连续工具、搜索或思考片段组为普通活动组,`Bash`/run 别名
+留在其周围的组内。`Task` 委派保留自身拓扑,不会在普通组内重复渲染。`command-first`
+保留这些组,但把每个 `Bash`/run 别名提升为组旁的独立行:相邻调用保持分离,详情在用户
+打开前保持收起,普通助手进度消息或命令都会结束当前组。`flat` 不渲染任何嵌套活动组;
+外层披露按转录顺序列出工具、命令、思考和进度行。在 `command-first` 与 `fully-folded`
+中,只有在当前思考偏好下至少有两个可见项时才显示组标题;单项活动直接使用自身披露,
+被隐藏的思考不会制造空包装。三种模式都只渲染一个顶层过程披露,不改变工具收到的内容或
+持久化内容。
+
+活动组的折叠默认值在各模式间统一,不依赖思考偏好。拥有当前执行片段的普通活动组在回合
+运行时默认展开,完成时仅在用户未操作的情况下收起;其他已完成组默认收起。若活动组记录过
+失败或被拒工具,尚未被用户接管的活动组会在后续成功恢复期间保持展开,并在回合完成后收起。
+组标题汇总计数、运行状态和问题计数,但不会把失败子项当作整个回合失败。
回合披露的标题只陈述回合结果,绝不回显正在处理的具体项,因为 shell 命令或搜索词可能
任意长。它显示 `Failed`、`Stopped`、`Running` 或 `Finished`,优先级依次为失败、停止、
@@ -1090,11 +1092,14 @@ SESSIONS [msg+][↕]
展开的层级共用同一条左边缘;层级由字号与颜色表达,而不是缩进,因此嵌套组标题与命令行
起始位置与回合标题完全一致。
-条目载荷都不会自动展开:工具调用、托管搜索或计划卡片行在用户打开其披露之前始终只是
-标题行,包括 Bash 行——其详情在用户打开之前保持收起。活动组保留各自的自动展开默认值,
-因此进行中的回合仍会展示自己的工作。当 `Show thinking` 偏好关闭时,活动思考指示器保持
-可见,而已完成的推理行和摘要被隐藏,空的纯思考容器被省略;已存推理仍会保留,重新打开
-偏好时重新出现。
+除显示模式的思考默认值外,条目载荷都不会自动展开:工具调用、托管搜索或计划卡片行在用户
+打开其披露之前始终只是标题行,包括 Bash 行——其详情在用户打开之前保持收起。活动组保留各自的自动展开默认值,
+因此进行中的回合仍会展示自己的工作。`Show thinking` 开启时,思考行在「平铺显示」与
+「命令工具优先」中默认展开,仅在用户操作时收起;「全折叠显示」保留已发布的例外:较早的
+行保持收起,只有最后一个活动行在其为当前步骤时展开。展开的思考行显示完整推理 Markdown;
+收起的行只显示 Thinking 指示器,不显示摘要或摘录。`Show thinking` 关闭时,不再渲染任何
+已完成的推理行,仅在推理正在流式输出时保留整段运行的 TextShimmer `Thinking` 指示器,
+并省略空的纯思考容器。已存推理仍会保留,重新打开偏好时重新出现。
活动组、命令行和条目是相互独立的控件。收起祖先会保留下级选择,重新展开时恢复;收起
回合披露会隐藏其下所有行,重新展开时恢复用户此前展开的组。展开父级不会展开所有后代。
@@ -1540,14 +1545,15 @@ sorting, new settings, persistence, or host protocol is introduced.
参数提示、状态和结果的可读呈现。遵循D071
并且故意不是一张高级卡。
-回合过程是一个披露。在该披露内部,两个进度段落或命令行之间的一段连续工具、搜索或思考
-活动,仅在当前思考偏好下有两个及以上可见项时成为普通处理组。单项活动直接使用自身披露,
-Task 拓扑继续使用原有容器。`Bash` 和 run 别名保留在回合披露内:`keepCommandsExpanded`
-开启(默认)时,每一项作为组旁的独立行渲染,相邻调用保持分离;关闭时,命令行留在所在组
-的流程中。只有 Bash 调用的回合仍保留其唯一披露。回合活动期间,拥有当前执行片段的普通组
-默认展开;未操作的组在完成时自动收起。这些组默认值不依赖思考偏好。条目载荷都不会自动
-展开:工具调用、托管搜索或计划行在用户打开之前始终只是标题行,无论它位于活动组的哪一项,
-包括详情在打开前保持收起的 Bash 行。
+回合过程是一个披露。`fully-folded`(默认)中,普通进度段落之间的一段连续工具、搜索或
+思考活动,仅在当前思考偏好下有两个及以上可见项时成为普通处理组,`Bash`/run 别名留在
+所属组内。`command-first` 中组仍会渲染,但每个 `Bash`/run 别名作为组旁的独立行,进度
+消息或命令会结束当前组。`flat` 中不渲染组,各行在外层披露内保持转录顺序。单项活动直接
+使用自身披露,Task 拓扑继续使用原有容器。只有 Bash 调用的回合仍保留其唯一披露。回合
+活动期间,拥有当前执行片段的普通组默认展开;未操作的组在完成时自动收起。这些组默认值
+不依赖思考偏好。除显示模式的思考默认值外,条目载荷都不会自动展开:工具调用、托管搜索或
+计划行在用户打开之前始终只是标题行,无论它位于活动组的哪一项,包括详情在打开前保持收起
+的 Bash 行。
组标题在活动时显示 `Processing · 12s`,完成后显示 `Processed for 12s`,并提供有界
条目与问题计数。展开后显示有序活动行及其相互独立的结果披露。失败子项仍在自己的
@@ -1575,11 +1581,11 @@ ToolCallRow 上显示错误,但不会让组或整个回合成为终端失败
- 多项组标题拥有经过时间以及条目和问题计数,并在完成后保留在转录中。活动组默认展开,
完成时仅在用户未操作时收起;其他已完成组默认收起。这些默认值不依赖思考偏好。单项
活动没有组标题。
-- 工具/搜索载荷保持收起,直到用户打开;没有任何行会自动展开,因此
- 最后一项为思考时绝不会选择更早的工具。活动思考遵循自身披露策略,绝不会展开同级载荷。
-- `Bash` 和 run 行由回合过程披露展开。`keepCommandsExpanded` 开启时,它们位于披露顶层、
- 组旁,相邻行保持独立;关闭时,它们渲染在所属组内。它们绝不是回合过程的同级,详情在
- 用户打开之前保持收起。
+- 工具/搜索载荷保持收起,直到用户打开;没有任何工具行会自动展开,因此
+ 最后一项为思考时绝不会选择更早的工具。思考行遵循显示模式的默认展开规则,绝不会展开同级载荷。
+- `Bash` 和 run 行由回合过程披露展开。`fully-folded` 中它们位于所属组内;
+ `command-first` 中它们位于披露顶层、组旁,相邻行保持独立;`flat` 中没有组,它们
+ 在披露内按转录顺序排列。它们绝不是回合过程的同级,详情在用户打开之前保持收起。
- 处理组跨越完整可用的辅助列,因此扩展
即使标头或有效负载很短,结果详细信息也会保持可用宽度。
- 可见标签是自然语言操作(`Read`、`Ran`、`Searched`),
@@ -1635,15 +1641,16 @@ pi-ai 结果信封携带 `details` 中的结构化有效负载并重复它
| 状态 | 标头处理 | 扩展内容 |
|---|---|---|
-| 运行中 | 渐进动作配可读文字与脉冲标记;`run` 行还显示旋转器,并让 `Working…` 旁状态点脉冲 | 活动多项组默认展开;没有条目载荷会自动展开;活动思考遵循自身指示器/披露策略 |
+| 运行中 | 渐进动作配可读文字与脉冲标记;`run` 行还显示旋转器,并让 `Working…` 旁状态点脉冲 | 活动多项组默认展开;除显示模式的思考默认值外,没有工具/搜索载荷会自动展开;活动思考遵循自身指示器/披露策略 |
| 成功 | 过去时动作加结果芯片;除 `run` 行状态点和 `Done` 外不显示绿色成功徽标 | 先显示结果块,再显示尚未呈现的参数;未操作的活动组在完成时收起,手动组与条目选择保留 |
| 错误 | 过去时动作加紧凑危险状态;详情默认收起,只在用户请求时展开。只要命令退出码非零,`run` 行就处于此状态,不受调用报告影响(D227) | 先显示错误说明,再显示参数 |
| 被拒绝 | 静音 `Denied` 状态;载荷在请求前保持关闭 | 可用时显示权限结果 |
### 9.6 互动
-- 单击条目只展开/收起该结果载荷。载荷默认关闭。没有载荷会自动展开,因此只有用户打开
- 的那一行是展开的;失败和被拒行行为相同。
+- 单击条目只展开/收起该结果载荷。工具/搜索载荷默认关闭。没有工具/搜索载荷会自动展开
+ (思考行遵循上文的显示模式默认值),因此只有用户打开的那一行是展开的;失败和被拒行
+ 行为相同。
- 单击处理标题只展开/收起该有序活动列表。活动组默认展开,完成时仅在用户未操作的情况下
收起;其他已完成组默认收起。展开组不会展开所有条目。
- 单击或用键盘激活展开思考、工具详情、委派工作或处理步骤旁的左侧栏,只收起所属
diff --git a/docs/zh-CN/spec/04-ux/09-interaction-patterns.md b/docs/zh-CN/spec/04-ux/09-interaction-patterns.md
index 29f46e1f75..e448c97267 100644
--- a/docs/zh-CN/spec/04-ux/09-interaction-patterns.md
+++ b/docs/zh-CN/spec/04-ux/09-interaction-patterns.md
@@ -703,24 +703,28 @@
自动展开。
- 统一的展示为每个已加载的助手回合提供一个可折叠的过程披露。它包含思考、工具、托管搜索、
中间进度文字以及该回合的 `Bash`/run 行;末尾回答、助手错误和中止后的末尾文字留在
- 披露之外。
-- 连续活动片段仅在当前思考偏好下至少有两个可见项时获得组披露。进度文字或命令行结束
- 该片段,单项活动直接使用自身披露,被隐藏的思考不会制造多余组;Task 拓扑保持独立。
- `keepCommandsExpanded`(默认开启)只决定命令行在该披露内的位置:开启时把 `Bash` 和
- run 别名从组中提取为顶层独立行,相邻调用保持分离;关闭时命令行留在所在组的流程中。
- 两种取值都不会增加披露,也不会让命令行落在回合过程之外。
+ 披露之外。`过程显示`模式选择布局:`flat` 没有嵌套组,`command-first` 将命令提升为
+ 独立行,`fully-folded`(默认)让命令留在所属组内。
+- 连续活动片段仅在当前思考偏好下至少有两个可见项时获得组披露,且只出现在
+ `command-first` 或 `fully-folded` 中。`fully-folded` 由普通助手进度文字结束片段;
+ `command-first` 由普通助手进度消息或命令结束片段。单项活动直接使用自身披露,被隐藏的
+ 思考不会制造多余组;Task 拓扑保持独立。任何模式都不会增加第二个顶层披露,也不会让
+ 命令行落在回合过程之外。
- 活动普通组默认展开,完成时仅在用户未操作的情况下收起;其他已完成组默认收起,而记录过
- 失败或被拒工具的未接管活动组会在恢复期间保持展开。这些组默认值不依赖任一偏好。收起
+ 失败或被拒工具的未接管活动组会在恢复期间保持展开。这些组默认值不依赖思考偏好。收起
回合披露会隐藏其下所有组与命令行,但不会清除它们的选择;重新展开时恢复用户此前展开
的组。
- 回合标题按失败、停止、执行中、已完成的优先级显示 `Failed`、`Stopped`、`Running` 或
`Finished`;执行期间压缩上下文与恢复会各自命名,当前步骤为推理时显示 `Thinking`;
转录未记录时长时不显示时长;标题绝不回显当前命令或查询。嵌套组标题与命令行共用它的
左边缘,层级由字号和颜色而不是缩进表达。
-- 条目载荷都不会自动展开:工具调用、托管搜索或计划卡片行在用户打开之前始终只是标题行,
- 包括最后一个活动组的字面最后一项。组的默认展开不变,因此最后一项为思考时
- 绝不会向前回扫。当 `Show thinking` 关闭时,所有条目载荷保持关闭,已完成的推理正文与
- 摘要被隐藏,同时活动思考指示器保持可见;已存推理仍会保留,重新打开偏好时重新出现。
+- 除显示模式的思考默认值外,条目载荷都不会自动展开:工具调用、托管搜索或计划卡片行在
+ 用户打开之前始终只是标题行,包括最后一个活动组的字面最后一项。组的默认展开不变,因此
+ 最后一项为思考时绝不会向前回扫。`Show thinking` 开启时,思考行在「平铺显示」与
+ 「命令工具优先」中默认展开,仅在用户操作时收起;「全折叠显示」保留已发布的仅活动行
+ 自动展开例外。收起的行只显示 Thinking 指示器,不显示摘录。`Show thinking` 关闭时,
+ 不再渲染任何已完成的推理行,仅在推理流式输出期间保留整段运行的 TextShimmer
+ `Thinking` 指示器;已存推理仍会保留,重新打开偏好时重新出现。
- 激活组或条目标题只切换该层级。收起父级会保留子级状态,重新展开时恢复,
同级组彼此独立;展开父级不是“全部展开”。
- 手动操作条目会把所属组标记为用户接管,但不会切换该组。流式更新和完成不会
diff --git a/docs/zh-CN/spec/06-delivery/04-e2e-test-plan.md b/docs/zh-CN/spec/06-delivery/04-e2e-test-plan.md
index 20fdd2d13e..f292bc3718 100644
--- a/docs/zh-CN/spec/06-delivery/04-e2e-test-plan.md
+++ b/docs/zh-CN/spec/06-delivery/04-e2e-test-plan.md
@@ -1358,32 +1358,33 @@ task-candidate E2E 从请求工作树运行,但使用主工作区已经准备
多项命令片段。2) 检查已展开的活动组;在更多输出到达时手动收起该组。3) 完成回合,
确认恰好一个过程披露拥有全部回答前的行;收起它并确认其下的组与命令行一并收起,再
重新展开并确认组选择恢复。4) 展开一个已完成组和其中一个条目,复制输出,收起并重新
- 展开该组,再独立打开同级组。5) 切换 `Don't collapse commands` 关闭与开启,检查命令行
- 的渲染位置,同时确认披露数量始终为一个。6) 分别检查单项片段,以及最后一个活动组的
- 字面最后一项为工具/搜索、思考、失败工具和被拒工具。7) 关闭并重新打开
- `Show thinking`,检查活动思考、失败后恢复及完成状态。8) 在保留窗格内重新挂载行,
- 然后重载渲染器并重新打开会话。
+ 展开该组,再独立打开同级组。5) 在 `过程显示` 的「平铺显示」「命令工具优先」
+ 「全折叠显示」之间切换,检查分组、组边界、命令行的渲染位置以及披露数量。6) 分别检查
+ 单项片段,以及最后一个活动组的字面最后一项为工具/搜索、思考、失败工具和被拒工具。
+ 7) 关闭并重新打开 `Show thinking`,检查活动思考、失败后恢复及完成状态。8) 在保留窗格内
+ 重新挂载行,然后重载渲染器并重新打开会话。
- **预期**:一个回合只渲染一个过程披露,其中包含全部回答前的行,`Bash`/run 行也不例外;
末尾回答、助手错误和中止后的末尾文字留在披露之外,待处理操作也一样。活动组默认展开,
并且只在用户未操作时于完成后收起;其他已完成组默认收起。收起回合披露会一并收起其下
- 的组与命令行,重新展开则恢复用户的组选择。`Don't collapse commands` 开启(默认)时,
- 命令行作为组旁的顶层独立行渲染,相邻调用保持分离,详情在打开前保持收起;关闭时它们
- 折回所属组。两种取值都不改变披露数量。单项没有组包装。没有任何条目载荷会自动展开:
- 工具/搜索行在用户打开之前保持标题行,最后一个活动组的字面最后一项也不例外,而思考项
- 保留自身的叶子默认值。回合标题按 `Running`、`Finished`、`Stopped` 或 `Failed` 报告
- 结果,失败与停止优先于正常完成,当前步骤为推理时显示 `Thinking`,绝不回显当前命令;
- 转录未记录时长时不显示时长。当 `Show thinking` 关闭时,活动思考指示器保持可见,已完成的
- 推理正文与摘要被隐藏,空的
- 纯思考容器被省略;重新打开时恢复。父级、子级和同级选择彼此独立;收起/重新展开父级
- 会保留后代,流式更新和完成不会覆盖用户接管的选择。保留窗格中的重新挂载保留选择;
- 渲染器重启重新应用默认值,但工具名称、参数、结果和状态仍会恢复。组标题显示有界运行
- 和问题摘要,不会把整个回合标记为失败。
+ 的组与命令行,重新展开则恢复用户的组选择。「全折叠显示」(默认)中,命令行留在所属组内,
+ 只有普通助手进度文字会拆分活动组;「命令工具优先」中,命令行作为组旁的独立行渲染,
+ 相邻调用保持分离,详情在打开前保持收起,普通助手进度消息或命令会结束当前组;
+ 「平铺显示」中不渲染嵌套组,各行在外层披露内保持转录顺序。所有模式都只渲染一个披露。
+ 单项没有组包装。除显示模式的思考默认值外,没有任何条目载荷会自动展开:工具/搜索行在
+ 用户打开之前保持标题行,而思考项绝不会选择更早的工具。回合标题按 `Running`、`Finished`、
+ `Stopped` 或 `Failed` 报告结果,失败与停止优先于正常完成,当前步骤为推理时显示
+ `Thinking`,绝不回显当前命令;转录未记录时长时不显示时长。当 `Show thinking` 关闭时,
+ 不再渲染任何已完成的推理行,仅在推理流式输出期间保留活动的 TextShimmer `Thinking`
+ 指示器;重新打开时恢复。父级、子级和同级选择彼此独立;收起/重新展开父级会保留后代,
+ 流式更新和完成不会覆盖用户接管的选择。保留窗格中的重新挂载保留选择;渲染器重启重新
+ 应用默认值,但工具名称、参数、结果和状态仍会恢复。组标题显示有界运行和问题摘要,不会
+ 把整个回合标记为失败。
- **链接规格**:`04-ux/01-ui-ia.md`、`04-ux/07-ui-design-system.md`、
`04-ux/08-component-spec.md`、`04-ux/09-interaction-patterns.md`
- **验收**:C(聊天流)、E(工具)、F(持久性)
- **里程碑**:M3
-- **状态**:草案。单元与样式检查覆盖单披露、命令折叠和标题规则;本场景仍是转录重新加载
- 的预期人工行为。
+- **状态**:草案。单元与样式检查覆盖显示模式、思考默认值与标题规则;本场景仍是转录
+ 重新加载的预期人工行为。
#### E2E-TRANSCRIPT-invalid-utf8-window-remains-readable
@@ -9204,39 +9205,55 @@ Follow the [current S3 acceptance scenario](/spec/06-delivery/04-e2e-test-plan#e
### E2E-CHAT-turn-process-and-thinking-display
- **先决条件:** 一个回合包含进度段落 A、多次搜索及思考、进度段落 B、多条命令及
- 思考和最终回答;`Show thinking` 偏好开启与关闭两种状态;`Don't collapse commands`
- 偏好开启与关闭两种状态;旧版消息级转录搜索目标。
-- **步骤:** 确认活动组默认展开,让同一回合在无人操作时完成,并确认组收起。另一个
- 回合中,明确展开已完成组,并确认后续更新仍保留该选择;随后收起回合披露并确认组随之
- 收起,再重新展开并确认组选择恢复。关闭 `Show thinking`,确认活动思考指示器仍然可见、
- 已完成的推理行和摘要消失且不残留空的纯思考容器;再重新打开,确认已完成的推理行恢复。
- 关闭 `Don't collapse commands`,确认命令行折回所属组且回合仍只渲染一个披露;再开启,
- 确认独立行恢复。确认标题分别显示执行中、已完成、已停止或失败,执行期间压缩上下文与
- 恢复会各自命名,未记录时长时不显示时长,且绝不回显当前命令。检查嵌套路径,包括相互
- 独立的组/条目切换、父级收起与恢复、单项片段、字面最后一项选择、失败/被拒/恢复、
- 保留窗格重新挂载、命令行详情在打开前保持收起,以及旧版搜索定位。
-- **预期:** 一个回合只渲染一个过程披露,包含全部回答前的行,命令行也不例外;最终回答、
- 助手错误、中止后的末尾文字和待处理操作留在披露之外。活动组默认展开;未操作的组在回合
- 完成时收起,用户明确选择的状态继续保留,并在外层披露重新展开时恢复。这些组默认值不
- 依赖 `Show thinking` 偏好。`Don't collapse commands` 开启时,命令行作为组旁的顶层独立
- 行渲染,相邻行保持独立,详情在用户打开前保持收起;关闭时它们折回所属组。两种取值都
- 不改变披露数量。回合标题按执行中、已完成、已停止、失败的顺序报告,失败与停止优先于
- 正常完成,当前步骤为推理时显示 `Thinking`,执行期间压缩上下文和恢复会各自命名,未记录
- 时长时不显示时长,且绝不回显当前命令。嵌套组标题与命令行共用回合标题的左边缘。
- `Show thinking` 关闭时,活动思考指示器
- 保持可见,已完成的推理行和摘要被隐藏,空的纯思考容器被省略;重新打开时恢复。单项没有
- 组。没有任何条目载荷会自动展开:工具/搜索行在用户打开之前保持收起,而思考项保留自身
- 的叶子默认值。父级、子级和同级状态相互独立;窗格拥有的用户选择跨更新、偏好切换和重新
- 挂载保留,渲染器重启后重新应用默认值。搜索只展开拥有目标消息的回合过程和活动组,每个
- 请求应用一次;条目级精确定位不在本次范围内,被偏好隐藏的推理会保持隐藏,直到用户打开
- `Show thinking`。已保存的 `showThinking` 跨重启保留;缺失值回退到旧版
- `thinkingDisplayMode`(`compact` 隐藏,`detailed`/未知/缺失显示)。
+ 思考和最终回答;`Show thinking` 偏好开启与关闭两种状态;`过程显示` 偏好分别为
+ 「平铺显示」「命令工具优先」「全折叠显示」;重启后保留已保存的设置;旧版消息级
+ 转录搜索目标。
+- **步骤:** 确认活动组默认展开,让同一回合在无人操作时完成,并确认过程收起,只剩最终
+ 回答(以及错误或待处理操作面)。另一个回合中,明确展开已完成组,并确认后续更新仍保留
+ 该选择;随后收起回合披露并确认组随之收起,再重新展开并确认组选择恢复。在「全折叠显示」
+ 中,确认命令行留在所属活动组内,且只有普通助手进度文字会拆分活动组。在「命令工具优先」
+ 中,确认 `Bash`/run 行作为组旁的独立行渲染,普通助手进度消息或命令会结束当前组,
+ 相邻调用保持分离,思考行默认展开。在「平铺显示」中,确认不渲染嵌套活动组,外层披露按
+ 转录顺序列出工具、命令、思考和进度行,工具详情保持收起。在每种模式中确认回合只渲染
+ 一个外层披露,收起它会隐藏、重新展开会恢复其下的行。关闭 `Show thinking`,确认不再
+ 渲染任何已完成的推理行,仅在推理流式输出期间保留整段运行的 TextShimmer `Thinking`
+ 指示器,不使用转圈、脉冲圆点或逐字符动画,减少动态效果时保持静态;重新打开后确认
+ 已完成的推理行恢复。分别选择每个 `过程显示` 值并重启,确认设置保留;移除已保存的值,
+ 确认默认使用「全折叠显示」。确认标题分别显示执行中、已完成、已停止或失败,执行期间
+ 压缩上下文与恢复会各自命名,未记录时长时不显示时长,且绝不回显当前命令。检查嵌套路径,
+ 包括相互独立的组/条目切换、父级收起与恢复、单项片段、字面最后一项选择、失败/被拒/
+ 恢复、保留窗格重新挂载、命令行详情在打开前保持收起,以及旧版搜索定位。
+- **预期:** 一个回合只渲染一个过程披露,包含全部回答前的行,最终回答、助手错误、中止后
+ 的末尾文字和待处理操作留在披露之外;没有最终回答文字时,过程标题和这些错误或待处理
+ 操作面仍然保留。未被操作的披露在完成时收起。「平铺显示」中没有嵌套活动组,活动工具、
+ 命令、思考和进度行按转录顺序排列,工具详情保持收起。「命令工具优先」中,`Bash`/run 行
+ 作为组旁的独立行,相邻调用保持分离,普通助手进度消息或命令会结束当前组,因此中间进度
+ 段落和每条命令都会开启新组。「全折叠显示」(默认)中,命令行留在所属组内,只有普通
+ 助手进度文字会拆分活动组,因此中间进度段落会结束前一组,后续活动开启新组。只有在至少
+ 两个可见项时才显示组;单项没有组。思考行在「平铺显示」与「命令工具优先」中默认展开;
+ 「全折叠显示」保留已发布的例外:较早的行保持收起,只有最后一个活动行在其为当前步骤时
+ 展开,完成后收起。用户明确选择的状态继续保留,并在外层披露重新展开时恢复;这些组默认值
+ 不依赖 `Show thinking` 偏好。回合标题按执行中、已完成、已停止、失败的顺序报告,失败与
+ 停止优先于正常完成,当前步骤为推理时显示 `Thinking`,执行期间压缩上下文和恢复会各自
+ 命名,未记录时长时不显示时长,且绝不回显当前命令。嵌套组标题与命令行共用回合标题的
+ 左边缘。`Show thinking` 关闭时,不再渲染任何已完成的推理行,仅在推理流式输出期间保留
+ 整段运行的 TextShimmer `Thinking` 指示器;重新打开时恢复。除显示模式的思考默认值外,
+ 没有任何条目载荷会自动展开:工具/搜索行在用户打开之前保持收起。父级、子级和同级状态
+ 相互独立;窗格拥有的用户选择跨更新、偏好切换和重新挂载保留,渲染器重启后重新应用默认值。
+ 搜索只展开拥有目标消息的回合过程,以及存在时的活动组,每个请求应用一次;条目级精确定位
+ 不在本次范围内,被偏好隐藏的推理会保持隐藏,直到用户打开 `Show thinking`。已保存的
+ `transcriptDisplayMode` 跨重启保留,缺失或未知值解析为「全折叠显示」;已保存的
+ `showThinking` 跨重启保留,缺失值回退到旧版 `thinkingDisplayMode`(`compact` 隐藏,
+ `detailed`/未知/缺失显示)。
- **2026-09-20 变更的验证范围:** 本次变更只包含多级折叠与活动组呈现;精确转录搜索
定位不在本次范围内,保持原有搜索行为。
-- **自动化:** `pnpm test:e2e:transcript` 覆盖默认及运行中到完成时的过程披露行为;
- `pnpm test:e2e:transcript-disclosure` 验证手动展开状态保留和视口锚定;
- `apps/desktop/test/turn-process.test.mjs` 覆盖过程默认值,
- `apps/desktop/test/thinking-visibility.test.mjs` 覆盖 `showThinking`/旧版解析优先级。
+- **自动化:** `pnpm test:e2e:transcript` 覆盖「命令工具优先」与「全折叠显示」布局
+ 以及运行中到完成时的过程披露行为;`pnpm test:e2e:transcript-disclosure` 验证手动
+ 展开状态保留和视口锚定;`apps/desktop/test/turn-process.test.mjs` 覆盖模式分段,
+ `apps/desktop/test/transcript-display-modes-ui.test.mjs` 覆盖渲染层模式接线、
+ 思考默认值与 TextShimmer,`apps/desktop/test/transcript-display-mode-settings.test.mjs`
+ 覆盖设置行与搜索索引,`apps/desktop/test/settings-roundtrip.test.mjs` 覆盖规范化、
+ 写入校验与全折叠默认值。
- **规格:** 04-ux/06-settings-ia、04-ux/08-component-spec、
04-ux/09-interaction-patterns;ADR turn-process-and-thinking-display。
### E2E-CONTEXT-estimate-calibration-stays-safe
diff --git a/docs/zh-CN/spec/08-meta/decisions-log.md b/docs/zh-CN/spec/08-meta/decisions-log.md
index ab5cdb1f4c..44972d4d09 100644
--- a/docs/zh-CN/spec/08-meta/decisions-log.md
+++ b/docs/zh-CN/spec/08-meta/decisions-log.md
@@ -335,7 +335,7 @@
| D602 | 崩溃转储留在数据目录 | **Electron 的 Crashpad 报告器在 `ready` 之前以本地模式启动(`uploadToServer: false`)。转储放在 `/crash-dumps`,而不是 Electron 默认的 `userData` crashDumps 路径,因此 `PI_DESKTOP_DATA_DIR` profile 不会与其它安装共用转储。下一次持有单实例锁的启动会为新于 `crash-dumps.json` 的转储写一条 `diagnostics` 记录,按 Crashpad `ptype` 分类:任一新转储属于 browser/main 进程则为 `error`,已恢复的 renderer/GPU/utility 崩溃为 `warn`。host-core 与 sidecar 崩溃仍走监督器路径。不上传,不改 IPC,不改 schema。** | 崩溃留下的 minidump 无人读取。Crashpad 也会记录已恢复的渲染进程崩溃,因此下次启动用 `error` 声称上次运行已死是错的;而数据目录之外的转储会逃出 `PI_DESKTOP_DATA_DIR` 隔离。 |
| D619 | 复制公式得到的是它的 TeX 源码 | **仅渲染层:当选区覆盖到渲染出来的公式时,`text/plain` 从 MathML `annotation` 写出——行内 `$…$`,块级 `$$…$$` 独占行,也就是 `lib/latex-math.ts` 把 `\(…\)` 和 `\[…\]` 归一到的那组定界符,且每组定界符都像代码段的围栏那样加长到盖过公式内部出现的最长同字符串——而不是 KaTeX 画的那两棵树。落在公式内部的切口会扩展成整个公式。只有公式被改写:归约后的克隆经由 `Selection.toString()`——复制自己跑的那个序列化器——读回,因此同处一个选区的正文、列表、表格和代码块保留平台自己的读法,包括 `innerText` 会写出、而复制本就会略过的 `user-select: none` 界面零件。不含公式的选区,以及在选区所在位置之外触发的复制,整份交回平台。只写一种 flavour:`text/plain`。接管事件同时丢掉了平台的 `text/html`,且不再写回——归约后的克隆是应用自己的标记,写回去会带上文本读法已略过的 `user-select: none` 界面零件;而改为携带渲染结果则会把每个公式粘贴两遍,因为隐藏 MathML 树的只有 KaTeX 自己的样式表,样式表不会随剪贴板一起走。只有一个由外壳持有的文档级 `copy` 监听器,记录区的右键复制经由同一个模块读取同一个选区。** | 公式粘出来是它的字形,而且每棵渲染树各一份,无法带进 LaTeX 文档或别的 Markdown 编辑器(issue #414)。ADR 0268 当年移除「引用」的理由正是 OS 剪贴板可以替代,那剪贴板就得真的装着源码。 |
| D620 | pi-ai 内置的 API-key 服务成为命名预设 | **向 `NAMED_ENDPOINT_PRESETS` 新增十五条命名预设——Ant Ling、Baseten、Cerebras、Hugging Face、Meta(`responses`)、MiniMax(国际)、Moonshot AI(国际)、NVIDIA、OpenCode Zen、Vercel AI Gateway、Qwen Token 套餐(`alibaba-token-plan`)、Qwen Token 套餐(中国)、小米 Token 套餐(中国/欧洲/新加坡)——各自使用官方主机名;models.dev 键与 pi-ai 提供方 id 不同的那几条,把 pi-ai id 保留为别名。八个内置提供方仍作例外并写明原因:Amazon Bedrock、Azure OpenAI、Cloudflare AI Gateway、Cloudflare Workers AI、Google Vertex AI(URL 里带账户或区域),GitHub Copilot 与 OpenAI Codex(以厂商账号行提供),以及 Radius(这里的 `pi_messages` 仅限账号)。pi-ai 升级后若某提供方既未被覆盖也不在例外中,`packages/agent-runtime/src/pi-ai-provider-sync.test.ts` 会失败。不改协议、存储或 IPC。** | pi-ai 其他能力本就可达,但服务目录的 API-key 一半靠手工维护,已经跟库自带的提供方列表脱节(ADR 0307)。 |
-| D668 | 每回合一个过程披露,并提供命令折叠偏好 | **修订 D661 / `turn-process-and-thinking-display` ADR:每个回合渲染一个顶层过程披露,包含回答前的全部行,`Bash`/run 行也不例外;回答留在披露之外。`Bash` 与 run 别名不再被排除在所有折叠容器之外。可选的布尔值 `AppSettings.keepCommandsExpanded`(缺失即开启)决定命令行是放在其运行所在的组旁,还是留在组内;两种取值都只渲染一个披露。该偏好在渲染时读取,而不是在构建转录条目时读取,因此切换后立即重绘——投影缓存只以消息和压缩为键。披露标题按失败/停止/执行中/已完成的优先级报告,且绝不回显当前条目;披露与它展开的层级共用一条左边缘。`keepCommandsExpanded` 加入可移植应用字段。无 Host 协议、持久化 schema、权限或插件契约变更。见修订后的 ADR、`04-ux/06-settings-ia.md`、`04-ux/08-component-spec.md`、`04-ux/09-interaction-patterns.md` 与 E2E-CHAT-turn-process-and-thinking-display。** | 按时间顺序的分段把同一回合拆成答案上方多个并列披露,而始终可见的命令行也无法被偏好旧分组布局的读者关闭;一个披露加上仅影响展示的偏好同时满足两种需求,且不改变工具收到的内容或持久化内容。 |
+| D668 | 每回合一个过程披露,并提供三种转录显示模式 | **修订 D661 / `turn-process-and-thinking-display` ADR:每个回合渲染一个顶层过程披露,包含回答前的全部行;回答留在披露之外。`AppSettings.transcriptDisplayMode` 选择布局:`flat` 不渲染嵌套活动组,`command-first` 将 `Bash`/run 行作为活动组旁的独立行,`fully-folded`(缺失或无效值的默认)让命令留在所属组内,且只有普通助手进度文字会拆分活动组。该模式在渲染时读取,因此切换后立即重绘——投影缓存只以消息和压缩为键。披露标题按失败/停止/执行中/已完成的优先级报告,且绝不回显当前条目;披露与它展开的层级共用一条左边缘。`transcriptDisplayMode` 加入可移植应用字段;`keepCommandsExpanded` 已弃用,仅为持久化设置兼容性保留,不再暴露,也不再参与渲染读取。无 Host 协议、持久化 schema、权限或插件契约变更。见修订后的 ADR、`04-ux/06-settings-ia.md`、`04-ux/08-component-spec.md`、`04-ux/09-interaction-patterns.md` 与 E2E-CHAT-turn-process-and-thinking-display。** | 按时间顺序的分段把同一回合拆成答案上方多个并列披露,而布尔命令折叠偏好只能表达两种布局;三种模式覆盖平铺、命令优先与已发布的分组视图,且不改变工具收到的内容或持久化内容。 |
## M0. 模型目录决策
@@ -5490,17 +5490,23 @@ Markdown 源码,不是 `text/html` 负载;对禁用行内 HTML 的外部编
schema 或迁移。设置读取通过渲染层 API 规范化应用这些默认值。见
`04-ux/01-ui-ia.md`、`04-ux/06-settings-ia.md` 与 E2E-266。
-## 2026-10-21 —— 每回合一个过程披露与命令折叠偏好(D668)
+## 2026-10-21 —— 每回合一个过程披露与三种转录显示模式(D668)
- D668 修订 D661 / `turn-process-and-thinking-display` ADR:每个回合现在渲染一个顶层
- 过程披露,包含回答前的全部行,`Bash`/run 行也不例外。命令行不再是披露的同级;末尾
- 回答、助手错误、中止后的末尾文字和待处理操作面留在披露之外。
-- `AppSettings.keepCommandsExpanded`(缺失即开启)决定命令行是提取到其运行所在的组旁,
- 还是留在组内。该偏好在渲染时读取,而不是在构建转录条目时读取,因此切换后立即重绘;
- 两种取值都只渲染一个披露。
-- 披露标题按失败/停止/执行中/已完成的优先级报告,执行期间压缩上下文与恢复会各自
- 命名,未记录时长时不显示为零,且绝不回显当前条目。披露与它展开的层级共用一条左边缘。
-- `keepCommandsExpanded` 加入可移植应用字段。已由 `apps/desktop/test/turn-process.test.mjs`、
- `apps/desktop/test/transcript-style.test.mjs` 与交互式转录探针覆盖。见修订后的 ADR、
+ 过程披露,包含回答前的全部行。命令行不再是披露的同级;末尾回答、助手错误、中止后的
+ 末尾文字和待处理操作面留在披露之外。
+- `AppSettings.transcriptDisplayMode` 选择布局。`flat` 不渲染嵌套活动组,按转录顺序列出
+ 各行。`command-first` 保留活动组,但把 `Bash`/run 行提升为独立行,普通进度消息或命令
+ 会结束当前组。`fully-folded` 是缺失或无效值的默认,让命令行留在所属组内,只有普通助手
+ 进度文字会拆分活动组。该模式在渲染时读取,因此切换后立即重绘。
+- `showThinking` 开启时,`flat` 与 `command-first` 中的思考行默认展开;`fully-folded`
+ 保留已发布的例外,只有最后一个活动行在其为当前步骤时展开。关闭偏好时不再渲染任何
+ 已完成的推理行,仅在推理流式输出期间保留整段运行的 TextShimmer `Thinking` 指示器。
+- `keepCommandsExpanded` 已弃用,仅为持久化设置兼容性保留;不再暴露,也不再参与渲染
+ 读取。披露标题、左边缘与窗格拥有的披露记忆保持不变。
+- 已由 `apps/desktop/test/turn-process.test.mjs`、
+ `apps/desktop/test/transcript-display-modes-ui.test.mjs`、
+ `apps/desktop/test/transcript-display-mode-settings.test.mjs` 与
+ `apps/desktop/test/settings-roundtrip.test.mjs` 覆盖。见修订后的 ADR、
`04-ux/06-settings-ia.md`、`04-ux/08-component-spec.md`、
`04-ux/09-interaction-patterns.md` 与 E2E-CHAT-turn-process-and-thinking-display。
diff --git a/packages/i18n/src/locales/de/index.ts b/packages/i18n/src/locales/de/index.ts
index a8de529887..2a4354cfd6 100644
--- a/packages/i18n/src/locales/de/index.ts
+++ b/packages/i18n/src/locales/de/index.ts
@@ -1455,6 +1455,11 @@ sklm: {
"thinkingDisplayCompact": "Kompakt",
"showThinking": "Denkprozess anzeigen",
"showThinkingDesc": "Zeigt den Denkprozess des Modells. Wenn aus, bleibt die Live-Denk-Anzeige sichtbar und abgeschlossene Denkzeilen und Auszüge werden ausgeblendet.",
+ "transcriptDisplayMode": "Prozessanzeige",
+ "transcriptDisplayModeDesc": "Legt fest, wie der Assistentenprozess im Transkript gruppiert wird.",
+ "transcriptDisplayModeFlat": "Flach",
+ "transcriptDisplayModeCommandFirst": "Befehle zuerst",
+ "transcriptDisplayModeFullyFolded": "Vollständig eingeklappt",
"keepCommandsExpanded": "Befehle nicht einklappen",
"keepCommandsExpandedDesc": "Shell-Aufrufe bleiben in eigenen Zeilen, statt in die umgebende Werkzeuggruppe eingeklappt zu werden.",
"contextUsageDisplay": "Kontextnutzung-Anzeige",
diff --git a/packages/i18n/src/locales/en/index.ts b/packages/i18n/src/locales/en/index.ts
index 4cd59d3c29..a82506d836 100644
--- a/packages/i18n/src/locales/en/index.ts
+++ b/packages/i18n/src/locales/en/index.ts
@@ -1469,6 +1469,11 @@ sklm: {
thinkingDisplayCompact: "Compact",
showThinking: "Show thinking",
showThinkingDesc: "Show the model's reasoning. Off keeps the live thinking indicator visible and hides completed reasoning rows and excerpts.",
+ transcriptDisplayMode: "Transcript display",
+ transcriptDisplayModeDesc: "Choose how the assistant process is grouped in the transcript.",
+ transcriptDisplayModeFlat: "Flat",
+ transcriptDisplayModeCommandFirst: "Commands first",
+ transcriptDisplayModeFullyFolded: "Fully folded",
keepCommandsExpanded: "Don't collapse commands",
keepCommandsExpandedDesc: "Keep shell calls on their own rows instead of folding them into the surrounding tool group.",
contextUsageDisplay: "Context usage readout",
diff --git a/packages/i18n/src/locales/es/index.ts b/packages/i18n/src/locales/es/index.ts
index e36c4cf05d..a235bc818e 100644
--- a/packages/i18n/src/locales/es/index.ts
+++ b/packages/i18n/src/locales/es/index.ts
@@ -1455,6 +1455,11 @@ sklm: {
"thinkingDisplayCompact": "Compacto",
"showThinking": "Mostrar razonamiento",
"showThinkingDesc": "Muestra el razonamiento del modelo. Desactivado, el indicador de razonamiento en vivo sigue visible y las filas y extractos de razonamiento completados quedan ocultos.",
+ "transcriptDisplayMode": "Visualización del proceso",
+ "transcriptDisplayModeDesc": "Elige cómo se agrupa el proceso del asistente en la transcripción.",
+ "transcriptDisplayModeFlat": "Plano",
+ "transcriptDisplayModeCommandFirst": "Comandos primero",
+ "transcriptDisplayModeFullyFolded": "Totalmente plegado",
"keepCommandsExpanded": "No plegar los comandos",
"keepCommandsExpandedDesc": "Las llamadas de shell se mantienen en filas propias en lugar de plegarse en el grupo de herramientas contiguo.",
"contextUsageDisplay": "Lectura del uso del contexto",
diff --git a/packages/i18n/src/locales/fr/index.ts b/packages/i18n/src/locales/fr/index.ts
index c3f39ca019..ed45c0db03 100644
--- a/packages/i18n/src/locales/fr/index.ts
+++ b/packages/i18n/src/locales/fr/index.ts
@@ -1455,6 +1455,11 @@ sklm: {
"thinkingDisplayCompact": "Compact",
"showThinking": "Afficher le raisonnement",
"showThinkingDesc": "Affiche le raisonnement du modèle. Désactivé, l'indicateur de raisonnement en direct reste visible et les lignes et extraits de raisonnement terminés sont masqués.",
+ "transcriptDisplayMode": "Affichage du processus",
+ "transcriptDisplayModeDesc": "Choisit comment le processus de l'assistant est regroupé dans la transcription.",
+ "transcriptDisplayModeFlat": "À plat",
+ "transcriptDisplayModeCommandFirst": "Commandes d'abord",
+ "transcriptDisplayModeFullyFolded": "Entièrement replié",
"keepCommandsExpanded": "Ne pas replier les commandes",
"keepCommandsExpandedDesc": "Les appels shell restent sur leurs propres lignes au lieu d'être repliés dans le groupe d'outils voisin.",
"contextUsageDisplay": "Affichage de l'usage du contexte",
diff --git a/packages/i18n/src/locales/ko/index.ts b/packages/i18n/src/locales/ko/index.ts
index 4834527621..fbfe5c79c3 100644
--- a/packages/i18n/src/locales/ko/index.ts
+++ b/packages/i18n/src/locales/ko/index.ts
@@ -1465,6 +1465,11 @@ sklm: {
thinkingDisplayCompact: "간결",
showThinking: "사고 과정 표시",
showThinkingDesc: "모델의 사고 과정을 표시합니다. 끄면 실시간 사고 표시기는 계속 보이고 완료된 사고 행과 발췌는 숨겨집니다.",
+ transcriptDisplayMode: "프로세스 표시",
+ transcriptDisplayModeDesc: "트랜스크립트에서 어시스턴트 프로세스를 묶는 방식을 선택합니다.",
+ transcriptDisplayModeFlat: "평면 표시",
+ transcriptDisplayModeCommandFirst: "명령 우선",
+ transcriptDisplayModeFullyFolded: "전체 접기",
keepCommandsExpanded: "명령 접지 않기",
keepCommandsExpandedDesc: "셸 호출을 주변 도구 그룹에 접지 않고 자체 행으로 유지합니다.",
contextUsageDisplay: "컨텍스트 사용량 표시",
diff --git a/packages/i18n/src/locales/pt-BR/index.ts b/packages/i18n/src/locales/pt-BR/index.ts
index e4d19e8e14..eacfa53f90 100644
--- a/packages/i18n/src/locales/pt-BR/index.ts
+++ b/packages/i18n/src/locales/pt-BR/index.ts
@@ -1428,6 +1428,11 @@ export const ptBR = {
thinkingDisplayCompact: "Compacto",
showThinking: "Mostrar raciocínio",
showThinkingDesc: "Mostra o raciocínio do modelo. Quando desativado, o indicador de raciocínio ao vivo continua visível e as linhas e trechos de raciocínio concluídos ficam ocultos.",
+ transcriptDisplayMode: "Exibição do processo",
+ transcriptDisplayModeDesc: "Escolha como o processo do assistente é agrupado na transcrição.",
+ transcriptDisplayModeFlat: "Plano",
+ transcriptDisplayModeCommandFirst: "Comandos primeiro",
+ transcriptDisplayModeFullyFolded: "Totalmente recolhido",
keepCommandsExpanded: "Não recolher comandos",
keepCommandsExpandedDesc: "As chamadas de shell ficam em linhas próprias em vez de serem recolhidas no grupo de ferramentas ao redor.",
contextUsageDisplay: "Indicador de uso do contexto",
diff --git a/packages/i18n/src/locales/tr/index.ts b/packages/i18n/src/locales/tr/index.ts
index 4f3ef83640..26b8f40150 100644
--- a/packages/i18n/src/locales/tr/index.ts
+++ b/packages/i18n/src/locales/tr/index.ts
@@ -1459,6 +1459,11 @@ sklm: {
thinkingDisplayCompact: "Sade",
showThinking: "Düşünmeyi göster",
showThinkingDesc: "Modelin düşünmesini gösterir. Kapalıyken canlı düşünme göstergesi görünür kalır; tamamlanan düşünme satırları ve alıntılar gizlenir.",
+ transcriptDisplayMode: "Süreç görünümü",
+ transcriptDisplayModeDesc: "Asistan sürecinin transkriptte nasıl gruplanacağını seçer.",
+ transcriptDisplayModeFlat: "Düz",
+ transcriptDisplayModeCommandFirst: "Önce komutlar",
+ transcriptDisplayModeFullyFolded: "Tamamen katlanmış",
keepCommandsExpanded: "Komutları katlama",
keepCommandsExpandedDesc: "Kabuk çağrıları, çevresindeki araç grubuna katlanmak yerine kendi satırlarında kalır.",
contextUsageDisplay: "Bağlam kullanımı göstergesi",
diff --git a/packages/i18n/src/locales/zh-CN/index.ts b/packages/i18n/src/locales/zh-CN/index.ts
index fe9dd50d87..c1c7cc373c 100644
--- a/packages/i18n/src/locales/zh-CN/index.ts
+++ b/packages/i18n/src/locales/zh-CN/index.ts
@@ -1449,6 +1449,11 @@ sklm: {
thinkingDisplayCompact: "精简",
showThinking: "显示思考",
showThinkingDesc: "显示模型的推理内容。关闭后仍显示实时思考指示器,并隐藏已完成的推理行和摘要。",
+ transcriptDisplayMode: "过程显示",
+ transcriptDisplayModeDesc: "选择助手过程在对话中的分组方式。",
+ transcriptDisplayModeFlat: "平铺显示",
+ transcriptDisplayModeCommandFirst: "命令工具优先",
+ transcriptDisplayModeFullyFolded: "全折叠显示",
keepCommandsExpanded: "命令不折叠",
keepCommandsExpandedDesc: "命令行单独成行显示,不并入上下文的工具分组。",
contextUsageDisplay: "上下文用量读数",
diff --git a/packages/i18n/src/locales/zh-TW/index.ts b/packages/i18n/src/locales/zh-TW/index.ts
index 1f13023ed9..434bfa4167 100644
--- a/packages/i18n/src/locales/zh-TW/index.ts
+++ b/packages/i18n/src/locales/zh-TW/index.ts
@@ -1449,6 +1449,11 @@ sklm: {
thinkingDisplayCompact: "精簡",
showThinking: "顯示思考",
showThinkingDesc: "顯示模型的推理內容。關閉後仍顯示即時思考指示器,並隱藏已完成的推理列和摘要。",
+ transcriptDisplayMode: "過程顯示",
+ transcriptDisplayModeDesc: "選擇助理過程在對話中的分組方式。",
+ transcriptDisplayModeFlat: "平鋪顯示",
+ transcriptDisplayModeCommandFirst: "命令工具優先",
+ transcriptDisplayModeFullyFolded: "全摺疊顯示",
keepCommandsExpanded: "指令不折疊",
keepCommandsExpandedDesc: "指令列單獨成列顯示,不併入上下文的工具分組。",
contextUsageDisplay: "上下文用量讀數",
diff --git a/packages/shared/src/types/settings.ts b/packages/shared/src/types/settings.ts
index ce2f9040d2..fbb7c1b276 100644
--- a/packages/shared/src/types/settings.ts
+++ b/packages/shared/src/types/settings.ts
@@ -37,6 +37,8 @@ export type JevKeyCheckResult = {
*/
export type CloseBehavior = "ask" | "tray" | "quit";
+export type TranscriptDisplayMode = "flat" | "command-first" | "fully-folded";
+
export type AppSettings = {
imageGeneration?: import("../image-generation.js").ImageGenerationBinding | null;
/** All models marked for image generation; absent falls back to imageGeneration. */
@@ -107,13 +109,19 @@ export type AppSettings = {
*/
showThinking?: boolean;
/**
- * Keep shell calls (`Bash`, `exec`, `shell`, …) as their own rows instead of
- * folding them into the surrounding tool group. Absent means `true`, so an
- * existing install keeps today's scannable command rows.
+ * How the assistant turn's process is grouped in the transcript.
+ *
+ * - `flat`: one outer process disclosure, no nested activity groups.
+ * - `command-first`: run rows stay standalone; other activity groups.
+ * - `fully-folded`: the v0.20.0 layout; run rows join activity groups.
*
- * The turn's process disclosure itself is not affected: both values render
- * exactly one top-level disclosure per turn. This preference only decides
- * whether a run row sits inside a group or beside it.
+ * Absent means `fully-folded`, preserving the released transcript layout.
+ * This is presentation only and never changes tool execution or stored data.
+ */
+ transcriptDisplayMode?: TranscriptDisplayMode;
+ /**
+ * @deprecated Replaced by `transcriptDisplayMode`. Retained for persisted
+ * settings and older clients; current rendering no longer reads it.
*/
keepCommandsExpanded?: boolean;
/**
diff --git a/scripts/e2e/transcript-render.tsx b/scripts/e2e/transcript-render.tsx
index d3ce4d7d84..8f535942f0 100644
--- a/scripts/e2e/transcript-render.tsx
+++ b/scripts/e2e/transcript-render.tsx
@@ -64,7 +64,7 @@ async function markdownLinkInteractionProbe(
useAppStore.setState({
activeSessionId: "markdown-link-probe",
page: "chat",
- settings: { ...initialState.settings, linkOpenTarget: "workpanel" },
+ settings: { ...initialState.settings, linkOpenTarget: "workpanel", transcriptDisplayMode: "command-first" },
openUrlInWorkPanel: (url) => openedUrls.push(url),
});
flushSync(() =>
@@ -362,6 +362,7 @@ globalThis.resetContextOverflowRecoveryProbe = async () => {
enterToSend: true,
onboardingDismissed: false,
smoothStreaming: false,
+ transcriptDisplayMode: "command-first",
},
});
};
@@ -424,6 +425,7 @@ globalThis.transcriptRenderProbe = async () => {
enterToSend: true,
onboardingDismissed: false,
smoothStreaming: false,
+ transcriptDisplayMode: "command-first",
},
});
const container = document.createElement("div");
diff --git a/scripts/e2e/turn-process.tsx b/scripts/e2e/turn-process.tsx
index 98c5b10ddb..3f25c1133d 100644
--- a/scripts/e2e/turn-process.tsx
+++ b/scripts/e2e/turn-process.tsx
@@ -6,7 +6,7 @@ import { en } from "@pi-desktop/i18n";
import type { AppSettings, UiMessage } from "@pi-desktop/shared";
import { AssistantTurn } from "../../apps/desktop/src/features/chat/transcript/AssistantTurn";
import { ShowThinkingRow } from "../../apps/desktop/src/components/settings/ShowThinkingRow";
-import { KeepCommandsExpandedRow } from "../../apps/desktop/src/components/settings/KeepCommandsExpandedRow";
+import { TranscriptDisplayModeRow } from "../../apps/desktop/src/components/settings/TranscriptDisplayModeRow";
import { buildTranscriptEntries } from "../../apps/desktop/src/lib/assistant-turns";
import { TranscriptSearchContext } from "../../apps/desktop/src/lib/transcript-search-context";
import type { TranscriptSearchTarget } from "../../apps/desktop/src/lib/transcript-reading";
@@ -67,6 +67,7 @@ export async function turnProcessProbe() {
theme: "light",
enterToSend: true,
onboardingDismissed: true,
+ transcriptDisplayMode: "command-first",
};
const setSettings = (patch: Partial = {}) =>
flushSync(() => useAppStore.setState({ settings: { ...baseSettings, ...patch } }));
@@ -540,7 +541,7 @@ export async function turnProcessProbe() {
container.querySelectorAll(".turn-run-row").length === 2,
"the mounted turn starts with standalone command rows",
);
- setSettings({ keepCommandsExpanded: false });
+ setSettings({ transcriptDisplayMode: "fully-folded" });
check(
container.querySelectorAll(".turn-process").length === 1 &&
container.querySelectorAll(".turn-run-row").length === 0,
@@ -575,9 +576,21 @@ export async function turnProcessProbe() {
"toggling command folding back restores standalone rows without a remount",
);
+ // Flat keeps the outer process but suppresses nested activity groups and
+ // standalone run wrappers.
+ setSettings({ transcriptDisplayMode: "flat" });
+ render(contiguous, false, null, "flat-mode");
+ check(
+ container.querySelector(".turn-process") !== null &&
+ container.querySelectorAll(".process-activity-group").length === 0 &&
+ container.querySelectorAll(".turn-run-row").length === 0,
+ "flat mode renders one outer process with no nested activity groups",
+ );
+ setSettings();
+
// The active tail may be wrapped in a merged off-mode part; the merged group
// must still receive the live disclosure defaults.
- setSettings({ keepCommandsExpanded: false });
+ setSettings({ transcriptDisplayMode: "fully-folded" });
render(
[read, grep, run("live-folded-bash", "pnpm test")],
true,
@@ -630,29 +643,32 @@ export async function turnProcessProbe() {
"an aborted running Bash row reports the turn stopped",
);
- // The Settings row is a boolean command-folding toggle, defaulting to on.
- let foldSaved: Partial | undefined;
+ // The Settings row is a three-way transcript display mode control.
+ let modeSaved: Partial | undefined;
flushSync(() =>
root.render(
- {
- foldSaved = patch;
+ modeSaved = patch;
}}
/>
,
),
);
- const foldToggle = container.querySelector('[role="switch"]');
+ const modeButtons = Array.from(
+ container.querySelectorAll('[role="radiogroup"] button'),
+ );
check(
- foldToggle?.getAttribute("aria-checked") === "true",
- "the command-folding row defaults to keeping commands expanded",
+ modeButtons.length === 3 &&
+ modeButtons[1]?.getAttribute("aria-checked") === "true",
+ "the transcript-display row exposes flat, command-first and fully-folded with command-first selected",
);
- click(foldToggle);
+ click(modeButtons[2] ?? null);
check(
- foldSaved?.keepCommandsExpanded === false,
- "the command-folding row saves the boolean preference",
+ modeSaved?.transcriptDisplayMode === "fully-folded",
+ "the transcript-display row saves the selected mode",
);
From 60817a510958d48317391a2ab6855064f6684a60 Mon Sep 17 00:00:00 2001
From: v_wyxgwang
Date: Wed, 21 Oct 2026 18:04:51 +0800
Subject: [PATCH 14/44] test(transcript): align turn-process probe with
Thinking defaults
Open the completed process and Thinking disclosure before asserting the
retained reasoning text now that a collapsed Thinking row shows only its
label. Also assert flat mode keeps one outer process without nested
activity groups or standalone run wrappers.
---
scripts/e2e/turn-process.tsx | 9 ++++++++-
1 file changed, 8 insertions(+), 1 deletion(-)
diff --git a/scripts/e2e/turn-process.tsx b/scripts/e2e/turn-process.tsx
index 3f25c1133d..7ee20cade8 100644
--- a/scripts/e2e/turn-process.tsx
+++ b/scripts/e2e/turn-process.tsx
@@ -512,9 +512,16 @@ export async function turnProcessProbe() {
Boolean(container.querySelector(".tool-row.thinking")),
"turning show thinking back on restores the completed reasoning row",
);
+ click(processHeaders()[0] ?? null);
+ const restoredThinking = container.querySelector(
+ ".tool-row.thinking .tool-row-header",
+ );
+ if (restoredThinking?.getAttribute("aria-expanded") !== "true") {
+ click(restoredThinking);
+ }
check(
container.textContent?.includes("Reasoning before the answer"),
- "the restored row shows the retained reasoning text",
+ "the restored row shows the retained reasoning text when opened",
);
// Search reveal opens the process chunk that owns the named message.
From f5b35021b82d22f45caadee7084cf4d1b330a73f Mon Sep 17 00:00:00 2001
From: luoshang
Date: Wed, 21 Oct 2026 18:08:31 +0800
Subject: [PATCH 15/44] fix(agent-runtime): skip expired OS trust anchors when
merging the CA set
The sidecar merges the operating system's trust store into Node's default CA
set at startup. Those stores are a cache and keep entries that already
expired: Windows still lists Let's Encrypt's `ISRG Root X2` and `R3` with a
2025-09-15 expiry long after the fact.
Merging one of those makes OpenSSL accept an expired certificate as the anchor
for any chain that names it as issuer. A chain like
leaf -> YE2 -> Root YE -> ISRG Root X2 -> ISRG Root X1
stopped at the expired `ISRG Root X2` instead of walking up to the valid
`ISRG Root X1`, so the handshake failed with `CERT_HAS_EXPIRED` even though
the provider's own chain was valid. The failure is reported as a TLS category
error and is correctly not retried, so the provider is unusable until the
expired entry leaves the store.
Every provider behind such a chain failed, which is why the report looked
provider-specific (issue #1393). Reproduced on Windows 11 with Electron 43.6.0:
`tls.getCACertificates("system")` returned 146 certificates, 17 of them
expired, and the same host handshakes fine with the bundled roots alone.
An anchor that has already expired can verify nothing, so it is never merged.
The bundled and `NODE_EXTRA_CA_CERTS` sets are untouched, and chain,
expiration and hostname validation stay enabled - this narrows the merge, it
never disables verification.
- `system-ca.ts`: filter the system store by `validTo` before merging.
- `system-ca.test.ts`: assert no expired system anchor reaches the defaults.
- `e2e-provider-certificates.mjs`: the trust probe now measures the usable
system roots, because the previous "every system certificate is present"
expectation cannot hold once expired entries are excluded.
---
packages/agent-runtime/src/system-ca.test.ts | 27 +++++++++++++++++++
packages/agent-runtime/src/system-ca.ts | 28 +++++++++++++++++---
scripts/e2e-provider-certificates.mjs | 8 ++++--
scripts/e2e/provider-certificate-sidecar.ts | 14 ++++++++--
4 files changed, 69 insertions(+), 8 deletions(-)
diff --git a/packages/agent-runtime/src/system-ca.test.ts b/packages/agent-runtime/src/system-ca.test.ts
index f2119849f6..0749ff3e4a 100644
--- a/packages/agent-runtime/src/system-ca.test.ts
+++ b/packages/agent-runtime/src/system-ca.test.ts
@@ -28,3 +28,30 @@ it("applyAdditiveDefaultCaCertificates is idempotent", () => {
const twice = fingerprints(tls.getCACertificates("default")).size;
expect(twice).toBe(once);
});
+
+it("applyAdditiveDefaultCaCertificates never adds an already expired system anchor", () => {
+ const now = Date.now();
+ const bundled = fingerprints(tls.getCACertificates("bundled"));
+ const expiredSystem = tls
+ .getCACertificates("system")
+ .filter((pem) => {
+ try {
+ return new Date(new X509Certificate(pem).validTo).getTime() <= now;
+ } catch {
+ return false;
+ }
+ })
+ .map((pem) => new X509Certificate(pem).fingerprint256);
+
+ applyAdditiveDefaultCaCertificates();
+
+ const after = fingerprints(tls.getCACertificates("default"));
+ for (const fingerprint of expiredSystem) {
+ // A bundled root that happens to be expired stays: the bundled set is the
+ // runtime's own baseline. Only the system merge is filtered, because a
+ // stale cache entry there can act as the anchor for a live chain.
+ if (bundled.has(fingerprint)) continue;
+ expect(after.has(fingerprint)).toBe(false);
+ }
+});
+
diff --git a/packages/agent-runtime/src/system-ca.ts b/packages/agent-runtime/src/system-ca.ts
index 6dcebe3fea..12e0a070d9 100644
--- a/packages/agent-runtime/src/system-ca.ts
+++ b/packages/agent-runtime/src/system-ca.ts
@@ -1,3 +1,4 @@
+import { X509Certificate } from "node:crypto";
import * as tls from "node:tls";
/**
@@ -18,7 +19,25 @@ import * as tls from "node:tls";
* and an inherited `NODE_EXTRA_CA_CERTS` still lands in the `extra` set.
* Certificate chain, expiration and hostname validation are untouched — this
* widens the trust set, it never disables verification.
+ *
+ * The OS stores are a cache, so they keep entries that already expired: Windows
+ * still lists Let's Encrypt's `ISRG Root X2` and `R3` with a 2025-09-15 expiry
+ * long after the fact. Merging one of those makes OpenSSL accept an expired
+ * certificate as the anchor for any chain that names it as issuer, and the
+ * handshake then fails with `CERT_HAS_EXPIRED` even though the server's own
+ * chain is valid and reaches a current root. An anchor that has already
+ * expired can verify nothing, so it is never merged.
*/
+function isExpiredCertificate(pem: string, now: number): boolean {
+ try {
+ return new Date(new X509Certificate(pem).validTo).getTime() <= now;
+ } catch {
+ // Unparseable input is left to the runtime: dropping it would silently
+ // narrow the trust set this function exists to widen.
+ return false;
+ }
+}
+
export function applyAdditiveDefaultCaCertificates(): void {
if (typeof tls.setDefaultCACertificates !== "function") return;
const bundled = tls.getCACertificates("bundled");
@@ -27,11 +46,12 @@ export function applyAdditiveDefaultCaCertificates(): void {
if (system.length === 0) return;
const seen = new Set(bundled.map((cert) => cert));
const merged = [...bundled, ...extra.filter((cert) => !seen.has(cert))];
+ const now = Date.now();
for (const cert of system) {
- if (!seen.has(cert)) {
- seen.add(cert);
- merged.push(cert);
- }
+ if (seen.has(cert)) continue;
+ if (isExpiredCertificate(cert, now)) continue;
+ seen.add(cert);
+ merged.push(cert);
}
try {
tls.setDefaultCACertificates(merged);
diff --git a/scripts/e2e-provider-certificates.mjs b/scripts/e2e-provider-certificates.mjs
index 9990ffa2dc..2ee8ef9396 100644
--- a/scripts/e2e-provider-certificates.mjs
+++ b/scripts/e2e-provider-certificates.mjs
@@ -54,8 +54,12 @@ try {
define: { PI_BUNDLED_NODE: "true" },
banner: { js: `import { createRequire as __piCreateRequire } from 'node:module'; const require = __piCreateRequire(import.meta.url);
import __certificateProbeTls from 'node:tls';
-{ const tls = __certificateProbeTls; const defaults = new Set(tls.getCACertificates('default'));
-process.stdout.write(JSON.stringify({jsonrpc:'2.0',method:'test.trust',params:{systemCount:tls.getCACertificates('system').length,systemIncluded:tls.getCACertificates('system').every(c=>defaults.has(c)),extraIncluded:tls.getCACertificates('extra').every(c=>defaults.has(c))}})+'\\n'); }` },
+{ const tls = __certificateProbeTls; const { X509Certificate: __ProbeCert } = require('node:crypto');
+const defaults = new Set(tls.getCACertificates('default')); const now = Date.now();
+// An OS store is a cache and keeps expired entries; a merged expired anchor can
+// never verify anything, so only the usable roots are expected in the defaults.
+const usable = tls.getCACertificates('system').filter(c=>{ try { return new Date(new __ProbeCert(c).validTo).getTime() > now } catch { return true } });
+process.stdout.write(JSON.stringify({jsonrpc:'2.0',method:'test.trust',params:{systemCount:tls.getCACertificates('system').length,usableSystemCount:usable.length,systemIncluded:usable.every(c=>defaults.has(c)),extraIncluded:tls.getCACertificates('extra').every(c=>defaults.has(c))}})+'\\n'); }` },
});
await build({ entryPoints: [join(root, "scripts/e2e/provider-certificate-sidecar.ts")],
outfile: join(temp, "parent.mjs"), bundle: true, platform: "node", format: "esm",
diff --git a/scripts/e2e/provider-certificate-sidecar.ts b/scripts/e2e/provider-certificate-sidecar.ts
index a736dcdd3d..80326bb48d 100644
--- a/scripts/e2e/provider-certificate-sidecar.ts
+++ b/scripts/e2e/provider-certificate-sidecar.ts
@@ -8,7 +8,14 @@ sidecar.setHost({
async call() { return { session: { messages: [] } } as T; },
onNotification: () => () => {}, onExit: () => () => {},
});
-let trust: { systemCount: number; systemIncluded: boolean; extraIncluded: boolean } | undefined;
+let trust:
+ | {
+ systemCount: number;
+ usableSystemCount: number;
+ systemIncluded: boolean;
+ extraIncluded: boolean;
+ }
+ | undefined;
const events: AgentEventEnvelope[] = [];
const ended = Promise.withResolvers();
sidecar.onNotification((method, params) => {
@@ -32,7 +39,10 @@ try {
},
});
await ended.promise;
- assert.ok(trust?.systemIncluded, "sidecar must include OS-trusted roots");
+ assert.ok(
+ trust?.systemIncluded,
+ "sidecar must include every non-expired OS-trusted root",
+ );
assert.ok(trust?.extraIncluded, "inherited extra CA must remain trusted");
const messages = events.flatMap(({ event }) => event.type === "message_end" ? [event.message] : []);
const expected = process.argv[4];
From 8576493a8bc1dbb09e72d02c746ddca2d31b29af Mon Sep 17 00:00:00 2001
From: v_wyxgwang
Date: Wed, 21 Oct 2026 18:21:07 +0800
Subject: [PATCH 16/44] test(transcript): mock TextShimmer in session reference
probe
The shared transcript module now imports the Thinking shimmer. Keep the
session-reference renderer probe's dependency table complete so it can
continue exercising message references without loading the app store.
---
apps/desktop/test/session-reference-ui.test.mjs | 3 +++
1 file changed, 3 insertions(+)
diff --git a/apps/desktop/test/session-reference-ui.test.mjs b/apps/desktop/test/session-reference-ui.test.mjs
index 107e0c3665..1db27721a1 100644
--- a/apps/desktop/test/session-reference-ui.test.mjs
+++ b/apps/desktop/test/session-reference-ui.test.mjs
@@ -73,6 +73,9 @@ const shared = load(new URL("../src/features/chat/transcript/shared.tsx", import
"react-i18next": { useTranslation: () => ({ t, i18n: { language: locale } }) },
"@pi-desktop/shared": await import("@pi-desktop/shared"),
"./disclosure": {},
+ "./TextShimmer": {
+ TextShimmer: ({ text }) => React.createElement("span", null, text),
+ },
"../../../hooks/use-preview-target": {
useOpenChatFileRef: () => () => {},
useOpenPreviewTarget: () => undefined,
From 02aa5678ddb3d836230e0f2e7c569a8dcbc1154c Mon Sep 17 00:00:00 2001
From: vastsa
Date: Wed, 21 Oct 2026 20:14:46 +0800
Subject: [PATCH 17/44] fix(e2e): test certificate probe kill escalation
Keep the normal Electron path unchanged while asserting that a child
ignoring SIGTERM receives SIGKILL after the grace period.
---
package.json | 2 +-
scripts/e2e-provider-client-certificate.mjs | 34 +++-----
scripts/e2e/wait-for-child-exit.mjs | 29 +++++++
scripts/e2e/wait-for-child-exit.test.mjs | 87 +++++++++++++++++++++
4 files changed, 126 insertions(+), 26 deletions(-)
create mode 100644 scripts/e2e/wait-for-child-exit.mjs
create mode 100644 scripts/e2e/wait-for-child-exit.test.mjs
diff --git a/package.json b/package.json
index 2efe64d370..c4c192713e 100644
--- a/package.json
+++ b/package.json
@@ -46,7 +46,7 @@
"test:e2e:copy-tex": "node scripts/e2e-copy-tex.mjs",
"test:e2e:transcript-disclosure": "node scripts/e2e-transcript-disclosure-anchor.mjs",
"test:e2e:images": "node scripts/e2e-image-generation.mjs && node scripts/e2e-image-generation-ui.mjs && node scripts/e2e-image-chat.mjs",
- "test:e2e:provider-client-certificate": "node scripts/e2e-provider-client-certificate.mjs",
+ "test:e2e:provider-client-certificate": "node --test scripts/e2e/wait-for-child-exit.test.mjs && node scripts/e2e-provider-client-certificate.mjs",
"test:e2e:provider-order": "node scripts/e2e-provider-order.mjs",
"test:e2e:project-edit": "node scripts/e2e-project-edit.mjs",
"test:e2e:provider-api-style": "node scripts/e2e-provider-api-style.mjs",
diff --git a/scripts/e2e-provider-client-certificate.mjs b/scripts/e2e-provider-client-certificate.mjs
index f29cb14846..a0aac14957 100644
--- a/scripts/e2e-provider-client-certificate.mjs
+++ b/scripts/e2e-provider-client-certificate.mjs
@@ -8,6 +8,7 @@ import { tmpdir } from "node:os";
import { join } from "node:path";
import { fileURLToPath } from "node:url";
import { resolveElectronBinary } from "./e2e/boot.mjs";
+import { waitForChildExitWithEscalation } from "./e2e/wait-for-child-exit.mjs";
const root = fileURLToPath(new URL("..", import.meta.url));
const { build } = createRequire(join(root, "packages/agent-runtime/package.json"))("esbuild");
@@ -34,29 +35,12 @@ try {
// mid-init, and the `close` event then never arrives, so the step waits out
// the job's 30-minute budget and is cancelled with no failing step to read
// (#1751 hit exactly this). Escalate to SIGKILL after a short grace period.
- let killedBy = null;
- const termTimer = setTimeout(() => {
- killedBy = "SIGTERM";
- child.kill("SIGTERM");
- }, 60_000);
- const killTimer = setTimeout(() => {
- killedBy = "SIGKILL";
- child.kill("SIGKILL");
- }, 65_000);
- try {
- const code = await new Promise((resolve, reject) => {
- child.once("error", reject);
- child.once("close", resolve);
- });
- assert.equal(
- killedBy,
- null,
- `provider client certificate E2E hung and was killed by ${killedBy} after ${killedBy === "SIGKILL" ? 65 : 60}s: ${output}`,
- );
- assert.equal(code, 0, output);
- assert.match(output, /provider client certificate E2E passed/);
- } finally {
- clearTimeout(termTimer);
- clearTimeout(killTimer);
- }
+ const { code, killedBy } = await waitForChildExitWithEscalation(child);
+ assert.equal(
+ killedBy,
+ null,
+ `provider client certificate E2E hung and was killed by ${killedBy} after ${killedBy === "SIGKILL" ? 65 : 60}s: ${output}`,
+ );
+ assert.equal(code, 0, output);
+ assert.match(output, /provider client certificate E2E passed/);
} finally { await rm(temp, { recursive: true, force: true }); }
diff --git a/scripts/e2e/wait-for-child-exit.mjs b/scripts/e2e/wait-for-child-exit.mjs
new file mode 100644
index 0000000000..9bb26d6fc5
--- /dev/null
+++ b/scripts/e2e/wait-for-child-exit.mjs
@@ -0,0 +1,29 @@
+export async function waitForChildExitWithEscalation(
+ child,
+ {
+ termAfterMs = 60_000,
+ killAfterMs = 65_000,
+ setTimer = setTimeout,
+ clearTimer = clearTimeout,
+ } = {},
+) {
+ let killedBy = null;
+ const termTimer = setTimer(() => {
+ killedBy = "SIGTERM";
+ child.kill("SIGTERM");
+ }, termAfterMs);
+ const killTimer = setTimer(() => {
+ killedBy = "SIGKILL";
+ child.kill("SIGKILL");
+ }, killAfterMs);
+ try {
+ const code = await new Promise((resolve, reject) => {
+ child.once("error", reject);
+ child.once("close", resolve);
+ });
+ return { code, killedBy };
+ } finally {
+ clearTimer(termTimer);
+ clearTimer(killTimer);
+ }
+}
diff --git a/scripts/e2e/wait-for-child-exit.test.mjs b/scripts/e2e/wait-for-child-exit.test.mjs
new file mode 100644
index 0000000000..78ca767607
--- /dev/null
+++ b/scripts/e2e/wait-for-child-exit.test.mjs
@@ -0,0 +1,87 @@
+import assert from "node:assert/strict";
+import { EventEmitter } from "node:events";
+import test from "node:test";
+import { waitForChildExitWithEscalation } from "./wait-for-child-exit.mjs";
+
+function controlledTimers() {
+ let nextId = 0;
+ const pending = new Map();
+ return {
+ setTimer(callback, delay) {
+ const id = ++nextId;
+ pending.set(id, { callback, delay });
+ return id;
+ },
+ clearTimer(id) {
+ pending.delete(id);
+ },
+ fireAfter(delay) {
+ for (const [id, timer] of pending) {
+ if (timer.delay === delay) {
+ pending.delete(id);
+ timer.callback();
+ }
+ }
+ },
+ pending,
+ };
+}
+
+test("a normally closing child exits without signals and clears both timers", async () => {
+ const child = new EventEmitter();
+ child.kill = () => assert.fail("a normally closing child must not be killed");
+ const timers = controlledTimers();
+
+ const result = waitForChildExitWithEscalation(child, {
+ setTimer: timers.setTimer,
+ clearTimer: timers.clearTimer,
+ });
+ child.emit("close", 0);
+
+ assert.deepEqual(await result, { code: 0, killedBy: null });
+ assert.equal(timers.pending.size, 0);
+});
+
+test("a child that ignores SIGTERM receives SIGKILL after the grace period", async () => {
+ const child = new EventEmitter();
+ const signals = [];
+ child.kill = (signal) => signals.push(signal);
+ const timers = controlledTimers();
+
+ const result = waitForChildExitWithEscalation(child, {
+ termAfterMs: 60,
+ killAfterMs: 65,
+ setTimer: timers.setTimer,
+ clearTimer: timers.clearTimer,
+ });
+
+ timers.fireAfter(60);
+ assert.deepEqual(signals, ["SIGTERM"]);
+ timers.fireAfter(65);
+ assert.deepEqual(signals, ["SIGTERM", "SIGKILL"]);
+ child.emit("close", null);
+
+ assert.deepEqual(await result, { code: null, killedBy: "SIGKILL" });
+ assert.equal(timers.pending.size, 0);
+});
+
+test("a child that exits after SIGTERM is not escalated", async () => {
+ const child = new EventEmitter();
+ const signals = [];
+ child.kill = (signal) => signals.push(signal);
+ const timers = controlledTimers();
+
+ const result = waitForChildExitWithEscalation(child, {
+ termAfterMs: 60,
+ killAfterMs: 65,
+ setTimer: timers.setTimer,
+ clearTimer: timers.clearTimer,
+ });
+
+ timers.fireAfter(60);
+ child.emit("close", 0);
+
+ assert.deepEqual(await result, { code: 0, killedBy: "SIGTERM" });
+ assert.deepEqual(signals, ["SIGTERM"]);
+ assert.equal(timers.pending.size, 0);
+});
From a1427526710bb9e06e4e13523d01f0a363629d81 Mon Sep 17 00:00:00 2001
From: vastsa
Date: Wed, 21 Oct 2026 20:14:42 +0800
Subject: [PATCH 18/44] fix(mcp): localize missing DCR recovery
Fail before opening OAuth with an unregistered client, and send a
stable error code so settings can show translated recovery guidance.
---
apps/desktop/electron/main/mcp-oauth.ts | 19 +++++++++++++++++--
.../src/components/settings/AgentMcpPage.tsx | 7 ++++++-
apps/desktop/src/lib/mcp-oauth-error.ts | 14 ++++++++++++++
.../test/agent-capability-settings.test.mjs | 5 +++++
apps/desktop/test/mcp-oauth-error.test.mjs | 12 ++++++++++++
apps/desktop/test/mcp-oauth.test.mjs | 9 +++++++--
docs/spec/03-runtime/01-ipc-protocol.md | 4 +++-
docs/spec/06-delivery/04-e2e-test-plan.md | 1 +
docs/zh-CN/spec/03-runtime/01-ipc-protocol.md | 4 +++-
.../spec/06-delivery/04-e2e-test-plan.md | 1 +
packages/i18n/src/locales/de/index.ts | 1 +
packages/i18n/src/locales/en/index.ts | 2 ++
packages/i18n/src/locales/es/index.ts | 1 +
packages/i18n/src/locales/fr/index.ts | 1 +
packages/i18n/src/locales/ko/index.ts | 2 ++
packages/i18n/src/locales/pt-BR/index.ts | 1 +
packages/i18n/src/locales/tr/index.ts | 1 +
packages/i18n/src/locales/zh-CN/index.ts | 1 +
packages/i18n/src/locales/zh-TW/index.ts | 1 +
packages/i18n/test/catalogs.test.mjs | 10 ++++++++++
packages/shared/src/types/capabilities.ts | 4 +++-
21 files changed, 93 insertions(+), 8 deletions(-)
create mode 100644 apps/desktop/src/lib/mcp-oauth-error.ts
create mode 100644 apps/desktop/test/mcp-oauth-error.test.mjs
diff --git a/apps/desktop/electron/main/mcp-oauth.ts b/apps/desktop/electron/main/mcp-oauth.ts
index 099df47cac..68c5158eb2 100644
--- a/apps/desktop/electron/main/mcp-oauth.ts
+++ b/apps/desktop/electron/main/mcp-oauth.ts
@@ -3,6 +3,7 @@ import { createServer, type Server } from "node:http";
import type { AddressInfo } from "node:net";
import {
isUserSuppliedHostname,
+ type McpOAuthLoginErrorCode,
type McpOAuthLoginEvent,
type McpServerRecord,
type McpServerStatus,
@@ -42,6 +43,18 @@ export type McpOAuthDeps = {
newId?: () => string;
};
+class McpOAuthError extends Error {
+ readonly errorCode: McpOAuthLoginErrorCode;
+
+ constructor(
+ errorCode: McpOAuthLoginErrorCode,
+ message: string,
+ ) {
+ super(message);
+ this.errorCode = errorCode;
+ }
+}
+
export function secretRefForMcpOAuth(serverId: string): string {
return `secret:mcp:${serverId}:oauth`;
}
@@ -686,8 +699,9 @@ export class McpOAuthManager {
// Fail here, before opening anything, saying what is missing.
// The message must not promise a settings field that does not
// exist yet: it names the two real ways forward.
- throw new Error(
- `MCP server "${session.serverId}" does not support Dynamic Client Registration, and PI-Desktop has no client id registered with ${metadata.authorizationEndpoint}. Ask the server operator for a client id, or use a server that supports DCR.`,
+ throw new McpOAuthError(
+ "MCP_OAUTH_DCR_UNAVAILABLE",
+ `MCP server "${session.serverId}" has no registered client id and does not support Dynamic Client Registration.`,
);
}
@@ -775,6 +789,7 @@ export class McpOAuthManager {
serverId: session.serverId,
kind: "error",
message,
+ ...(error instanceof McpOAuthError ? { errorCode: error.errorCode } : {}),
});
}
} finally {
diff --git a/apps/desktop/src/components/settings/AgentMcpPage.tsx b/apps/desktop/src/components/settings/AgentMcpPage.tsx
index 98f57b45e0..45e1b909e9 100644
--- a/apps/desktop/src/components/settings/AgentMcpPage.tsx
+++ b/apps/desktop/src/components/settings/AgentMcpPage.tsx
@@ -9,6 +9,7 @@ import {
import { api } from "../../lib/api";
import { useAppStore } from "../../stores/app-store";
import { useHostCollection } from "../../hooks/use-host-collection";
+import { mcpOAuthErrorTranslationKey } from "../../lib/mcp-oauth-error";
import {
AgentCapabilityPage,
AgentProjectPicker,
@@ -295,7 +296,11 @@ export function AgentMcpPage() {
});
cleanup();
} else if (event.kind === "error") {
- showToast(event.message || t("extensions.mcp.authFailed"), { variant: "error" });
+ const errorKey = mcpOAuthErrorTranslationKey(event.errorCode);
+ showToast(
+ (errorKey && t(errorKey)) || event.message || t("extensions.mcp.authFailed"),
+ { variant: "error" },
+ );
cleanup();
} else if (event.kind === "cancelled") {
cleanup();
diff --git a/apps/desktop/src/lib/mcp-oauth-error.ts b/apps/desktop/src/lib/mcp-oauth-error.ts
new file mode 100644
index 0000000000..9b7622a88a
--- /dev/null
+++ b/apps/desktop/src/lib/mcp-oauth-error.ts
@@ -0,0 +1,14 @@
+import type { McpOAuthLoginErrorCode } from "@pi-desktop/shared";
+
+type McpOAuthErrorTranslationKey = "extensions.mcp.authDcrUnavailable";
+
+export function mcpOAuthErrorTranslationKey(
+ errorCode: McpOAuthLoginErrorCode | undefined,
+): McpOAuthErrorTranslationKey | undefined {
+ switch (errorCode) {
+ case "MCP_OAUTH_DCR_UNAVAILABLE":
+ return "extensions.mcp.authDcrUnavailable";
+ default:
+ return undefined;
+ }
+}
diff --git a/apps/desktop/test/agent-capability-settings.test.mjs b/apps/desktop/test/agent-capability-settings.test.mjs
index a194886e30..35cc31330d 100644
--- a/apps/desktop/test/agent-capability-settings.test.mjs
+++ b/apps/desktop/test/agent-capability-settings.test.mjs
@@ -470,3 +470,8 @@ test("MCP OAuth subscribe is owned by a ref cleaned up on unmount", () => {
assert.match(mcp, /api\.onMcpOAuth\(/);
assert.match(mcpIpc, /oauth\.start\(server\.id, server\.url, server\)/);
});
+
+test("MCP OAuth error events use localized recovery copy when available", () => {
+ assert.match(mcp, /mcpOAuthErrorTranslationKey\(event\.errorCode\)/);
+ assert.match(mcp, /\(errorKey && t\(errorKey\)\) \|\| event\.message/);
+});
diff --git a/apps/desktop/test/mcp-oauth-error.test.mjs b/apps/desktop/test/mcp-oauth-error.test.mjs
new file mode 100644
index 0000000000..20cc3e60ad
--- /dev/null
+++ b/apps/desktop/test/mcp-oauth-error.test.mjs
@@ -0,0 +1,12 @@
+import assert from "node:assert/strict";
+import test from "node:test";
+
+import { mcpOAuthErrorTranslationKey } from "../src/lib/mcp-oauth-error.ts";
+
+test("the no-DCR OAuth error selects localized recovery guidance", () => {
+ assert.equal(
+ mcpOAuthErrorTranslationKey("MCP_OAUTH_DCR_UNAVAILABLE"),
+ "extensions.mcp.authDcrUnavailable",
+ );
+ assert.equal(mcpOAuthErrorTranslationKey(undefined), undefined);
+});
diff --git a/apps/desktop/test/mcp-oauth.test.mjs b/apps/desktop/test/mcp-oauth.test.mjs
index 2465f4ac2e..9b07cc9fd7 100644
--- a/apps/desktop/test/mcp-oauth.test.mjs
+++ b/apps/desktop/test/mcp-oauth.test.mjs
@@ -995,6 +995,7 @@ test("McpOAuthManager: a server without DCR fails loudly instead of opening a de
const { mockFetch } = createMockFetch({ withoutRegistration: true });
const { mockCreateServer } = createMockServerFactory();
const opened = [];
+ const events = [];
const manager = new McpOAuthManager({
call: host.call,
fetchImpl: mockFetch,
@@ -1002,7 +1003,7 @@ test("McpOAuthManager: a server without DCR fails loudly instead of opening a de
opened.push(url);
},
createServer: mockCreateServer,
- emit: () => {},
+ emit: (event) => events.push(event),
});
t.after(() => manager.disposeAll());
@@ -1013,7 +1014,8 @@ test("McpOAuthManager: a server without DCR fails loudly instead of opening a de
// forward; a bare "failed" leaves the user where the 404 did.
assert.match(error.message, /Dynamic Client Registration/);
assert.match(error.message, /client id/);
- assert.match(error.message, /https:\/\/notion\.test\/authorize/);
+ assert.equal(error.errorCode, "MCP_OAUTH_DCR_UNAVAILABLE");
+ assert.doesNotMatch(error.message, /https:\/\/notion\.test\/authorize/);
return true;
},
);
@@ -1021,4 +1023,7 @@ test("McpOAuthManager: a server without DCR fails loudly instead of opening a de
// The whole point: no browser tab, so no dead authorization page. Before
// this change the app opened `?client_id=pi-desktop` and the user saw a 404.
assert.deepEqual(opened, [], "no authorization URL may be opened without a usable client id");
+ assert.ok(events.some((event) =>
+ event.kind === "error" && event.errorCode === "MCP_OAUTH_DCR_UNAVAILABLE",
+ ));
});
diff --git a/docs/spec/03-runtime/01-ipc-protocol.md b/docs/spec/03-runtime/01-ipc-protocol.md
index bfb5551364..8eea0bc404 100644
--- a/docs/spec/03-runtime/01-ipc-protocol.md
+++ b/docs/spec/03-runtime/01-ipc-protocol.md
@@ -1759,11 +1759,13 @@ type McpOAuthLoginEvent = {
| { kind: "authUrl"; url: string; instructions?: string; opened: boolean }
| { kind: "progress"; message: string }
| { kind: "done"; status: McpServerStatus }
- | { kind: "error"; message: string }
+ | { kind: "error"; message: string; errorCode?: "MCP_OAUTH_DCR_UNAVAILABLE" }
| { kind: "cancelled" }
);
```
+When authorization-server metadata has no `registration_endpoint` and no reusable client is available, login fails before opening the external browser. The error event carries `MCP_OAUTH_DCR_UNAVAILABLE`; the renderer shows localized recovery guidance. The main-process message remains diagnostic and must not include discovered authorization endpoint URLs.
+
#### Status and Token Storage
- `McpServerStatus` includes:
- `hasOauth: boolean` — whether the server has an encrypted OAuth secret stored in host-core (`secret:mcp::oauth`).
diff --git a/docs/spec/06-delivery/04-e2e-test-plan.md b/docs/spec/06-delivery/04-e2e-test-plan.md
index e351bd066b..ced0b4975c 100644
--- a/docs/spec/06-delivery/04-e2e-test-plan.md
+++ b/docs/spec/06-delivery/04-e2e-test-plan.md
@@ -8512,6 +8512,7 @@ must keep splitting are covered by `markdown-blocks.test.mjs`.
6. Settings UI updates status to `Ready` with discovered tools, shows localized success toast, and displays `OAuth` badge.
7. When access token expires, `UserMcpRuntime` transparently uses refresh token to obtain a fresh access token without user prompt.
8. Moving the server via `mcp.transfer` preserves and re-keys the OAuth token secret under the destination ID.
+- **No-DCR case**: When authorization-server metadata omits `registration_endpoint` and there is no reusable client, Authorize does not open a browser. The error event contains `MCP_OAUTH_DCR_UNAVAILABLE` and Settings shows localized recovery guidance to request a client ID from the server operator or use a DCR-capable server.
- **Specs linked**: `03-runtime/01-ipc-protocol.md`, ADR 0283, ADR 0142
- **Acceptance**: E (tools & permissions), Security
- **Milestone**: M5
diff --git a/docs/zh-CN/spec/03-runtime/01-ipc-protocol.md b/docs/zh-CN/spec/03-runtime/01-ipc-protocol.md
index 09c5c014f4..a2bf727edd 100644
--- a/docs/zh-CN/spec/03-runtime/01-ipc-protocol.md
+++ b/docs/zh-CN/spec/03-runtime/01-ipc-protocol.md
@@ -1321,11 +1321,13 @@ type McpOAuthLoginEvent = {
| { kind: "authUrl"; url: string; instructions?: string; opened: boolean }
| { kind: "progress"; message: string }
| { kind: "done"; status: McpServerStatus }
- | { kind: "error"; message: string }
+ | { kind: "error"; message: string; errorCode?: "MCP_OAUTH_DCR_UNAVAILABLE" }
| { kind: "cancelled" }
);
```
+如果授权服务器元数据没有 `registration_endpoint`,且没有可复用的客户端,登录会在打开外部浏览器前失败。错误事件携带 `MCP_OAUTH_DCR_UNAVAILABLE`,渲染层显示本地化的恢复指引。主进程错误消息用于诊断,不应包含发现到的授权端点 URL。
+
#### 状态与凭证存储
- `McpServerStatus` 包含:
- `hasOauth: boolean` — 服务是否在 host-core 加密凭据库存储有 OAuth 凭据(`secret:mcp::oauth`)。
diff --git a/docs/zh-CN/spec/06-delivery/04-e2e-test-plan.md b/docs/zh-CN/spec/06-delivery/04-e2e-test-plan.md
index e81de2283f..d6b1181541 100644
--- a/docs/zh-CN/spec/06-delivery/04-e2e-test-plan.md
+++ b/docs/zh-CN/spec/06-delivery/04-e2e-test-plan.md
@@ -5146,6 +5146,7 @@ eleven-tool-round desktop paths are verified by
6. 设置界面状态更新为已连接及工具数量,弹出成功提示,并显示 OAuth 徽标。
7. 访问令牌过期时,`UserMcpRuntime` 透明使用 refresh token 换取新令牌,无需用户重新交互。
8. 通过 `mcp.transfer` 迁移服务器时,自动将 OAuth 令牌迁移至新 ID 下。
+- **无 DCR 的情况**:如果授权服务器元数据缺少 `registration_endpoint`,且没有可复用的客户端,点击“授权”不会打开浏览器。错误事件包含 `MCP_OAUTH_DCR_UNAVAILABLE`,设置页会显示本地化恢复指引,建议向服务器运营方索取客户端 ID,或改用支持 DCR 的服务器。
- **链接规格**:`03-runtime/01-ipc-protocol.md`、ADR 0283、ADR 0142
- **验收**:E(工具和权限)、安全性
- **里程碑**:M5
diff --git a/packages/i18n/src/locales/de/index.ts b/packages/i18n/src/locales/de/index.ts
index 2a4354cfd6..9345e590c3 100644
--- a/packages/i18n/src/locales/de/index.ts
+++ b/packages/i18n/src/locales/de/index.ts
@@ -2522,6 +2522,7 @@ sklm: {
"authReady_one": "Autorisiert · 1 Tool",
"authReady_other": "Autorisiert · {{count}} Tools",
"authFailed": "Autorisierung fehlgeschlagen",
+ "authDcrUnavailable": "Dieser MCP-Server unterstützt keine dynamische Clientregistrierung. Bitte frage den Serverbetreiber nach einer Client-ID oder verwende einen Server mit DCR-Unterstützung.",
"oauthBadge": "OAuth",
"transport": "Wie wird eine Verbindung hergestellt",
"transportStdio": "Lokales Programm",
diff --git a/packages/i18n/src/locales/en/index.ts b/packages/i18n/src/locales/en/index.ts
index a82506d836..405e9ea7cb 100644
--- a/packages/i18n/src/locales/en/index.ts
+++ b/packages/i18n/src/locales/en/index.ts
@@ -2565,6 +2565,8 @@ importConfirm: "Imported extensions run inside the agent process with the same a
authReady_one: "Authorized · 1 tool",
authReady_other: "Authorized · {{count}} tools",
authFailed: "Authorization failed",
+ authDcrUnavailable:
+ "This MCP server does not support Dynamic Client Registration. Ask the server operator for a client ID, or use a server that supports DCR.",
oauthBadge: "OAuth",
transport: "How it connects",
transportStdio: "Local program",
diff --git a/packages/i18n/src/locales/es/index.ts b/packages/i18n/src/locales/es/index.ts
index a235bc818e..a035c89ebe 100644
--- a/packages/i18n/src/locales/es/index.ts
+++ b/packages/i18n/src/locales/es/index.ts
@@ -2522,6 +2522,7 @@ sklm: {
"authReady_one": "Autorizado · 1 herramienta",
"authReady_other": "Autorizado · {{count}} herramientas",
"authFailed": "Error de autorización",
+ "authDcrUnavailable": "Este servidor MCP no admite el registro dinámico de clientes. Pide al operador del servidor un ID de cliente o usa un servidor compatible con DCR.",
"oauthBadge": "OAuth",
"transport": "Cómo se conecta",
"transportStdio": "Programa local",
diff --git a/packages/i18n/src/locales/fr/index.ts b/packages/i18n/src/locales/fr/index.ts
index ed45c0db03..8e868e16d3 100644
--- a/packages/i18n/src/locales/fr/index.ts
+++ b/packages/i18n/src/locales/fr/index.ts
@@ -2522,6 +2522,7 @@ sklm: {
"authReady_one": "Autorisé · 1 outil",
"authReady_other": "Autorisé · {{count}} outils",
"authFailed": "Échec de l'autorisation",
+ "authDcrUnavailable": "Ce serveur MCP ne prend pas en charge l’inscription dynamique des clients. Demandez à l’opérateur du serveur un identifiant client ou utilisez un serveur compatible avec DCR.",
"oauthBadge": "OAuth",
"transport": "Comment il se connecte",
"transportStdio": "Programme local",
diff --git a/packages/i18n/src/locales/ko/index.ts b/packages/i18n/src/locales/ko/index.ts
index fbfe5c79c3..29135c06c0 100644
--- a/packages/i18n/src/locales/ko/index.ts
+++ b/packages/i18n/src/locales/ko/index.ts
@@ -2557,6 +2557,8 @@ importConfirm: "가져온 확장은 에이전트 프로세스 안에서 에이
authReady_one: "인증됨 · 도구 1개",
authReady_other: "인증됨 · 도구 {{count}}개",
authFailed: "인증 실패",
+ authDcrUnavailable:
+ "이 MCP 서버는 동적 클라이언트 등록을 지원하지 않습니다. 서버 운영자에게 클라이언트 ID를 요청하거나 DCR을 지원하는 서버를 사용하세요.",
oauthBadge: "OAuth",
transport: "연결 방식",
transportStdio: "로컬 프로그램",
diff --git a/packages/i18n/src/locales/pt-BR/index.ts b/packages/i18n/src/locales/pt-BR/index.ts
index eacfa53f90..9035d36093 100644
--- a/packages/i18n/src/locales/pt-BR/index.ts
+++ b/packages/i18n/src/locales/pt-BR/index.ts
@@ -2486,6 +2486,7 @@ export const ptBR = {
authReady_one: "Autorizado · 1 ferramenta",
authReady_other: "Autorizado · {{count}} ferramentas",
authFailed: "Falha na autorização",
+ authDcrUnavailable: "Este servidor MCP não oferece suporte ao registro dinâmico de clientes. Peça ao operador do servidor um ID de cliente ou use um servidor compatível com DCR.",
oauthBadge: "OAuth",
transport: "Como se conecta",
transportStdio: "Programa local",
diff --git a/packages/i18n/src/locales/tr/index.ts b/packages/i18n/src/locales/tr/index.ts
index 26b8f40150..d64f99d0a8 100644
--- a/packages/i18n/src/locales/tr/index.ts
+++ b/packages/i18n/src/locales/tr/index.ts
@@ -2551,6 +2551,7 @@ importConfirm: "İçe aktarılan uzantılar ajan sürecinde, ajanın kendi araç
authReady_one: "Yetkilendirildi · 1 araç",
authReady_other: "Yetkilendirildi · {{count}} araç",
authFailed: "Yetkilendirme başarısız",
+ authDcrUnavailable: "Bu MCP sunucusu Dinamik İstemci Kaydı'nı desteklemiyor. Sunucu operatöründen bir istemci kimliği isteyin veya DCR destekleyen bir sunucu kullanın.",
oauthBadge: "OAuth",
transport: "Nasıl bağlanır",
transportStdio: "Yerel program",
diff --git a/packages/i18n/src/locales/zh-CN/index.ts b/packages/i18n/src/locales/zh-CN/index.ts
index c1c7cc373c..f2552173ec 100644
--- a/packages/i18n/src/locales/zh-CN/index.ts
+++ b/packages/i18n/src/locales/zh-CN/index.ts
@@ -2519,6 +2519,7 @@ sklm: {
authReady_one: "已授权 · 1 个工具",
authReady_other: "已授权 · {{count}} 个工具",
authFailed: "授权失败",
+ authDcrUnavailable: "此 MCP 服务器不支持动态客户端注册。请向服务器运营方索取客户端 ID,或改用支持 DCR 的服务器。",
oauthBadge: "OAuth",
transport: "连接方式",
transportStdio: "本地程序",
diff --git a/packages/i18n/src/locales/zh-TW/index.ts b/packages/i18n/src/locales/zh-TW/index.ts
index 434bfa4167..6c5f1f13a1 100644
--- a/packages/i18n/src/locales/zh-TW/index.ts
+++ b/packages/i18n/src/locales/zh-TW/index.ts
@@ -2518,6 +2518,7 @@ sklm: {
authReady_one: "已授權 · 1 個工具",
authReady_other: "已授權 · {{count}} 個工具",
authFailed: "授權失敗",
+ authDcrUnavailable: "此 MCP 伺服器不支援動態用戶端註冊。請向伺服器管理員索取用戶端 ID,或改用支援 DCR 的伺服器。",
oauthBadge: "OAuth",
transport: "連線方式",
transportStdio: "本地程式",
diff --git a/packages/i18n/test/catalogs.test.mjs b/packages/i18n/test/catalogs.test.mjs
index 85b25c021a..50048b556c 100644
--- a/packages/i18n/test/catalogs.test.mjs
+++ b/packages/i18n/test/catalogs.test.mjs
@@ -75,6 +75,16 @@ test("Live Voice preparation and call recovery copy is localized in every shippe
assert.match(english["liveVoice.enableDetail"], /switch sessions by voice/);
});
+test("MCP OAuth no-DCR recovery guidance is localized in every shipped catalog", () => {
+ const key = "extensions.mcp.authDcrUnavailable";
+ for (const [id, catalog] of Object.entries(catalogs)) {
+ const value = flattenCatalog(catalog)[key];
+ assert.equal(typeof value, "string", `${id} ${key}`);
+ assert.notEqual(value.trim(), "", `${id} ${key}`);
+ if (id !== "en") assert.notEqual(value, english[key], `${id} ${key} must not fall back to English`);
+ }
+});
+
test("canonical thinking levels are not translated catalog entries", () => {
const levels = ["off", "minimal", "low", "medium", "high", "xhigh", "max"];
const effortKeys = [
diff --git a/packages/shared/src/types/capabilities.ts b/packages/shared/src/types/capabilities.ts
index 402f50fbda..20d3c300a9 100644
--- a/packages/shared/src/types/capabilities.ts
+++ b/packages/shared/src/types/capabilities.ts
@@ -110,6 +110,8 @@ export type McpServerView = McpServerRecord & {
};
/** Progress of one MCP OAuth login attempt, pushed to the renderer. */
+export type McpOAuthLoginErrorCode = "MCP_OAUTH_DCR_UNAVAILABLE";
+
export type McpOAuthLoginEvent = {
loginId: string;
serverId: string;
@@ -117,7 +119,7 @@ export type McpOAuthLoginEvent = {
| { kind: "authUrl"; url: string; instructions?: string; opened: boolean }
| { kind: "progress"; message: string }
| { kind: "done"; status: McpServerStatus }
- | { kind: "error"; message: string }
+ | { kind: "error"; message: string; errorCode?: McpOAuthLoginErrorCode }
| { kind: "cancelled" }
);
From 18a416b26fca5c3e5ca6023546576bc4f95abdc9 Mon Sep 17 00:00:00 2001
From: muzimu217
Date: Tue, 20 Oct 2026 08:05:02 -0700
Subject: [PATCH 19/44] fix(transcript): fall back to the bookmarked offset
when its row is unmounted
Stacked on #1783, which fixes who owns the reveal edge but not this path.
A reveal mounts only a trailing slice of history (TRANSCRIPT_INITIAL_MOUNT 15,
then TRANSCRIPT_WINDOW_MIN 60, lib/transcript-window.ts:23-28), so an older
bookmark routinely names a row that is not in the DOM. restoreTranscriptReading
Position reported that as false, and the alignment loop returns on false without
arming the deadline that would clear pendingRef (use-transcript-reading-
position.ts:99). While a restore is pending, useTranscriptScroll discards every
scroll event (:384-387), so the reader cannot travel up to mount the row either:
no restore, no scrolling, permanently.
The bookmark already recorded the absolute offset it was taken at
(TranscriptReadingPosition.scrollTop, captured at :59/:68), but the restore path
never read it. Use it as the fallback: an approximate place is strictly better
than a pane that can neither scroll nor restore. A bookmark with no usable
offset (NaN, negative, infinite) still reports failure, and a pane with no
layout box is still refused outright.
Tests: transcript-reading-position-fallback.test.mjs (5) covers the mounted-row
path, the unmounted-row fallback, a zero-height row, unusable offsets, and the
no-layout refusal. Related suites: 42/42. typecheck clean after a workspace
build.
---
.../src/lib/transcript-reading-position.ts | 31 +++--
...nscript-reading-position-fallback.test.mjs | 114 ++++++++++++++++++
2 files changed, 138 insertions(+), 7 deletions(-)
create mode 100644 apps/desktop/test/transcript-reading-position-fallback.test.mjs
diff --git a/apps/desktop/src/lib/transcript-reading-position.ts b/apps/desktop/src/lib/transcript-reading-position.ts
index 1090b8bddd..d24fbe9e31 100644
--- a/apps/desktop/src/lib/transcript-reading-position.ts
+++ b/apps/desktop/src/lib/transcript-reading-position.ts
@@ -75,12 +75,29 @@ export function restoreTranscriptReadingPosition(
content: HTMLElement,
position: TranscriptReadingPosition,
): boolean {
- if (!transcriptHasLayout(scroller) || !position.messageId) return false;
- const id = CSS.escape(position.messageId);
- const row = content.querySelector(`[data-minimap-id="${id}"], [data-message-id="${id}"]`);
- if (!row) return false;
- const rect = row.getBoundingClientRect();
- if (rect.height === 0) return false;
- scroller.scrollTop += rect.top - scroller.getBoundingClientRect().top - position.offset;
+ if (!transcriptHasLayout(scroller)) return false;
+ if (position.messageId) {
+ const id = CSS.escape(position.messageId);
+ const row = content.querySelector(`[data-minimap-id="${id}"], [data-message-id="${id}"]`);
+ if (row) {
+ const rect = row.getBoundingClientRect();
+ if (rect.height > 0) {
+ scroller.scrollTop += rect.top - scroller.getBoundingClientRect().top - position.offset;
+ return true;
+ }
+ }
+ }
+ // The anchored row is not mounted. A reveal mounts only a trailing slice of
+ // history (lib/transcript-window.ts:23-28), so an older bookmark routinely
+ // points at a row that is not in the DOM yet — and waiting for it to arrive
+ // cannot work, because a pending restore makes `useTranscriptScroll` discard
+ // every scroll event, so the reader can never travel up to mount it.
+ //
+ // The bookmark already recorded the absolute offset it was taken at, so fall
+ // back to it: an approximation of the same place beats a pane that cannot be
+ // scrolled and does not restore. `false` is reserved for a bookmark with no
+ // usable offset at all, which only a never-laid-out pane produces.
+ if (!Number.isFinite(position.scrollTop) || position.scrollTop < 0) return false;
+ scroller.scrollTop = position.scrollTop;
return true;
}
diff --git a/apps/desktop/test/transcript-reading-position-fallback.test.mjs b/apps/desktop/test/transcript-reading-position-fallback.test.mjs
new file mode 100644
index 0000000000..f0ba7a301e
--- /dev/null
+++ b/apps/desktop/test/transcript-reading-position-fallback.test.mjs
@@ -0,0 +1,114 @@
+import assert from "node:assert/strict";
+import { register } from "node:module";
+import test from "node:test";
+
+register(new URL("./helpers/ts-import-hooks.mjs", import.meta.url));
+
+// `restoreTranscriptReadingPosition` escapes the id with the browser-only
+// `CSS.escape`; this suite runs the function directly in Node.
+globalThis.CSS ??= { escape: (value) => String(value).replace(/["\\]/g, "\\$&") };
+const { restoreTranscriptReadingPosition } = await import(
+ "../src/lib/transcript-reading-position.ts"
+);
+
+/*
+ #1771, the path #1783 does not cover.
+
+ A reveal mounts only a trailing slice of history
+ (lib/transcript-window.ts:23-28: TRANSCRIPT_INITIAL_MOUNT 15, then
+ TRANSCRIPT_WINDOW_MIN 60), so an older bookmark routinely names a row that is
+ not in the DOM. While a restore is pending `useTranscriptScroll` discards
+ every scroll event, so the reader cannot travel up to mount that row either —
+ the two together used to deadlock: no restore, no scrolling, ever.
+
+ The bookmark already carries the absolute offset it was taken at, so a
+ missing row now falls back to that offset instead of reporting failure.
+*/
+
+/** Minimal stand-ins for the two DOM objects the function touches. */
+function fakeScroller({ scrollTop = 0, top = 0 } = {}) {
+ return {
+ scrollTop,
+ getBoundingClientRect: () => ({ top, bottom: top + 600, left: 0, right: 800 }),
+ // `transcriptHasLayout` needs a real box.
+ clientHeight: 600,
+ scrollHeight: 1200,
+ offsetHeight: 600,
+ };
+}
+function fakeContent({ row = null } = {}) {
+ return {
+ querySelector: () => row,
+ getBoundingClientRect: () => ({ top: 0, bottom: 0, left: 0, right: 0 }),
+ offsetHeight: 1200,
+ };
+}
+
+const bookmark = (overrides = {}) => ({
+ pinned: false,
+ messageId: "m-late",
+ offset: 24,
+ scrollTop: 480,
+ windowSize: 60,
+ ...overrides,
+});
+
+test("an anchored row that is mounted still restores by its rect", () => {
+ const scroller = fakeScroller({ scrollTop: 100, top: 0 });
+ const row = {
+ getBoundingClientRect: () => ({ top: 140, bottom: 200, height: 60, left: 0, right: 800 }),
+ offsetHeight: 60,
+ };
+ assert.equal(
+ restoreTranscriptReadingPosition(scroller, fakeContent({ row }), bookmark()),
+ true,
+ );
+ // 100 + (140 - 0) - 24 = 216
+ assert.equal(scroller.scrollTop, 216);
+});
+
+test("a bookmark whose row is above the mounted window falls back to its offset", () => {
+ const scroller = fakeScroller({ scrollTop: 0, top: 0 });
+ const content = fakeContent({ row: null });
+ assert.equal(
+ restoreTranscriptReadingPosition(scroller, content, bookmark({ scrollTop: 480 })),
+ true,
+ "a missing row must not report failure: that is what stalled the pane",
+ );
+ assert.equal(scroller.scrollTop, 480);
+});
+
+test("a row that is mounted but has no height is treated as missing", () => {
+ const scroller = fakeScroller({ scrollTop: 0, top: 0 });
+ const collapsed = {
+ getBoundingClientRect: () => ({ top: 0, bottom: 0, height: 0, left: 0, right: 800 }),
+ offsetHeight: 0,
+ };
+ assert.equal(
+ restoreTranscriptReadingPosition(scroller, fakeContent({ row: collapsed }), bookmark({ scrollTop: 300 })),
+ true,
+ );
+ assert.equal(scroller.scrollTop, 300);
+});
+
+test("a bookmark without a usable offset still reports failure", () => {
+ const scroller = fakeScroller();
+ const content = fakeContent({ row: null });
+ for (const scrollTop of [Number.NaN, -1, Number.POSITIVE_INFINITY]) {
+ assert.equal(
+ restoreTranscriptReadingPosition(scroller, content, bookmark({ scrollTop })),
+ false,
+ `scrollTop ${scrollTop} must not be applied`,
+ );
+ }
+});
+
+test("a pane with no layout is still refused outright", () => {
+ // A hidden pane reports no box; applying any offset there would corrupt the
+ // bookmark it is supposed to protect.
+ const scroller = { scrollTop: 0, clientHeight: 0, scrollHeight: 0, offsetHeight: 0, getBoundingClientRect: () => ({ top: 0, bottom: 0, left: 0, right: 0 }) };
+ assert.equal(
+ restoreTranscriptReadingPosition(scroller, fakeContent({ row: null }), bookmark()),
+ false,
+ );
+});
From ee2f4fd0c21506b84e038284657de25b2c4fd89a Mon Sep 17 00:00:00 2001
From: liuzixiang
Date: Wed, 21 Oct 2026 21:57:10 +0800
Subject: [PATCH 20/44] fix(host-runtime): expect the platform scratch
separator in the launch-resolver test
join(dataDir, ...) yields native separators and the assertion hardcoded the POSIX spelling, so the suite failed on every Windows checkout while Linux CI stayed green. Mirror the production expression instead.
---
packages/host-runtime/src/launch-resolver.test.ts | 3 ++-
1 file changed, 2 insertions(+), 1 deletion(-)
diff --git a/packages/host-runtime/src/launch-resolver.test.ts b/packages/host-runtime/src/launch-resolver.test.ts
index 1a8e4679b4..a893ae749b 100644
--- a/packages/host-runtime/src/launch-resolver.test.ts
+++ b/packages/host-runtime/src/launch-resolver.test.ts
@@ -1,3 +1,4 @@
+import { join } from "node:path";
import { describe, expect, it } from "vitest";
import { createHeadlessLaunchResolver, type HostProviderRecord } from "./launch-resolver.js";
@@ -68,7 +69,7 @@ describe("createHeadlessLaunchResolver", () => {
expect(launch.projectPath).toBe("/work/project");
expect(launch.sidecarParams.provider.apiKey).toBe("sk-test");
expect(launch.sidecarParams.provider.modelConfig?.name).toBe("gpt-a");
- expect(launch.sidecarParams.scratchDir).toBe("/data/scratch/s1");
+ expect(launch.sidecarParams.scratchDir).toBe(join("/data", "scratch", "s1"));
expect(launch.sidecarParams.pluginSkills).toEqual([{ id: "review", name: "Review", description: "Review code" }]);
expect(launch.sidecarParams.pluginTools).toEqual([]);
expect(launch.sidecarParams.projectMemory).toBe("remember me");
From caa76f224ce10acf9edccdd4157cae5d8b091734 Mon Sep 17 00:00:00 2001
From: liuzixiang
Date: Wed, 21 Oct 2026 21:57:11 +0800
Subject: [PATCH 21/44] fix(agent-runtime): tolerate the Windows symlink
privilege in the sessionDir tests
The #1732 tests create real file symlinks, which EPERMs on an unprivileged Windows checkout and crashes the fixtures (storage-directory-migration already degrades the same way). Catch EPERM and keep the remaining assertions, which hold without the alias; privileged runs and CI keep the full coverage.
---
.../agent-runtime/src/native-pi-session.test.ts | 16 ++++++++++++++--
1 file changed, 14 insertions(+), 2 deletions(-)
diff --git a/packages/agent-runtime/src/native-pi-session.test.ts b/packages/agent-runtime/src/native-pi-session.test.ts
index 8b52699847..98f4e1bedc 100644
--- a/packages/agent-runtime/src/native-pi-session.test.ts
+++ b/packages/agent-runtime/src/native-pi-session.test.ts
@@ -92,7 +92,13 @@ describe("NativePiSessionService", () => {
);
const outside = join(f.root, "outside.jsonl");
writeFileSync(outside, sessionText("outside-id", f.project, "outside session"));
- symlinkSync(outside, join(customDir, "escape.jsonl"));
+ // Windows without the symlink privilege cannot create the alias; the
+ // escape entry is then simply absent and the assertions below still hold.
+ try {
+ symlinkSync(outside, join(customDir, "escape.jsonl"));
+ } catch (error) {
+ if ((error as NodeJS.ErrnoException).code !== "EPERM") throw error;
+ }
const service = new NativePiSessionService({ agentDir: f.agentDir, sessionRoot: f.sessionRoot });
const sessions = await service.list({ projectPaths: [f.project] });
@@ -151,7 +157,13 @@ describe("NativePiSessionService", () => {
mkdirSync(customDir, { recursive: true });
writeFileSync(join(f.project, ".pi", "settings.json"), `${JSON.stringify({ sessionDir: ".pi/sessions" })}\n`);
writeFileSync(join(customDir, "local.jsonl"), sessionText("local-id", f.project, "project local session"));
- symlinkSync(join(customDir, "local.jsonl"), join(customDir, "latest.jsonl"));
+ // Same Windows symlink-privilege caveat: without the alias the dedupe is
+ // exercised only on privileged runs, and one real row still lists.
+ try {
+ symlinkSync(join(customDir, "local.jsonl"), join(customDir, "latest.jsonl"));
+ } catch (error) {
+ if ((error as NodeJS.ErrnoException).code !== "EPERM") throw error;
+ }
const service = new NativePiSessionService({ agentDir: f.agentDir, sessionRoot: f.sessionRoot });
const sessions = await service.list({ projectPaths: [f.project] });
const matches = sessions.filter((session) => session.title === "project local session");
From d008073814aa54bb89261ca22bc5469721e17bb0 Mon Sep 17 00:00:00 2001
From: vastsa
Date: Wed, 21 Oct 2026 22:23:13 +0800
Subject: [PATCH 22/44] feat(composer): toggle background task output from the
whole row
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
The background-tasks bar only opened a task's log through its "Output"
button, so the row itself — the state dot, the command and the meta text —
looked clickable but did nothing, and the click target was a few pixels
wide.
The row lead is now the toggle: mouse click, Enter and Space all flip the
log, with aria-expanded on the interactive region. Stop and dismiss keep
their own buttons outside that region, and a source test pins the split so
a later refactor cannot regress the click target.
---
.../src/components/BackgroundTasksBar.tsx | 50 +++++++++++-----
apps/desktop/src/styles/composer.css | 25 +++++++-
.../background-tasks-bar-row-toggle.test.mjs | 58 +++++++++++++++++++
3 files changed, 117 insertions(+), 16 deletions(-)
create mode 100644 apps/desktop/test/background-tasks-bar-row-toggle.test.mjs
diff --git a/apps/desktop/src/components/BackgroundTasksBar.tsx b/apps/desktop/src/components/BackgroundTasksBar.tsx
index 16d838121c..ace12f696a 100644
--- a/apps/desktop/src/components/BackgroundTasksBar.tsx
+++ b/apps/desktop/src/components/BackgroundTasksBar.tsx
@@ -43,32 +43,52 @@ export function BackgroundTasksBar(): React.JSX.Element | null {
{tasks.map((task) => {
const isRunning = task.state === "running";
const stopping = stoppingIds.has(task.id);
+ const isExpanded = expandedId === task.id;
return (
-
-
- {task.command}
-
-
- {t(`backgroundTasks.${task.state}`)}
- {isRunning ? ` · ${formatElapsed(task.elapsedMs)}` : ""}
- {task.exitCode !== undefined ? ` · ${task.exitCode}` : ""}
-
+ {/* The row body toggles the log; the explicit action buttons keep
+ their own behavior and stay out of it. Kept as a div with a
+ button role so Enter / Space match the projection button. */}
+
void toggleOutput(task.id)}
+ onKeyDown={(event) => {
+ if (event.target !== event.currentTarget) return;
+ if (event.key === "Enter" || event.key === " ") {
+ event.preventDefault();
+ void toggleOutput(task.id);
+ }
+ }}
+ >
+
+
+ {task.command}
+
+
+ {t(`backgroundTasks.${task.state}`)}
+ {isRunning ? ` · ${formatElapsed(task.elapsedMs)}` : ""}
+ {task.exitCode !== undefined ? ` · ${task.exitCode}` : ""}
+
+
void toggleOutput(task.id)}
- aria-expanded={expandedId === task.id}
+ aria-expanded={isExpanded}
>
{t("backgroundTasks.output")}
@@ -94,7 +114,7 @@ export function BackgroundTasksBar(): React.JSX.Element | null {
{t("backgroundTasks.dismiss")}
)}
- {expandedId === task.id ? (
+ {isExpanded ? (
{outputText || NO_OUTPUT}
diff --git a/apps/desktop/src/styles/composer.css b/apps/desktop/src/styles/composer.css
index 04cd62fbd3..e80887af4f 100644
--- a/apps/desktop/src/styles/composer.css
+++ b/apps/desktop/src/styles/composer.css
@@ -1018,11 +1018,34 @@
align-items: center;
gap: 8px;
min-width: 0;
- padding: 6px 10px;
+ padding: 0;
color: var(--ds-text-secondary);
font-size: var(--text-sm);
}
+/* The row body opens the log; the action buttons sit outside it in the same
+ flex line, so the clickable area is everything except the controls. */
+.background-task-main {
+ display: flex;
+ flex: 1 1 auto;
+ flex-wrap: wrap;
+ align-items: center;
+ gap: 8px;
+ min-width: 0;
+ padding: 6px 10px;
+ border-radius: var(--radius-sm);
+ cursor: pointer;
+}
+
+.background-task-main:focus-visible {
+ outline: 2px solid var(--ds-focus);
+ outline-offset: -2px;
+}
+
+.background-task[data-expanded="true"] .background-task-main {
+ color: var(--ds-text-primary);
+}
+
.background-task-error {
margin: 0;
padding: 6px 10px;
diff --git a/apps/desktop/test/background-tasks-bar-row-toggle.test.mjs b/apps/desktop/test/background-tasks-bar-row-toggle.test.mjs
new file mode 100644
index 0000000000..e119fe4946
--- /dev/null
+++ b/apps/desktop/test/background-tasks-bar-row-toggle.test.mjs
@@ -0,0 +1,58 @@
+import assert from "node:assert/strict";
+import { readFile } from "node:fs/promises";
+import test from "node:test";
+
+/*
+ * The row body of the background-tasks bar toggles the log, not only the
+ * "output" button: the clickable surface is the whole row lead (state dot,
+ * command, meta), while stop / dismiss keep their own behavior.
+ */
+
+const [bar, composerStyles] = await Promise.all([
+ readFile(new URL("../src/components/BackgroundTasksBar.tsx", import.meta.url), "utf8"),
+ readFile(new URL("../src/styles/composer.css", import.meta.url), "utf8"),
+]);
+
+test("the row body is an interactive element that toggles the log", () => {
+ const main = bar.match(
+ /
/,
+ );
+ assert.ok(main, "row body element missing");
+ assert.match(main[0], /role="button"/);
+ assert.match(main[0], /tabIndex=\{0\}/);
+ assert.match(main[0], /aria-expanded=\{isExpanded\}/);
+ assert.match(main[0], /onClick=\{\(\) => void toggleOutput\(task\.id\)\}/);
+ // Keyboard parity with a real button.
+ assert.match(main[0], /event\.key === "Enter" \|\| event\.key === " "/);
+ assert.match(main[0], /if \(event\.target !== event\.currentTarget\) return;/);
+});
+
+test("the toggle surface covers the state dot, command and meta rows", () => {
+ const main = bar.match(
+ /
/,
+ )[0];
+ for (const className of ["background-task-state", "background-task-command", "background-task-meta"]) {
+ assert.match(main, new RegExp(`className="${className}"`));
+ }
+});
+
+test("stop and dismiss stay outside the toggle surface", () => {
+ const toggleEnd = bar.indexOf('className="background-task-main"');
+ const stopAt = bar.indexOf('background-task-action is-stop"');
+ const dismissAt = bar.indexOf('onClick={() => dismiss(task.id)}');
+ assert.ok(stopAt > toggleEnd && dismissAt > toggleEnd);
+ // Exactly one projection button remains.
+ assert.equal(bar.match(/t\("backgroundTasks\.output"\)/g)?.length, 1);
+});
+
+test("the row styles keep the body clickable and focus-visible", () => {
+ assert.match(
+ composerStyles,
+ /\.background-task-main\s*\{[^{}]*flex: 1 1 auto/,
+ );
+ assert.match(composerStyles, /\.background-task-main\s*\{[^{}]*cursor: pointer/);
+ assert.match(
+ composerStyles,
+ /\.background-task-main:focus-visible\s*\{[^{}]*outline: 2px solid var\(--ds-focus\)/,
+ );
+});
From 533639f615a0bf513236189bb16a1c967aa70b2f Mon Sep 17 00:00:00 2001
From: vastsa
Date: Wed, 21 Oct 2026 22:38:40 +0800
Subject: [PATCH 23/44] docs(spec): restore the missing rationale cell on D669
The D669 decision row landed with three cells in a four-column table in
both languages, so `pnpm --filter @pi-desktop/docs test` fails on
`origin/main` with a page-structure error.
Fill in the rationale the decision actually records: the shallowest-8000
entry index matched nothing for a script several folders down, which is
what issue #1781 reported. The table parses again.
---
docs/spec/08-meta/decisions-log.md | 2 +-
docs/zh-CN/spec/08-meta/decisions-log.md | 2 +-
2 files changed, 2 insertions(+), 2 deletions(-)
diff --git a/docs/spec/08-meta/decisions-log.md b/docs/spec/08-meta/decisions-log.md
index 4f7383c095..7259a0e986 100644
--- a/docs/spec/08-meta/decisions-log.md
+++ b/docs/spec/08-meta/decisions-log.md
@@ -333,7 +333,7 @@ Gold source: local Codex electron captures; latest row wins where rows conflict.
| D619 | A copied formula is its TeX source | **Renderer only: a copy whose selection covers rendered math writes `text/plain` from the MathML `annotation` — `$…$` inline, `$$…$$` on its own lines, the delimiters `lib/latex-math.ts` normalizes `\(…\)` and `\[…\]` to, each run widened past any run inside the formula as a code span's fence is — instead of the two trees KaTeX paints. A cut that lands inside a formula grows to the whole formula. Only the formulas are rewritten: the reduced clone is read back through `Selection.toString()`, the serializer a copy itself runs, so prose, lists, tables and code blocks sharing the selection keep the platform's own reading — `user-select: none` chrome left behind included, which `innerText` would have written out. A selection with no formula in it, and a copy raised where the selection does not live, are left to the platform entirely. One flavour is written, `text/plain`: taking the event over drops the platform's `text/html` too and none is written back, because the reduced clone is app markup that would carry the `user-select: none` chrome the text reading drops, and because carrying the rendering instead would paste every formula twice — KaTeX's stylesheet is the only thing hiding the MathML tree and no stylesheet travels on the clipboard. One document `copy` listener owned by the shell, and the transcript's right-click Copy reads the same selection through the same module.** | A formula pasted as its glyphs, once per rendered tree, so it could not be carried into a LaTeX document or another Markdown editor (issue #414). ADR 0268 removed quoting on the grounds that the OS clipboard was the substitute; the clipboard had to actually carry the source. |
| D620 | pi-ai built-in API-key services are named presets | **Add fifteen named endpoint presets — Ant Ling, Baseten, Cerebras, Hugging Face, Meta (`responses`), MiniMax (International), Moonshot AI (International), NVIDIA, OpenCode Zen, Vercel AI Gateway, Qwen Token Plan (`alibaba-token-plan`), Qwen Token Plan (China), Xiaomi Token Plan (China / Europe / Singapore) — to `NAMED_ENDPOINT_PRESETS`, each at its published host, with the pi-ai provider id kept as an alias wherever the models.dev key differs. Eight built-in providers remain exceptions with a recorded reason: Amazon Bedrock, Azure OpenAI, Cloudflare AI Gateway, Cloudflare Workers AI, Google Vertex AI (account- or region-scoped URLs), GitHub Copilot and OpenAI Codex (vendor-account rows), and Radius (`pi_messages` is account-only here). `packages/agent-runtime/src/pi-ai-provider-sync.test.ts` fails on a pi-ai upgrade that leaves a provider neither covered nor excepted. No protocol, storage, or IPC change.** | Every other pi-ai capability was already reachable, but the API-key half of the service catalog was hand-maintained and had drifted from the library's own provider list (ADR 0307). |
| D668 | One process disclosure per turn, with three transcript display modes | **Amend D661 / the `turn-process-and-thinking-display` ADR. A turn renders exactly one top-level process disclosure holding every pre-answer row; the answer stays outside it. `AppSettings.transcriptDisplayMode` selects the layout: `flat` renders no nested activity groups, `command-first` renders `Bash`/run rows as standalone rows beside activity groups, and `fully-folded` (the default for absent or invalid values) keeps commands inside their groups and lets only ordinary assistant progress text split them. The mode is read while rendering, so switching repaints immediately - the projection cache is keyed by messages and compactions only. The disclosure header reports failed / stopped / running / finished with precedence in that order and never echoes the current item, and the disclosure shares one left edge with the levels it reveals. `transcriptDisplayMode` joins the portable application fields; `keepCommandsExpanded` is deprecated, retained only for persisted-settings compatibility, and no longer exposed or read for rendering. No host protocol, persistence schema, permission, or plugin contract change. See the amended ADR, `04-ux/06-settings-ia.md`, `04-ux/08-component-spec.md`, `04-ux/09-interaction-patterns.md`, and E2E-CHAT-turn-process-and-thinking-display.** | Chronological segmentation split one turn into several sibling disclosures above the answer, and the boolean command-folding preference could only express two layouts; a three-mode setting covers flat, command-first, and the released grouped view without changing what a tool received or stored. |
-| D669 | `@` queries search past a truncated file index | **Amend D124: while the 8000-entry `fs/index` snapshot is truncated, a non-empty `@` query is also searched over the root's full listing through the read-only Electron channel `pi-desktop/fs/search` once typing pauses, and its best 50 rows merge with the local matches. A complete index never searches. Remote sessions keep their snapshot. No host RPC, storage, or schema change.** |
+| D669 | `@` queries search past a truncated file index | **Amend D124: while the 8000-entry `fs/index` snapshot is truncated, a non-empty `@` query is also searched over the root's full listing through the read-only Electron channel `pi-desktop/fs/search` once typing pauses, and its best 50 rows merge with the local matches. A complete index never searches. Remote sessions keep their snapshot. No host RPC, storage, or schema change.** | The shallowest-8000-entry index left a script several folders down matching no query at all, even though the truncation note invited the reader to refine it (issue #1781). |
## M0. Model catalog decisions
diff --git a/docs/zh-CN/spec/08-meta/decisions-log.md b/docs/zh-CN/spec/08-meta/decisions-log.md
index 6d1aea64b4..50bb3987ad 100644
--- a/docs/zh-CN/spec/08-meta/decisions-log.md
+++ b/docs/zh-CN/spec/08-meta/decisions-log.md
@@ -336,7 +336,7 @@
| D619 | 复制公式得到的是它的 TeX 源码 | **仅渲染层:当选区覆盖到渲染出来的公式时,`text/plain` 从 MathML `annotation` 写出——行内 `$…$`,块级 `$$…$$` 独占行,也就是 `lib/latex-math.ts` 把 `\(…\)` 和 `\[…\]` 归一到的那组定界符,且每组定界符都像代码段的围栏那样加长到盖过公式内部出现的最长同字符串——而不是 KaTeX 画的那两棵树。落在公式内部的切口会扩展成整个公式。只有公式被改写:归约后的克隆经由 `Selection.toString()`——复制自己跑的那个序列化器——读回,因此同处一个选区的正文、列表、表格和代码块保留平台自己的读法,包括 `innerText` 会写出、而复制本就会略过的 `user-select: none` 界面零件。不含公式的选区,以及在选区所在位置之外触发的复制,整份交回平台。只写一种 flavour:`text/plain`。接管事件同时丢掉了平台的 `text/html`,且不再写回——归约后的克隆是应用自己的标记,写回去会带上文本读法已略过的 `user-select: none` 界面零件;而改为携带渲染结果则会把每个公式粘贴两遍,因为隐藏 MathML 树的只有 KaTeX 自己的样式表,样式表不会随剪贴板一起走。只有一个由外壳持有的文档级 `copy` 监听器,记录区的右键复制经由同一个模块读取同一个选区。** | 公式粘出来是它的字形,而且每棵渲染树各一份,无法带进 LaTeX 文档或别的 Markdown 编辑器(issue #414)。ADR 0268 当年移除「引用」的理由正是 OS 剪贴板可以替代,那剪贴板就得真的装着源码。 |
| D620 | pi-ai 内置的 API-key 服务成为命名预设 | **向 `NAMED_ENDPOINT_PRESETS` 新增十五条命名预设——Ant Ling、Baseten、Cerebras、Hugging Face、Meta(`responses`)、MiniMax(国际)、Moonshot AI(国际)、NVIDIA、OpenCode Zen、Vercel AI Gateway、Qwen Token 套餐(`alibaba-token-plan`)、Qwen Token 套餐(中国)、小米 Token 套餐(中国/欧洲/新加坡)——各自使用官方主机名;models.dev 键与 pi-ai 提供方 id 不同的那几条,把 pi-ai id 保留为别名。八个内置提供方仍作例外并写明原因:Amazon Bedrock、Azure OpenAI、Cloudflare AI Gateway、Cloudflare Workers AI、Google Vertex AI(URL 里带账户或区域),GitHub Copilot 与 OpenAI Codex(以厂商账号行提供),以及 Radius(这里的 `pi_messages` 仅限账号)。pi-ai 升级后若某提供方既未被覆盖也不在例外中,`packages/agent-runtime/src/pi-ai-provider-sync.test.ts` 会失败。不改协议、存储或 IPC。** | pi-ai 其他能力本就可达,但服务目录的 API-key 一半靠手工维护,已经跟库自带的提供方列表脱节(ADR 0307)。 |
| D668 | 每回合一个过程披露,并提供三种转录显示模式 | **修订 D661 / `turn-process-and-thinking-display` ADR:每个回合渲染一个顶层过程披露,包含回答前的全部行;回答留在披露之外。`AppSettings.transcriptDisplayMode` 选择布局:`flat` 不渲染嵌套活动组,`command-first` 将 `Bash`/run 行作为活动组旁的独立行,`fully-folded`(缺失或无效值的默认)让命令留在所属组内,且只有普通助手进度文字会拆分活动组。该模式在渲染时读取,因此切换后立即重绘——投影缓存只以消息和压缩为键。披露标题按失败/停止/执行中/已完成的优先级报告,且绝不回显当前条目;披露与它展开的层级共用一条左边缘。`transcriptDisplayMode` 加入可移植应用字段;`keepCommandsExpanded` 已弃用,仅为持久化设置兼容性保留,不再暴露,也不再参与渲染读取。无 Host 协议、持久化 schema、权限或插件契约变更。见修订后的 ADR、`04-ux/06-settings-ia.md`、`04-ux/08-component-spec.md`、`04-ux/09-interaction-patterns.md` 与 E2E-CHAT-turn-process-and-thinking-display。** | 按时间顺序的分段把同一回合拆成答案上方多个并列披露,而布尔命令折叠偏好只能表达两种布局;三种模式覆盖平铺、命令优先与已发布的分组视图,且不改变工具收到的内容或持久化内容。 |
-| D669 | `@` 查询越过被截断的文件索引 | **修订 D124:8000 条的 `fs/index` 快照被截断时,非空的 `@` 查询会在输入停顿后,通过只读的 Electron 通道 `pi-desktop/fs/search` 在该根目录的完整清单中搜索,最好的 50 行与本地匹配合并。完整的索引从不搜索。远程会话保持使用快照。不改变主机 RPC、存储或 schema。** |
+| D669 | `@` 查询越过被截断的文件索引 | **修订 D124:8000 条的 `fs/index` 快照被截断时,非空的 `@` 查询会在输入停顿后,通过只读的 Electron 通道 `pi-desktop/fs/search` 在该根目录的完整清单中搜索,最好的 50 行与本地匹配合并。完整的索引从不搜索。远程会话保持使用快照。不改变主机 RPC、存储或 schema。** | 只保留最浅 8000 条的索引,会让深几层目录里的脚本对任何查询都匹配不到,而截断提示还在邀请用户细化查询(issue #1781)。 |
## M0. 模型目录决策
From c6db17b881938f5f3c980e9bb48e1915dab94769 Mon Sep 17 00:00:00 2001
From: vastsa
Date: Wed, 21 Oct 2026 23:00:21 +0800
Subject: [PATCH 24/44] fix(e2e): bound the client certificate baseline fetch
Electron's direct fetch rejects before reaching the TLS fixture on macOS,
but can stall at the same client-certificate negotiation on Linux. Bound
the baseline probe and accept its abort as the platform-specific outcome,
while still requiring that no HTTP request reached the fixture.
This keeps the certificate discovery, proxy, redirect, and cancellation
assertions running instead of letting the child process time out.
---
scripts/e2e/provider-client-certificate.ts | 19 +++++++++++++++++--
1 file changed, 17 insertions(+), 2 deletions(-)
diff --git a/scripts/e2e/provider-client-certificate.ts b/scripts/e2e/provider-client-certificate.ts
index c9b70710ee..db1c97279b 100644
--- a/scripts/e2e/provider-client-certificate.ts
+++ b/scripts/e2e/provider-client-certificate.ts
@@ -75,9 +75,24 @@ void app.whenReady().then(async () => {
assert.ok(address && typeof address !== "string" && proxyAddress && typeof proxyAddress !== "string");
const baseUrl = `https://localhost:${address.port}/v1`;
await applyNetworkProxy({ mode: "direct" });
- await assert.rejects(net.fetch(`${baseUrl}/models`), /ERR_SSL_CLIENT_AUTH_CERT_NEEDED/);
+ const baselineController = new AbortController();
+ const baselineAbortTimer = setTimeout(() => baselineController.abort(), 8_000);
+ try {
+ await assert.rejects(
+ net.fetch(`${baseUrl}/models`, { signal: baselineController.signal }),
+ (error: unknown) => {
+ const isCertificateError = error instanceof Error &&
+ error.message.includes("ERR_SSL_CLIENT_AUTH_CERT_NEEDED");
+ const isPlatformHang = error instanceof Error && error.name === "AbortError";
+ assert.ok(isCertificateError || isPlatformHang, `unexpected baseline error: ${String(error)}`);
+ return true;
+ },
+ );
+ } finally {
+ clearTimeout(baselineAbortTimer);
+ }
assert.equal(requests, 0, "the original Electron 43 failure precedes HTTP");
- console.log("baseline: Electron 43 net.fetch fails before HTTP");
+ console.log("baseline: Electron 43 net.fetch failed or stalled before HTTP");
const options = { baseUrl, apiKey: "fixture", signal: AbortSignal.timeout(8_000) };
assert.deepEqual((await probeModelList(options)).models, [{ modelId: "fixture-model", displayName: "fixture-model" }]);
assert.equal((await probeProviderEndpoint(options)).status, 200);
From 82ef18b28cefe74035450bd19408a19e31a9e7b6 Mon Sep 17 00:00:00 2001
From: vastsa
Date: Wed, 21 Oct 2026 23:23:04 +0800
Subject: [PATCH 25/44] fix(e2e): bound the client certificate baseline probe
Electron's direct fetch can remain pending during client-certificate
negotiation on Linux, and its AbortSignal does not reliably interrupt
that platform request. Race the baseline probe against a short deadline;
keep the process alive for the remaining discovery checks, then exit
Electron after the fixture has been verified.
A successful fetch still fails the test, and the fixture must receive no
HTTP request before the certificate error or platform timeout.
---
scripts/e2e/provider-client-certificate.ts | 36 +++++++++++++---------
1 file changed, 21 insertions(+), 15 deletions(-)
diff --git a/scripts/e2e/provider-client-certificate.ts b/scripts/e2e/provider-client-certificate.ts
index db1c97279b..9ae3eb0d62 100644
--- a/scripts/e2e/provider-client-certificate.ts
+++ b/scripts/e2e/provider-client-certificate.ts
@@ -75,24 +75,30 @@ void app.whenReady().then(async () => {
assert.ok(address && typeof address !== "string" && proxyAddress && typeof proxyAddress !== "string");
const baseUrl = `https://localhost:${address.port}/v1`;
await applyNetworkProxy({ mode: "direct" });
- const baselineController = new AbortController();
- const baselineAbortTimer = setTimeout(() => baselineController.abort(), 8_000);
- try {
- await assert.rejects(
- net.fetch(`${baseUrl}/models`, { signal: baselineController.signal }),
- (error: unknown) => {
- const isCertificateError = error instanceof Error &&
- error.message.includes("ERR_SSL_CLIENT_AUTH_CERT_NEEDED");
- const isPlatformHang = error instanceof Error && error.name === "AbortError";
- assert.ok(isCertificateError || isPlatformHang, `unexpected baseline error: ${String(error)}`);
- return true;
- },
+ let baselineTimer: ReturnType | undefined;
+ const baselineTimeout = new Promise<{ kind: "timeout" }>((resolve) => {
+ baselineTimer = setTimeout(() => resolve({ kind: "timeout" }), 8_000);
+ });
+ const baselineOutcome = await Promise.race([
+ net.fetch(`${baseUrl}/models`).then(
+ () => ({ kind: "response" as const }),
+ (error: unknown) => ({ kind: "error" as const, error }),
+ ),
+ baselineTimeout,
+ ]);
+ if (baselineTimer !== undefined) clearTimeout(baselineTimer);
+ if (baselineOutcome.kind === "response") {
+ assert.fail("client certificate was unexpectedly omitted and the request succeeded");
+ }
+ if (baselineOutcome.kind === "error") {
+ assert.ok(
+ baselineOutcome.error instanceof Error &&
+ baselineOutcome.error.message.includes("ERR_SSL_CLIENT_AUTH_CERT_NEEDED"),
+ `unexpected baseline error: ${String(baselineOutcome.error)}`,
);
- } finally {
- clearTimeout(baselineAbortTimer);
}
assert.equal(requests, 0, "the original Electron 43 failure precedes HTTP");
- console.log("baseline: Electron 43 net.fetch failed or stalled before HTTP");
+ console.log(`baseline: Electron 43 net.fetch ${baselineOutcome.kind === "timeout" ? "stalled" : "failed"} before HTTP`);
const options = { baseUrl, apiKey: "fixture", signal: AbortSignal.timeout(8_000) };
assert.deepEqual((await probeModelList(options)).models, [{ modelId: "fixture-model", displayName: "fixture-model" }]);
assert.equal((await probeProviderEndpoint(options)).status, 200);
From fb81b1fc83607c4707e371a0fdfc227af0f3943b Mon Sep 17 00:00:00 2001
From: xieqiying
Date: Thu, 22 Oct 2026 00:06:24 +0800
Subject: [PATCH 26/44] fix(chat): parse positioned and ambiguous file
references safely
Fixes #1722
Tested: pnpm lint && node --test apps/desktop/test/chat-links.test.mjs apps/desktop/test/chat-ref-resolve.test.mjs && pnpm --filter @pi-desktop/agent-runtime exec vitest run src/runtime.test.ts && node scripts/e2e-file-ref-line-scroll.mjs && pnpm docs:check
passed (exit code 0)
---
apps/desktop/src/lib/chat-link-scanner.ts | 8 +--
apps/desktop/src/lib/chat-links.ts | 19 ++---
apps/desktop/test/chat-links.test.mjs | 29 +++++++-
apps/desktop/test/chat-ref-resolve.test.mjs | 41 +++++++++--
...62-chat-file-refs-open-in-the-file-view.md | 12 ++--
docs/spec/03-runtime/01-ipc-protocol.md | 7 +-
docs/spec/04-ux/09-interaction-patterns.md | 8 ++-
docs/spec/06-delivery/04-e2e-test-plan.md | 18 ++---
packages/agent-runtime/src/runtime.test.ts | 4 ++
packages/agent-runtime/src/runtime.ts | 2 +
packages/host-runtime/src/chat-ref-resolve.ts | 71 ++++++-------------
scripts/e2e-file-ref-line-scroll.mjs | 2 +-
scripts/e2e/file-ref-line-scroll.tsx | 4 +-
13 files changed, 135 insertions(+), 90 deletions(-)
diff --git a/apps/desktop/src/lib/chat-link-scanner.ts b/apps/desktop/src/lib/chat-link-scanner.ts
index 7bca4529e8..55d033f60d 100644
--- a/apps/desktop/src/lib/chat-link-scanner.ts
+++ b/apps/desktop/src/lib/chat-link-scanner.ts
@@ -55,7 +55,7 @@ export type ChatLinkCandidateDispositionResolver = (
) => ChatLinkCandidateDisposition;
const PATH_WORD_RE = /^[\p{L}\p{N}_@+./\\-]$/u;
-const TERMINAL_FILE_RE = /\.[A-Za-z0-9]{1,8}(?:[+@-][\p{L}\p{N}_@+-]*)?(?::\d+(?::\d+)?)?$/u;
+const TERMINAL_FILE_RE = /\.[A-Za-z0-9]{1,8}(?:[+@-][\p{L}\p{N}_@+-]*)?(?::\d+(?::\d+|-\d+)?|#[lL]\d+(?:-[lL]?\d+)?)?$/u;
const PROSE_BOUNDARIES = new Set([
"a", "an", "and", "against", "because", "but", "change", "check",
"copy", "create", "created", "delete", "edit", "find", "fix", "for",
@@ -603,7 +603,7 @@ export function scanChatLinkCandidates(
const PATH_WORD = String.raw`[\p{L}\p{N}_@+.-]+`;
const PATH_SEGMENT = String.raw`[\p{L}\p{N}_@+. -]+`;
const PATH_CONTINUATION = String.raw`[\p{L}\p{N}_@+.-]*[\\/]`;
-const FILE_END = String.raw`\.[A-Za-z0-9]{1,8}(?:[+@-][\p{L}\p{N}_@+-]*)?(?::\d+(?::\d+)?)?(?![A-Za-z0-9_@+-]|\.[A-Za-z0-9]|${PATH_CONTINUATION})`;
+const FILE_END = String.raw`\.[A-Za-z0-9]{1,8}(?:[+@-][\p{L}\p{N}_@+-]*)?(?::\d+(?::\d+|-\d+)?|#[lL]\d+(?:-[lL]?\d+)?)?(?![A-Za-z0-9_@+-]|\.[A-Za-z0-9]|${PATH_CONTINUATION})`;
const BARE_FILE_END = String.raw`(?:${[...KNOWN_BARE_CHAT_FILES].join("|")})(?![\p{L}\p{N}_@+.-]|${PATH_CONTINUATION})`;
const FILE_NAME = String.raw`(?:${PATH_SEGMENT}?${FILE_END}|${BARE_FILE_END})`;
const UNC_PREFIX = String.raw`(?:\\\\[^\\/\s]+[\\/]|\/\/[^/\s]+\/)`;
@@ -615,8 +615,8 @@ const FILE_SCAN_SOURCE = [
String.raw`${SPACED_START}[\\/](?:${PATH_SEGMENT}[\\/])*?${FILE_NAME}`,
String.raw`${SPACED_START}(?:\.[A-Za-z0-9_-]+)*${FILE_END}`,
String.raw`(?:${PATH_WORD}[\\/])+(?:${PATH_SEGMENT}[\\/])*?${FILE_NAME}`,
- String.raw`(?:~[\\/])?\/?\.{1,2}[\\/](?:${PATH_WORD}\/)*${PATH_WORD}(?::\d+(?::\d+)?)?`,
- String.raw`(?:~[\\/])?\/?(?:${PATH_WORD}\/)+${PATH_WORD}(?::\d+(?::\d+)?)?`,
+ String.raw`(?:~[\\/])?\/?\.{1,2}[\\/](?:${PATH_WORD}\/)*${PATH_WORD}(?::\d+(?::\d+|-\d+)?|#[lL]\d+(?:-[lL]?\d+)?)?`,
+ String.raw`(?:~[\\/])?\/?(?:${PATH_WORD}\/)+${PATH_WORD}(?::\d+(?::\d+|-\d+)?|#[lL]\d+(?:-[lL]?\d+)?)?`,
String.raw`[\p{L}\p{N}_@+-][\p{L}\p{N}_@+.-]*${FILE_END}`,
].join("|");
const FILE_SCAN_RE = new RegExp(FILE_SCAN_SOURCE, "uy");
diff --git a/apps/desktop/src/lib/chat-links.ts b/apps/desktop/src/lib/chat-links.ts
index 7e89f4f5c1..83496ee920 100644
--- a/apps/desktop/src/lib/chat-links.ts
+++ b/apps/desktop/src/lib/chat-links.ts
@@ -39,7 +39,7 @@ const KNOWN_EXTS = new Set([
]);
const FILE_TOKEN_RE =
- /^(?:(?:[A-Za-z]:[\\/]|~[\\/]|\\\\|\/\/|[\\/])|(?:\.{1,2}[\\/])?)[\p{L}\p{N}_@+. -]+(?:[\\/][\p{L}\p{N}_@+. -]+)*(?::\d+(?::\d+)?)?$/u;
+ /^(?:(?:[A-Za-z]:[\\/]|~[\\/]|\\\\|\/\/|[\\/])|(?:\.{1,2}[\\/])?)[\p{L}\p{N}_@+. -]+(?:[\\/][\p{L}\p{N}_@+. -]+)*(?::\d+(?::\d+|-\d+)?|#[lL]\d+(?:-[lL]?\d+)?)?$/u;
const AT_QUOTED_RE = /^@"([^"\n]+)"$/;
const AT_UNQUOTED_RE = /^@(\/?[^\s]+)$/;
@@ -53,22 +53,23 @@ export function isHtmlFilePath(path: string): boolean {
}
function stripLineRef(path: string): string {
- return path.replace(/:\d+(?::\d+)?$/, "");
+ return path.replace(/(?::\d+(?::\d+|-\d+)?|#[lL]\d+(?:-[lL]?\d+)?)$/u, "");
}
-/** Trailing `:line[:col]` on a file token, if any. */
+/** Trailing line, column, range, or GitHub line anchor on a file token. */
export function parseFileRefPosition(
text: string,
): { line: number; column?: number } | null {
const token = text.trim().replace(/[.,!?;:,。!?;:]+$/u, "");
- const match = token.match(/:(\d+)(?::(\d+))?$/);
+ const match = token.match(/(?::(\d+)(?::(\d+)|-(\d+))?|#L(\d+)(?:-L?(\d+))?)$/iu);
if (!match) return null;
- const line = Number(match[1]);
+ const line = Number(match[1] ?? match[4]);
if (!Number.isFinite(line) || line < 1) return null;
- const column = match[2] !== undefined ? Number(match[2]) : undefined;
- return column !== undefined && Number.isFinite(column) && column >= 1
- ? { line, column }
- : { line };
+ const column = match[2] ? Number(match[2]) : undefined;
+ if (column !== undefined && (!Number.isFinite(column) || column < 1)) return null;
+ const rangeEnd = match[3] ?? match[5];
+ if (rangeEnd !== undefined && (!Number.isFinite(Number(rangeEnd)) || Number(rangeEnd) < line)) return null;
+ return { line, ...(column !== undefined ? { column } : {}) };
}
function leafName(path: string): string {
diff --git a/apps/desktop/test/chat-links.test.mjs b/apps/desktop/test/chat-links.test.mjs
index 3f6ab9dbbd..ea04b6db6b 100644
--- a/apps/desktop/test/chat-links.test.mjs
+++ b/apps/desktop/test/chat-links.test.mjs
@@ -155,6 +155,9 @@ test("parseFileRef accepts pathy tokens and strips line refs", () => {
assert.equal(parseFileRef("apps/desktop/src/App.tsx"), "apps/desktop/src/App.tsx");
assert.equal(parseFileRef("src/main.rs:42"), "src/main.rs");
assert.equal(parseFileRef("src/main.rs:42:7"), "src/main.rs");
+ assert.equal(parseFileRef("src/main.rs:42-44"), "src/main.rs");
+ assert.equal(parseFileRef("src/main.rs#L42"), "src/main.rs");
+ assert.equal(parseFileRef("src/main.rs#L42-L44"), "src/main.rs");
assert.equal(parseFileRef("./scripts/build.sh"), "./scripts/build.sh");
assert.equal(parseFileRef("/abs/path/file.ts"), "/abs/path/file.ts");
assert.equal(parseFileRef("docs/Makefile"), "docs/Makefile");
@@ -879,13 +882,27 @@ test("URL link creation is capped per conversion without changing source text",
);
});
-test("parseFileRefPosition keeps :line[:col] that parseFileRef strips", () => {
+test("parseFileRefPosition handles line, column, range, and GitHub anchors", () => {
assert.deepEqual(parseFileRefPosition("src/main.rs:42"), { line: 42 });
assert.deepEqual(parseFileRefPosition("src/main.rs:42:7"), { line: 42, column: 7 });
+ assert.deepEqual(parseFileRefPosition("src/main.rs:42-44"), { line: 42 });
+ assert.deepEqual(parseFileRefPosition("src/main.rs#L42"), { line: 42 });
+ assert.deepEqual(parseFileRefPosition("src/main.rs#L42-L44"), { line: 42 });
assert.deepEqual(parseFileRefPosition("src/main.rs:42."), { line: 42 });
assert.deepEqual(parseFileRefPosition("src/main.rs:42:7,"), { line: 42, column: 7 });
assert.equal(parseFileRefPosition("src/main.rs"), null);
assert.equal(parseFileRefPosition("src/main.rs:0"), null);
+ assert.equal(parseFileRefPosition("src/main.rs:42-41"), null);
+});
+
+test("splitChatText preserves common line-reference formats as positioned file chips", () => {
+ for (const [suffix, line] of [[":42-44", 42], ["#L43", 43], ["#L44-L48", 44]]) {
+ const source = `See src/main.rs${suffix}.`;
+ const segments = splitChatText(source, ROOT);
+ const target = segments.find((segment) => segment.kind === "target");
+ assert.deepEqual(target?.target, { kind: "file", path: "src/main.rs", line }, source);
+ assert.equal(segments.map((segment) => segment.text).join(""), source);
+ }
});
test("resolvePreviewTarget carries line/col on file chips (#681)", () => {
@@ -900,6 +917,16 @@ test("resolvePreviewTarget carries line/col on file chips (#681)", () => {
line: 42,
column: 7,
});
+ assert.deepEqual(resolvePreviewTarget("src/a.ts:42-48", ROOT), {
+ kind: "file",
+ path: "src/a.ts",
+ line: 42,
+ });
+ assert.deepEqual(resolvePreviewTarget("src/a.ts#L43-L48", ROOT), {
+ kind: "file",
+ path: "src/a.ts",
+ line: 43,
+ });
assert.deepEqual(resolvePreviewTarget("src/a.ts:42:7.", ROOT), {
kind: "file",
path: "src/a.ts",
diff --git a/apps/desktop/test/chat-ref-resolve.test.mjs b/apps/desktop/test/chat-ref-resolve.test.mjs
index 9fe1644054..33044757a4 100644
--- a/apps/desktop/test/chat-ref-resolve.test.mjs
+++ b/apps/desktop/test/chat-ref-resolve.test.mjs
@@ -37,8 +37,8 @@ const resolve = (ref, options) => resolveChatFileRef(ref, roots(options));
* but names only `openimage.js` in its reply, so the click resolved to a
* workspace-root path that does not exist and the panel opened blank. The
* contract under test is the product priority — the open project answers
- * first, the session scratch store second — plus the "best" rule inside one
- * root: longest matching tail, then shallowest path.
+ * first, the session scratch store second — plus safe matching inside one
+ * root: an exact path or unique complete suffix only.
*/
function tempTree(name, files) {
@@ -150,7 +150,7 @@ test("an exact relative link within its root remains resolvable", async () => {
test("a stale fuzzy index skips escaped and missing candidates in priority order", async () => {
const workspace = tempTree("stale-index", ["a/page.md", "b/page.md", "c/page.md"]);
- assert.equal((await resolve("page.md", { workspace }))?.relativePath, "a/page.md");
+ assert.equal(await resolve("page.md", { workspace }), null);
renameSync(join(workspace, "a"), join(workspace, "old-a"));
renameSync(join(workspace, "b"), join(workspace, "old-b"));
const outside = tempTree("stale-outside", ["page.md"]);
@@ -172,19 +172,50 @@ test("a dangling relative link, including a middle directory, does not fall back
assert.equal(await resolve("linked/page.md", { scratch }), null);
});
-test("a longer matching tail beats a bare leaf name", async () => {
+test("a unique complete path suffix resolves", async () => {
const workspace = tempTree("ws", ["deep/openimage.js", "src/dir/openimage.js"]);
const match = await resolve("dir/openimage.js", { workspace });
assert.equal(match?.matchedBy, "path-suffix");
assert.equal(match?.relativePath, "src/dir/openimage.js");
});
-test("the shallowest candidate wins when the tail length ties", async () => {
+test("an exact root-level path wins even when shorthand matches are ambiguous", async () => {
const workspace = tempTree("ws", ["a/b/openimage.js", "openimage.js"]);
const match = await resolve("openimage.js", { workspace });
+ assert.equal(match?.matchedBy, "exact-relative");
assert.equal(match?.relativePath, "openimage.js");
});
+test("ambiguous basename and directory suffix references do not guess", async () => {
+ const workspace = tempTree("ambiguous", [
+ "crates/host-core/src/main.rs",
+ "crates/agent/src/main.rs",
+ "src/deep/file.ts",
+ "other/deep/file.ts",
+ ]);
+ assert.equal(await resolve("main.rs", { workspace }), null);
+ assert.equal(await resolve("deep/file.ts", { workspace }), null);
+});
+
+test("a partial path never degrades to a matching basename", async () => {
+ const workspace = tempTree("partial-path", ["crates/host-core/src/main.rs"]);
+ assert.equal(await resolve("acp-server/src/main.rs", { workspace }), null);
+});
+
+test("an ambiguous project match does not fall through to a different root", async () => {
+ const workspace = tempTree("ambiguous-priority", ["a/page.md", "b/page.md"]);
+ const scratch = tempTree("unique-scratch", ["page.md"]);
+ assert.equal(await resolve("page.md", { workspace, scratch }), null);
+});
+
+test("line suffixes are stripped before host-side file resolution", async () => {
+ const workspace = tempTree("line-ref", ["src/main.rs"]);
+ for (const reference of ["src/main.rs:42-44", "src/main.rs#L42", "src/main.rs#L42-L44"]) {
+ const match = await resolve(reference, { workspace });
+ assert.equal(match?.relativePath, "src/main.rs", reference);
+ }
+});
+
test("the project answers before the session scratch store", async () => {
const workspace = tempTree("ws", ["notes/openimage.js"]);
const scratch = tempTree("scratch", ["openimage.js"]);
diff --git a/docs/adr/0262-chat-file-refs-open-in-the-file-view.md b/docs/adr/0262-chat-file-refs-open-in-the-file-view.md
index 3369e58935..2dd41f3c0a 100644
--- a/docs/adr/0262-chat-file-refs-open-in-the-file-view.md
+++ b/docs/adr/0262-chat-file-refs-open-in-the-file-view.md
@@ -40,16 +40,18 @@ work-panel tab already carries was honoured by main for `pi.browser` only.
first, the session scratch store second, the attachment store last** — and
the first root that answers wins, so the project is searched to exhaustion
before the scratch store is considered;
- - inside one root, an exact path beats a shorthand; among shorthands the
- longest matching tail wins, then the shallowest path, so `src/dir/a.ts`
- beats a second `dir/a.ts` buried deeper;
+ - inside one root, an exact path beats a shorthand; a shorthand resolves
+ only when its complete supplied suffix uniquely identifies one safe file.
+ It never degrades to a shorter suffix, and ambiguous matches resolve to
+ nothing;
- the files panel's ignore set applies, so a dependency tree is never
searched;
- a reference that matches nothing opens **nothing** and reports itself. No
empty panel, no blank browser page.
2. **The destination follows where the reference resolved.** A project file
- opens in the `pi.file-manager` view, except a `path:line` reference, which
- opens in the host's read-only `file:` tab so the requested source line can
+ opens in the `pi.file-manager` view, except a positioned reference (`:line`,
+ `:line:column`, `:line-range` or `#Lline[-Lend]`), which opens in the host's
+ read-only `file:` tab so the requested source line can
be brought into view. The bundled view accepts opaque path locations and has
no line-navigation contract; this keeps the path unchanged and uses the
host viewer's existing scroll support. A file in the session scratch or
diff --git a/docs/spec/03-runtime/01-ipc-protocol.md b/docs/spec/03-runtime/01-ipc-protocol.md
index 8eea0bc404..1abc005b8d 100644
--- a/docs/spec/03-runtime/01-ipc-protocol.md
+++ b/docs/spec/03-runtime/01-ipc-protocol.md
@@ -1952,9 +1952,10 @@ Renderer IPC kept for the Plan-safe preview facade and URL fallback:
other folders, which are then searched in the group's own order (ADR 0263),
so a shorthand resolves in a sibling folder as readily as in the primary one,
and the match names the folder that answered. Inside one root an exact path
- beats a shorthand; among shorthands the longest matching tail wins, then the
- shallowest path. Relative and indexed candidates must resolve to regular files
- whose real paths remain inside their answering root; an exact path through an
+ beats a shorthand; a shorthand matches only when its complete supplied suffix
+ identifies one safe file. It never degrades to a shorter suffix, and an
+ ambiguous match returns `match: null`. Relative and indexed candidates must
+ resolve to regular files whose real paths remain inside their answering root; an exact path through an
escaping or dangling link cannot fall back to a same-name indexed file. The
files-panel ignore set applies. An absolute reference may also name a store
the app reads without searching it: the whole scratch store
diff --git a/docs/spec/04-ux/09-interaction-patterns.md b/docs/spec/04-ux/09-interaction-patterns.md
index 78bca69413..4e38d5ae9d 100644
--- a/docs/spec/04-ux/09-interaction-patterns.md
+++ b/docs/spec/04-ux/09-interaction-patterns.md
@@ -1400,9 +1400,11 @@ Project drag/drop follows these patterns:
No project is required to open a scratch artifact. Missing workspace state
is normalized consistently across asynchronous session-change guards.
Local `file:` Markdown URLs are converted to file references before
- sanitization, not admitted as native links. `path:line[:column]` retains
- source navigation in plain text, inline code and Markdown links, including
- HTML; unavailable browser views report an error without auto-enabling.
+ sanitization, not admitted as native links. `path:line[:column]`,
+ `path:line-range` and GitHub `path#Lline[-Lend]` retain source navigation
+ from plain text, inline code and Markdown links, including HTML; ranges open
+ at their starting line. Ambiguous shorthand paths do not resolve. Unavailable
+ browser views report an error without auto-enabling.
The address handed to
the work panel follows the folder that answered: a file of the primary folder
travels as a project-relative path, a file of a sibling folder of the same
diff --git a/docs/spec/06-delivery/04-e2e-test-plan.md b/docs/spec/06-delivery/04-e2e-test-plan.md
index ced0b4975c..4d0281b1a9 100644
--- a/docs/spec/06-delivery/04-e2e-test-plan.md
+++ b/docs/spec/06-delivery/04-e2e-test-plan.md
@@ -13498,10 +13498,9 @@ are withdrawn with ADR 0165.
- Clicking `openimage.js` opens the project's `img/openimage.js`, although the
scratch store holds a file with that same leaf name: the project is
searched to exhaustion before the scratch store is considered at all.
- - `dir/a.ts` opens `src/dir/a.ts`: an exact path beats a shorthand, a longer
- matching tail beats a bare leaf name, and the shallowest candidate wins a
- tail-length tie, so the deeper `packages/app/dir/a.ts` is never the one
- that opens.
+ - `dir/a.ts` matches both `src/dir/a.ts` and
+ `packages/app/dir/a.ts`, so the shorthand is ambiguous and opens nothing.
+ The exact reference `src/dir/a.ts` opens that path.
- A reference the project cannot answer resolves in the session scratch
store; one that neither answers resolves in the attachment store, and an
`attachments/` ref opens that stored blob.
@@ -18074,18 +18073,19 @@ renderer's durable transcript reads. No real model or provider is contacted.
closure behavior. Covered by the parameterized runtime overflow user-path test.
-#### E2E-262: Transcript path:line opens and scrolls the host file viewer
+#### E2E-262: Transcript positioned file references open and scroll the host file viewer
- **Preconditions:** Isolated Electron/Chromium, an active workspace and session,
the bundled file-manager view available, and deterministic filesystem IPC
fixtures.
-- **Steps:** Render a real transcript `path:line:column` reference followed by
+- **Steps:** Render a real transcript `path:line-range` reference followed by
sentence punctuation; click its verified file chip and wait for the host file
- viewer to load.
+ viewer to load. Unit coverage also exercises `path:line:column` and GitHub
+ `path#Lline[-Lend]` references.
- **Expected:** Despite the bundled file-manager view being available, the
positioned reference opens in the host's read-only file tab. The file request
- retains its line and column, and the viewer scrolls the requested line into
- the visible center area. The path and file contents remain the same as the
+ retains the range's starting line, and the viewer scrolls that line into the
+ visible center area. The path and file contents remain the same as the
reference target.
- **Specs:** `04-ux/08` §11.8; ADR 0262.
- **Status:** `node scripts/e2e-file-ref-line-scroll.mjs` mounts production
diff --git a/packages/agent-runtime/src/runtime.test.ts b/packages/agent-runtime/src/runtime.test.ts
index fc0cc4b8e9..c50577bacd 100644
--- a/packages/agent-runtime/src/runtime.test.ts
+++ b/packages/agent-runtime/src/runtime.test.ts
@@ -377,6 +377,9 @@ describe("custom system prompt files (issue #542)", () => {
// Operational rules from the default prompt must survive the replacement.
expect(prompt).toContain("Complete the requested work and relevant checks");
expect(prompt).toContain("Before each tool batch, briefly state its purpose");
+ expect(prompt).toContain("File references: when citing a real local file, use a Markdown link");
+ expect(prompt).toContain("do not use ranges or GitHub #L anchors");
+ expect(prompt).toContain("Do not wrap links in backticks or use file://, vscode://, or https://");
expect(prompt).toContain("Editing workflow: inside the advertised workspace");
expect(prompt).toContain("You are operating in Agent mode.");
@@ -423,6 +426,7 @@ describe("custom system prompt files (issue #542)", () => {
const prompt = promptOf(runtime);
expect(prompt).toContain("You are PI-Desktop");
+ expect(prompt).toContain("File references: when citing a real local file, use a Markdown link");
expect(prompt).not.toContain("MARKER-XYZ-123");
await runtime.dispose();
diff --git a/packages/agent-runtime/src/runtime.ts b/packages/agent-runtime/src/runtime.ts
index 7249de1521..966ca3eaec 100644
--- a/packages/agent-runtime/src/runtime.ts
+++ b/packages/agent-runtime/src/runtime.ts
@@ -2077,6 +2077,8 @@ export class DesktopAgentRuntime {
"Complete the requested work and relevant checks without expanding scope. Preserve unrelated user changes. Resolve recoverable blockers yourself.",
// Visibility rules.
"Before each tool batch, briefly state its purpose. Keep the user informed during long work. The final response must state the outcome, verification, and remaining blockers. Never claim actions or checks you did not perform.",
+ // File-reference formatting.
+ "File references: when citing a real local file, use a Markdown link with a short label and the exact absolute path as its target, e.g. [file.ts](/workspace/src/file.ts:42). Add only a starting line (:line or :line:column) when useful; do not use ranges or GitHub #L anchors. Wrap destinations containing spaces in angle brackets. Do not wrap links in backticks or use file://, vscode://, or https:// for local files. Link only to existing files in the accessible workspace; mention unavailable or other-repository files as code text.",
// Delegation steering (ADR 0089).
...(this.subagents.length
? [
diff --git a/packages/host-runtime/src/chat-ref-resolve.ts b/packages/host-runtime/src/chat-ref-resolve.ts
index 9803053ebb..54ace884df 100644
--- a/packages/host-runtime/src/chat-ref-resolve.ts
+++ b/packages/host-runtime/src/chat-ref-resolve.ts
@@ -26,9 +26,9 @@ import { getWorkspaceFileIndex } from "./fs-index.js";
* first, the session's own scratch store second, the attachment blob
* store last — and the first root that answers wins, so the project is
* searched to exhaustion before the scratch store is considered;
- * 4. inside one root an exact path beats a shorthand, and among shorthands
- * the longest matching tail wins, then the shallowest path, so
- * `src/dir/a.ts` beats a second `dir/a.ts` buried deeper.
+ * 4. inside one root an exact path wins; a shorthand resolves only when the
+ * complete supplied suffix matches one safe file. Ambiguous or shortened
+ * suffixes remain unresolved.
*/
export type ChatRefRoots = {
@@ -69,8 +69,6 @@ type CanonicalChatRefRoot = ChatRefRootEntry & { realPath: string | null };
const MAX_REF_LENGTH = 512;
const ATTACHMENT_HASH_PATTERN = /^[0-9a-f]{64}$/i;
-/** A tail longer than this is a user quoting a full path, not a shorthand. */
-const MAX_FUZZY_TAIL_SEGMENTS = 6;
/** Bound for the scratch/attachment walk; those trees are small by design. */
const MAX_ROOT_WALK_ENTRIES = 4000;
@@ -90,11 +88,11 @@ function matchesSegment(candidate: string, wanted: string): boolean {
return CASE_INSENSITIVE_FS && candidate.toLowerCase() === wanted.toLowerCase();
}
-/** Strip the composer sigil, optional quotes, and a `:line[:col]` reference. */
+/** Strip the composer sigil, optional quotes, and a file line reference. */
function cleanRef(raw: string): string {
let value = stripRefDecorations(String(raw ?? ""));
if (value.includes("\0")) return "";
- value = value.replace(/:\d+(?::\d+)?$/, "");
+ value = value.replace(/(?::\d+(?::\d+|-\d+)?|#L\d+(?:-L?\d+)?)$/i, "");
return value;
}
@@ -250,14 +248,7 @@ function segmentsOf(path: string): string[] {
return toPosix(path).split("/").filter(Boolean);
}
-/** Fewer segments first, then a stable lexicographic order. */
-function compareCandidates(a: string, b: string): number {
- const depthDelta = segmentsOf(a).length - segmentsOf(b).length;
- if (depthDelta !== 0) return depthDelta;
- return a.localeCompare(b);
-}
-
-function endsWithTail(fileSegments: string[], tail: string[]): boolean {
+function endsWithTail(fileSegments: readonly string[], tail: readonly string[]): boolean {
if (fileSegments.length < tail.length) return false;
const offset = fileSegments.length - tail.length;
for (let index = 0; index < tail.length; index += 1) {
@@ -268,35 +259,17 @@ function endsWithTail(fileSegments: string[], tail: string[]): boolean {
type FuzzyCandidate = { relativePath: string; matchedBy: FsChatRefMatchKind };
-/**
- * Longest tail first, so a two-segment shorthand beats a bare leaf name.
- * Within one tail the shallowest file wins.
- */
+/** Only a unique candidate matching the complete supplied suffix is safe. */
function fuzzyCandidates(
files: readonly string[],
- tails: readonly string[][],
+ segments: readonly string[],
): FuzzyCandidate[] {
- const parsedFiles = files.map((file) => ({
- file,
- segments: segmentsOf(file),
- }));
- const candidates: FuzzyCandidate[] = [];
- const seen = new Set();
- for (const tail of tails) {
- const matches = parsedFiles
- .filter((entry) => endsWithTail(entry.segments, tail))
- .map((entry) => entry.file)
- .sort(compareCandidates);
- for (const file of matches) {
- if (seen.has(file)) continue;
- seen.add(file);
- candidates.push({
- relativePath: file,
- matchedBy: tail.length === 1 ? "basename" : "path-suffix",
- });
- }
- }
- return candidates;
+ return files
+ .filter((file) => endsWithTail(segmentsOf(file), segments))
+ .map((relativePath) => ({
+ relativePath,
+ matchedBy: segments.length === 1 ? "basename" : "path-suffix",
+ }));
}
async function isContainedRegularFile(root: string, relativePath: string): Promise {
@@ -444,11 +417,6 @@ export async function resolveChatFileRef(
// outright: the open project is searched to exhaustion before the session
// scratch store is considered at all. Inside one root the reference read
// as a path verbatim outranks a tail match.
- const tails: string[][] = [];
- const longestTail = Math.min(parsed.segments.length, MAX_FUZZY_TAIL_SEGMENTS);
- for (let length = longestTail; length >= 1; length -= 1) {
- tails.push(parsed.segments.slice(parsed.segments.length - length));
- }
for (const root of rootList) {
const absolutePath = join(root.path, ...parsed.segments);
if (await isRegularFile(absolutePath)) {
@@ -465,10 +433,17 @@ export async function resolveChatFileRef(
if (await hasInvalidLinkAncestor(root.path, parsed.segments)) return null;
const candidates = fuzzyCandidates(
await listRootFiles(root.kind, root.path),
- tails,
+ parsed.segments,
);
+ const safeCandidates: FuzzyCandidate[] = [];
for (const candidate of candidates) {
- if (!(await isContainedRegularFile(root.path, candidate.relativePath))) continue;
+ if (await isContainedRegularFile(root.path, candidate.relativePath)) {
+ safeCandidates.push(candidate);
+ if (safeCandidates.length > 1) return null;
+ }
+ }
+ const candidate = safeCandidates[0];
+ if (candidate) {
return {
root: root.kind,
relativePath: candidate.relativePath,
diff --git a/scripts/e2e-file-ref-line-scroll.mjs b/scripts/e2e-file-ref-line-scroll.mjs
index 8238b6d295..c95c31b37c 100644
--- a/scripts/e2e-file-ref-line-scroll.mjs
+++ b/scripts/e2e-file-ref-line-scroll.mjs
@@ -90,7 +90,7 @@ app.whenReady().then(async () => {
assert.deepEqual(result.resolveRefs, ["src/scroll-target.txt", "核查报告.md", "src/scroll-target.txt"]);
assert.deepEqual(result.readPaths, ["src/scroll-target.txt"]);
assert.equal(result.selectedPath, "src/scroll-target.txt");
- assert.deepEqual(result.request, { path: "src/scroll-target.txt", seq: 1, line: 65, column: 4 });
+ assert.deepEqual(result.request, { path: "src/scroll-target.txt", seq: 1, line: 65 });
assert.deepEqual(result.scrollCall, { line: "65", block: "center" });
assert.ok(result.scrollTop > 0, "host file viewer did not scroll away from the top");
assert.equal(result.targetLineVisible, true, "requested line is outside the visible viewer area");
diff --git a/scripts/e2e/file-ref-line-scroll.tsx b/scripts/e2e/file-ref-line-scroll.tsx
index daf189fb8d..2e08c0e2cf 100644
--- a/scripts/e2e/file-ref-line-scroll.tsx
+++ b/scripts/e2e/file-ref-line-scroll.tsx
@@ -110,7 +110,7 @@ void i18n
root.render(
-
+
@@ -178,7 +178,7 @@ void i18n
pluginEnableCalls,
fileManagerLocation: fileManagerTab?.location ?? null,
selectedPath: document.querySelector(".file-viewer-path")?.textContent,
- segments: splitChatText(`Review ${targetPath}:${targetLine}:4.`, "/workspace"),
+ segments: splitChatText(`Review ${targetPath}:${targetLine}-70.`, "/workspace"),
resolveRefs,
readPaths,
request,
From 986212f64342b44d85cb2734f851db612164d4b2 Mon Sep 17 00:00:00 2001
From: xieqiying
Date: Thu, 22 Oct 2026 02:44:28 +0800
Subject: [PATCH 27/44] fix(transcript): keep activity details visible after
turns settle
Fixes #1806
Tested: pnpm test:e2e:transcript && node --test apps/desktop/test/thinking-ui.test.mjs apps/desktop/test/transcript-display-modes-ui.test.mjs && pnpm typecheck
passed (exit code 0)
---
.../chat/transcript/ActivityGroup.tsx | 9 +-
.../chat/transcript/ActivityItems.tsx | 12 +--
apps/desktop/test/thinking-ui.test.mjs | 7 +-
.../test/transcript-display-modes-ui.test.mjs | 7 +-
docs/adr/turn-process-and-thinking-display.md | 46 ++++----
docs/spec/04-ux/08-component-spec.md | 60 +++++------
docs/spec/04-ux/09-interaction-patterns.md | 24 ++---
docs/spec/06-delivery/04-e2e-test-plan.md | 24 +++--
docs/spec/08-meta/decisions-log.md | 17 +++
scripts/e2e/turn-process.tsx | 100 +++++++++++++++++-
10 files changed, 212 insertions(+), 94 deletions(-)
diff --git a/apps/desktop/src/features/chat/transcript/ActivityGroup.tsx b/apps/desktop/src/features/chat/transcript/ActivityGroup.tsx
index 48c4a65836..488e4379a9 100644
--- a/apps/desktop/src/features/chat/transcript/ActivityGroup.tsx
+++ b/apps/desktop/src/features/chat/transcript/ActivityGroup.tsx
@@ -61,6 +61,8 @@ type Translate = (key: string, options?: Record) => string;
type ActivityItem = AssistantActivityItem;
+const AUTOMATIC_OPEN_MAX_ITEMS = 4;
+
function waitingSubagentActionLabel(
agent: AgentActivityAgent,
@@ -204,7 +206,6 @@ export const ActivityGroup = memo(function ActivityGroup({
const showThinking = useAppStore((state) => resolveShowThinking(state.settings));
const hideThinking = !showThinking;
const displayMode = useAppStore((state) => resolveTranscriptDisplayMode(state.settings));
- const thinkingDefaultOpen = displayMode !== "fully-folded";
const { t } = useTranslation();
const detailsId = useId();
const rawDelegateItems = useMemo(() => items.filter(isDelegationActivityItem), [items]);
@@ -241,8 +242,11 @@ export const ActivityGroup = memo(function ActivityGroup({
? searchTarget.requestId : undefined, [items, searchTarget]);
const visibleItems = useMemo(() => cachedVisibleActivityItems(items, hideThinking, isActive), [items, hideThinking, isActive]);
const first = items[0];
+ // Groups frame their rows; each tool or search payload keeps its own
+ // disclosure, so leaving a small group open does not reveal tool details.
+ const automaticallyOpen = hasSubagentTopology || live || visibleItems.length <= AUTOMATIC_OPEN_MAX_ITEMS;
const disclosure = useAutomaticDisclosure(
- hasSubagentTopology ? live : visibleItems.length <= 1 || live,
+ automaticallyOpen,
revealRequest,
disclosureKey("activity", first?.message.id ?? "", first?.kind ?? "", first?.kind === "hostedSearch" ? first.round.id : ""),
);
@@ -321,7 +325,6 @@ export const ActivityGroup = memo(function ActivityGroup({
delegationStatuses={delegationStatuses}
delegationTimings={delegationTimings}
onUserInteraction={claimDisclosure}
- thinkingDefaultOpen={thinkingDefaultOpen}
/>;
// Flat mode has one outer process disclosure and no nested group at all.
diff --git a/apps/desktop/src/features/chat/transcript/ActivityItems.tsx b/apps/desktop/src/features/chat/transcript/ActivityItems.tsx
index 72c9aa8e7f..59a8cc006b 100644
--- a/apps/desktop/src/features/chat/transcript/ActivityItems.tsx
+++ b/apps/desktop/src/features/chat/transcript/ActivityItems.tsx
@@ -22,13 +22,10 @@ type ActivityItemsProps = {
delegationStatuses: ReadonlyMap;
delegationTimings: ReadonlyMap;
onUserInteraction: () => void;
- /** Flat and command-first expand every Thinking row by default. */
- thinkingDefaultOpen?: boolean;
};
type ActivityItemBlockProps = Omit & {
block: RenderBlock;
- lastItem?: AssistantActivityItem;
topologyItem?: AssistantActivityItem;
delegateItems?: DelegationActivityItem[];
delegationStatuses?: ReadonlyMap;
@@ -36,9 +33,8 @@ type ActivityItemBlockProps = Omit{block.items.map((item) => {
// The topology predicate narrows to all tools, but a false result can still
@@ -74,7 +70,7 @@ const ActivityItemBlock = memo(function ActivityItemBlock({
key={`thinking-${item.message.id}`}
message={item.message}
streaming={isActive && item.message.status === "streaming"}
- autoOpen={thinkingDefaultOpen || (live && item === lastItem)}
+ autoOpen
onUserInteraction={onUserInteraction}
/>;
})}>;
@@ -82,23 +78,19 @@ const ActivityItemBlock = memo(function ActivityItemBlock({
export const ActivityItems = memo(function ActivityItems({ items, ...context }: ActivityItemsProps) {
const blocks = useRenderBlocks(items, itemKey);
- const lastItem = items.at(-1);
const topologyItem = context.delegateItems[0];
return <>{blocks.map((block) => {
- const ownsLast = lastItem !== undefined && block.items.includes(lastItem);
const ownsTopology = topologyItem !== undefined && block.items.includes(topologyItem);
return ;
})}>;
});
diff --git a/apps/desktop/test/thinking-ui.test.mjs b/apps/desktop/test/thinking-ui.test.mjs
index a0773f7afd..401c10618f 100644
--- a/apps/desktop/test/thinking-ui.test.mjs
+++ b/apps/desktop/test/thinking-ui.test.mjs
@@ -278,10 +278,13 @@ test("tool and search rows stay collapsed while thinking keeps its leaf default"
assert.match(transcriptDisclosureSource, /revealRequest\?: number/);
assert.match(transcriptDisclosureSource, /const currentOpen = useRef\(open\)/);
assert.match(transcriptDisclosureSource, /const setManualOpen = useCallback/);
- assert.match(transcriptSource, /useAutomaticDisclosure\(\s*hasSubagentTopology \? live : visibleItems\.length <= 1/);
assert.match(
transcriptSource,
- / {
assert.match(turnProcessSource, /isStandaloneRunActivity\(item\)/);
});
-test("thinking expands by default outside fully-folded mode", () => {
- assert.match(activityGroupSource, /displayMode !== "fully-folded"/);
- assert.match(activityGroupSource, /thinkingDefaultOpen=\{thinkingDefaultOpen\}/);
- assert.match(activityItemsSource, /autoOpen=\{thinkingDefaultOpen \|\| \(live && item === lastItem\)\}/);
+test("thinking rows expand by default in every transcript display mode", () => {
+ assert.doesNotMatch(activityGroupSource, /thinkingDefaultOpen/);
+ assert.match(activityItemsSource, / {
diff --git a/docs/adr/turn-process-and-thinking-display.md b/docs/adr/turn-process-and-thinking-display.md
index 01a8a399f4..daee9ad9f5 100644
--- a/docs/adr/turn-process-and-thinking-display.md
+++ b/docs/adr/turn-process-and-thinking-display.md
@@ -2,8 +2,8 @@
- Status: Accepted
- Date: 2026-09-17
-- Amended: 2026-10-21
-- Issues: #510, #461
+- Amended: 2026-10-22
+- Issues: #510, #461, #1806
- Amends: D071, [ADR 0242](0242-delta-only-streaming-updates.md)
## Context
@@ -64,11 +64,11 @@ still load, is no longer exposed in Settings, and is not read for rendering; new
writes store `transcriptDisplayMode`.
Group folding defaults are unified across modes and do not depend on the
-thinking preference. Where a group renders, the group that owns the active
-execution segment starts open, then closes on completion only while untouched.
-Other completed groups start closed. An untouched active group containing any
-recorded failed or denied tool stays open through later recovery and closes on
-turn completion if still untouched.
+thinking preference. The active ordinary group stays open while its segment is
+active. After completion, ordinary groups with at most four visible items stay
+open, larger ordinary groups start closed, and Task topology groups stay open.
+Tool, search and run-row payloads keep their own closed defaults. Explicit user
+choices remain authoritative.
The turn's disclosure header states the turn's outcome and never echoes the item
it is working on, because a shell command or search query can be arbitrarily
@@ -87,13 +87,11 @@ The disclosure and the levels it reveals share one left edge. Hierarchy is
carried by type size and colour, not by indentation, so a nested group header and
a run row start exactly where the turn header does.
-The thinking preference is a boolean `showThinking`. With it on, `flat` and
-`command-first` expand every Thinking row by default and let the user collapse
-them; an expanded row shows the full reasoning markdown, while a collapsed row
-shows only the Thinking indicator with no summary or excerpt. `fully-folded`
-keeps the released exception: earlier Thinking rows stay collapsed, and the last
-active Thinking row opens only while it is the live step, so completed rows
-collapse. With the preference off, no completed reasoning row renders; only a
+The thinking preference is a boolean `showThinking`. With it on, every visible
+Thinking row expands by default in all three display modes and the user may
+collapse each row independently; an expanded row shows the full reasoning
+markdown, while a collapsed row shows only the Thinking indicator with no summary
+or excerpt. With the preference off, no completed reasoning row renders; only a
live whole-run `TextShimmer` `Thinking` indicator remains while reasoning is
actively streaming. The shimmer is a 1.2s linear sweep with a 220ms fade — no
spinner, pulsing dot, or per-character animation — and stays static under
@@ -151,10 +149,11 @@ turn.
- One disclosure per turn keeps the final answer and actionable interruptions
reachable, and makes a long turn collapsible in a single gesture.
- Group folding defaults are unified across display modes: active work stays
- visible, untouched completed groups fold by default, and explicit disclosure
- choices are preserved regardless of the thinking preference. Closing the
- turn's disclosure closes the groups under it, and reopening restores the groups
- the user had opened.
+ visible, small completed ordinary groups and Task topology groups stay open,
+ and larger ordinary groups start closed. Explicit disclosure choices are
+ preserved regardless of the thinking preference. Closing the turn's disclosure
+ hides the groups under it, and reopening restores their defaults and explicit
+ choices.
- With `showThinking` off, no completed reasoning row renders; only the live
whole-run TextShimmer `Thinking` indicator remains while reasoning streams.
Stored reasoning is retained and reappears when the preference is turned back
@@ -165,8 +164,8 @@ turn.
groups; all three render exactly one disclosure, and reading the mode while
rendering repaints the transcript immediately instead of waiting for new
messages.
-- With `showThinking` on, Thinking rows default expanded in `flat` and
- `command-first`; `fully-folded` keeps the live-only auto-open exception.
+- With `showThinking` on, Thinking rows default expanded in `flat`,
+ `command-first`, and `fully-folded`.
- The header answers "how did this turn end up" in one short line. Echoing the
current command was removed: it pushed the counts off the row and duplicated
what opening the item already shows.
@@ -191,6 +190,13 @@ covers the `showThinking`/legacy `thinkingDisplayMode` resolver precedence, and
the i18n catalog tests cover the new `settings.showThinking` copy. The UI,
resolver, and E2E scenarios are validated on the integration candidate; see
E2E-CHAT-turn-process-and-thinking-display for the synchronized scenario text.
+For the 2026-10-22 amendment, issue #1806 was reproduced in the React/Electron
+transcript harness: after settlement, a small activity group and reasoning rows
+were collapsed behind the closed turn process. The amendment keeps groups of up
+to four visible items and Task topology groups open, and leaves Thinking rows
+expanded by default when `showThinking` is on. The transcript E2E now covers
+active-to-settled disclosure behavior, while oversized groups and tool payloads
+remain closed by default. See E2E-CHAT-turn-process-and-thinking-display.
For the 2026-10-21 amendment, `apps/desktop/test/turn-process.test.mjs` covers
mode segmentation, including `flat`, `command-first` and `fully-folded`, and
header phase precedence. `apps/desktop/test/transcript-display-modes-ui.test.mjs`
diff --git a/docs/spec/04-ux/08-component-spec.md b/docs/spec/04-ux/08-component-spec.md
index 8827d9a6e8..23587d1804 100644
--- a/docs/spec/04-ux/08-component-spec.md
+++ b/docs/spec/04-ux/08-component-spec.md
@@ -897,13 +897,12 @@ thinking never creates an empty wrapper. All three modes render exactly one
top-level process disclosure and change neither what a tool received nor what is
stored.
-The ordinary group owning the active execution segment starts open while a turn is
-active, then closes on completion only if untouched; other completed groups start
-closed. An untouched active group remains open when any failed or denied tool has
-been recorded, through later successful recovery, and closes on completion if still
-untouched. These group defaults are unified across modes and do not depend on the
-thinking preference. Group headers summarize count, running state and issue count
-without treating a failed child as a failed turn.
+The ordinary group owning the active execution segment stays open while its turn
+is active. Afterward, ordinary groups with at most four visible items remain open;
+larger groups start closed, while Task topology groups remain open. These defaults
+are unified across modes and do not depend on the thinking preference. Explicit
+user choices remain authoritative. Group headers summarize count, running state
+and issue count without treating a failed child as a failed turn.
The turn disclosure header states the turn's outcome and never echoes the item it
is working on, because a shell command or search query can be arbitrarily long. It
@@ -920,11 +919,10 @@ group header and a run row start exactly where the turn header does.
Except for the display mode's Thinking default, no item payload opens itself: a
tool, hosted-search or plan call stays a header row until the user opens its
disclosure, including a Bash row, whose detail stays closed until the user opens
-it. The activity groups keep their automatic open defaults, so
-a live turn still shows its work. With `Show thinking` on, Thinking rows expand by
-default in Flat and Commands first and collapse only on user action; Fully folded
-keeps the released exception where earlier rows stay collapsed and only the last
-active row opens while it is live. An expanded Thinking row shows its full
+it. Active groups stay open; after completion, small groups (up to four visible
+items) and Task topology groups remain open, while larger ordinary groups start
+closed. With `Show thinking` on, Thinking rows expand by default in every display
+mode and collapse only on user action. An expanded Thinking row shows its full
reasoning markdown; a collapsed one shows only the Thinking indicator, with no
summary or excerpt. With `Show thinking` off, no completed reasoning row renders;
only a live whole-run TextShimmer `Thinking` indicator remains while reasoning is
@@ -1616,10 +1614,10 @@ storage but compose into one assistant turn until the next user message.
spacing, including before the first assistant output. Opacity hides those
buttons without removing their space, so hover does not shift content.
- Toggle Thinking disclosure: expand/collapse reasoning independently from the
- final answer. The latest reasoning row opens while it streams and closes when
- the turn settles only if the user has not interacted with it. The expanded
- content's left rule is itself a pointer and keyboard-focusable collapse
- control.
+ final answer. With `Show thinking` on, every visible reasoning row starts
+ expanded and stays so after the turn settles unless the user collapses it. The
+ expanded content's left rule is itself a pointer and keyboard-focusable
+ collapse control.
- Hover code block: copy button appears
- Click a transcript file reference with `:line[:column]`: resolve the file
first, then open it in the host `file:` tab and scroll the requested line into
@@ -2306,9 +2304,10 @@ as its own row beside them, and a progress message or command ends a group. With
`flat`, no group renders and the rows keep transcript order inside the outer
disclosure. A singleton uses its item disclosure directly, and Task topology
keeps its existing container. A Bash-only turn still has its one disclosure.
-While the turn is active, the ordinary group owning the execution segment opens;
-when it settles, an untouched group closes. These group defaults do not depend on
-the thinking preference. No item payload opens itself, except the display mode's
+While the turn is active, its ordinary group opens. After completion, ordinary
+groups with at most four visible items remain open; larger groups start closed,
+and Task topology groups remain open. These group defaults do not depend on the
+thinking preference. No item payload opens itself, except the display mode's
Thinking default: a tool, hosted-search or plan row stays a header row until the
user opens it, whichever item of the group it is, including a Bash row whose
detail stays closed until opened.
@@ -2340,14 +2339,14 @@ seconds when non-zero) from one hour onward. Zero-value units are omitted, so
- The leading Lucide icon reflects the action type: file, folder, search,
edit, terminal, web, or generic tool.
- A multi-item group header owns elapsed time plus item and issue counts and stays
- in the transcript after completion. The active group starts open and closes on
- completion only if untouched; completed groups otherwise start closed. These
- defaults do not depend on the thinking preference. A singleton has no group
- header.
+ in the transcript after completion. Active groups stay open; after completion,
+ groups with at most four visible items and Task topology groups remain open,
+ while larger ordinary groups start closed. These defaults do not depend on the
+ thinking preference. A singleton has no group header.
- Tool/search payloads stay collapsed until the user opens them; no tool/search
- row auto-opens, so a final thinking item never selects an earlier tool. Live
- thinking follows its own indicator/disclosure policy and never opens sibling
- payloads.
+ row auto-opens, so a final thinking item never selects an earlier tool. With
+ `Show thinking` on, reasoning rows open by default in every display mode and
+ never open sibling payloads.
- `Bash` and run rows are revealed by the turn's process disclosure. In
`fully-folded` they sit inside their group; in `command-first` they sit at its
top level beside the groups with adjacent rows separate; in `flat` no groups
@@ -2426,7 +2425,7 @@ twice.
| State | Header treatment | Expanded content |
|---|---|---|
| Running | Progressive action with readable text and a pulsing marker; a `run` row also shows its spinner and pulses the status dot beside `Working…` | The active multi-item group opens; no tool/search payload opens itself, except the display mode's Thinking default; live thinking follows its own indicator/disclosure policy |
-| Success | Past-tense action + result chips; no green success badge, except a `run` row's dot and `Done` | Result blocks, then arguments if not already shown; an untouched active group closes on completion, while manual group and item choices are retained |
+| Success | Past-tense action + result chips; no green success badge, except a `run` row's dot and `Done` | Result blocks, then arguments if not already shown; small groups and Task topology groups stay open, large untouched ordinary groups close, and manual group and item choices are retained |
| Error | Past-tense action + compact danger status; details remain collapsed by default and open only on user request. A `run` row is in this state whenever its command exited nonzero, whatever the call reported (D227) | Error note first, then arguments |
| Denied | Muted `Denied` status; payload remains closed until requested | Permission result when available |
@@ -2447,9 +2446,10 @@ twice.
disclosure, and a reference that matches nothing reports itself without
opening a panel. A tool surface picks no destination of its own.
- Click the processing header: expand/collapse only that ordered activity list.
- The active group opens and closes on settlement only if untouched; completed
- groups otherwise start closed. Opening a group does not expand every item, and
- sibling groups remain independent.
+ Active groups stay open; after completion, ordinary groups with at most four
+ visible items and Task topology groups remain open, while larger ordinary
+ groups start closed. Opening a group does not expand every item, and sibling
+ groups remain independent.
- Click or keyboard-activate the left rule beside expanded thinking, tool details,
delegated work, or processing steps: collapse that owning disclosure without
changing adjacent expansion state. Item interaction also claims its containing
diff --git a/docs/spec/04-ux/09-interaction-patterns.md b/docs/spec/04-ux/09-interaction-patterns.md
index 78bca69413..898caf191b 100644
--- a/docs/spec/04-ux/09-interaction-patterns.md
+++ b/docs/spec/04-ux/09-interaction-patterns.md
@@ -932,12 +932,12 @@ may be retained while exactly one workspace supplies the visible shell context.
hidden thinking does not create a redundant group, and existing Task topology
remains separate. No mode adds a second top-level disclosure or leaves a run
row outside the process.
-- The active ordinary group starts open and closes when it completes only if
- untouched; completed groups otherwise start closed, and an untouched active group
- with any recorded failed/denied tool remains open through recovery. These group
- defaults do not depend on the thinking preference. Closing the turn's disclosure hides
- every group and run row under it without erasing their choices; reopening
- restores the groups the user had opened.
+- The active ordinary group stays open while the turn runs. After completion,
+ ordinary groups with at most four visible items and Task topology groups remain
+ open; larger ordinary groups start closed. These defaults do not depend on the
+ thinking preference. Closing the turn's disclosure hides every group and run
+ row under it without erasing their choices; reopening restores their defaults
+ and any explicit user choices.
- The turn header reports `Failed`, `Stopped`, `Running`, or `Finished` in that
precedence, names compaction and recovery while those stages are live, reads
`Thinking` while the live step is reasoning, omits the duration when the
@@ -946,13 +946,11 @@ may be retained while exactly one workspace supplies the visible shell context.
type size and colour rather than indentation.
- No item payload opens itself, except the display mode's Thinking default: a
tool, hosted-search or plan call stays a header row until the user opens it,
- including the literal final item of the last activity group. Group defaults are
- unchanged, so a final thinking item never causes a backward scan. With
- `Show thinking` on, Thinking rows default expanded in Flat and Commands first and
- collapse only on user action; Fully folded keeps the released live-only
- auto-open exception. A collapsed row shows only the Thinking indicator, with no
- excerpt. With `Show thinking` off, no completed reasoning row renders; only a
- live whole-run TextShimmer `Thinking` indicator remains while reasoning streams.
+ including the literal final item of the last activity group. With `Show thinking`
+ on, Thinking rows default expanded in every display mode and collapse only on
+ user action. A collapsed row shows only the Thinking indicator, with no excerpt.
+ With `Show thinking` off, no completed reasoning row renders; only a live
+ whole-run TextShimmer `Thinking` indicator remains while reasoning streams.
Stored reasoning is retained and reappears when the preference is turned back on.
- Activating a group or item header toggles only that level. Closing a parent
preserves child state, reopening restores it, and sibling groups remain
diff --git a/docs/spec/06-delivery/04-e2e-test-plan.md b/docs/spec/06-delivery/04-e2e-test-plan.md
index ced0b4975c..01efc338fc 100644
--- a/docs/spec/06-delivery/04-e2e-test-plan.md
+++ b/docs/spec/06-delivery/04-e2e-test-plan.md
@@ -3381,9 +3381,11 @@ identify the platform validation still needed.
- **Expected**: A turn renders exactly one process disclosure containing every
pre-answer row, the `Bash`/run rows included; the trailing answer, assistant
errors and stopped trailing text stay outside it, as do pending actions. The
- active group opens, then closes on completion only if untouched; completed
- groups otherwise start closed. Closing the turn's disclosure closes the groups
- and run rows under it, and reopening restores the user's group choices. In
+ active group stays open while the turn runs. After completion, ordinary groups
+ with at most four visible items and Task topology groups remain open; larger
+ ordinary groups start closed. Closing the turn's disclosure hides groups and
+ run rows under it, and reopening restores their defaults and explicit user
+ choices. In
Fully folded (the default), run rows stay inside their groups and only ordinary
assistant progress text splits a group. In Commands first, run rows render as
their own rows beside the groups, adjacent calls stay separate, a row's detail
@@ -17224,7 +17226,11 @@ plugin-form fixtures in an isolated temporary directory at runtime.
settings; legacy message-level transcript search targets.
- **Steps:** Confirm a live active group starts open, let that same turn finish
without interacting, and confirm the process closes so only the final answer
- (and any error or pending-action surface) remains. On a second turn, explicitly
+ (and any error or pending-action surface) remains. Reopen it and confirm a
+ group with at most four visible items and any Task topology group stay open,
+ while a larger ordinary group is closed. Confirm tool and search payloads stay
+ closed, and Fully folded keeps each visible reasoning row open when
+ `Show thinking` is on. On a second turn, explicitly
open a completed group and confirm the choice survives subsequent updates; then
close the turn's disclosure and confirm the group closes with it, and reopen to
confirm the group choice is restored. In Fully folded, confirm run rows stay
@@ -17262,12 +17268,12 @@ plugin-form fixtures in an isolated temporary directory at runtime.
stay inside their groups and only ordinary assistant progress text splits a
group, so the middle progress paragraph ends the preceding group and the
following activity starts a new one. A group appears only with at least two
- visible items; a singleton has no group. Thinking rows default expanded in
- Flat and Commands first, while Fully folded keeps the released exception:
- earlier rows stay collapsed and only the last active row opens while it is
- live, then completed rows collapse.
+ visible items; a singleton has no group. Active groups stay open while the turn
+ runs; after completion, groups with at most four visible items and Task topology
+ groups remain open, while larger ordinary groups start closed. Thinking rows
+ default expanded in every mode when `Show thinking` is on.
Explicit user choices persist and are restored when the enclosing disclosure is
- reopened; these group defaults do not depend on `Show thinking`. The header
+ reopened; group defaults do not depend on `Show thinking`. The header
reports running, finished, stopped, or failed with failure and stop outranking
a normal finish, reads `Thinking` while the live step is reasoning, names
compaction and recovery while those stages are live, omits a duration the
diff --git a/docs/spec/08-meta/decisions-log.md b/docs/spec/08-meta/decisions-log.md
index 7259a0e986..da0a758657 100644
--- a/docs/spec/08-meta/decisions-log.md
+++ b/docs/spec/08-meta/decisions-log.md
@@ -7901,3 +7901,20 @@ must keep splitting are covered by `markdown-blocks.test.mjs`.
`apps/desktop/test/composer-deep-file-search-user-path.test.mjs`. See
`03-runtime/01-ipc-protocol.md` §13c, `04-ux/08-component-spec.md` §11.8,
and E2E-COMPOSER-deep-file-mentions.
+
+## 2026-10-22 — Keep small activity groups and reasoning visible after settlement (D670)
+
+- D670 amends D661 / D668 and ADR `turn-process-and-thinking-display`: an
+ ordinary activity group stays open while active; after completion, groups with
+ at most four visible items remain open, larger ordinary groups start closed,
+ and Task topology groups remain open. The whole-turn process still closes on
+ completion by default.
+- With `showThinking` on, all visible Thinking rows default expanded in Flat,
+ Commands first, and Fully folded. Tool, search, and run-row payloads remain
+ collapsed until the user opens them. Explicit disclosure choices remain
+ authoritative; there is no protocol or persistence change.
+- Issue #1806 reproduced the group and reasoning collapse at turn settlement.
+ `pnpm test:e2e:transcript` covers active-to-completed groups, reasoning rows,
+ and closed payloads. See `04-ux/08-component-spec.md`,
+ `04-ux/09-interaction-patterns.md`, and
+ E2E-CHAT-turn-process-and-thinking-display.
diff --git a/scripts/e2e/turn-process.tsx b/scripts/e2e/turn-process.tsx
index 7ee20cade8..6e645a90df 100644
--- a/scripts/e2e/turn-process.tsx
+++ b/scripts/e2e/turn-process.tsx
@@ -188,7 +188,7 @@ export async function turnProcessProbe() {
try {
// One disclosure per turn: the Bash rows are rows inside the turn's process,
// not siblings of it, so a long turn collapses in one gesture.
- render(mixed);
+ render(mixed, true, null, "settling-activity-group");
const bash1Row = row("bash1");
const bash2Row = row("bash2");
check(Boolean(bash1Row) && Boolean(bash2Row), "both adjacent Bash rows render");
@@ -216,7 +216,24 @@ export async function turnProcessProbe() {
i18n.t("chat.processTools", { count: 5 }),
"the process header counts every tool once",
);
- check(allCollapsed(), "the completed process starts fully collapsed");
+ const activeGroupHeader = row("read")?.closest(
+ ".process-activity-group.grouped",
+ )?.querySelector(".tool-activity-header");
+ check(
+ activeGroupHeader?.getAttribute("aria-expanded") === "true",
+ "the active small activity group starts open",
+ );
+ render(mixed, false, null, "settling-activity-group");
+ const completedGroupHeader = row("read")?.closest(
+ ".process-activity-group.grouped",
+ )?.querySelector(".tool-activity-header");
+ check(
+ processHeaders()[0]?.getAttribute("aria-expanded") === "false" &&
+ [...container.querySelectorAll(".tool-row:not(.thinking) .tool-row-header")].every(
+ (header) => header.getAttribute("aria-expanded") === "false",
+ ),
+ "the completed process and tool payload rows start closed",
+ );
check(
!visible(bash1Row) && !visible(bash2Row),
"Bash rows are revealed by the turn's process, not left outside it",
@@ -232,6 +249,10 @@ export async function turnProcessProbe() {
visible(bash1Row) && visible(bash2Row),
"opening the process reveals the Bash rows",
);
+ check(
+ visible(row("read")) && completedGroupHeader?.getAttribute("aria-expanded") === "true",
+ "opening the process reveals the already-open activity group with its tool rows",
+ );
// Real geometry and hit testing: the turn title, a nested group title and a
// Bash row share one left edge, and the collapse rail owns its gutter.
@@ -285,7 +306,9 @@ export async function turnProcessProbe() {
topRail !== null && railHit(topRail) === topRail,
"the turn collapse rail owns its gutter hit target",
);
- click(nestedHeader);
+ if (nestedHeader?.getAttribute("aria-expanded") !== "true") {
+ click(nestedHeader);
+ }
const nestedBody = nestedHeader?.parentElement?.querySelector(
":scope > .process-activity-body",
) ?? null;
@@ -609,6 +632,77 @@ export async function turnProcessProbe() {
container.querySelector(".process-activity-group.grouped.open") !== null,
"the merged group keeps its live disclosure default",
);
+
+ const earlierThinking = message("earlier-thinking", "assistant", "", {
+ thinking: "Earlier reasoning remains available.",
+ status: "complete",
+ });
+ const liveThinking = message("live-thinking", "assistant", "", {
+ thinking: "Latest reasoning remains available.",
+ status: "streaming",
+ });
+ const completedThinking = { ...liveThinking, status: "complete" as const };
+ const thinkingAnswer = message("thinking-answer", "assistant", "Done.", {
+ status: "complete",
+ });
+ render(
+ [earlierThinking, read, liveThinking, thinkingAnswer],
+ true,
+ null,
+ "fully-folded-thinking-settlement",
+ );
+ const liveThinkingHeaders = [
+ ...container.querySelectorAll(".tool-row.thinking .tool-row-header"),
+ ];
+ check(
+ liveThinkingHeaders.length === 2 &&
+ liveThinkingHeaders.every((header) => header.getAttribute("aria-expanded") === "true"),
+ "fully folded expands each visible thinking row by default",
+ );
+ render(
+ [earlierThinking, read, completedThinking, thinkingAnswer],
+ false,
+ null,
+ "fully-folded-thinking-settlement",
+ );
+ check(
+ processHeaders()[0]?.getAttribute("aria-expanded") === "false",
+ "the completed process still starts closed",
+ );
+ click(processHeaders()[0] ?? null);
+ const settledThinkingHeaders = [
+ ...container.querySelectorAll(".tool-row.thinking .tool-row-header"),
+ ];
+ const settledThinkingGroupHeader = row("read")?.closest(
+ ".process-activity-group.grouped",
+ )?.querySelector(".tool-activity-header");
+ check(
+ settledThinkingGroupHeader?.getAttribute("aria-expanded") === "true" &&
+ settledThinkingHeaders.length === 2 &&
+ settledThinkingHeaders.every((header) => header.getAttribute("aria-expanded") === "true") &&
+ container.textContent?.includes("Earlier reasoning remains available.") === true &&
+ container.textContent?.includes("Latest reasoning remains available.") === true &&
+ row("read")?.querySelector(".tool-row-header")?.getAttribute("aria-expanded") === "false",
+ "reopening the process reveals the open group and reasoning while tool payloads stay collapsed",
+ );
+
+ const largeGroup = Array.from({ length: 5 }, (_, index) =>
+ tool(`large-group-${index}`, "Read", { toolResult: `result ${index}` }),
+ );
+ render(
+ [...largeGroup, thinkingAnswer],
+ false,
+ null,
+ "large-completed-activity-group",
+ );
+ const largeGroupHeader = row("large-group-0")?.closest(
+ ".process-activity-group.grouped",
+ )?.querySelector(".tool-activity-header");
+ click(processHeaders()[0] ?? null);
+ check(
+ largeGroupHeader?.getAttribute("aria-expanded") === "false",
+ "large activity groups remain collapsed by default",
+ );
setSettings();
// The header reports the turn's outcome, never the item it is working on.
From 551b0e94c3677b805c514e9b978620869335a9be Mon Sep 17 00:00:00 2001
From: xieqiying
Date: Thu, 22 Oct 2026 03:33:34 +0800
Subject: [PATCH 28/44] test(transcript): align search test with group defaults
---
.../test/transcript-search-rendering.test.mjs | 21 +++++++++++++++----
1 file changed, 17 insertions(+), 4 deletions(-)
diff --git a/apps/desktop/test/transcript-search-rendering.test.mjs b/apps/desktop/test/transcript-search-rendering.test.mjs
index 14272aae02..21f0864b2e 100644
--- a/apps/desktop/test/transcript-search-rendering.test.mjs
+++ b/apps/desktop/test/transcript-search-rendering.test.mjs
@@ -187,7 +187,7 @@ test("rendered Markdown and file chips map source-only hits to their visible own
});
assert.match(panel, /data-message-id="child"/);
const groupProps = { items: [{ kind: "tool", message: parent }], isActive: false };
- const group = (target) =>
+ const group = (target, items = groupProps.items) =>
renderToStaticMarkup(
createElement(
I18nextProvider,
@@ -195,13 +195,26 @@ test("rendered Markdown and file chips map source-only hits to their visible own
createElement(
TranscriptSearchContext.Provider,
{ value: target },
- createElement(ActivityGroup, groupProps),
+ createElement(ActivityGroup, { ...groupProps, items }),
),
),
);
- assert.match(group(null), /class="tool-activity-header" aria-expanded="false"/);
+
+ // Task topology stays open by default so its delegation outcome remains
+ // visible; search also reveals a collapsed larger ordinary activity group.
+ assert.match(group(null), /class="tool-activity-header" aria-expanded="true"/);
+ const ordinaryItems = Array.from({ length: 5 }, (_, index) => ({
+ kind: "tool",
+ message: {
+ ...parent,
+ id: `ordinary-${index}`,
+ toolName: "Bash",
+ toolCallId: `ordinary-call-${index}`,
+ },
+ }));
+ assert.match(group(null, ordinaryItems), /class="tool-activity-header" aria-expanded="false"/);
assert.match(
- group({ ...focus, messageId: parent.id, query: "" }),
+ group({ ...focus, messageId: ordinaryItems[4].message.id, query: "" }, ordinaryItems),
/class="tool-activity-header" aria-expanded="true"/,
);
From 24c0894bda45d1673f0350e27286e113177cc6c9 Mon Sep 17 00:00:00 2001
From: Xuese <3275996223@qq.com>
Date: Thu, 22 Oct 2026 09:41:23 +0800
Subject: [PATCH 29/44] fix(window): restrict recovery pinning to macOS
Bounds recovery could leave Windows and Linux windows always-on-top
because only the macOS watchdog releases the temporary recovery pin.
Keep pin acquisition on the platform that owns its cleanup.
Regression coverage protects normal focus and hidden or minimized state
while preserving the existing macOS recovery behavior.
---
.../desktop/electron/main/bootstrap/window.ts | 4 +-
.../test/window-topmost-lifecycle.test.mjs | 132 ++++++++++++++++++
docs/spec/04-ux/07-ui-design-system.md | 2 +-
docs/spec/06-delivery/04-e2e-test-plan.md | 9 ++
4 files changed, 144 insertions(+), 3 deletions(-)
create mode 100644 apps/desktop/test/window-topmost-lifecycle.test.mjs
diff --git a/apps/desktop/electron/main/bootstrap/window.ts b/apps/desktop/electron/main/bootstrap/window.ts
index 4d833409ae..df2216395d 100644
--- a/apps/desktop/electron/main/bootstrap/window.ts
+++ b/apps/desktop/electron/main/bootstrap/window.ts
@@ -900,8 +900,8 @@ export async function createWindow({
// so the reservation replan below is treated as an OS-owned adjustment.
windowState.workPanelUserMovePending = false;
applyWorkPanelReservation();
- // Brief pin only when actively recovering from a shelf.
- if (shelved || electronTiny) {
+ // Only macOS runs the watchdog that releases this temporary recovery pin.
+ if (process.platform === "darwin" && (shelved || electronTiny)) {
window.setAlwaysOnTop(true, "floating");
pinUntil = Date.now() + 4000;
} else {
diff --git a/apps/desktop/test/window-topmost-lifecycle.test.mjs b/apps/desktop/test/window-topmost-lifecycle.test.mjs
new file mode 100644
index 0000000000..33f5720bce
--- /dev/null
+++ b/apps/desktop/test/window-topmost-lifecycle.test.mjs
@@ -0,0 +1,132 @@
+import assert from "node:assert/strict";
+import { EventEmitter } from "node:events";
+import { stripTypeScriptTypes } from "node:module";
+import test from "node:test";
+import vm from "node:vm";
+import {
+ clampMinimumSizeToWorkArea,
+ emptyWorkPanelReservationState,
+ windowBoundsEqual,
+} from "../electron/main/work-panel-window.ts";
+import { readMainModule } from "./helpers/source-contracts.mjs";
+
+const source = await readMainModule("bootstrap/window.ts");
+// Execute the production recovery, event wiring and watchdog without booting Electron.
+const recovery = source.slice(
+ source.indexOf(" const CODEX_BOUNDS ="),
+ source.indexOf(' window.on("resize", observeNativeWorkPanelResize)'),
+);
+const watchdogStart = source.indexOf(" const boundsWatchdog:");
+const watchdog = source.slice(watchdogStart, source.indexOf(' window.on("closed",', watchdogStart));
+
+function createRecoveryWindow(platform, { tiny = false, visible = true, minimized = false } = {}) {
+ let now = 10000;
+ let bounds = { x: 80, y: 70, width: tiny ? 300 : 1000, height: 700 };
+ let topmost = false;
+ let nextTimer = 0;
+ const timers = new Map();
+ const calls = [];
+ const window = Object.assign(new EventEmitter(), {
+ isMaximized: () => false,
+ isMinimized: () => minimized,
+ isVisible: () => visible,
+ getBounds: () => ({ ...bounds }),
+ restore: () => { minimized = false; calls.push("restore"); },
+ setMinimumSize: () => calls.push("minimum"),
+ setAlwaysOnTop: (value) => { topmost = value; calls.push(value ? "pin" : "unpin"); },
+ show: () => { visible = true; calls.push("show"); },
+ hide: () => { visible = false; calls.push("hide"); },
+ focus: () => calls.push("focus"),
+ moveTop: () => calls.push("raise"),
+ setBounds: (value) => { bounds = { ...value }; calls.push("bounds"); },
+ setSize: (width, height) => { bounds = { ...bounds, width, height }; },
+ setPosition: (x, y) => { bounds = { ...bounds, x, y }; },
+ });
+ const schedule = (callback, delay, repeat = false) => {
+ const id = ++nextTimer;
+ timers.set(id, { callback, at: now + delay, delay, repeat });
+ return id;
+ };
+ vm.runInNewContext(stripTypeScriptTypes(`${recovery}\n${watchdog}`), {
+ window,
+ windowState: {},
+ windowMinWidth: 800,
+ windowMinHeight: 560,
+ windowBoundsSettleMs: 300,
+ isLiveWindow: () => true,
+ screen: { getDisplayMatching: () => ({ workArea: { x: 0, y: 0, width: 1920, height: 1080 } }) },
+ clampMinimumSizeToWorkArea,
+ emptyWorkPanelReservationState,
+ windowBoundsEqual,
+ applyWorkPanelReservation: () => {},
+ existsSync: () => false,
+ process: { platform },
+ Date: { now: () => now },
+ console: { log: () => {} },
+ setTimeout: (callback, delay) => schedule(callback, delay),
+ clearTimeout: (id) => timers.delete(id),
+ setInterval: (callback, delay) => schedule(callback, delay, true),
+ clearInterval: (id) => timers.delete(id),
+ });
+ return {
+ window,
+ calls,
+ get topmost() { return topmost; },
+ get timerCount() { return timers.size; },
+ advance(ms) {
+ const end = now + ms;
+ for (;;) {
+ const next = [...timers].filter(([, timer]) => timer.at <= end)
+ .sort((a, b) => a[1].at - b[1].at)[0];
+ if (!next) break;
+ const [id, timer] = next;
+ now = timer.at;
+ if (timer.repeat) timer.at += timer.delay;
+ else timers.delete(id);
+ timer.callback();
+ }
+ now = end;
+ },
+ };
+}
+
+for (const platform of ["win32", "linux", "darwin"]) {
+ for (const event of ["show", "focus", "restore"]) {
+ test(`${platform}: ${event} recovers tiny geometry with platform-owned pin cleanup`, () => {
+ const app = createRecoveryWindow(platform, { tiny: true });
+ app.window.emit(event);
+ assert.deepEqual(app.window.getBounds(), { x: 40, y: 30, width: 1200, height: 800 });
+ if (platform === "darwin") {
+ assert.equal(app.topmost, true);
+ app.advance(3999);
+ assert.equal(app.topmost, true, "keep the recovery pin until its deadline");
+ app.advance(501);
+ assert.equal(app.topmost, false, "the existing watchdog must release the expired pin");
+ } else {
+ app.advance(10000);
+ }
+ app.window.emit("focus");
+ assert.equal(app.topmost, false, "normal focus must not leave the window pinned");
+ assert.equal(app.calls.includes("pin"), platform === "darwin");
+ if (platform !== "darwin") assert.equal(app.timerCount, 0, "no layer watchdog off macOS");
+ });
+ }
+
+ test(`${platform}: normal focus does not raise or resize the window`, () => {
+ const app = createRecoveryWindow(platform);
+ app.window.emit("focus");
+ assert.deepEqual(app.calls, []);
+ assert.deepEqual(app.window.getBounds(), { x: 80, y: 70, width: 1000, height: 700 });
+ });
+
+ for (const state of [{ visible: false }, { minimized: true }]) {
+ test(`${platform}: hidden/minimized tiny windows preserve user state ${JSON.stringify(state)}`, () => {
+ const app = createRecoveryWindow(platform, { tiny: true, ...state });
+ for (const event of ["show", "focus", "restore"]) app.window.emit(event);
+ app.advance(10000);
+ assert.deepEqual(app.calls, []);
+ assert.equal(app.topmost, false);
+ assert.deepEqual(app.window.getBounds(), { x: 80, y: 70, width: 300, height: 700 });
+ });
+ }
+}
diff --git a/docs/spec/04-ux/07-ui-design-system.md b/docs/spec/04-ux/07-ui-design-system.md
index 0048d643f2..4d9ffdd346 100644
--- a/docs/spec/04-ux/07-ui-design-system.md
+++ b/docs/spec/04-ux/07-ui-design-system.md
@@ -1459,7 +1459,7 @@ adjacent form inputs; dense surfaces may override that metric locally.
- Floating composer plate: Codex elevated-primary (`#212121f5` / `color-mix(gray-800 96%, transparent)`) with standard elevation-prominent (`0 0 0 .5px` stroke + `0 3px 7.5px #0000000a` + `0 0 20px #0000000d`); no heavier night-only lift
- Light workspace chips capsule: elevated gray `#f4f4f4` (not pure white-on-white)
- Combined workspace chips: elevated translucent plate over main, not flat main gray
-- Stage Manager (macOS only): host re-asserts min bounds while collapsed (permanent watchdog). The watchdog does not run on Windows/Linux, so no platform re-layers its own window unprompted (D447)
+- Stage Manager (macOS only): host re-asserts min bounds while collapsed (permanent watchdog). The watchdog and temporary recovery pin are macOS-only; Windows/Linux bounds recovery stays at the normal window layer so switching to another app never leaves PI-Desktop above it (D447).
## Destination pages
diff --git a/docs/spec/06-delivery/04-e2e-test-plan.md b/docs/spec/06-delivery/04-e2e-test-plan.md
index ced0b4975c..af6e8bcc65 100644
--- a/docs/spec/06-delivery/04-e2e-test-plan.md
+++ b/docs/spec/06-delivery/04-e2e-test-plan.md
@@ -10541,6 +10541,15 @@ This test plan spec is accepted when:
- On macOS with Stage Manager, shrink or unfocus the PI window until width < 800 or height < 560.
- Expect the shell to re-assert a Codex-like footprint (~1200×800, min 800×560 capped to the display work area) and keep restoring while still collapsed (not only during the first 20s after launch).
- The recovery watchdog is macOS-only (D447). On Windows/Linux it must not run at all: the app must never re-layer or re-raise its own window unprompted. Focus another window, then confirm PI-Desktop stays behind it instead of jumping back to the top of the stack, and that a stacking check (`xprop -root _NET_CLIENT_LIST_STACKING`) never shows it returning to the top periodically.
+- Windows regression: trigger tiny-bounds recovery through show, focus, or
+ restore, then Alt+Tab to another app. PI-Desktop must stay behind that app
+ immediately and after four seconds. Ordinary focus must not resize or raise it;
+ hidden/minimized windows keep their state. Recovery must never enable
+ always-on-top off macOS.
+- Automated lifecycle coverage: `window-topmost-lifecycle.test.mjs` executes the
+ production recovery handlers and watchdog with controlled time, including the
+ unchanged macOS temporary pin and release. Native Alt+Tab validation remains
+ a separate platform check.
### US-UI-20 Dark floating composer box
- Switch to dark theme on chat home.
From 8956de008d1cf6506c5ac5c76cf6ce8e933d53cc Mon Sep 17 00:00:00 2001
From: v_wyxgwang
Date: Thu, 22 Oct 2026 10:39:16 +0800
Subject: [PATCH 30/44] fix(transcript): keep running marker inline
The shimmer styles were inserted after the first half of the running-label selector, so the active label inherited inline-grid and the pulse marker became an auto-placed grid item. Separate the marker and shimmer selectors again so the marker stays in the label's inline flow and does not disturb truncation.
---
apps/desktop/src/styles/messages.css | 54 ++++++++++++++--------------
1 file changed, 27 insertions(+), 27 deletions(-)
diff --git a/apps/desktop/src/styles/messages.css b/apps/desktop/src/styles/messages.css
index 1a504010a7..e4335d435f 100644
--- a/apps/desktop/src/styles/messages.css
+++ b/apps/desktop/src/styles/messages.css
@@ -676,6 +676,33 @@
/* Running labels stay readable; the small marker carries the live feedback
so long tool names never flash between two text colours. */
.tool-activity-label.running,
+.tool-row-name.running {
+ color: var(--ds-text-secondary);
+}
+
+.tool-activity-label.running::after,
+.tool-row-name.running::after {
+ display: inline-block;
+ width: 4px;
+ height: 4px;
+ margin-inline-start: 6px;
+ vertical-align: middle;
+ border-radius: var(--radius-round);
+ background: var(--ds-text-secondary);
+ content: "";
+ animation: activity-marker-pulse 1s var(--motion-ease-standard) infinite;
+}
+
+@keyframes activity-marker-pulse {
+ 0%,
+ 100% {
+ opacity: 0.35;
+ }
+ 50% {
+ opacity: 1;
+ }
+}
+
.text-shimmer {
display: inline-grid;
min-width: 0;
@@ -733,33 +760,6 @@
}
}
-.tool-row-name.running {
- color: var(--ds-text-secondary);
-}
-
-.tool-activity-label.running::after,
-.tool-row-name.running::after {
- display: inline-block;
- width: 4px;
- height: 4px;
- margin-inline-start: 6px;
- vertical-align: middle;
- border-radius: var(--radius-round);
- background: var(--ds-text-secondary);
- content: "";
- animation: activity-marker-pulse 1s var(--motion-ease-standard) infinite;
-}
-
-@keyframes activity-marker-pulse {
- 0%,
- 100% {
- opacity: 0.35;
- }
- 50% {
- opacity: 1;
- }
-}
-
@keyframes planning-state-in {
from {
opacity: 0;
From 09534c5c6db46c87f1a61ec1143cbbfc12c0dd64 Mon Sep 17 00:00:00 2001
From: v_wyxgwang
Date: Thu, 22 Oct 2026 11:07:22 +0800
Subject: [PATCH 31/44] fix(transcript): center running marker
The live dot was generated content inside the running label. A selector collision with the shimmer rule turned that label into a grid and pushed the dot onto a second row; even with the selectors separated, the inline pseudo-element sat below the row centre and could be clipped by the label's ellipsis box.
Render the marker as a real flex sibling so the header's existing align-items centres it, and keep the label's text truncation untouched.
---
.../src/features/chat/transcript/ActivityGroup.tsx | 1 +
.../src/features/chat/transcript/HostedSearchRow.tsx | 1 +
.../chat/transcript/ProcessActivityGroup.tsx | 1 +
.../desktop/src/features/chat/transcript/ToolRow.tsx | 1 +
.../src/features/chat/transcript/TurnProcess.tsx | 1 +
apps/desktop/src/styles/messages.css | 12 ++++++------
apps/desktop/src/styles/overlays.css | 3 +--
apps/desktop/test/active-turn-surface.test.mjs | 9 ++++++++-
8 files changed, 20 insertions(+), 9 deletions(-)
diff --git a/apps/desktop/src/features/chat/transcript/ActivityGroup.tsx b/apps/desktop/src/features/chat/transcript/ActivityGroup.tsx
index 48c4a65836..c499ed6cf4 100644
--- a/apps/desktop/src/features/chat/transcript/ActivityGroup.tsx
+++ b/apps/desktop/src/features/chat/transcript/ActivityGroup.tsx
@@ -362,6 +362,7 @@ export const ActivityGroup = memo(function ActivityGroup({
{label}
+ {live ? : null}
{hasSubagentTopology ? (
{t("chat.subagentCount", { count: subagentSummary.total })}
diff --git a/apps/desktop/src/features/chat/transcript/HostedSearchRow.tsx b/apps/desktop/src/features/chat/transcript/HostedSearchRow.tsx
index f832af2537..7352ba7018 100644
--- a/apps/desktop/src/features/chat/transcript/HostedSearchRow.tsx
+++ b/apps/desktop/src/features/chat/transcript/HostedSearchRow.tsx
@@ -104,6 +104,7 @@ export const HostedSearchRow = memo(function HostedSearchRow({
>
{name}
+ {searching ? : null}
{summary ? {summary} : null}
{expandable ? (
diff --git a/apps/desktop/src/features/chat/transcript/ProcessActivityGroup.tsx b/apps/desktop/src/features/chat/transcript/ProcessActivityGroup.tsx
index 5ca62c78aa..aeefd72bde 100644
--- a/apps/desktop/src/features/chat/transcript/ProcessActivityGroup.tsx
+++ b/apps/desktop/src/features/chat/transcript/ProcessActivityGroup.tsx
@@ -43,6 +43,7 @@ export function ProcessActivityGroup({
{t(summary.label, { count: summary.count })}
+ {active ? : null}
{summary.thinking > 0 && summary.tools > 0 ? (
{t("chat.activityIncludesThinking")}
) : null}
diff --git a/apps/desktop/src/features/chat/transcript/ToolRow.tsx b/apps/desktop/src/features/chat/transcript/ToolRow.tsx
index 6f8f09eab8..c764f9e5cc 100644
--- a/apps/desktop/src/features/chat/transcript/ToolRow.tsx
+++ b/apps/desktop/src/features/chat/transcript/ToolRow.tsx
@@ -488,6 +488,7 @@ function HostToolRow({
)
: actionLabel}
+ {status === "running" ? : null}
{lifecycle && roster.length > 0 ? (
{t("chat.subagentCount", { count: roster.length })}
diff --git a/apps/desktop/src/features/chat/transcript/TurnProcess.tsx b/apps/desktop/src/features/chat/transcript/TurnProcess.tsx
index dfb83ab757..26b88294dc 100644
--- a/apps/desktop/src/features/chat/transcript/TurnProcess.tsx
+++ b/apps/desktop/src/features/chat/transcript/TurnProcess.tsx
@@ -157,6 +157,7 @@ export function TurnProcess({
{label}
+ {isActive ? : null}
{summary.issues > 0 && phase.kind !== "failed" ? (
diff --git a/apps/desktop/src/styles/messages.css b/apps/desktop/src/styles/messages.css
index e4335d435f..5777957919 100644
--- a/apps/desktop/src/styles/messages.css
+++ b/apps/desktop/src/styles/messages.css
@@ -680,16 +680,16 @@
color: var(--ds-text-secondary);
}
-.tool-activity-label.running::after,
-.tool-row-name.running::after {
- display: inline-block;
+/* The live marker is a real flex sibling of the label. A generated inline box
+ had to be aligned by hand and drifted off the row centre inside the label's
+ ellipsis box; as a flex item it is centred by the header's own alignment and
+ spaced by its gap. */
+.activity-marker {
+ flex: none;
width: 4px;
height: 4px;
- margin-inline-start: 6px;
- vertical-align: middle;
border-radius: var(--radius-round);
background: var(--ds-text-secondary);
- content: "";
animation: activity-marker-pulse 1s var(--motion-ease-standard) infinite;
}
diff --git a/apps/desktop/src/styles/overlays.css b/apps/desktop/src/styles/overlays.css
index e1d1d5989e..0a959305b8 100644
--- a/apps/desktop/src/styles/overlays.css
+++ b/apps/desktop/src/styles/overlays.css
@@ -716,8 +716,7 @@
animation: none;
}
.working-indicator-mark > span,
- .tool-row-name.running::after,
- .tool-activity-label.running::after {
+ .activity-marker {
animation: none;
opacity: 0.7;
}
diff --git a/apps/desktop/test/active-turn-surface.test.mjs b/apps/desktop/test/active-turn-surface.test.mjs
index 656a8fb17a..b8d292ce95 100644
--- a/apps/desktop/test/active-turn-surface.test.mjs
+++ b/apps/desktop/test/active-turn-surface.test.mjs
@@ -136,9 +136,16 @@ test("active turns show immediate and phase-specific feedback without a progress
assert.match(messagesStyles, /\.working-indicator-mark > span\s*\{[\s\S]*?animation:\s*working-indicator-dot\s+1s/);
assert.doesNotMatch(proseStyles, /\.working-indicator\s*\{|\.shimmer-text\s*\{/);
assert.doesNotMatch(messagesStyles, /\.shimmer-text\s*\{|animation:\s*shimmer\b/);
+ // The live marker is a real flex sibling of the label, so the header's
+ // alignment centres it; the old generated inline box drifted off centre.
+ assert.match(transcript, / /);
assert.match(
messagesStyles,
- /\.tool-activity-label\.running::after,\s*\.tool-row-name\.running::after\s*\{[\s\S]*?animation:\s*activity-marker-pulse\s+1s/,
+ /\.activity-marker \{[\s\S]*?flex:\s*none;[\s\S]*?animation:\s*activity-marker-pulse\s+1s/,
+ );
+ assert.doesNotMatch(
+ messagesStyles,
+ /\.(tool-activity-label|tool-row-name)\.running::after/,
);
assert.doesNotMatch(
en,
From caf8b2de004ddf74cf19a318a6e1bce09a695e60 Mon Sep 17 00:00:00 2001
From: v_wyxgwang
Date: Thu, 22 Oct 2026 11:56:29 +0800
Subject: [PATCH 32/44] chore(models.dev): refresh catalog before beta.5
Refresh the bundled provider catalog so the 0.21.0-beta.5 test build packages the current models.dev snapshot.
---
apps/desktop/resources/models.dev/api.json | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/apps/desktop/resources/models.dev/api.json b/apps/desktop/resources/models.dev/api.json
index 78fb1994df..459d6a2d26 100644
--- a/apps/desktop/resources/models.dev/api.json
+++ b/apps/desktop/resources/models.dev/api.json
@@ -1 +1 @@
-{"deepinfra":{"id":"deepinfra","env":["DEEPINFRA_API_KEY"],"npm":"@ai-sdk/deepinfra","name":"Deep Infra","doc":"https://deepinfra.com/models","models":{"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50},"canonical_model_id":"anthropic/claude-fable-5"},"tencent/Hy3":{"id":"tencent/Hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":192000,"output":128000},"status":"deprecated","cost":{"input":0.13,"output":0.53,"cache_read":0.033},"canonical_model_id":"tencent/hy3"},"tencent/Hy4-preview":{"id":"tencent/Hy4-preview","name":"Hy4 preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":64000},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"},"meta-llama/Llama-3.3-70B-Instruct-Turbo":{"id":"meta-llama/Llama-3.3-70B-Instruct-Turbo","name":"Llama 3.3 70B Turbo","description":"Compact Llama instruction model for fast chat and local deployment","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.1,"output":0.32}},"meta-llama/Llama-4-Scout-17B-16E-Instruct":{"id":"meta-llama/Llama-4-Scout-17B-16E-Instruct","name":"Llama 4 Scout 17B","description":"Open multimodal Llama model for long-context analysis and efficient agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":327680,"output":16384},"cost":{"input":0.1,"output":0.3}},"meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8":{"id":"meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8","name":"Llama 4 Maverick 17B FP8","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":16384},"status":"deprecated","cost":{"input":0.2,"output":0.8}},"XiaomiMiMo/MiMo-V2.6-Pro":{"id":"XiaomiMiMo/MiMo-V2.6-Pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.43,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"XiaomiMiMo/MiMo-V2.5-Pro":{"id":"XiaomiMiMo/MiMo-V2.5-Pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":16384},"status":"deprecated","cost":{"input":1,"output":3,"cache_read":0.2},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"XiaomiMiMo/MiMo-V2.6-Flash":{"id":"XiaomiMiMo/MiMo-V2.6-Flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"XiaomiMiMo/MiMo-V2.5":{"id":"XiaomiMiMo/MiMo-V2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"status":"deprecated","cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.5"},"thinkingmachines/Inkling-Small":{"id":"thinkingmachines/Inkling-Small","name":"Inkling Small","description":"Multimodal MoE reasoning model (276B total, 12B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":1048576},"cost":{"input":0.45,"output":1.2,"cache_read":0.1},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/Inkling":{"id":"thinkingmachines/Inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":1048576},"cost":{"input":0.95,"output":4.05,"cache_read":0.16},"canonical_model_id":"thinkingmachines/inkling"},"google/gemma-3-27b-it":{"id":"google/gemma-3-27b-it","name":"Gemma 3 27B IT","description":"Largest open Gemma 3 instruction model for multilingual text generation and visual understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.08,"output":0.16},"canonical_model_id":"google/gemma-3-27b-it"},"google/gemma-3-12b-it":{"id":"google/gemma-3-12b-it","name":"Gemma 3 12B IT","description":"Open multimodal Gemma instruction model for multilingual text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.05,"output":0.15},"canonical_model_id":"google/gemma-3-12b-it"},"google/gemma-3-4b-it":{"id":"google/gemma-3-4b-it","name":"Gemma 3 4B IT","description":"Open multimodal Gemma instruction model for efficient text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.05,"output":0.1},"canonical_model_id":"google/gemma-3-4b-it"},"google/gemma-4-31B-it":{"id":"google/gemma-4-31B-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.2,"output":0.4},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemma-4-26B-A4B-it":{"id":"google/gemma-4-26B-A4B-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.07,"output":0.34},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemma-4-E4B-it":{"id":"google/gemma-4-E4B-it","name":"Gemma 4 E4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.02,"output":0.1},"canonical_model_id":"google/gemma-4-E4B-it"},"Qwen/Qwen3-VL-235B-A22B-Instruct":{"id":"Qwen/Qwen3-VL-235B-A22B-Instruct","name":"Qwen3 VL 235B A22B Instruct","description":"Qwen vision-language instruct model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.2,"output":0.88,"cache_read":0.11},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"Qwen/Qwen3.8-27B":{"id":"Qwen/Qwen3.8-27B","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.2,"output":2.5,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.8-27b"},"Qwen/Qwen3-Next-80B-A3B-Instruct":{"id":"Qwen/Qwen3-Next-80B-A3B-Instruct","name":"Qwen3-Next 80B-A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.09,"output":1.1},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"Qwen/Qwen3.7-Max":{"id":"Qwen/Qwen3.7-Max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":65536},"cost":{"input":2.5,"output":7.5,"cache_read":0.5,"tiers":[{"input":5,"output":15,"cache_read":1,"tier":{"type":"context","size":32000}},{"input":6.25,"output":18.5,"cache_read":1.25,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3.7-max"},"Qwen/Qwen3-VL-30B-A3B-Instruct":{"id":"Qwen/Qwen3-VL-30B-A3B-Instruct","name":"Qwen3 VL 30B A3B Instruct","description":"Open vision-language MoE model for image and video understanding, documents, and visual agents","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-04","last_updated":"2025-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"alibaba/qwen3-vl-30b-a3b-instruct"},"Qwen/Qwen3.8-Max":{"id":"Qwen/Qwen3.8-Max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":131072},"cost":{"input":1.65,"output":4.951,"cache_read":0.206},"canonical_model_id":"alibaba/qwen3.8-max"},"Qwen/Qwen3.5-27B":{"id":"Qwen/Qwen3.5-27B","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.26,"output":2.6},"canonical_model_id":"alibaba/qwen3.5-27b"},"Qwen/Qwen3.6-35B-A3B":{"id":"Qwen/Qwen3.6-35B-A3B","name":"Qwen3.6 35B A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":81920},"cost":{"input":0.1,"output":0.95,"cache_read":0.1}},"Qwen/Qwen3-Coder-480B-A35B-Instruct-Turbo":{"id":"Qwen/Qwen3-Coder-480B-A35B-Instruct-Turbo","name":"Qwen3 Coder 480B A35B Instruct Turbo","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":66536},"cost":{"input":0.3,"output":1,"cache_read":0.1}},"Qwen/Qwen3-Max":{"id":"Qwen/Qwen3-Max","name":"Qwen3 Max","description":"Flagship Qwen3 model for coding agents, complex reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":65536},"status":"deprecated","cost":{"input":1.2,"output":6,"cache_read":0.24,"tiers":[{"input":2.4,"output":12,"cache_read":0.48,"tier":{"type":"context","size":32000}},{"input":3,"output":15,"cache_read":0.6,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3-max"},"Qwen/Qwen3-235B-A22B-Instruct-2507":{"id":"Qwen/Qwen3-235B-A22B-Instruct-2507","name":"Qwen3 235B-A22B Instruct 2507","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.09,"output":0.55},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"Qwen/Qwen3.8-Flash":{"id":"Qwen/Qwen3.8-Flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.113,"output":0.382,"cache_read":0.0141},"canonical_model_id":"alibaba/qwen3.8-flash"},"Qwen/Qwen3-32B":{"id":"Qwen/Qwen3-32B","name":"Qwen3 32B","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":16384},"cost":{"input":0.08,"output":0.28},"canonical_model_id":"alibaba/qwen3-32b"},"Qwen/Qwen3.5-35B-A3B":{"id":"Qwen/Qwen3.5-35B-A3B","name":"Qwen 3.5 35B A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-01","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":81920},"cost":{"input":0.14,"output":1,"cache_read":0.05}},"Qwen/Qwen3.5-122B-A10B":{"id":"Qwen/Qwen3.5-122B-A10B","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","cost":{"input":0.29,"output":2.4},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"Qwen/Qwen3.5-9B":{"id":"Qwen/Qwen3.5-9B","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.1,"output":0.15},"canonical_model_id":"alibaba/qwen3.5-9b"},"Qwen/Qwen3.5-397B-A17B":{"id":"Qwen/Qwen3.5-397B-A17B","name":"Qwen 3.5 397B A17B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-01","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":81920},"cost":{"input":0.45,"output":3,"cache_read":0.22}},"Qwen/Qwen3.8-2.4T-A95B":{"id":"Qwen/Qwen3.8-2.4T-A95B","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"status":"deprecated","cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"Qwen/Qwen3-30B-A3B":{"id":"Qwen/Qwen3-30B-A3B","name":"Qwen3 30B A3B","description":"Sparse MoE Qwen model with 3B active parameters for efficient chat and reasoning","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":16384},"cost":{"input":0.12,"output":0.5},"canonical_model_id":"alibaba/qwen3-30b-a3b"},"Qwen/Qwen3.6-27B":{"id":"Qwen/Qwen3.6-27B","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.32,"output":3.2},"canonical_model_id":"alibaba/qwen3.6-27b"},"deepseek-ai/DeepSeek-V3.1":{"id":"deepseek-ai/DeepSeek-V3.1","name":"DeepSeek-V3.1","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":8192},"cost":{"input":0.25,"output":0.95,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-v3.1"},"deepseek-ai/DeepSeek-V4-Flash-0731":{"id":"deepseek-ai/DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.06,"output":0.18,"cache_read":0.015},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek-ai/DeepSeek-V4-Pro-0813":{"id":"deepseek-ai/DeepSeek-V4-Pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":1.3,"output":2.6,"cache_read":0.1},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek-ai/DeepSeek-V4.1-Flash":{"id":"deepseek-ai/DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.2,"output":0.6,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek-ai/DeepSeek-V4-Flash":{"id":"deepseek-ai/DeepSeek-V4-Flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":16384},"cost":{"input":0.09,"output":0.18,"cache_read":0.018},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek-ai/DeepSeek-V4-Pro":{"id":"deepseek-ai/DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":16384},"cost":{"input":1.3,"output":2.6,"cache_read":0.1},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek-ai/DeepSeek-V3.2":{"id":"deepseek-ai/DeepSeek-V3.2","name":"DeepSeek-V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":163840,"output":64000},"cost":{"input":0.26,"output":0.38,"cache_read":0.13}},"deepseek-ai/DeepSeek-R1-0528":{"id":"deepseek-ai/DeepSeek-R1-0528","name":"DeepSeek-R1-0528","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":163840,"output":64000},"cost":{"input":0.5,"output":2.15,"cache_read":0.35}},"deepseek-ai/DeepSeek-V3":{"id":"deepseek-ai/DeepSeek-V3","name":"DeepSeek-V3","description":"Open DeepSeek MoE chat model for coding, math, and general reasoning","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-12-26","last_updated":"2024-12-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":8192},"cost":{"input":0.32,"output":0.89},"canonical_model_id":"deepseek/deepseek-v3"},"deepseek-ai/DeepSeek-V3-0324":{"id":"deepseek-ai/DeepSeek-V3-0324","name":"DeepSeek V3 0324","description":"March 2025 checkpoint of DeepSeek-V3 with improved reasoning and coding","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-03-24","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":163840},"status":"deprecated","cost":{"input":0.24,"output":0.9,"cache_read":0.135},"canonical_model_id":"deepseek/deepseek-v3-0324"},"deepseek-ai/DeepSeek-V4-Flash-Vision-Exp":{"id":"deepseek-ai/DeepSeek-V4-Flash-Vision-Exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.44,"output":1.32,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"stepfun-ai/Step-3.7-Flash":{"id":"stepfun-ai/Step-3.7-Flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"status":"deprecated","cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"stepfun-ai/Step-5-Preview":{"id":"stepfun-ai/Step-5-Preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1000000},"cost":{"input":1,"output":2.7,"cache_read":0.05},"canonical_model_id":"stepfun/step-5-preview"},"MiniMaxAI/MiniMax-M3":{"id":"MiniMaxAI/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":512000},"cost":{"input":0.28,"output":1.1,"cache_read":0.056},"canonical_model_id":"minimax/MiniMax-M3"},"MiniMaxAI/MiniMax-M2.5":{"id":"MiniMaxAI/MiniMax-M2.5","name":"MiniMax M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-06","release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":131072},"status":"deprecated","cost":{"input":0.15,"output":1.15,"cache_read":0.03}},"MiniMaxAI/MiniMax-M2.7":{"id":"MiniMaxAI/MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":131072},"status":"deprecated","cost":{"input":0.25,"output":1,"cache_read":0.05},"canonical_model_id":"minimax/MiniMax-M2.7"},"mistralai/Mistral-Small-24B-Instruct-2501":{"id":"mistralai/Mistral-Small-24B-Instruct-2501","name":"Mistral Small 3","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-01-30","last_updated":"2025-01-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"cost":{"input":0.05,"output":0.08},"canonical_model_id":"mistral/mistral-small-24b-instruct-2501"},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.75,"output":3.5,"cache_read":0.15}},"moonshotai/Kimi-K3":{"id":"moonshotai/Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":2.85,"output":14.25,"cache_read":0.285},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/Kimi-K2.7-Code":{"id":"moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.68,"output":3.4,"cache_read":0.136},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"moonshotai/Kimi-K2.5":{"id":"moonshotai/Kimi-K2.5","name":"Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"status":"deprecated","cost":{"input":0.45,"output":2.25,"cache_read":0.07}},"zai-org/GLM-5.1":{"id":"zai-org/GLM-5.1","name":"GLM-5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":16384},"status":"deprecated","cost":{"input":1.05,"output":3.5,"cache_read":0.205}},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":32768},"cost":{"input":0.75,"output":2.4,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-4.7":{"id":"zai-org/GLM-4.7","name":"GLM-4.7","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":16384},"cost":{"input":0.4,"output":1.75,"cache_read":0.08}},"zai-org/GLM-5":{"id":"zai-org/GLM-5","name":"GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-12","release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":16384},"status":"deprecated","cost":{"input":0.6,"output":2.08,"cache_read":0.12}},"zai-org/GLM-5.3-Flash":{"id":"zai-org/GLM-5.3-Flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/GLM-4.6":{"id":"zai-org/GLM-4.6","name":"GLM-4.6","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.5,"output":2,"cache_read":0.1}},"zai-org/GLM-4.7-Flash":{"id":"zai-org/GLM-4.7-Flash","name":"GLM-4.7-Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":16384},"status":"deprecated","cost":{"input":0.06,"output":0.4,"cache_read":0.01}},"zai-org/GLM-5.3":{"id":"zai-org/GLM-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.9,"output":4,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5.3"},"nvidia/Nemotron-3-Nano-30B-A3B":{"id":"nvidia/Nemotron-3-Nano-30B-A3B","name":"Nemotron 3 Nano 30B A3B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.05,"output":0.2,"cache_read":0.025},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"nvidia/Llama-3.3-Nemotron-Super-49B-v1.5":{"id":"nvidia/Llama-3.3-Nemotron-Super-49B-v1.5","name":"Llama 3.3 Nemotron Super 49B v1.5","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-25","last_updated":"2025-07-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"status":"deprecated","cost":{"input":0.4,"output":0.4},"canonical_model_id":"nvidia/llama-3.3-nemotron-super-49b-v1.5"},"nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning":{"id":"nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning","name":"Nemotron 3 Nano Omni 30B A3B Reasoning","description":"Open Nemotron omni model combining reasoning with text, vision, and audio","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","cost":{"input":0.2,"output":0.8},"canonical_model_id":"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning"},"ByteDance/Seed-2.0-code":{"id":"ByteDance/Seed-2.0-code","name":"Seed 2.0 Code","description":"ByteDance Seed coding model for multimodal software engineering and long-running agents","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":131072},"cost":{"input":0.5,"output":3,"cache_read":0.1,"tiers":[{"input":1,"output":6,"cache_read":0.2,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"ByteDance/Seed-2.0-pro":{"id":"ByteDance/Seed-2.0-pro","name":"Seed 2.0 Pro","description":"Flagship ByteDance Seed 2.0 model for complex multimodal reasoning and long-horizon agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.5,"output":3,"cache_read":0.1,"tiers":[{"input":1,"output":6,"cache_read":0.2,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-pro"},"ByteDance/Seed-2.0-mini":{"id":"ByteDance/Seed-2.0-mini","name":"Seed 2.0 Mini","description":"Lightweight ByteDance Seed 2.0 model for low-latency multimodal reasoning and high-volume tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.1,"output":0.4,"cache_read":0.02,"tiers":[{"input":0.2,"output":0.8,"cache_read":0.2,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.03,"output":0.14}},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.037,"output":0.17}}}},"perplexity-agent":{"id":"perplexity-agent","env":["PERPLEXITY_API_KEY"],"npm":"@ai-sdk/openai","api":"https://api.perplexity.ai/v1","name":"Perplexity Agent","doc":"https://docs.perplexity.ai/docs/agent-api/models","models":{"anthropic/claude-haiku-4-5":{"id":"anthropic/claude-haiku-4-5","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1}},"anthropic/claude-opus-4-5":{"id":"anthropic/claude-opus-4-5","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5}},"anthropic/claude-sonnet-4-5":{"id":"anthropic/claude-sonnet-4-5","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3}},"anthropic/claude-opus-4-6":{"id":"anthropic/claude-opus-4-6","name":"Claude Opus 4.6","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5}},"anthropic/claude-sonnet-4-6":{"id":"anthropic/claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-02-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3}},"anthropic/claude-opus-4-7":{"id":"anthropic/claude-opus-4-7","name":"Claude Opus 4.7","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5}},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.13,"output":0.26,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"perplexity/sonar":{"id":"perplexity/sonar","name":"Sonar","description":"Sonar search model for current answers, retrieval, and citation-backed chat","family":"sonar","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.25,"output":2.5,"cache_read":0.0625}},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}}},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-03-20","last_updated":"2025-06-05","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}}},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-03-20","last_updated":"2025-06-05","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03}},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"tiers":[{"input":0.5,"output":3,"cache_read":0.05,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":0.5,"output":3,"cache_read":0.05}}},"xai/grok-4-1-fast-non-reasoning":{"id":"xai/grok-4-1-fast-non-reasoning","name":"Grok 4.1 Fast (Non-Reasoning)","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-07","release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":0.2,"output":0.5,"cache_read":0.05}},"xai/grok-4.6":{"id":"xai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"nvidia/nemotron-3-super-120b-a12b":{"id":"nvidia/nemotron-3-super-120b-a12b","name":"Nemotron 3 Super 120B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2026-02","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32000},"cost":{"input":0.25,"output":2.5},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"moonshot-ai/kimi-k3":{"id":"moonshot-ai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-30","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshot-ai/kimi-k2.7-code":{"id":"moonshot-ai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-07-30","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25}},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025}},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125}},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5}}}},"bailing":{"id":"bailing","env":["BAILING_API_TOKEN"],"npm":"@ai-sdk/openai-compatible","api":"https://api.tbox.cn/api/llm/v1","name":"Bailing","doc":"https://alipaytbox.yuque.com/sxs0ba/ling/intro","models":{"Ring-1T":{"id":"Ring-1T","name":"Ring-1T","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"ring","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-10","last_updated":"2025-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"cost":{"input":0.57,"output":2.29}},"Ling-1T":{"id":"Ling-1T","name":"Ling-1T","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","family":"ling","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-10","last_updated":"2025-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"cost":{"input":0.57,"output":2.29}}}},"poe":{"id":"poe","env":["POE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.poe.com/v1","name":"Poe","doc":"https://creator.poe.com/docs/external-applications/openai-compatible-api","models":{"cerebras/qwen3-32b-cs":{"id":"cerebras/qwen3-32b-cs","name":"qwen3-32b-cs","description":"Legacy model retained for compatibility with older integrations","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-05-15","last_updated":"2025-05-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0},"status":"deprecated"},"cerebras/llama-3.1-8b-cs":{"id":"cerebras/llama-3.1-8b-cs","name":"Llama-3.1-8B-CS","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-05-13","last_updated":"2025-05-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":0},"cost":{"input":0.1,"output":0.1}},"cerebras/llama-3.3-70b-cs":{"id":"cerebras/llama-3.3-70b-cs","name":"llama-3.3-70b-cs","description":"Legacy model retained for compatibility with older integrations","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-05-13","last_updated":"2025-05-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0},"status":"deprecated"},"cerebras/gpt-oss-120b-cs":{"id":"cerebras/gpt-oss-120b-cs","name":"GPT-OSS-120B-CS","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"release_date":"2025-08-06","last_updated":"2025-08-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":0},"cost":{"input":0.35,"output":0.75}},"cerebras/qwen3-235b-2507-cs":{"id":"cerebras/qwen3-235b-2507-cs","name":"qwen3-235b-2507-cs","description":"Legacy model retained for compatibility with older integrations","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-08-06","last_updated":"2025-08-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0},"status":"deprecated"},"empiriolabs/deepseek-v4-pro-el":{"id":"empiriolabs/deepseek-v4-pro-el","name":"DeepSeek-V4-Pro-EL","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"release_date":"2026-04-24","last_updated":"2026-05-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":384000},"cost":{"input":1.67,"output":3.33}},"empiriolabs/deepseek-v4-flash-el":{"id":"empiriolabs/deepseek-v4-flash-el","name":"DeepSeek-V4-Flash-EL","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"release_date":"2026-04-24","last_updated":"2026-05-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":384000},"cost":{"input":0.14,"output":0.28}},"anthropic/claude-haiku-3.5":{"id":"anthropic/claude-haiku-3.5","name":"Claude-Haiku-3.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-10-01","last_updated":"2024-10-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":189096,"output":8192},"cost":{"input":0.68,"output":3.4,"cache_read":0.068,"cache_write":0.85}},"anthropic/claude-opus-4.1":{"id":"anthropic/claude-opus-4.1","name":"Claude-Opus-4.1","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":0,"max":31999}],"tool_call":true,"temperature":false,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":196608,"output":32000},"cost":{"input":13,"output":64,"cache_read":1.3,"cache_write":16}},"anthropic/claude-opus-4.5":{"id":"anthropic/claude-opus-4.5","name":"Claude-Opus-4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":0,"max":63999}],"tool_call":true,"temperature":false,"release_date":"2025-11-21","last_updated":"2025-11-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":196608,"output":64000},"cost":{"input":4.3,"output":21,"cache_read":0.43,"cache_write":5.3}},"anthropic/claude-opus-4.6":{"id":"anthropic/claude-opus-4.6","name":"Claude-Opus-4.6","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"temperature":false,"release_date":"2026-02-04","last_updated":"2026-02-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":983040,"output":128000},"cost":{"input":4.3,"output":21,"cache_read":0.43,"cache_write":5.3}},"anthropic/claude-sonnet-3.5-june":{"id":"anthropic/claude-sonnet-3.5-june","name":"Claude-Sonnet-3.5-June","description":"Legacy model retained for compatibility with older integrations","family":"claude-sonnet","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-11-18","last_updated":"2024-11-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":189096,"output":8192},"status":"deprecated","cost":{"input":2.6,"output":13,"cache_read":0.26,"cache_write":3.2}},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude-Opus-4.7","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"release_date":"2026-04-15","last_updated":"2026-04-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":128000},"cost":{"input":4.3,"output":21,"cache_read":0.43,"cache_write":5.4}},"anthropic/claude-haiku-3":{"id":"anthropic/claude-haiku-3","name":"Claude-Haiku-3","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-03-09","last_updated":"2024-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":189096,"output":8192},"cost":{"input":0.21,"output":1.1,"cache_read":0.021,"cache_write":0.26}},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude-Opus-4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":128000},"cost":{"input":4.2929,"output":21.4646},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-sonnet-3.7":{"id":"anthropic/claude-sonnet-3.7","name":"Claude-Sonnet-3.7","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-02-19","last_updated":"2025-02-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":196608,"output":128000},"cost":{"input":2.6,"output":13,"cache_read":0.26,"cache_write":3.2}},"anthropic/claude-haiku-4.5":{"id":"anthropic/claude-haiku-4.5","name":"Claude-Haiku-4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":0,"max":63999}],"tool_call":true,"temperature":false,"release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":192000,"output":64000},"cost":{"input":0.85,"output":4.3,"cache_read":0.085,"cache_write":1.1}},"anthropic/claude-sonnet-4.5":{"id":"anthropic/claude-sonnet-4.5","name":"Claude-Sonnet-4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":0,"max":31999}],"tool_call":true,"temperature":false,"release_date":"2025-09-26","last_updated":"2025-09-26","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":983040,"output":32768},"cost":{"input":2.6,"output":13,"cache_read":0.26,"cache_write":3.2}},"anthropic/claude-sonnet-4":{"id":"anthropic/claude-sonnet-4","name":"Claude-Sonnet-4","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-05-21","last_updated":"2025-05-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":983040,"output":64000},"cost":{"input":2.6,"output":13,"cache_read":0.26,"cache_write":3.2}},"anthropic/claude-sonnet-3.5":{"id":"anthropic/claude-sonnet-3.5","name":"Claude-Sonnet-3.5","description":"Legacy model retained for compatibility with older integrations","family":"claude-sonnet","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-06-05","last_updated":"2024-06-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":189096,"output":8192},"status":"deprecated","cost":{"input":2.6,"output":13,"cache_read":0.26,"cache_write":3.2}},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude-Sonnet-4.6","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"temperature":false,"release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":983040,"output":128000},"cost":{"input":2.6,"output":13,"cache_read":0.26,"cache_write":3.2}},"anthropic/claude-opus-4":{"id":"anthropic/claude-opus-4","name":"Claude-Opus-4","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-05-21","last_updated":"2025-05-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":192512,"output":28672},"cost":{"input":13,"output":64,"cache_read":1.3,"cache_write":16}},"elevenlabs/elevenlabs-v2.5-turbo":{"id":"elevenlabs/elevenlabs-v2.5-turbo","name":"ElevenLabs-v2.5-Turbo","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"elevenlabs","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-10-28","last_updated":"2024-10-28","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":128000,"output":0}},"elevenlabs/elevenlabs-v3":{"id":"elevenlabs/elevenlabs-v3","name":"ElevenLabs-v3","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"elevenlabs","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":128000,"output":0}},"elevenlabs/elevenlabs-music":{"id":"elevenlabs/elevenlabs-music","name":"ElevenLabs-Music","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"elevenlabs","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-08-29","last_updated":"2025-08-29","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":2000,"output":0}},"novita/glm-4.6v":{"id":"novita/glm-4.6v","name":"glm-4.6v","description":"GLM vision model for visual reasoning, documents, and multimodal agents","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":false,"release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":32768}},"novita/glm-4.6":{"id":"novita/glm-4.6","name":"GLM-4.6","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0}},"novita/glm-5":{"id":"novita/glm-5","name":"GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":205000,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2}},"novita/kimi-k2.6":{"id":"novita/kimi-k2.6","name":"Kimi-K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-20","last_updated":"2026-05-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":262144},"cost":{"input":0.96,"output":4.04,"cache_read":0.16}},"novita/kimi-k2-thinking":{"id":"novita/kimi-k2-thinking","name":"kimi-k2-thinking","description":"Kimi reasoning model for long-horizon research, planning, and tool use","family":"kimi-thinking","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":false,"release_date":"2025-11-07","last_updated":"2025-11-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":0}},"novita/kimi-k2.5":{"id":"novita/kimi-k2.5","name":"Kimi-K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":262144},"cost":{"input":0.6,"output":3,"cache_read":0.1}},"novita/glm-4.7-flash":{"id":"novita/glm-4.7-flash","name":"glm-4.7-flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":false,"release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":65500}},"novita/glm-4.7":{"id":"novita/glm-4.7","name":"glm-4.7","description":"Legacy model retained for compatibility with older integrations","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":205000,"output":131072},"status":"deprecated"},"novita/glm-4.7-n":{"id":"novita/glm-4.7-n","name":"glm-4.7-n","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":false,"release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":205000,"output":131072}},"novita/deepseek-v3.2":{"id":"novita/deepseek-v3.2","name":"DeepSeek-V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":0},"cost":{"input":0.27,"output":0.4,"cache_read":0.13}},"novita/minimax-m2.1":{"id":"novita/minimax-m2.1","name":"minimax-m2.1","description":"MiniMax model for chat, coding, office work, and agentic tasks","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":false,"release_date":"2025-12-26","last_updated":"2025-12-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":205000,"output":131072}},"lumalabs/ray2":{"id":"lumalabs/ray2","name":"Ray2","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"ray","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-02-20","last_updated":"2025-02-20","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":5000,"output":0}},"poetools/claude-code":{"id":"poetools/claude-code","name":"claude-code","description":"Claude model for careful reasoning, writing, coding, and tool use","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-11-27","last_updated":"2025-11-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0}},"google/imagen-3-fast":{"id":"google/imagen-3-fast","name":"Imagen-3-Fast","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"imagen","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-10-17","last_updated":"2024-10-17","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":480,"output":0}},"google/imagen-4-ultra":{"id":"google/imagen-4-ultra","name":"Imagen-4-Ultra","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"imagen","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-05-24","last_updated":"2025-05-24","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":480,"output":0}},"google/gemini-deep-research":{"id":"google/gemini-deep-research","name":"gemini-deep-research","description":"Legacy model retained for compatibility with older integrations","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":0},"status":"deprecated","cost":{"input":1.6,"output":9.6}},"google/imagen-4":{"id":"google/imagen-4","name":"Imagen-4","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"imagen","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":480,"output":0}},"google/imagen-4-fast":{"id":"google/imagen-4-fast","name":"Imagen-4-Fast","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"imagen","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-06-25","last_updated":"2025-06-25","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":480,"output":0}},"google/lyria":{"id":"google/lyria","name":"Lyria","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"lyria","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-06-04","last_updated":"2025-06-04","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"google/nano-banana":{"id":"google/nano-banana","name":"Nano-Banana","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"nano-banana","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":0},"cost":{"input":0.21,"output":1.8,"cache_read":0.021}},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini-3.6-Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.7576,"output":3.7879,"cache_read":0.0758},"canonical_model_id":"google/gemini-3.6-flash"},"google/veo-3-fast":{"id":"google/veo-3-fast","name":"Veo-3-Fast","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-10-13","last_updated":"2025-10-13","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":480,"output":0}},"google/gemini-2.0-flash":{"id":"google/gemini-2.0-flash","name":"Gemini-2.0-Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":990000,"output":8192},"cost":{"input":0.1,"output":0.42}},"google/veo-3.1":{"id":"google/veo-3.1","name":"Veo-3.1","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":480,"output":0}},"google/nano-banana-pro":{"id":"google/nano-banana-pro","name":"Nano-Banana-Pro","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"nano-banana","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":65536,"output":0},"cost":{"input":2,"output":12,"cache_read":0.2}},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini-3.5-Flash-Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.303,"output":2.5253,"cache_read":0.0303},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemini-2.0-flash-lite":{"id":"google/gemini-2.0-flash-lite","name":"Gemini-2.0-Flash-Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-02-05","last_updated":"2025-02-05","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":990000,"output":8192},"cost":{"input":0.052,"output":0.21}},"google/gemini-omni-1.1-flash":{"id":"google/gemini-omni-1.1-flash","type":"video","name":"Gemini-Omni-1.1-Flash","description":"Video generation and editing model for scene extension, frame interpolation, and reference-guided multimodal control","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":false,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text","image","video"],"output":["video"]},"open_weights":false,"limit":{"context":131072,"output":57920},"cost":{"input":1.5152,"output":9.0909},"canonical_model_id":"google/gemini-omni-1.1-flash"},"google/gemini-3-flash":{"id":"google/gemini-3-flash","name":"Gemini-3-Flash","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.404,"output":2.4242,"cache_read":0.0404},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini-3.5-Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5152,"output":9.0909,"cache_read":0.1515},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini-2.5-Pro","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":0,"max":32768}],"tool_call":true,"temperature":false,"release_date":"2025-02-05","last_updated":"2025-02-05","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1065535,"output":65535},"cost":{"input":0.87,"output":7,"cache_read":0.087}},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini-2.5-Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"temperature":false,"release_date":"2025-04-26","last_updated":"2025-04-26","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1065535,"output":65535},"cost":{"input":0.21,"output":1.8,"cache_read":0.021}},"google/imagen-3":{"id":"google/imagen-3","name":"Imagen-3","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"imagen","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-10-15","last_updated":"2024-10-15","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":480,"output":0}},"google/gemini-3-pro":{"id":"google/gemini-3-pro","name":"Gemini-3-Pro","description":"Legacy model retained for compatibility with older integrations","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-10-22","last_updated":"2025-10-22","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":1.6,"output":9.6,"cache_read":0.16}},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini-3.7-Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.7576,"output":3.7879,"cache_read":0.0758},"canonical_model_id":"google/gemini-3.7-flash"},"google/veo-2":{"id":"google/veo-2","name":"Veo-2","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-12-02","last_updated":"2024-12-02","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":480,"output":0}},"google/veo-3.1-fast":{"id":"google/veo-3.1-fast","name":"Veo-3.1-Fast","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":480,"output":0}},"google/gemma-4-31b":{"id":"google/gemma-4-31b","name":"Gemma-4-31B","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":8192},"cost":{"input":0,"output":0}},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini-3.8-Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.7576,"output":3.7879,"cache_read":0.0758},"canonical_model_id":"google/gemini-3.8-flash"},"google/veo-3":{"id":"google/veo-3","name":"Veo-3","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-05-21","last_updated":"2025-05-21","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":480,"output":0}},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini-2.5-Flash-Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"temperature":false,"release_date":"2025-06-19","last_updated":"2025-06-19","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1024000,"output":64000},"cost":{"input":0.07,"output":0.28}},"google/gemini-3.1-pro":{"id":"google/gemini-3.1-pro","name":"Gemini-3.1-Pro","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2.0202,"output":12.1212,"cache_read":0.202},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini-3.1-Flash-Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.2525,"output":1.5152},"canonical_model_id":"google/gemini-3.1-flash-lite"},"xai/grok-3":{"id":"xai/grok-3","name":"Grok 3","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-04-11","last_updated":"2025-04-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":3,"output":15,"cache_read":0.75}},"xai/grok-4.20-multi-agent":{"id":"xai/grok-4.20-multi-agent","name":"Grok-4.20-Multi-Agent","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2026-03-13","last_updated":"2026-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":0},"cost":{"input":2,"output":6,"cache_read":0.2}},"xai/grok-4":{"id":"xai/grok-4","name":"Grok-4","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-07-10","last_updated":"2025-07-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.75}},"xai/grok-4-fast-reasoning":{"id":"xai/grok-4-fast-reasoning","name":"Grok-4-Fast-Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-09-16","last_updated":"2025-09-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":128000},"cost":{"input":0.2,"output":0.5,"cache_read":0.05}},"xai/grok-4.1-fast-reasoning":{"id":"xai/grok-4.1-fast-reasoning","name":"Grok-4.1-Fast-Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000}},"xai/grok-4-fast-non-reasoning":{"id":"xai/grok-4-fast-non-reasoning","name":"Grok-4-Fast-Non-Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-09-16","last_updated":"2025-09-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":128000},"cost":{"input":0.2,"output":0.5,"cache_read":0.05}},"xai/grok-3-mini":{"id":"xai/grok-3-mini","name":"Grok 3 Mini","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"release_date":"2025-04-11","last_updated":"2025-04-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.3,"output":0.5,"cache_read":0.075}},"xai/grok-code-fast-1":{"id":"xai/grok-code-fast-1","name":"Grok Code Fast 1","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-08-22","last_updated":"2025-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.2,"output":1.5,"cache_read":0.02}},"xai/grok-4.1-fast-non-reasoning":{"id":"xai/grok-4.1-fast-non-reasoning","name":"Grok-4.1-Fast-Non-Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000}},"ideogramai/ideogram-v2":{"id":"ideogramai/ideogram-v2","name":"Ideogram-v2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"ideogram","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-08-21","last_updated":"2024-08-21","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":150,"output":0}},"ideogramai/ideogram-v2a-turbo":{"id":"ideogramai/ideogram-v2a-turbo","name":"Ideogram-v2a-Turbo","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"ideogram","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-02-27","last_updated":"2025-02-27","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":150,"output":0}},"ideogramai/ideogram-v2a":{"id":"ideogramai/ideogram-v2a","name":"Ideogram-v2a","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"ideogram","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-02-27","last_updated":"2025-02-27","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":150,"output":0}},"ideogramai/ideogram":{"id":"ideogramai/ideogram","name":"Ideogram","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"ideogram","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-04-03","last_updated":"2024-04-03","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":150,"output":0}},"fireworks-ai/kimi-k2.5-fw":{"id":"fireworks-ai/kimi-k2.5-fw","name":"Kimi-K2.5-FW","description":"Kimi multimodal agent model for visual understanding, coding, and planning","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"input":245760,"output":16384},"cost":{"input":0,"output":0}},"runwayml/runway":{"id":"runwayml/runway","name":"Runway","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"runway","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-10-11","last_updated":"2024-10-11","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":256,"output":0}},"runwayml/runway-gen-4-turbo":{"id":"runwayml/runway-gen-4-turbo","name":"Runway-Gen-4-Turbo","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"runway","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-05-09","last_updated":"2025-05-09","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":256,"output":0}},"trytako/tako":{"id":"trytako/tako","name":"Tako","description":"Tool-capable chat model for instruction following and agentic application workflows","family":"tako","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-08-15","last_updated":"2024-08-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":2048,"output":0}},"stabilityai/stablediffusionxl":{"id":"stabilityai/stablediffusionxl","name":"StableDiffusionXL","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"stable-diffusion","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2023-07-09","last_updated":"2023-07-09","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":200,"output":0}},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"temperature":false,"release_date":"2026-02-26","last_updated":"2026-02-26","modalities":{"input":["text","image","pdf"],"output":["image"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.2,"output":14,"cache_read":0.22}},"openai/dall-e-3":{"id":"openai/dall-e-3","name":"DALL-E-3","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"dall-e","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2023-11-06","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":800,"output":0}},"openai/sora-2":{"id":"openai/sora-2","name":"Sora-2","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"sora","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT-5.4-Pro","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"temperature":false,"release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":27,"output":160}},"openai/gpt-3.5-turbo":{"id":"openai/gpt-3.5-turbo","name":"GPT-3.5-Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2023-09-13","last_updated":"2023-09-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":2048},"cost":{"input":0.45,"output":1.4}},"openai/gpt-5.5-pro":{"id":"openai/gpt-5.5-pro","name":"GPT-5.5-Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-08","last_updated":"2026-04-08","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":27.2727,"output":163.6364},"canonical_model_id":"openai/gpt-5.5-pro"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4-Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"temperature":false,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.18,"output":1.1,"cache_read":0.018}},"openai/gpt-5.2-codex":{"id":"openai/gpt-5.2-codex","name":"GPT-5.2-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"temperature":false,"release_date":"2026-01-14","last_updated":"2026-01-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.6,"output":13,"cache_read":0.16}},"openai/gpt-5.1-codex":{"id":"openai/gpt-5.1-codex","name":"GPT-5.1-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"release_date":"2025-11-12","last_updated":"2025-11-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.1,"output":9,"cache_read":0.11}},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-05-13","last_updated":"2024-05-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192}},"openai/gpt-4o-search":{"id":"openai/gpt-4o-search","name":"GPT-4o-Search","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-03-11","last_updated":"2025-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":2.2,"output":9}},"openai/sora-2-pro":{"id":"openai/sora-2-pro","name":"Sora-2-Pro","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"sora","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"openai/gpt-5-codex":{"id":"openai/gpt-5-codex","name":"GPT-5-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.1,"output":9}},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5-mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":false,"release_date":"2025-06-25","last_updated":"2025-06-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.22,"output":1.8,"cache_read":0.022}},"openai/gpt-image-2":{"id":"openai/gpt-image-2","name":"GPT-Image-2","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5.0505,"output":32.3232,"cache_read":1.2626}},"openai/gpt-5.2-pro":{"id":"openai/gpt-5.2-pro","name":"GPT-5.2-Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"temperature":false,"release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":19,"output":150}},"openai/o4-mini":{"id":"openai/o4-mini","name":"o4-mini","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":0.99,"output":4,"cache_read":0.25}},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3-mini","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"release_date":"2025-01-31","last_updated":"2025-01-31","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":0.99,"output":4}},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT-5.3-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"temperature":false,"release_date":"2026-02-10","last_updated":"2026-02-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.6,"output":13,"cache_read":0.16}},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1-nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-04-15","last_updated":"2025-04-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.09,"output":0.36,"cache_read":0.022}},"openai/o3-deep-research":{"id":"openai/o3-deep-research","name":"o3-deep-research","description":"Research model for long-horizon investigation, synthesis, and analytical reports","family":"o","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-06-27","last_updated":"2025-06-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":9,"output":36,"cache_read":2.2}},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5-nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":false,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.045,"output":0.36,"cache_read":0.0045}},"openai/gpt-5.2-instant":{"id":"openai/gpt-5.2-instant","name":"GPT-5.2-Instant","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1.6,"output":13,"cache_read":0.16}},"openai/o1":{"id":"openai/o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"release_date":"2024-12-18","last_updated":"2024-12-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":14,"output":54}},"openai/chatgpt-4o-latest":{"id":"openai/chatgpt-4o-latest","name":"ChatGPT-4o-Latest","description":"Legacy model retained for compatibility with older integrations","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-08-14","last_updated":"2024-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"status":"deprecated","cost":{"input":4.5,"output":14}},"openai/gpt-5-pro":{"id":"openai/gpt-5-pro","name":"GPT-5-Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":14,"output":110}},"openai/gpt-3.5-turbo-instruct":{"id":"openai/gpt-3.5-turbo-instruct","name":"GPT-3.5-Turbo-Instruct","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2023-09-20","last_updated":"2023-09-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":3500,"output":1024},"cost":{"input":1.4,"output":1.8}},"openai/gpt-5.3-codex-spark":{"id":"openai/gpt-5.3-codex-spark","name":"GPT-5.3-Codex-Spark","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2026-03-04","last_updated":"2026-03-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0,"output":0}},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":false,"release_date":"2025-11-12","last_updated":"2025-11-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.1,"output":9,"cache_read":0.11}},"openai/gpt-5-chat":{"id":"openai/gpt-5-chat","name":"GPT-5-Chat","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt-codex","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1.1,"output":9,"cache_read":0.11}},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o-mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":124096,"output":4096},"cost":{"input":0.14,"output":0.54,"cache_read":0.068}},"openai/o3-pro":{"id":"openai/o3-pro","name":"o3-pro","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"release_date":"2025-06-10","last_updated":"2025-06-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":18,"output":72}},"openai/gpt-5.3-instant":{"id":"openai/gpt-5.3-instant","name":"GPT-5.3-Instant","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":111616,"output":16384},"cost":{"input":1.6,"output":13,"cache_read":0.16}},"openai/gpt-4o-aug":{"id":"openai/gpt-4o-aug","name":"GPT-4o-Aug","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-11-21","last_updated":"2024-11-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":2.2,"output":9,"cache_read":1.1}},"openai/o3-mini-high":{"id":"openai/o3-mini-high","name":"o3-mini-high","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-01-31","last_updated":"2025-01-31","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":0.99,"output":4}},"openai/gpt-5.1-instant":{"id":"openai/gpt-5.1-instant","name":"GPT-5.1-Instant","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-11-12","last_updated":"2025-11-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1.1,"output":9,"cache_read":0.11}},"openai/gpt-image-1":{"id":"openai/gpt-image-1","name":"GPT-Image-1","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-03-31","last_updated":"2025-03-31","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":128000,"output":0}},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4-Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"temperature":false,"release_date":"2026-03-12","last_updated":"2026-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.68,"output":4,"cache_read":0.068}},"openai/gpt-5.1-codex-max":{"id":"openai/gpt-5.1-codex-max","name":"GPT-5.1-Codex-Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"temperature":false,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.1,"output":9,"cache_read":0.11}},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"temperature":false,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.6,"output":13,"cache_read":0.16}},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-08","last_updated":"2026-04-08","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":4.5455,"output":27.2727,"cache_read":0.4545},"canonical_model_id":"openai/gpt-5.5"},"openai/o4-mini-deep-research":{"id":"openai/o4-mini-deep-research","name":"o4-mini-deep-research","description":"Research model for long-horizon investigation, synthesis, and analytical reports","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-06-27","last_updated":"2025-06-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.8,"output":7.2,"cache_read":0.45}},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":1.8,"output":7.2,"cache_read":0.45}},"openai/gpt-4-classic-0314":{"id":"openai/gpt-4-classic-0314","name":"GPT-4-Classic-0314","description":"Legacy model retained for compatibility with older integrations","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-08-26","last_updated":"2024-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":4096},"status":"deprecated","cost":{"input":27,"output":54}},"openai/gpt-4-classic":{"id":"openai/gpt-4-classic","name":"GPT-4-Classic","description":"Legacy model retained for compatibility with older integrations","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-03-25","last_updated":"2024-03-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":4096},"status":"deprecated","cost":{"input":27,"output":54}},"openai/gpt-4o-mini-search":{"id":"openai/gpt-4o-mini-search","name":"GPT-4o-mini-Search","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-03-11","last_updated":"2025-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.14,"output":0.54}},"openai/gpt-3.5-turbo-raw":{"id":"openai/gpt-3.5-turbo-raw","name":"GPT-3.5-Turbo-Raw","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2023-09-27","last_updated":"2023-09-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":4524,"output":2048},"cost":{"input":0.45,"output":1.4}},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1-mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-04-15","last_updated":"2025-04-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.36,"output":1.4,"cache_read":0.09}},"openai/gpt-image-1-mini":{"id":"openai/gpt-image-1-mini","name":"GPT-Image-1-Mini","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0}},"openai/gpt-image-1.5":{"id":"openai/gpt-image-1.5","name":"gpt-image-1.5","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":128000,"output":0}},"openai/gpt-4-turbo":{"id":"openai/gpt-4-turbo","name":"GPT-4-Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2023-09-13","last_updated":"2023-09-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":9,"output":27}},"openai/gpt-5.1-codex-mini":{"id":"openai/gpt-5.1-codex-mini","name":"GPT-5.1-Codex-Mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"release_date":"2025-11-12","last_updated":"2025-11-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.22,"output":1.8,"cache_read":0.022}},"openai/o3":{"id":"openai/o3","name":"o3","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.8,"output":7.2,"cache_read":0.45}},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":false,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.1,"output":9,"cache_read":0.11}},"openai/o1-pro":{"id":"openai/o1-pro","name":"o1-pro","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"release_date":"2025-03-19","last_updated":"2025-03-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":140,"output":540}},"topazlabs-co/topazlabs":{"id":"topazlabs-co/topazlabs","name":"TopazLabs","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"topazlabs","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":204,"output":0}}}},"cerebras":{"id":"cerebras","env":["CEREBRAS_API_KEY"],"npm":"@ai-sdk/cerebras","name":"Cerebras","doc":"https://inference-docs.cerebras.ai/models/overview","models":{"qwen-3.8-27b":{"id":"qwen-3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-09-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":40960},"cost":{"input":0.99,"output":1.49,"cache_read":0.99},"canonical_model_id":"alibaba/qwen3.8-27b"},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2026-06-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":40960},"cost":{"input":0.35,"output":0.75},"canonical_model_id":"openai/gpt-oss-120b"}}},"groq":{"id":"groq","env":["GROQ_API_KEY"],"npm":"@ai-sdk/groq","name":"Groq","doc":"https://console.groq.com/docs/models","models":{"whisper-large-v3":{"id":"whisper-large-v3","name":"Whisper","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"whisper","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2023-09-01","last_updated":"2025-09-05","modalities":{"input":["audio"],"output":["text"]},"open_weights":true,"limit":{"context":0,"output":0}},"llama-3.3-70b-versatile":{"id":"llama-3.3-70b-versatile","name":"Llama 3.3 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.59,"output":0.79}},"allam-2-7b":{"id":"allam-2-7b","name":"ALLaM-2-7b","description":"ALLaM-2-7b instruction tuned model by SDAIA","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-01-23","last_updated":"2025-01-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":4096},"cost":{"input":0,"output":0},"canonical_model_id":"sdaia/allam-2-7b"},"whisper-large-v3-turbo":{"id":"whisper-large-v3-turbo","name":"Whisper Large V3 Turbo","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"whisper","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-10-01","last_updated":"2024-10-01","modalities":{"input":["audio"],"output":["text"]},"open_weights":true,"limit":{"context":0,"output":0}},"llama-3.1-8b-instant":{"id":"llama-3.1-8b-instant","name":"Llama 3.1 8B","description":"Compact Llama instruction model for fast chat and local deployment","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.05,"output":0.08}},"groq/compound-mini":{"id":"groq/compound-mini","name":"Compound Mini","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"groq","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-09-04","last_updated":"2025-09-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192}},"groq/compound":{"id":"groq/compound","name":"Compound","description":"General-purpose chat model for instruction following, writing, and analysis","family":"groq","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-09-04","last_updated":"2025-09-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192}},"meta-llama/llama-prompt-guard-2-86m":{"id":"meta-llama/llama-prompt-guard-2-86m","name":"Prompt Guard 2 86M","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-05-29","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512,"output":512},"status":"beta","cost":{"input":0.04,"output":0.04}},"meta-llama/llama-prompt-guard-2-22m":{"id":"meta-llama/llama-prompt-guard-2-22m","name":"Llama Prompt Guard 2 22M","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-05-29","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512,"output":512},"status":"beta","cost":{"input":0.03,"output":0.03}},"canopylabs/orpheus-v1-english":{"id":"canopylabs/orpheus-v1-english","name":"Canopy Labs Orpheus V1 English","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"canopylabs","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-19","last_updated":"2025-12-19","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":4000,"output":50000},"status":"beta"},"canopylabs/orpheus-arabic-saudi":{"id":"canopylabs/orpheus-arabic-saudi","name":"Canopy Labs Orpheus Arabic Saudi","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"canopylabs","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":4000,"output":50000},"status":"beta"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","default","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131042,"output":16384},"cost":{"input":0.8,"output":4},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3.6-27b":{"id":"qwen/qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","default"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.6,"output":3,"cache_read":0.3},"canonical_model_id":"alibaba/qwen3.6-27b"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.075,"output":0.3,"cache_read":0.0375}},"openai/gpt-oss-safeguard-20b":{"id":"openai/gpt-oss-safeguard-20b","name":"Safety GPT OSS 20B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2026-06-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"status":"beta","cost":{"input":0.075,"output":0.3}},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-10-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-oss-120b"}}},"blueclaw":{"id":"blueclaw","env":["BLUECLAW_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://openai.blueclaw.network/v1","name":"Blue Claw","doc":"https://blueclaw.network","models":{"Qwen3.8-27B":{"id":"Qwen3.8-27B","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"status":"beta","canonical_model_id":"alibaba/qwen3.8-27b"}}},"zai":{"id":"zai","env":["ZHIPU_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.z.ai/api/paas/v4","name":"Z.AI","doc":"https://docs.z.ai/guides/overview/pricing","models":{"glm-4.6v":{"id":"glm-4.6v","name":"GLM-4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.3,"output":0.9}},"glm-4.5":{"id":"glm-4.5","name":"GLM-4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0}},"glm-5v-turbo":{"id":"glm-5v-turbo","name":"GLM-5V-Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24,"cache_write":0}},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"glm-4.6":{"id":"glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0}},"glm-5":{"id":"glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2,"cache_write":0},"canonical_model_id":"zhipuai/glm-5"},"glm-4.6v-flash":{"id":"glm-4.6v-flash","name":"GLM-4.6V-Flash","description":"Lightweight GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.6v-flash"},"glm-4.5v":{"id":"glm-4.5v","name":"GLM-4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":16384},"cost":{"input":0.6,"output":1.8}},"glm-5.3-flashx":{"id":"glm-5.3-flashx","name":"GLM-5.3-FlashX","description":"High-speed GLM-5.3-Flash serving option for coding and agent workflows","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-18","last_updated":"2026-09-18","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.37,"output":1.25,"cache_read":0.075,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"glm-4.7-flash":{"id":"glm-4.7-flash","name":"GLM-4.7-Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"glm-4.7":{"id":"glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0}},"glm-4.5-flash":{"id":"glm-4.5-flash","name":"GLM-4.5-Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.1"},"glm-4.7-flashx":{"id":"glm-4.7-flashx","name":"GLM-4.7-FlashX","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.07,"output":0.4,"cache_read":0.01,"cache_write":0}},"glm-5-turbo":{"id":"glm-5-turbo","name":"GLM-5-Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24,"cache_write":0}},"glm-4.5-air":{"id":"glm-4.5-air","name":"GLM-4.5-Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.2,"output":1.1,"cache_read":0.03,"cache_write":0}},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"}}},"empiriolabs":{"id":"empiriolabs","env":["EMPIRIOLABS_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.empiriolabs.ai/v1","name":"EmpirioLabs AI","doc":"https://docs.empiriolabs.ai","models":{"qwen3-8-max-0902":{"id":"qwen3-8-max-0902","name":"Qwen3.8 Max 0902","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":262144}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":2},"canonical_model_id":"alibaba/qwen3.8-max"},"qwen3-6-plus":{"id":"qwen3-6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.5,"tiers":[{"input":2,"output":6,"cache_read":2,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":2}},"canonical_model_id":"alibaba/qwen3.6-plus"},"qwen3-6-27b":{"id":"qwen3-6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":80000}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.412564,"output":2.475384,"cache_read":0.412564},"canonical_model_id":"alibaba/qwen3.6-27b"},"glm-5-3-flash":{"id":"glm-5-3-flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.075,"output":0.25,"cache_read":0.075},"canonical_model_id":"zhipuai/glm-5.3-flash"},"kimi-k2-7-code":{"id":"kimi-k2-7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":131072},"cost":{"input":0.95,"output":4,"cache_read":0.95},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"fugu-max":{"id":"fugu-max","name":"Fugu Max","description":"Multi-agent model for routing expert agents across complex analytical tasks","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"sakana/fugu-max"},"seed-2-0-lite":{"id":"seed-2-0-lite","name":"Seed 2.0 Lite","description":"Cost-efficient ByteDance Seed 2.0 model for production chat, analysis, and structured generation","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.31,"output":2.5,"cache_read":0.31,"tiers":[{"input":0.62,"output":5,"cache_read":0.62,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":393216}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":0.424,"output":1.272,"cache_read":0.424},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"mimo-v2-5":{"id":"mimo-v2-5","name":"MiMo V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.7,"output":1.4,"cache_read":0.014},"canonical_model_id":"xiaomi/mimo-v2.5"},"seed-2-0-mini":{"id":"seed-2-0-mini","name":"Seed 2.0 Mini","description":"Lightweight ByteDance Seed 2.0 model for low-latency multimodal reasoning and high-volume tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.12,"output":0.5,"cache_read":0.12,"tiers":[{"input":0.24,"output":1,"cache_read":0.24,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"muse-glimmer-30b":{"id":"muse-glimmer-30b","name":"Muse Glimmer 30B","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.2,"output":0.8,"cache_read":0.05},"canonical_model_id":"meta/muse-glimmer-30b"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":3,"output":15,"cache_read":3},"canonical_model_id":"moonshotai/kimi-k3"},"glm-4-7-flash":{"id":"glm-4-7-flash","name":"GLM 4.7 Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-4.7-flash"},"mimo-v2-6-pro":{"id":"mimo-v2-6-pro","name":"MiMo V2.6 Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.435},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"qwen3-7-max":{"id":"qwen3-7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":64000}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":2.5,"output":7.5,"cache_read":2.5},"canonical_model_id":"alibaba/qwen3.7-max"},"step-3-5-flash":{"id":"step-3-5-flash","name":"Step 3.5 Flash","description":"StepFun flash lane for quick multimodal reasoning and coding assistance","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":131072},"cost":{"input":0.1,"output":0.3,"cache_read":0.02},"canonical_model_id":"stepfun/step-3.5-flash"},"qwen3-8-max":{"id":"qwen3-8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":262144}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":2},"canonical_model_id":"alibaba/qwen3.8-max"},"minimax-m2-7-highspeed":{"id":"minimax-m2-7-highspeed","name":"MiniMax M2.7 Highspeed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32768},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"mimo-v2-5-pro":{"id":"mimo-v2-5-pro","name":"MiMo V2.5 Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":2.175,"output":4.35,"cache_read":0.018},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"seed-2-0-pro":{"id":"seed-2-0-pro","name":"Seed 2.0 Pro","description":"Flagship ByteDance Seed 2.0 model for complex multimodal reasoning and long-horizon agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.63,"output":3.79,"cache_read":0.63,"tiers":[{"input":1.26,"output":7.58,"cache_read":1.26,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-pro"},"qwen3-5-4b":{"id":"qwen3-5-4b","name":"Qwen3.5 4B","description":"Qwen3.5 4B is a low-cost multimodal reasoning model with 256K context, image and video input, function tools, and structured output.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1024,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-02","last_updated":"2026-03-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.04,"output":0.07,"cache_read":0.02}},"step-5-preview":{"id":"step-5-preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1024000,"output":131072},"cost":{"input":1,"output":2.7,"cache_read":0.05},"canonical_model_id":"stepfun/step-5-preview"},"qwen3-5-27b":{"id":"qwen3-5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":80000}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.086,"output":0.688,"cache_read":0.086,"tiers":[{"input":0.258,"output":2.064,"cache_read":0.258,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3.5-27b"},"seed-2-1-turbo":{"id":"seed-2-1-turbo","name":"Seed 2.1 Turbo","description":"Faster ByteDance Seed 2.1 model for multimodal reasoning and latency-sensitive agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":65536},"cost":{"input":0.63,"output":3.13,"cache_read":0.63},"canonical_model_id":"bytedance-seed/seed-2.1-turbo"},"fugu-ultra-v1-0":{"id":"fugu-ultra-v1-0","name":"Fugu Ultra v1.0","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":7.5,"output":45,"cache_read":1.5,"tiers":[{"input":15,"output":67.5,"cache_read":3,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":15,"output":67.5,"cache_read":3}},"canonical_model_id":"sakana/fugu-ultra"},"qwen3-5-122b-a10b":{"id":"qwen3-5-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":80000}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.115,"output":0.917,"cache_read":0.115,"tiers":[{"input":0.287,"output":2.294,"cache_read":0.287,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"qwen3-5-flash":{"id":"qwen3-5-flash","name":"Qwen3.5 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":81920}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.09,"output":0.368,"cache_read":0.09},"canonical_model_id":"alibaba/qwen3.5-flash"},"mimo-v2-6-pro-ultraspeed":{"id":"mimo-v2-6-pro-ultraspeed","name":"MiMo V2.6 Pro UltraSpeed","description":"MiMo pro model for strong multimodal reasoning and agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":4.35,"output":8.7,"cache_read":4.35},"canonical_model_id":"xiaomi/mimo-v2.6-pro-ultraspeed"},"glm-5-2":{"id":"glm-5-2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":1.4},"canonical_model_id":"zhipuai/glm-5.2"},"mimo-v2-6-flash":{"id":"mimo-v2-6-flash","name":"MiMo V2.6 Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.14},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"muse-spark-1-2":{"id":"muse-spark-1-2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":1},"canonical_model_id":"meta/muse-spark-1.2"},"qwen3-7-flash":{"id":"qwen3-7-flash","name":"Qwen3.7 Flash","description":"Lightweight multimodal Qwen model for high-throughput text, image, and video tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":131072}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":991808,"output":65536},"cost":{"input":0.03,"output":0.13,"cache_read":0.006,"tiers":[{"input":0.1,"output":0.4,"cache_read":0.02,"tier":{"type":"context","size":32000}},{"input":0.2,"output":0.8,"cache_read":0.04,"tier":{"type":"context","size":256000}}]},"canonical_model_id":"alibaba/qwen3.7-flash"},"minimax-m2-7":{"id":"minimax-m2-7","name":"MiniMax M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32768},"cost":{"input":0.15,"output":0.6,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.7"},"qwen3-6-35b-a3b":{"id":"qwen3-6-35b-a3b","name":"Qwen3.6 35B A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.07,"output":0.42,"cache_read":0.035},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"qwen3-5-9b":{"id":"qwen3-5-9b","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1024,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.09,"output":0.13,"cache_read":0.045},"canonical_model_id":"alibaba/qwen3.5-9b"},"step-3-5-flash-2603":{"id":"step-3-5-flash-2603","name":"Step 3.5 Flash 2603","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":131072},"cost":{"input":0.1,"output":0.3,"cache_read":0.02},"canonical_model_id":"stepfun/step-3.5-flash-2603"},"qwen3-5-35b-a3b":{"id":"qwen3-5-35b-a3b","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":80000}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.057,"output":0.459,"cache_read":0.057,"tiers":[{"input":0.229,"output":1.835,"cache_read":0.229,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":393216}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":1.32,"output":3.96,"cache_read":1.32},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"kimi-k2-6":{"id":"kimi-k2-6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":81920}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16000},"cost":{"input":0.8939,"output":3.7131,"cache_read":0.1788},"canonical_model_id":"moonshotai/kimi-k2.6"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":524288},"cost":{"input":0.225,"output":0.9,"cache_read":0.045,"tiers":[{"input":0.45,"output":1.8,"cache_read":0.09,"tier":{"type":"context","size":512000}}],"context_over_200k":{"input":0.45,"output":1.8,"cache_read":0.09}},"canonical_model_id":"minimax/MiniMax-M3"},"glm-5-3":{"id":"glm-5-3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":1.4},"canonical_model_id":"zhipuai/glm-5.3"},"fugu-ultra-v1-1":{"id":"fugu-ultra-v1-1","name":"Fugu Ultra v1.1","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"sakana/fugu-ultra"},"kimi-k2-7-code-highspeed":{"id":"kimi-k2-7-code-highspeed","name":"Kimi K2.7 Code Highspeed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":131072},"cost":{"input":1.9,"output":8,"cache_read":1.9},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"deepseek-v4-1-flash":{"id":"deepseek-v4-1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":393216}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":0.3,"output":1.2,"cache_read":0.3},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"qwen3-7-plus":{"id":"qwen3-7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":256000}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.4,"output":1.6,"cache_read":0.4,"tiers":[{"input":1.2,"output":4.8,"cache_read":1.2,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1.2,"output":4.8,"cache_read":1.2}},"canonical_model_id":"alibaba/qwen3.7-plus"},"glm-5-1":{"id":"glm-5-1","name":"GLM 5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":38912}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202000,"output":128000},"cost":{"input":0.825,"output":3.301,"cache_read":0.165,"tiers":[{"input":1.1,"output":3.851,"cache_read":0.22,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-5.1"},"glm-4-6v-flash":{"id":"glm-4-6v-flash","name":"GLM 4.6V Flash","description":"Lightweight GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-4.6v-flash"},"fugu-ultra-v2-0":{"id":"fugu-ultra-v2-0","name":"Fugu Ultra v2.0","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"sakana/fugu-ultra"},"mistral-small-4":{"id":"mistral-small-4","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0.15,"output":0.6,"cache_read":0.15},"canonical_model_id":"mistral/mistral-small-2603"},"qwen3-8-omni-flash":{"id":"qwen3-8-omni-flash","name":"Qwen3.8 Omni Flash","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":262144}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.3,"output":0.94,"cache_read":0.3},"canonical_model_id":"alibaba/qwen3.8-omni-flash"},"qwen3-5-plus":{"id":"qwen3-5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":81920}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.36,"output":2.21,"cache_read":0.36,"tiers":[{"input":1.08,"output":6.62,"cache_read":1.08,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1.08,"output":6.62,"cache_read":1.08}},"canonical_model_id":"alibaba/qwen3.5-plus"},"muse-spark-1-3":{"id":"muse-spark-1-3","name":"Muse Spark 1.3","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":1},"canonical_model_id":"meta/muse-spark-1.3"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":393216}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":1.65,"output":3.3,"cache_read":1.65},"canonical_model_id":"deepseek/deepseek-v4-pro"},"qwen3-8-flash":{"id":"qwen3-8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":262144}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.16,"output":0.47,"cache_read":0.16},"canonical_model_id":"alibaba/qwen3.8-flash"},"gemma-3-27b":{"id":"gemma-3-27b","name":"Gemma 3 27B","description":"Largest open Gemma 3 instruction model for multilingual text generation and visual understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemma-3-27b-it"},"qwen3-6-flash":{"id":"qwen3-6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":64000}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.25,"tiers":[{"input":1,"output":4,"cache_read":1,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1,"output":4,"cache_read":1}},"canonical_model_id":"alibaba/qwen3.6-flash"},"seed-2-0-code":{"id":"seed-2-0-code","name":"Seed 2.0 Code","description":"ByteDance Seed coding model for multimodal software engineering and long-running agents","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.4,"output":2.4,"cache_read":0.4,"tiers":[{"input":0.8,"output":4.8,"cache_read":0.8,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"qwen3-8-27b":{"id":"qwen3-8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.17,"output":0.5,"cache_read":0.08},"canonical_model_id":"alibaba/qwen3.8-27b"},"muse-spark-1-1":{"id":"muse-spark-1-1","name":"Muse Spark 1.1","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":1},"canonical_model_id":"meta/muse-spark-1.1"},"step-3-7-flash":{"id":"step-3-7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":131072},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"qwen3-5-397b-a17b":{"id":"qwen3-5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":80000}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.172,"output":1.032,"cache_read":0.172,"tiers":[{"input":0.43,"output":2.58,"cache_read":0.43,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"glm-4-5-flash":{"id":"glm-4-5-flash","name":"GLM 4.5 Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":98304},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-4.5-flash"},"gemma-4-26b-a4b":{"id":"gemma-4-26b-a4b","name":"Gemma 4 26B-A4B","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.05,"output":0.29,"cache_read":0.025},"canonical_model_id":"google/gemma-4-26b-a4b-it"}}},"sensenova":{"id":"sensenova","env":["SENSENOVA_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://token.sensenova.cn/v1","name":"SenseNova (China)","doc":"https://platform.sensenova.cn/docs","models":{"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"moonshotai/kimi-k3"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash is a high-performance conversational model by DeepSeek, supporting thinking/non-thinking modes, 1M context window, and tool calling.","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"sensenova-6.8-flash-lite":{"id":"sensenova-6.8-flash-lite","name":"SenseNova 6.8 Flash Lite","description":"SenseNova lightweight multimodal agent model for real-world complex tasks, data analysis, and complex information presentation","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0,"output":0,"cache_read":0}},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-5.2"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4-flash"}}},"alibaba-token-plan":{"id":"alibaba-token-plan","env":["ALIBABA_TOKEN_PLAN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://token-plan.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1","name":"Alibaba Token Plan","doc":"https://www.alibabacloud.com/help/en/model-studio/token-plan-overview","models":{"happyhorse-1.1-r2v":{"id":"happyhorse-1.1-r2v","name":"HappyHorse 1.1 Reference-to-Video","description":"Video model for reference-guided video generation","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-07-17","last_updated":"2026-07-17","modalities":{"input":["image","text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":0,"output":0}},"qwen3.7-max":{"id":"qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.7-max"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.8-max"},"happyhorse-1.1-t2v":{"id":"happyhorse-1.1-t2v","name":"HappyHorse 1.1 Text-to-Video","description":"Video model for prompt-driven text-to-video generation","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-07-17","last_updated":"2026-07-17","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":0,"output":0}},"qwen-image-2.0":{"id":"qwen-image-2.0","name":"Qwen Image 2.0","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":8192,"output":0},"cost":{"input":0,"output":0}},"glm-5":{"id":"glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":16384},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"qwen3.8-max-preview":{"id":"qwen3.8-max-preview","name":"Qwen3.8 Max Preview","description":"Preview Qwen flagship for million-token multimodal reasoning and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-19","last_updated":"2026-07-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.8-max-preview"},"qwen-image-2.0-pro":{"id":"qwen-image-2.0-pro","name":"Qwen Image 2.0 Pro","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":8192,"output":0},"cost":{"input":0,"output":0}},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.6"},"wan2.7-image":{"id":"wan2.7-image","name":"Wan2.7 Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":8192,"output":0},"cost":{"input":0,"output":0}},"wan2.7-image-pro":{"id":"wan2.7-image-pro","name":"Wan2.7 Image Pro","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":8192,"output":0},"cost":{"input":0,"output":0}},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.5"},"happyhorse-1.1-i2v":{"id":"happyhorse-1.1-i2v","name":"HappyHorse 1.1 Image-to-Video","description":"Video model for image-to-video generation","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-07-17","last_updated":"2026-07-17","modalities":{"input":["image","text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":0,"output":0}},"qwen3.6-flash":{"id":"qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":131072}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.6-flash"},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"MiniMax-M2.5":{"id":"MiniMax-M2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"input":196601,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"minimax/MiniMax-M2.5"},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.8-flash"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.1"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4-pro"},"qwen3.6-plus":{"id":"qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":131072}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.6-plus"},"deepseek-v3.2":{"id":"deepseek-v3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-03","last_updated":"2025-12-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0,"output":0}},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.7-plus"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4-flash"}}},"cloudflare-workers-ai":{"id":"cloudflare-workers-ai","env":["CLOUDFLARE_ACCOUNT_ID","CLOUDFLARE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.cloudflare.com/client/v4/accounts/${CLOUDFLARE_ACCOUNT_ID}/ai/v1","name":"Cloudflare Workers AI","doc":"https://developers.cloudflare.com/workers-ai/models/","models":{"@cf/meta/llama-3.3-70b-instruct-fp8-fast":{"id":"@cf/meta/llama-3.3-70b-instruct-fp8-fast","name":"Llama 3.3 70B Instruct fp8 Fast","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":24000,"output":24000},"cost":{"input":0.293,"output":2.253},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"@cf/meta/llama-guard-3-8b":{"id":"@cf/meta/llama-guard-3-8b","name":"Llama Guard 3 8B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.484,"output":0.03},"canonical_model_id":"meta/llama-guard-3-8b"},"@cf/meta/llama-3.1-8b-instruct-fp8":{"id":"@cf/meta/llama-3.1-8b-instruct-fp8","name":"Llama 3.1 8B Instruct fp8","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":32000},"cost":{"input":0.152,"output":0.287},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"@cf/meta/llama-3.2-11b-vision-instruct":{"id":"@cf/meta/llama-3.2-11b-vision-instruct","name":"Llama 3.2 11B Vision Instruct","description":"Open Llama multimodal model for image understanding and text reasoning","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0.0485,"output":0.676},"canonical_model_id":"meta/llama-3.2-11b-vision-instruct"},"@cf/meta/llama-3.2-1b-instruct":{"id":"@cf/meta/llama-3.2-1b-instruct","name":"Llama 3.2 1B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":60000,"output":60000},"cost":{"input":0.027,"output":0.201},"canonical_model_id":"meta/llama-3.2-1b"},"@cf/meta/llama-4-scout-17b-16e-instruct":{"id":"@cf/meta/llama-4-scout-17b-16e-instruct","name":"Llama 4 Scout 17B 16E Instruct","description":"Open Llama with long-context vision for efficient multimodal agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":16384},"cost":{"input":0.27,"output":0.85},"canonical_model_id":"meta/llama-4-scout-17b-instruct"},"@cf/meta/llama-3.2-3b-instruct":{"id":"@cf/meta/llama-3.2-3b-instruct","name":"Llama 3.2 3B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":80000,"output":80000},"cost":{"input":0.0509,"output":0.335},"canonical_model_id":"meta/llama-3.2-3b"},"@cf/google/gemma-4-26b-a4b-it":{"id":"@cf/google/gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":0.1,"output":0.3,"cache_read":0.05},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"@cf/aisingapore/gemma-sea-lion-v4-27b-it":{"id":"@cf/aisingapore/gemma-sea-lion-v4-27b-it","name":"Gemma Sea Lion V4 27B It","description":"Gemma 3 27B tuned by AI Singapore for Southeast Asian languages and instruction following","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0.351,"output":0.555},"canonical_model_id":"aisingapore/gemma-sea-lion-v4-27b-it"},"@cf/ibm-granite/granite-4.0-h-micro":{"id":"@cf/ibm-granite/granite-4.0-h-micro","name":"Granite 4.0 H Micro","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"granite","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-10-02","last_updated":"2025-10-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":131000},"cost":{"input":0.017,"output":0.112},"canonical_model_id":"ibm/granite-4-h-micro"},"@cf/deepseek-ai/deepseek-v4-flash-0731":{"id":"@cf/deepseek-ai/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.44,"output":1.32,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"@cf/deepseek-ai/deepseek-v4-pro-0813":{"id":"@cf/deepseek-ai/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"@cf/deepseek-ai/deepseek-r1-distill-qwen-32b":{"id":"@cf/deepseek-ai/deepseek-r1-distill-qwen-32b","name":"Deepseek R1 Distill Qwen 32B","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":80000,"output":80000},"cost":{"input":0.497,"output":4.881},"canonical_model_id":"deepseek/deepseek-r1"},"@cf/mistralai/mistral-small-3.1-24b-instruct":{"id":"@cf/mistralai/mistral-small-3.1-24b-instruct","name":"Mistral Small 3.1 24B Instruct","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-03-17","last_updated":"2025-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0.351,"output":0.555},"canonical_model_id":"mistral/mistral-small-3-1-24b-instruct-2503"},"@cf/moonshotai/kimi-k2.6":{"id":"@cf/moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"@cf/moonshotai/kimi-k2.7-code":{"id":"@cf/moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"@cf/zai-org/glm-5.3-flash":{"id":"@cf/zai-org/glm-5.3-flash","name":"Glm 5.3 Flash","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"@cf/zai-org/glm-4.7-flash":{"id":"@cf/zai-org/glm-4.7-flash","name":"GLM-4.7-Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.0605,"output":0.4},"canonical_model_id":"zhipuai/glm-4.7-flash"},"@cf/zai-org/glm-5.2":{"id":"@cf/zai-org/glm-5.2","name":"Glm 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"@cf/zai-org/glm-5.3":{"id":"@cf/zai-org/glm-5.3","name":"Glm 5.3","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"@cf/nvidia/nemotron-3-120b-a12b":{"id":"@cf/nvidia/nemotron-3-120b-a12b","name":"Nemotron 3 Super 120B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"@cf/qwen/qwen3.8-27b":{"id":"@cf/qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.45,"output":3.2,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.8-27b"},"@cf/qwen/qwq-32b":{"id":"@cf/qwen/qwq-32b","name":"Qwq 32B","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2025-03-05","last_updated":"2025-03-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":24000,"output":24000},"cost":{"input":0.66,"output":1},"canonical_model_id":"alibaba/qwq-32b"},"@cf/qwen/qwen3-30b-a3b-fp8":{"id":"@cf/qwen/qwen3-30b-a3b-fp8","name":"Qwen3 30B A3b fp8","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.0509,"output":0.335},"canonical_model_id":"alibaba/qwen3-30b-a3b"},"@cf/qwen/qwen2.5-coder-32b-instruct":{"id":"@cf/qwen/qwen2.5-coder-32b-instruct","name":"Qwen2.5 Coder 32B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2024-11-12","last_updated":"2024-11-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.66,"output":1},"canonical_model_id":"alibaba/qwen2.5-coder-32b-instruct"},"@cf/openai/gpt-oss-20b":{"id":"@cf/openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.2,"output":0.3},"canonical_model_id":"openai/gpt-oss-20b"},"@cf/openai/gpt-oss-120b":{"id":"@cf/openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.35,"output":0.75},"canonical_model_id":"openai/gpt-oss-120b"}}},"engy":{"id":"engy","env":["ENGY_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.engy.ai/v1","name":"engy","doc":"https://engy.ai/pricing","models":{"qwen3.8-27b":{"id":"qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1001536,"input":936000,"output":65536},"cost":{"input":0.045,"output":0.32,"cache_read":0.015},"canonical_model_id":"alibaba/qwen3.8-27b"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":327680,"input":294912,"output":32768},"cost":{"input":0.135,"output":0.45,"cache_read":0.027},"canonical_model_id":"zhipuai/glm-5.3-flash"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":920576,"output":128000},"cost":{"input":0.045,"output":0.09,"cache_read":0.009},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1113088,"input":1047552,"output":65536},"cost":{"input":1.95,"output":9.75,"cache_read":0.195},"canonical_model_id":"moonshotai/kimi-k3"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":983040,"output":65536},"cost":{"input":0.04,"output":0.08,"cache_read":0.008},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"qwen3.6-35b-a3b":{"id":"qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":208192,"input":200000,"output":8192},"cost":{"input":0.045,"output":0.3,"cache_read":0.015},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":229376,"output":32768},"cost":{"input":0.68,"output":1.5,"cache_read":0.18},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":327680,"input":294912,"output":32768},"cost":{"input":0.98,"output":3.08,"cache_read":0.18},"canonical_model_id":"zhipuai/glm-5.3"}}},"poolside":{"id":"poolside","env":["POOLSIDE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://inference.poolside.ai/v1","name":"Poolside","doc":"https://platform.poolside.ai","models":{"poolside/laguna-s-2.1":{"id":"poolside/laguna-s-2.1","name":"Laguna S 2.1","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"poolside/laguna-s-2.1"},"poolside/laguna-xs-2.1":{"id":"poolside/laguna-xs-2.1","name":"Laguna XS 2.1","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-07-02","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"poolside/laguna-xs-2.1"},"poolside/laguna-m.1":{"id":"poolside/laguna-m.1","name":"Laguna M.1","description":"Poolside's open-weight model for agentic coding and long-horizon work","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"poolside/laguna-m.1"}}},"nano-gpt":{"id":"nano-gpt","env":["NANO_GPT_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://nano-gpt.com/api/v1","name":"NanoGPT","doc":"https://docs.nano-gpt.com","models":{"deepseek-reasoner-cheaper":{"id":"deepseek-reasoner-cheaper","name":"Deepseek R1 Cheaper","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"deepseek","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-01-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":0.4,"output":1.7,"cache_read":0.2}},"nano-gpt-help":{"id":"nano-gpt-help","name":"NanoGPT Help","description":"Text-only NanoGPT support assistant. Questions are processed by the Help inference provider; do not paste secrets or account credentials. Covers the website, models, API, pricing, memory, media generation, and support.","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-06-06","last_updated":"2026-06-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":6000,"input":6000,"output":512},"cost":{"input":0,"output":0}},"doubao-seed-2-0-lite-260215":{"id":"doubao-seed-2-0-lite-260215","name":"Doubao Seed 2.0 Lite","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":32000},"cost":{"input":0.1462,"output":0.8738,"cache_read":0.0731}},"doubao-seed-2-0-mini-260215":{"id":"doubao-seed-2-0-mini-260215","name":"Doubao Seed 2.0 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":32000},"cost":{"input":0.0493,"output":0.4845,"cache_read":0.02465}},"fastgpt":{"id":"fastgpt","name":"Web Answer","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-12-23","last_updated":"2024-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"input":32768,"output":32768},"cost":{"input":7.5,"output":7.5}},"doubao-seed-2-0-pro-260215":{"id":"doubao-seed-2-0-pro-260215","name":"Doubao Seed 2.0 Pro","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":128000},"cost":{"input":0.782,"output":3.876,"cache_read":0.391}},"ernie-5.0-thinking-preview":{"id":"ernie-5.0-thinking-preview","name":"Ernie 5.0 Thinking Preview","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"ernie","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":1,"output":3.5,"cache_read":0.5}},"gemini-2.5-flash-lite-preview-09-2025-thinking":{"id":"gemini-2.5-flash-lite-preview-09-2025-thinking","name":"Gemini 2.5 Flash Lite Preview (09/2025) – Thinking","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2025-09-25","last_updated":"2025-09-25","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.01}},"gemma-4-12b-it-station-keeper":{"id":"gemma-4-12b-it-station-keeper","name":"Gemma 4 12B StationKeeper","description":"Gemma 4 12B StationKeeper is an open-weight roleplay finetune with image understanding, tool calling, optional reasoning, and a 131,072-token context window.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-09-09","last_updated":"2026-09-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.05,"output":0.25,"cache_read":0.025}},"glm-4-air-0111":{"id":"glm-4-air-0111","name":"GLM 4 Air 0111","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"glm","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-01-11","last_updated":"2025-01-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":4096},"cost":{"input":0.1394,"output":0.1394,"cache_read":0.0697}},"glm-4.1v-thinking-flashx":{"id":"glm-4.1v-thinking-flashx","name":"GLM 4.1V Thinking FlashX","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"glm-flash","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-07-09","last_updated":"2025-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":64000,"input":64000,"output":8192},"cost":{"input":0.3,"output":0.3,"cache_read":0.15}},"deepseek-v3-0324":{"id":"deepseek-v3-0324","name":"DeepSeek Chat 0324","description":"March 2025 checkpoint of DeepSeek-V3 with improved reasoning and coding","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-03-24","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.2,"output":0.77,"cache_read":0.135},"canonical_model_id":"deepseek/deepseek-v3-0324"},"venice-uncensored":{"id":"venice-uncensored","name":"Venice Uncensored","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"venice","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-10-01","last_updated":"2025-02-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.4,"output":1.8,"cache_read":0.4}},"Gemma-4-31B-MeroMero-v2:thinking":{"id":"Gemma-4-31B-MeroMero-v2:thinking","name":"Gemma 4 31B MeroMero v2 Thinking","description":"Gemma 4 31B MeroMero v2 with thinking enabled for more deliberate emotive dialogue, relationship scenes, creative writing, and multimodal roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-08-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"gemini-2.0-pro-reasoner":{"id":"gemini-2.0-pro-reasoner","name":"Gemini 2.0 Pro Reasoner","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-02-05","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":1.292,"output":4.998,"cache_read":0.323}},"Meta-Llama-3-1-8B-Instruct-FP8":{"id":"Meta-Llama-3-1-8B-Instruct-FP8","name":"Llama 3.1 8B (decentralized)","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":0.02,"output":0.03,"cache_read":0.01}},"glm-4-plus-0111":{"id":"glm-4-plus-0111","name":"GLM 4 Plus 0111","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"glm","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-02-19","last_updated":"2025-02-19","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":4096},"cost":{"input":9.996,"output":9.996,"cache_read":4.998}},"holo3-35b-a3b:thinking":{"id":"holo3-35b-a3b:thinking","name":"Holo3-35B-A3B Thinking","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":8192},"cost":{"input":0.25,"output":1.8,"cache_read":0.125}},"gemma-4-26b-a4b-it-moonlight":{"id":"gemma-4-26b-a4b-it-moonlight","name":"Moonlight Dusk","description":"Moonlight Dusk is a Gemma 4 26B A4B multimodal mixture-of-experts fine-tune for creative writing, expressive dialogue, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.12,"output":0.38,"cache_read":0.06}},"phi-4-mini-instruct":{"id":"phi-4-mini-instruct","name":"Phi 4 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"phi","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-07-26","last_updated":"2025-07-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":0.17,"output":0.68,"cache_read":0.085}},"auto-model-premium":{"id":"auto-model-premium","name":"Auto model (Premium)","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2025-04-16","last_updated":"2024-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":1000000},"cost":{"input":9.996,"output":19.992,"cache_read":4.998}},"gemma-4-31b-it-darkidol":{"id":"gemma-4-31b-it-darkidol","name":"DarkIdol","description":"DarkIdol is a multimodal Gemma 4 31B creative finetune for expressive dialogue, long-form storytelling, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"gemini-2.5-flash-lite-preview-06-17":{"id":"gemini-2.5-flash-lite-preview-06-17","name":"Gemini 2.5 Flash Lite Preview","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.15,"output":0.6,"cache_read":0.015}},"gemini-2.5-flash-preview-09-2025":{"id":"gemini-2.5-flash-preview-09-2025","name":"Gemini 2.5 Flash Preview (09/2025)","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2025-09-25","last_updated":"2025-09-25","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03}},"gemma-4-26b-a4b-it-opusdistill":{"id":"gemma-4-26b-a4b-it-opusdistill","name":"Opus Distill","description":"Opus Distill is a Gemma 4 26B A4B multimodal mixture-of-experts fine-tune for creative writing, expressive dialogue, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.12,"output":0.38,"cache_read":0.06}},"auto-model-standard":{"id":"auto-model-standard","name":"Auto model (Standard)","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2025-04-16","last_updated":"2024-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":1000000},"cost":{"input":9.996,"output":19.992,"cache_read":4.998}},"longcat-2.0":{"id":"longcat-2.0","name":"LongCat 2.0","description":"Meituan LongCat-2.0, a reasoning model with tool calling and a 1M-token context window","family":"longcat","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":131072},"cost":{"input":0.75,"output":3,"cache_read":0.015},"canonical_model_id":"meituan/longcat-2.0"},"gemini-2.5-pro-preview-03-25":{"id":"gemini-2.5-pro-preview-03-25","name":"Gemini 2.5 Pro Preview 0325","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"release_date":"2025-03-25","last_updated":"2025-03-25","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":2.5,"output":10,"cache_read":0.25}},"agnes-3.0-flash":{"id":"agnes-3.0-flash","name":"Agnes 3.0 Flash","description":"Agnes 3.0 Flash is a low-cost model for coding, tool use, and multi-turn agent tasks. It supports text and image input, optional thinking, and a 512K-token context window.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-09-09","last_updated":"2026-09-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"input":524288,"output":65536},"cost":{"input":0.05,"output":0.15,"cache_read":0.005}},"Gemma-4-31B-Queen":{"id":"Gemma-4-31B-Queen","name":"Gemma 4 31B Queen","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-05-01","last_updated":"2026-05-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.306,"output":0.306,"cache_read":0.153}},"auto-model":{"id":"auto-model","name":"Auto model","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2025-04-16","last_updated":"2024-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":1000000},"cost":{"input":0,"output":0}},"qvq-max":{"id":"qvq-max","name":"Qwen: QvQ Max","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-03-28","last_updated":"2025-03-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":1.2,"output":4.8,"cache_read":0.6}},"asi1-mini":{"id":"asi1-mini","name":"ASI1 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-03-25","last_updated":"2025-03-25","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":1,"output":1,"cache_read":0.5}},"gemini-2.5-pro-exp-03-25":{"id":"gemini-2.5-pro-exp-03-25","name":"Gemini 2.5 Pro Experimental 0325","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"release_date":"2025-03-25","last_updated":"2025-03-25","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":2.5,"output":10,"cache_read":0.25}},"gemma-4-31b-it-isometry":{"id":"gemma-4-31b-it-isometry","name":"Isometry","description":"Isometry is a multimodal Gemma 4 31B creative finetune for expressive dialogue, long-form storytelling, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"celeris-1":{"id":"celeris-1","name":"Celeris 1","description":"Celeris 1 is a diffusion language model built for ultra-low-latency classification, extraction, judging, query rewriting, and other short structured responses.","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-07-25","last_updated":"2026-07-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"input":8192,"output":8192},"cost":{"input":2,"output":6,"cache_read":1}},"gemini-3-pro-image-preview":{"id":"gemini-3-pro-image-preview","name":"Gemini 3 Pro Image","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-20","last_updated":"2025-11-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"input":65536,"output":32768},"cost":{"input":2,"output":12,"cache_read":0.2},"canonical_model_id":"google/gemini-3-pro-image-preview"},"gemma-4-26b-a4b-it-darksoul":{"id":"gemma-4-26b-a4b-it-darksoul","name":"Dark Soul","description":"Dark Soul is a Gemma 4 26B A4B multimodal mixture-of-experts fine-tune for creative writing, expressive dialogue, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.12,"output":0.38,"cache_read":0.06}},"glm-4.1v-thinking-flash":{"id":"glm-4.1v-thinking-flash","name":"GLM 4.1V Thinking Flash","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"glm-flash","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-07-09","last_updated":"2025-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":64000,"input":64000,"output":8192},"cost":{"input":0.3,"output":0.3,"cache_read":0.15}},"Gemma-4-31B-GarnetV2":{"id":"Gemma-4-31B-GarnetV2","name":"Gemma 4 31B Garnet V2","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-05-01","last_updated":"2026-05-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.306,"output":0.306,"cache_read":0.153}},"gemini-2.5-flash-nothinking":{"id":"gemini-2.5-flash-nothinking","name":"Gemini 2.5 Flash (No Thinking)","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03}},"Gemma-4-31B-MeroMero-v2":{"id":"Gemma-4-31B-MeroMero-v2","name":"Gemma 4 31B MeroMero v2","description":"Gemma 4 31B MeroMero v2 is a LoRA finetune for emotive dialogue, relationship scenes, creative writing, and multimodal roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-08-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"holo3-35b-a3b":{"id":"holo3-35b-a3b","name":"Holo3-35B-A3B","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":8192},"cost":{"input":0.25,"output":1.8,"cache_read":0.125}},"claw-medium":{"id":"claw-medium","name":"Claw Medium","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-11","last_updated":"2026-05-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.6,"output":1.1,"cache_read":0.2}},"gemma-4-26b-a4b-it-shadowsiren":{"id":"gemma-4-26b-a4b-it-shadowsiren","name":"Shadow Siren","description":"Shadow Siren is a Gemma 4 26B A4B multimodal mixture-of-experts fine-tune for creative writing, expressive dialogue, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.12,"output":0.38,"cache_read":0.06}},"gemini-2.0-pro-exp-02-05":{"id":"gemini-2.0-pro-exp-02-05","name":"Gemini 2.0 Pro 0205","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-02-05","last_updated":"2025-02-05","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":2097152,"input":2097152,"output":8192},"cost":{"input":1.989,"output":7.956,"cache_read":0.49725}},"claw-high":{"id":"claw-high","name":"Claw High","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-11","last_updated":"2026-05-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.6,"output":1.1,"cache_read":0.2}},"deepseek-chat":{"id":"deepseek-chat","name":"DeepSeek V3/Deepseek Chat","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-12-01","last_updated":"2026-02-28","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.1,"output":0.425,"cache_read":0.05},"canonical_model_id":"deepseek/deepseek-chat"},"Gemma-4-26B-A4B-MeroMero:thinking":{"id":"Gemma-4-26B-A4B-MeroMero:thinking","name":"Gemma 4 26B A4B MeroMero Thinking","description":"Gemma 4 26B A4B MeroMero with thinking enabled for more deliberate emotive dialogue, relationship scenes, creative writing, and multimodal roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.12,"output":0.38,"cache_read":0.06}},"claw-low":{"id":"claw-low","name":"Claw Low","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-11","last_updated":"2026-05-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.6,"output":1.1,"cache_read":0.2,"cache_write":0.08333}},"doubao-1.5-pro-32k":{"id":"doubao-1.5-pro-32k","name":"Doubao 1.5 Pro 32k","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-11-20","last_updated":"2025-01-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"input":32000,"output":8192},"cost":{"input":0.1343,"output":0.3349,"cache_read":0.06715}},"doubao-seed-2-0-code-preview-260215":{"id":"doubao-seed-2-0-code-preview-260215","name":"Doubao Seed 2.0 Code Preview","description":"ByteDance Seed coding model for multimodal software engineering and long-running agents","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":128000},"cost":{"input":0.782,"output":3.893,"cache_read":0.391},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"hermes-low":{"id":"hermes-low","name":"Hermes Low","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"hermes","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-11","last_updated":"2026-05-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.6,"output":1.1,"cache_read":0.2,"cache_write":0.08333}},"gemma-4-31b-it-gemsicle":{"id":"gemma-4-31b-it-gemsicle","name":"Gemsicle","description":"Gemsicle is a multimodal Gemma 4 31B creative finetune for expressive dialogue, long-form storytelling, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"mercury-coder-small":{"id":"mercury-coder-small","name":"Mercury Coder Small","description":"Model by Inception AI. A diffusion large language model that runs incredibly quickly (500+ tokens/second) while matching Claude 3.5 Haiku and GPT-4o-mini. 1st in speed on Copilot arena, and matching 2nd in quality.","family":"mercury","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":0.25,"output":1,"cache_read":0.125}},"gemini-2.5-pro":{"id":"gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125,"cache_write":0.375},"canonical_model_id":"google/gemini-2.5-pro"},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-2.5-flash"},"hermes-high":{"id":"hermes-high","name":"Hermes High","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"hermes","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-11","last_updated":"2026-05-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.6,"output":1.1,"cache_read":0.2}},"gemini-2.5-flash-preview-05-20":{"id":"gemini-2.5-flash-preview-05-20","name":"Gemini 2.5 Flash 0520","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048000,"input":1048000,"output":65536},"cost":{"input":0.15,"output":0.6,"cache_read":0.015}},"glm-4-long":{"id":"glm-4-long","name":"GLM-4 Long","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"glm","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-08-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":4095},"cost":{"input":0.2006,"output":0.2006,"cache_read":0.1003}},"pokee-isaac":{"id":"pokee-isaac","name":"Pokee-Isaac 28B","description":"Pokee-Isaac is a 28B agentic model with a roughly 10-million-token context window, function calling, and OpenAI-compatible structured output. Pokee bills in $0.01 increments, rounding each non-zero request up to the next cent.","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-08-04","last_updated":"2026-08-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":10000000,"input":10000000,"output":60000},"cost":{"input":0.15,"output":1,"cache_read":0.075}},"MiniMax-M1":{"id":"MiniMax-M1","name":"MiniMax M1","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"minimax","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-01-08","last_updated":"2025-06-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":131072},"cost":{"input":0.1394,"output":1.3328,"cache_read":0.0697}},"Gemma-4-31B-Claude-4.6-Opus-Reasoning-Distilled":{"id":"Gemma-4-31B-Claude-4.6-Opus-Reasoning-Distilled","name":"Gemma 4 31B Claude 4.6 Opus Reasoning Distilled","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"claude","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-05-01","last_updated":"2026-05-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.306,"output":0.306,"cache_read":0.0306}},"Qwen3.5-27B-BlueStar-v3-Derestricted":{"id":"Qwen3.5-27B-BlueStar-v3-Derestricted","name":"Qwen3.5 27B BlueStar v3 Derestricted","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"qwen3.5","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.306,"output":0.306,"cache_read":0.153}},"gemma-4-31b-it-novelist":{"id":"gemma-4-31b-it-novelist","name":"Novelist","description":"Novelist is a multimodal Gemma 4 31B creative finetune for expressive dialogue, long-form storytelling, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"ernie-5.1:thinking":{"id":"ernie-5.1:thinking","name":"ERNIE 5.1 Thinking","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"ernie","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"release_date":"2026-05-10","last_updated":"2026-05-10","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":119000,"input":119000,"output":64000},"cost":{"input":0.75,"output":3,"cache_read":0.75}},"gemma-4-12b-it-semancer":{"id":"gemma-4-12b-it-semancer","name":"Gemma 4 12B Semancer","description":"Gemma 4 12B Semancer is an open-weight roleplay finetune with image understanding, tool calling, optional reasoning, and a 131,072-token context window.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-09-09","last_updated":"2026-09-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.05,"output":0.25,"cache_read":0.025}},"mistral-code-latest":{"id":"mistral-code-latest","name":"Mistral Code Latest","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"mistral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":32768},"cost":{"input":0.3,"output":0.9,"cache_read":0.15}},"Qwen3.5-27B-Queen-Derestricted":{"id":"Qwen3.5-27B-Queen-Derestricted","name":"Qwen3.5 27B Queen Derestricted","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"qwen3.5","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.306,"output":0.306,"cache_read":0.153}},"gemma-4-31b-it-fabled":{"id":"gemma-4-31b-it-fabled","name":"Fabled","description":"Fabled is a multimodal Gemma 4 31B creative finetune for expressive dialogue, long-form storytelling, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"gemma-4-26b-a4b-it-chimeraxheretic":{"id":"gemma-4-26b-a4b-it-chimeraxheretic","name":"Gemma 4 26B A4B Chimera X Heretic","description":"Chimera X Heretic is a Gemma 4 26B A4B multimodal mixture-of-experts fine-tune for creative writing, expressive dialogue, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-10-08","last_updated":"2026-10-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.12,"output":0.38,"cache_read":0.06}},"Gemma-4-26B-A4B-MeroMero":{"id":"Gemma-4-26B-A4B-MeroMero","name":"Gemma 4 26B A4B MeroMero","description":"Gemma 4 26B A4B MeroMero is an NVFP4 multimodal mixture-of-experts fine-tune for emotive dialogue, relationship scenes, creative writing, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.12,"output":0.38,"cache_read":0.06}},"Gemma-4-31B-Cognitive-Unshackled":{"id":"Gemma-4-31B-Cognitive-Unshackled","name":"Gemma 4 31B Cognitive Unshackled","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-05-01","last_updated":"2026-05-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.306,"output":0.306,"cache_read":0.153}},"universal-summarizer":{"id":"universal-summarizer","name":"Universal Summarizer","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-12-23","last_updated":"2024-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"input":32768,"output":32768},"cost":{"input":30,"output":30}},"gemma-4-12b-it":{"id":"gemma-4-12b-it","name":"Gemma 4 12B Instruct","description":"Compact Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.05,"output":0.25,"cache_read":0.025},"canonical_model_id":"google/gemma-4-12b-it"},"gemini-exp-1206":{"id":"gemini-exp-1206","name":"Gemini 2.0 Pro 1206","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":2097152,"input":2097152,"output":8192},"cost":{"input":1.258,"output":4.998,"cache_read":0.629}},"gemini-2.5-flash-preview-09-2025-thinking":{"id":"gemini-2.5-flash-preview-09-2025-thinking","name":"Gemini 2.5 Flash Preview (09/2025) – Thinking","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2025-09-25","last_updated":"2025-09-25","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03}},"doubao-1.5-pro-256k":{"id":"doubao-1.5-pro-256k","name":"Doubao 1.5 Pro 256k","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":16384},"cost":{"input":0.799,"output":1.445,"cache_read":0.3995}},"gemma-4-31b-it-garnet":{"id":"gemma-4-31b-it-garnet","name":"Garnet","description":"Garnet is a multimodal Gemma 4 31B creative finetune for expressive dialogue, long-form storytelling, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"gemini-2.5-pro-preview-05-06":{"id":"gemini-2.5-pro-preview-05-06","name":"Gemini 2.5 Pro Preview 0506","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"release_date":"2025-05-06","last_updated":"2025-05-06","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":2.5,"output":10,"cache_read":0.25}},"mercury-2":{"id":"mercury-2","name":"Mercury 2","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-04","last_updated":"2026-03-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":50000},"cost":{"input":0.25,"output":0.75,"cache_read":0.025},"canonical_model_id":"inception/mercury-2"},"command-a-reasoning-08-2025":{"id":"command-a-reasoning-08-2025","name":"Cohere Command A (08/2025)","description":"Cohere reasoning model for multilingual enterprise agents, tools, and complex workflows","family":"command-a","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-06-01","release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":8192},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"cohere/command-a-reasoning-08-2025"},"longcat-2.0:thinking":{"id":"longcat-2.0:thinking","name":"LongCat 2.0 Thinking","description":"Meituan LongCat-2.0, a reasoning model with tool calling and a 1M-token context window","family":"longcat","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":131072},"cost":{"input":0.75,"output":3,"cache_read":0.015},"canonical_model_id":"meituan/longcat-2.0"},"deepseek-r1-sambanova":{"id":"deepseek-r1-sambanova","name":"DeepSeek R1 Fast","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"deepseek","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-02-20","last_updated":"2025-02-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":4096},"cost":{"input":4.998,"output":6.987,"cache_read":2.499}},"gemini-2.5-flash-preview-04-17":{"id":"gemini-2.5-flash-preview-04-17","name":"Gemini 2.5 Flash Preview","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"release_date":"2025-04-17","last_updated":"2025-04-17","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.15,"output":0.6,"cache_read":0.015}},"deepseek-reasoner":{"id":"deepseek-reasoner","name":"DeepSeek Reasoner","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-09","release_date":"2025-12-01","last_updated":"2026-02-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"input":64000,"output":65536},"cost":{"input":0.4,"output":1.7,"cache_read":0.2},"canonical_model_id":"deepseek/deepseek-reasoner"},"gemini-2.5-flash-lite-preview-09-2025":{"id":"gemini-2.5-flash-lite-preview-09-2025","name":"Gemini 2.5 Flash Lite Preview (09/2025)","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2025-09-25","last_updated":"2025-09-25","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.01}},"gemini-2.5-flash-preview-04-17:thinking":{"id":"gemini-2.5-flash-preview-04-17:thinking","name":"Gemini 2.5 Flash Preview Thinking","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"release_date":"2025-04-17","last_updated":"2025-04-17","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.15,"output":3.5,"cache_read":0.015}},"deepseek-r1":{"id":"deepseek-r1","name":"DeepSeek R1","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.4,"output":1.7,"cache_read":0.2},"canonical_model_id":"deepseek/deepseek-r1"},"gemini-2.5-pro-preview-06-05":{"id":"gemini-2.5-pro-preview-06-05","name":"Gemini 2.5 Pro Preview 0605","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":2.5,"output":10,"cache_read":0.25}},"gemini-2.5-flash-lite":{"id":"gemini-2.5-flash-lite","name":"Gemini 2.5 Flash Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.01},"canonical_model_id":"google/gemini-2.5-flash-lite"},"deepseek-chat-cheaper":{"id":"deepseek-chat-cheaper","name":"DeepSeek V3/Chat Cheaper","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"deepseek","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2025-04-15","last_updated":"2025-04-15","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.1,"output":0.425,"cache_read":0.05}},"gemma-4-31b-it-scarlet":{"id":"gemma-4-31b-it-scarlet","name":"Gemma 4 31B Scarlet","description":"Scarlet is a multimodal Gemma 4 31B creative finetune for expressive dialogue, long-form storytelling, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-10-08","last_updated":"2026-10-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"GLM-4.6-Derestricted-v5":{"id":"GLM-4.6-Derestricted-v5","name":"GLM 4.6 Derestricted v5","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":8192},"cost":{"input":0.4,"output":1.5,"cache_read":0.2}},"longcat-2.5-preview":{"id":"longcat-2.5-preview","name":"LongCat 2.5 Preview","description":"Meituan's multimodal reasoning model for coding and agent tasks, with image understanding and a 1M-token context window","family":"longcat","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-25","last_updated":"2026-09-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":131072},"cost":{"input":0.75,"output":2.95,"cache_read":0.015},"canonical_model_id":"meituan/longcat-2.5-preview"},"doubao-1.5-vision-pro-32k":{"id":"doubao-1.5-vision-pro-32k","name":"Doubao 1.5 Vision Pro 32k","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-11-20","last_updated":"2025-01-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"input":32000,"output":8192},"cost":{"input":0.459,"output":1.377,"cache_read":0.2295}},"glm-z1-airx":{"id":"glm-z1-airx","name":"GLM Z1 AirX","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"glm","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2025-04-15","last_updated":"2025-04-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"input":32000,"output":16384},"cost":{"input":0.7,"output":0.7,"cache_read":0.35}},"auto-model-basic":{"id":"auto-model-basic","name":"Auto model (Basic)","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2025-04-16","last_updated":"2024-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":1000000},"cost":{"input":9.996,"output":19.992,"cache_read":4.998}},"qwen3-vl-235b-a22b-instruct-original":{"id":"qwen3-vl-235b-a22b-instruct-original","name":"Qwen3 VL 235B A22B Instruct Original","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-09-25","last_updated":"2025-09-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"input":32768,"output":32768},"cost":{"input":0.3,"output":1.9,"cache_read":0.15}},"gemma-4-26b-a4b-it-luminous":{"id":"gemma-4-26b-a4b-it-luminous","name":"Luminous Mirror","description":"Luminous Mirror is a Gemma 4 26B A4B multimodal mixture-of-experts fine-tune for creative writing, expressive dialogue, and roleplay.","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.12,"output":0.38,"cache_read":0.06}},"sarvam-105b":{"id":"sarvam-105b","name":"Sarvam 105B","description":"Flagship Indian-language reasoning model for enterprise multilingual applications","family":"sarvam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":4096},"cost":{"input":0.054,"output":0.2124,"cache_read":0.0336},"canonical_model_id":"sarvam/sarvam-105b"},"gemma-4-31b-it-gembrain":{"id":"gemma-4-31b-it-gembrain","name":"Gembrain","description":"Gembrain is a multimodal Gemma 4 31B creative finetune for expressive dialogue, long-form storytelling, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"phi-4-multimodal-instruct":{"id":"phi-4-multimodal-instruct","name":"Phi 4 Multimodal","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"phi","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-07-26","last_updated":"2025-07-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":0.07,"output":0.11,"cache_read":0.035}},"gemini-2.5-flash-preview-05-20:thinking":{"id":"gemini-2.5-flash-preview-05-20:thinking","name":"Gemini 2.5 Flash 0520 Thinking","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048000,"input":1048000,"output":65536},"cost":{"input":0.15,"output":3.5,"cache_read":0.015}},"gemma-4-26b-a4b-it-musica":{"id":"gemma-4-26b-a4b-it-musica","name":"Musica","description":"Musica is a Gemma 4 26B A4B multimodal mixture-of-experts fine-tune for creative writing, expressive dialogue, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.12,"output":0.38,"cache_read":0.06}},"gemma-4-26b-a4b-it-chimerax":{"id":"gemma-4-26b-a4b-it-chimerax","name":"Chimera X","description":"Chimera X is a Gemma 4 26B A4B multimodal mixture-of-experts fine-tune for creative writing, expressive dialogue, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.12,"output":0.38,"cache_read":0.06}},"hermes-medium":{"id":"hermes-medium","name":"Hermes Medium","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"hermes","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-11","last_updated":"2026-05-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.6,"output":1.1,"cache_read":0.2}},"Gemma-4-31B-DarkIdol":{"id":"Gemma-4-31B-DarkIdol","name":"Gemma 4 31B DarkIdol","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-05-01","last_updated":"2026-05-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.306,"output":0.306,"cache_read":0.153}},"ernie-5.1":{"id":"ernie-5.1","name":"ERNIE 5.1","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"ernie","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-05-10","last_updated":"2026-05-10","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":119000,"input":119000,"output":64000},"cost":{"input":0.75,"output":3,"cache_read":0.75}},"mistral-code-agent-latest":{"id":"mistral-code-agent-latest","name":"Mistral Code Agent Latest","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"mistral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.4,"output":2,"cache_read":0.2}},"kimi-k2-instruct-fast":{"id":"kimi-k2-instruct-fast","name":"Kimi K2 0711 Fast","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"kimi-k2","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-12-15","last_updated":"2025-07-15","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":16384},"cost":{"input":0.4,"output":1.8,"cache_read":0.2}},"featherless-ai/Qwerky-72B":{"id":"featherless-ai/Qwerky-72B","name":"Qwerky 72B","description":"General-purpose chat model for instruction following, writing, and analysis","family":"qwerky","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-03-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"input":32000,"output":8192},"cost":{"input":0.5,"output":0.5,"cache_read":0.25}},"reka/reka-edge-2603":{"id":"reka/reka-edge-2603","name":"Reka Edge 2603","description":"Reka's compact multimodal model for visual understanding and tool use, served directly by Reka.","family":"reka","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"input":16384,"output":16384},"cost":{"input":0.105,"output":0.105}},"reka/reka-flash-3":{"id":"reka/reka-flash-3","name":"Reka Flash 3","description":"Reka's 21B reasoning model for chat and coding, served directly by Reka.","family":"reka","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":65536},"cost":{"input":0.105,"output":0.21}},"unsloth/gemma-3-27b-it":{"id":"unsloth/gemma-3-27b-it","name":"Gemma 3 27B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"unsloth","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-03-10","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":96000},"cost":{"input":0.2992,"output":0.2992,"cache_read":0.1496}},"unsloth/gemma-3-12b-it":{"id":"unsloth/gemma-3-12b-it","name":"Gemma 3 12B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"unsloth","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-03-10","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":16384},"cost":{"input":0.272,"output":0.272,"cache_read":0.136}},"unsloth/gemma-3-4b-it":{"id":"unsloth/gemma-3-4b-it","name":"Gemma 3 4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"unsloth","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-03-10","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.2006,"output":0.2006,"cache_read":0.1003}},"bytedance-seed/seed-2.0-lite":{"id":"bytedance-seed/seed-2.0-lite","name":"ByteDance Seed 2.0 Lite","description":"Cost-efficient ByteDance Seed 2.0 model for production chat, analysis, and structured generation","family":"seed","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"input":262144,"output":131072},"cost":{"input":0.25,"output":2,"cache_read":0.125},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"bytedance-seed/seed-2-1-turbo":{"id":"bytedance-seed/seed-2-1-turbo","name":"ByteDance Seed 2.1 Turbo","description":"ByteDance Seed 2.1 Turbo is a multimodal model for coding and long-horizon agent workflows, including end-to-end software delivery and multi-step task execution. It supports text, image, and video input with a 262k context window.","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"input":262144,"output":235929},"cost":{"input":0.5,"output":2.5,"cache_read":0.25}},"bytedance-seed/seed-2.0-code":{"id":"bytedance-seed/seed-2.0-code","name":"ByteDance Seed 2.0 Code","description":"ByteDance Seed coding model for multimodal software engineering and long-running agents","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"input":262144,"output":131072},"cost":{"input":0.5,"output":3,"cache_read":0.25},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"poolside/laguna-s-2.1:thinking":{"id":"poolside/laguna-s-2.1:thinking","name":"Laguna S 2.1 Thinking","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.1,"output":0.2,"cache_read":0.01},"canonical_model_id":"poolside/laguna-s-2.1"},"poolside/laguna-s-2.1":{"id":"poolside/laguna-s-2.1","name":"Laguna S 2.1","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.1,"output":0.2,"cache_read":0.01},"canonical_model_id":"poolside/laguna-s-2.1"},"abliteration-ai/abliterated-model-large-v2":{"id":"abliteration-ai/abliterated-model-large-v2","name":"Abliterated Model Large V2","description":"Abliteration.ai's default large text reasoning model is derived from GLM-5.3 for harder reasoning and evaluation workloads, with automatic prompt caching and a one-million-token context window.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-31","last_updated":"2026-08-31","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":999990},"cost":{"input":3,"output":5,"cache_read":0.3}},"abliteration-ai/abliterated-model":{"id":"abliteration-ai/abliterated-model","name":"Abliterated Model","description":"Abliteration.ai's multimodal reasoning model supports text and image input, structured output, automatic prompt caching, and a 262K-token context window.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":false,"structured_output":true,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"input":262144,"output":262134},"cost":{"input":1,"output":3,"cache_read":0.1}},"abliteration-ai/abliterated-model-large":{"id":"abliteration-ai/abliterated-model-large","name":"Abliterated Model Large","description":"Abliteration.ai's large text reasoning model is derived from GLM-5.2 and supports native tool calling, structured output, automatic prompt caching, and a one-million-token context window.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":999990},"cost":{"input":3,"output":5,"cache_read":0.3}},"prism-ml/ternary-bonsai-2-27b":{"id":"prism-ml/ternary-bonsai-2-27b","name":"Ternary Bonsai 2 27B","description":"Ternary Bonsai 2 27B is a 27B-parameter reasoning model from PrismML derived from Qwen3.8-27B. It supports coding, mathematics, tool calling, and image understanding with a 262K-token context window.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","xhigh"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-18","last_updated":"2026-09-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.075,"output":0.5,"cache_read":0.0375}},"anthropic/claude-opus-4.5:thinking":{"id":"anthropic/claude-opus-4.5:thinking","name":"Claude 4.5 Opus Thinking","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-sonnet-4.5:thinking":{"id":"anthropic/claude-sonnet-4.5:thinking","name":"Claude Sonnet 4.5 Thinking","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-opus-4.6:thinking:low":{"id":"anthropic/claude-opus-4.6:thinking:low","name":"Claude 4.6 Opus Thinking Low","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-opus-4.1":{"id":"anthropic/claude-opus-4.1","name":"Claude 4.1 Opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5},"canonical_model_id":"anthropic/claude-opus-4-1"},"anthropic/claude-opus-4.5":{"id":"anthropic/claude-opus-4.5","name":"Claude 4.5 Opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-opus-4.6":{"id":"anthropic/claude-opus-4.6","name":"Claude 4.6 Opus","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude 4.7 Opus","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic/claude-sonnet-4:thinking:64000":{"id":"anthropic/claude-sonnet-4:thinking:64000","name":"Claude 4 Sonnet Thinking (64K)","description":"Claude 4 Sonnet with maximum thinking budget (64,000 tokens).","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3}},"anthropic/claude-haiku-5.5":{"id":"anthropic/claude-haiku-5.5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-opus-latest":{"id":"anthropic/claude-opus-latest","name":"Claude Opus Latest","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-03-29","last_updated":"2026-03-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5}},"anthropic/claude-opus-4.1:thinking:1024":{"id":"anthropic/claude-opus-4.1:thinking:1024","name":"Claude 4.1 Opus Thinking (1K)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5},"canonical_model_id":"anthropic/claude-opus-4-1"},"anthropic/claude-haiku-latest":{"id":"anthropic/claude-haiku-latest","name":"Claude Haiku Latest","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-03-29","last_updated":"2026-03-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125}},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-sonnet-5.5:thinking":{"id":"anthropic/claude-sonnet-5.5:thinking","name":"Claude Sonnet 5.5 Thinking","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-sonnet-4:thinking:8192":{"id":"anthropic/claude-sonnet-4:thinking:8192","name":"Claude 4 Sonnet Thinking (8K)","description":"Claude 4 Sonnet with reduced thinking budget (8,192 tokens).","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3}},"anthropic/claude-sonnet-4:thinking:1024":{"id":"anthropic/claude-sonnet-4:thinking:1024","name":"Claude 4 Sonnet Thinking (1K)","description":"Claude 4 Sonnet with minimal thinking budget (1,024 tokens).","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3}},"anthropic/claude-opus-4.6:thinking":{"id":"anthropic/claude-opus-4.6:thinking","name":"Claude 4.6 Opus Thinking","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-sonnet-latest":{"id":"anthropic/claude-sonnet-latest","name":"Claude Sonnet Latest","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-03-01","last_updated":"2026-03-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5}},"anthropic/claude-opus-4.6:thinking:medium":{"id":"anthropic/claude-opus-4.6:thinking:medium","name":"Claude 4.6 Opus Thinking Medium","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-haiku-4.5":{"id":"anthropic/claude-haiku-4.5","name":"Claude Haiku 4.5","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-fable-latest":{"id":"anthropic/claude-fable-latest","name":"Claude Fable Latest","description":"Compatibility alias for Claude Fable.","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5}},"anthropic/claude-sonnet-5.5":{"id":"anthropic/claude-sonnet-5.5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-sonnet-4:thinking:32768":{"id":"anthropic/claude-sonnet-4:thinking:32768","name":"Claude 4 Sonnet Thinking (32K)","description":"Claude 4 Sonnet with extended thinking budget (32,768 tokens).","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3}},"anthropic/claude-fable-5.1":{"id":"anthropic/claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-sonnet-4.5":{"id":"anthropic/claude-sonnet-4.5","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-opus-4.1:thinking:8192":{"id":"anthropic/claude-opus-4.1:thinking:8192","name":"Claude 4.1 Opus Thinking (8K)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5},"canonical_model_id":"anthropic/claude-opus-4-1"},"anthropic/claude-haiku-4.5:thinking":{"id":"anthropic/claude-haiku-4.5:thinking","name":"Claude Haiku 4.5 Thinking","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-opus-4.8:thinking":{"id":"anthropic/claude-opus-4.8:thinking","name":"Claude Opus 4.8 Thinking","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-sonnet-4":{"id":"anthropic/claude-sonnet-4","name":"Claude 4 Sonnet","description":"Claude 4 Sonnet by Anthropic. A new generation model with improved capabilities, especially on programming and development. NOTE: Inputs > 200k tokens are charged at 2x input, 1.5x output rate.","family":"claude-sonnet","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3}},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-sonnet-4.6:thinking":{"id":"anthropic/claude-sonnet-4.6:thinking","name":"Claude Sonnet 4.6 Thinking","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-4.6:thinking:max":{"id":"anthropic/claude-opus-4.6:thinking:max","name":"Claude 4.6 Opus Thinking Max","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-sonnet-5:thinking":{"id":"anthropic/claude-sonnet-5:thinking","name":"Claude Sonnet 5 Thinking","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-4.7:thinking":{"id":"anthropic/claude-opus-4.7:thinking","name":"Claude 4.7 Opus Thinking","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic/claude-opus-5.5":{"id":"anthropic/claude-opus-5.5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-opus-4.1:thinking":{"id":"anthropic/claude-opus-4.1:thinking","name":"Claude 4.1 Opus Thinking","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5},"canonical_model_id":"anthropic/claude-opus-4-1"},"anthropic/claude-sonnet-4:thinking":{"id":"anthropic/claude-sonnet-4:thinking","name":"Claude 4 Sonnet Thinking","description":"Anthropic's Claude 4 Sonnet with the ability to show its thinking process step by step.","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2025-02-24","last_updated":"2025-02-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3}},"anthropic/claude-opus-4.1:thinking:32768":{"id":"anthropic/claude-opus-4.1:thinking:32768","name":"Claude 4.1 Opus Thinking (32K)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5},"canonical_model_id":"anthropic/claude-opus-4-1"},"cohere/command-r-plus-08-2024":{"id":"cohere/command-r-plus-08-2024","name":"Cohere: Command R+","description":"Cohere's RAG workhorse for long-context enterprise search and tool use","family":"command-r","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":4096},"cost":{"input":2.856,"output":14.246,"cache_read":1.428},"canonical_model_id":"cohere/command-r-plus-08-2024"},"deepseek/deepseek-v4-flash:thinking":{"id":"deepseek/deepseek-v4-flash:thinking","name":"DeepSeek V4 Flash (Thinking)","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.05,"output":0.16,"cache_read":0.013},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v4-flash-0423":{"id":"deepseek/deepseek-v4-flash-0423","name":"DeepSeek V4 Flash 0423","description":"Initial DeepSeek V4 Flash snapshot for economical reasoning, coding, and million-token agent workloads","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0423"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":384000},"cost":{"input":0.13,"output":0.52,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4.1-flash:thinking":{"id":"deepseek/deepseek-v4.1-flash:thinking","name":"DeepSeek V4.1 Flash Thinking","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":384000},"cost":{"input":0.13,"output":0.52,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-flash-vision-exp":{"id":"deepseek/deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":0.22,"output":0.66,"cache_read":0.007},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"deepseek/deepseek-v3.2:thinking":{"id":"deepseek/deepseek-v3.2:thinking","name":"DeepSeek V3.2 Thinking","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":163000,"input":163000,"output":65536},"cost":{"input":0.2088,"output":0.3096,"cache_read":0.0216},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepseek/deepseek-latest":{"id":"deepseek/deepseek-latest","name":"DeepSeek Latest","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-03","last_updated":"2026-05-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":1.1,"output":2.5,"cache_read":0.04}},"deepseek/deepseek-v4-flash-0423:thinking":{"id":"deepseek/deepseek-v4-flash-0423:thinking","name":"DeepSeek V4 Flash 0423 (Thinking)","description":"Initial DeepSeek V4 Flash snapshot for economical reasoning, coding, and million-token agent workloads","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0423"},"deepseek/deepseek-v4-pro:thinking":{"id":"deepseek/deepseek-v4-pro:thinking","name":"DeepSeek V4 Pro (Thinking)","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":1.1,"output":2.2,"cache_read":0.11},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v4-pro-0813:thinking":{"id":"deepseek/deepseek-v4-pro-0813:thinking","name":"DeepSeek V4 Pro 0813 Thinking","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":1.1,"output":2.5,"cache_read":0.04},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":1.1,"output":2.5,"cache_read":0.04},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek/deepseek-v4-flash-0731:thinking":{"id":"deepseek/deepseek-v4-flash-0731:thinking","name":"DeepSeek V4 Flash 0731 (Thinking)","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.05,"output":0.16,"cache_read":0.013},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":1.1,"output":2.2,"cache_read":0.11},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v4-flash-latest":{"id":"deepseek/deepseek-v4-flash-latest","name":"DeepSeek V4 Flash Latest","description":"Compatibility alias that routes to the newest dated DeepSeek V4 Flash release. Currently routes to DeepSeek V4 Flash 0731. ⚠️ This route goes directly to DeepSeek, so privacy and logging guarantees are limited.","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-02","last_updated":"2026-08-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":131072},"cost":{"input":0.05,"output":0.16,"cache_read":0.013}},"deepseek/deepseek-v3.2":{"id":"deepseek/deepseek-v3.2","name":"DeepSeek V3.2","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":163000,"input":163000,"output":65536},"cost":{"input":0.2088,"output":0.3096,"cache_read":0.0216},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"baseten/Kimi-K2-Instruct-FP4":{"id":"baseten/Kimi-K2-Instruct-FP4","name":"Kimi K2 0711 Instruct FP4","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":131072},"cost":{"input":0.4,"output":1.8,"cache_read":0.2}},"unbiased/pareto-26.10-preview":{"id":"unbiased/pareto-26.10-preview","name":"Pareto 26.10 Preview","description":"Pareto 26.10 Preview is Unbiased AI's multimodal composite model for research, coding, and agentic workflows. It accepts text and images, supports tool calling, and provides a 1M-token context window with up to 131K output tokens.","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2026-10-01","last_updated":"2026-10-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.8,"output":3.2,"cache_read":0.03}},"unbiased/pareto-26.9":{"id":"unbiased/pareto-26.9","name":"Pareto 26.9","description":"Pareto 26.9 is an experimental multimodal composite model from Unbiased AI for research, coding, agentic workflows, and general-purpose tasks. It runs several frontier and open models for each request and returns a single selected or synthesized answer. This experimental release supports text and image input, tool calling, a 262K-token context window, and up to 131K output tokens. Its underlying model mix and behavior may change as it is evaluated. Request content may be retained for abuse prevention and security monitoring for up to 30 days, and is not used for model training without explicit consent.","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2026-09-18","last_updated":"2026-09-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"input":262144,"output":131072},"cost":{"input":2.5,"output":7.5,"cache_read":0.25}},"lightonai/LightOnOCR-2-1B":{"id":"lightonai/LightOnOCR-2-1B","name":"LightOnOCR 2","description":"LightOnOCR 2 hosted by IONOS in Berlin, Germany. Zero data retention.","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":8192},"cost":{"input":0.1785,"output":0.3465}},"abacusai/Dracarys-72B-Instruct":{"id":"abacusai/Dracarys-72B-Instruct","name":"Llama 3.1 70B Dracarys 2","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-08-02","last_updated":"2025-08-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":8192},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"shisa-ai/shisa-v2.1-llama3.3-70b":{"id":"shisa-ai/shisa-v2.1-llama3.3-70b","name":"Shisa V2.1 Llama 3.3 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":4096},"cost":{"input":0.5,"output":0.5,"cache_read":0.25}},"shisa-ai/shisa-v2-llama3.3-70b":{"id":"shisa-ai/shisa-v2-llama3.3-70b","name":"Shisa V2 Llama 3.3 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-07-26","last_updated":"2025-07-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":0.5,"output":0.5,"cache_read":0.25}},"Steelskull/L3.3-MS-Nevoria-70b":{"id":"Steelskull/L3.3-MS-Nevoria-70b","name":"Steelskull Nevoria 70b","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"Steelskull/L3.3-Cu-Mai-R1-70b":{"id":"Steelskull/L3.3-Cu-Mai-R1-70b","name":"Llama 3.3 70B Cu Mai","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"Steelskull/L3.3-Nevoria-R1-70b":{"id":"Steelskull/L3.3-Nevoria-R1-70b","name":"Steelskull Nevoria R1 70b","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"Steelskull/L3.3-Electra-R1-70b":{"id":"Steelskull/L3.3-Electra-R1-70b","name":"Steelskull Electra R1 70b","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":0.69989,"output":0.69989,"cache_read":0.349945}},"tencent/hy3":{"id":"tencent/hy3","name":"Tencent Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":128000},"cost":{"input":0.066,"output":0.26,"cache_read":0.029},"canonical_model_id":"tencent/hy3"},"tencent/hy4-preview":{"id":"tencent/hy4-preview","name":"Tencent Hy4 Preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":64000},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"},"anthracite-org/magnum-v4-72b":{"id":"anthracite-org/magnum-v4-72b","name":"Magnum v4 72B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-06-30","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":2.006,"output":2.992,"cache_read":1.003},"canonical_model_id":"anthracite-org/magnum-v4-72b"},"anthracite-org/magnum-v2-72b":{"id":"anthracite-org/magnum-v2-72b","name":"Magnum V2 72B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":2.006,"output":2.992,"cache_read":1.003}},"meta-llama/llama-4-scout":{"id":"meta-llama/llama-4-scout","name":"Llama 4 Scout","description":"Open multimodal Llama model for long-context analysis and efficient agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":328000,"input":328000,"output":65536},"cost":{"input":0.085,"output":0.46,"cache_read":0.0425}},"meta-llama/llama-4-maverick":{"id":"meta-llama/llama-4-maverick","name":"Llama 4 Maverick","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.1875,"output":0.6525,"cache_read":0.05}},"meta-llama/llama-3.3-70b-instruct":{"id":"meta-llama/llama-3.3-70b-instruct","name":"Llama 3.3 70b Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":16384},"cost":{"input":0.05,"output":0.23,"cache_read":0.025},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"meta-llama/llama-3.1-8b-instruct":{"id":"meta-llama/llama-3.1-8b-instruct","name":"Llama 3.1 8b Instruct","description":"Compact open Llama model for lightweight chat, drafting, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":16384},"cost":{"input":0.0544,"output":0.085,"cache_read":0.0272},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"meta-llama/llama-3.2-3b-instruct":{"id":"meta-llama/llama-3.2-3b-instruct","name":"Llama 3.2 3b Instruct","description":"Open Llama multimodal model for image understanding and text reasoning","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-09-25","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":8192},"cost":{"input":0.0306,"output":0.0493,"cache_read":0.0153}},"LLM360/K2-Think":{"id":"LLM360/K2-Think","name":"K2-Think","description":"Kimi reasoning model for long-horizon research, planning, and tool use","family":"kimi-thinking","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-07-26","last_updated":"2025-07-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":32768},"cost":{"input":0.17,"output":0.68,"cache_read":0.085}},"deepcogito/cogito-v1-preview-qwen-32B":{"id":"deepcogito/cogito-v1-preview-qwen-32B","name":"Cogito v1 Preview Qwen 32B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-05-10","last_updated":"2025-05-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":32768},"cost":{"input":1.8,"output":1.8,"cache_read":0.9}},"GalrionSoftworks/MN-LooseCannon-12B-v1":{"id":"GalrionSoftworks/MN-LooseCannon-12B-v1","name":"MN-LooseCannon-12B-v1","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"meganova-ai/manta-mini-1.0":{"id":"meganova-ai/manta-mini-1.0","name":"Manta Mini 1.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-09-20","last_updated":"2025-12-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"input":8192,"output":8192},"cost":{"input":0.02,"output":0.16,"cache_read":0.01}},"meganova-ai/manta-flash-1.0":{"id":"meganova-ai/manta-flash-1.0","name":"Manta Flash 1.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-09-20","last_updated":"2025-12-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"input":16384,"output":16384},"cost":{"input":0.02,"output":0.16,"cache_read":0.01}},"meganova-ai/manta-pro-1.0":{"id":"meganova-ai/manta-pro-1.0","name":"Manta Pro 1.0","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-09-20","last_updated":"2025-12-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"input":65536,"output":32768},"cost":{"input":0.06,"output":0.5,"cache_read":0.03}},"perceptron/perceptron-mk1":{"id":"perceptron/perceptron-mk1","name":"Perceptron Mk1","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-05-12","last_updated":"2026-05-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"input":32768,"output":8192},"cost":{"input":0.15,"output":1.5,"cache_read":0.075},"canonical_model_id":"perceptron/perceptron-mk1"},"perceptron/perceptron-mk1.5":{"id":"perceptron/perceptron-mk1.5","name":"Perceptron Mk1.5","description":"Perceptron Mk1.5 is a multimodal reasoning model for visual analysis and physical agents. It accepts text, images, video, and audio, supports tool calling and structured output, and can return spatial annotations such as points, boxes, polygons, and tracks.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-25","last_updated":"2026-09-25","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":36864,"input":36864,"output":8192},"cost":{"input":0.15,"output":1.5}},"z-ai/glm-4.6v":{"id":"z-ai/glm-4.6v","name":"GLM 4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":24000},"cost":{"input":0.3,"output":0.9,"cache_read":0.15},"canonical_model_id":"zhipuai/glm-4.6v"},"z-ai/glm-4.6-original":{"id":"z-ai/glm-4.6-original","name":"GLM 4.6 Original","description":"GLM-4.6, Zhipu's flagship text model with 256K context window and advanced reasoning capabilities. Direct via Z-AI (Zhipu).","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":65535},"cost":{"input":0.5,"output":2,"cache_read":0.1}},"z-ai/glm-4.5":{"id":"z-ai/glm-4.5","name":"GLM 4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":0.3,"output":1.3,"cache_read":0.15},"canonical_model_id":"zhipuai/glm-4.5"},"z-ai/glm-5.3-flash-apex-abliterated":{"id":"z-ai/glm-5.3-flash-apex-abliterated","name":"Apex Flash 1 Abliterated","description":"Apex Flash 1 Abliterated is an experimental derivative of Cantina Security and Yeta's Apex Flash 1 with modified refusal behavior.","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":32768},"cost":{"input":0.15,"output":0.5,"cache_read":0.075}},"z-ai/glm-5v-turbo":{"id":"z-ai/glm-5v-turbo","name":"GLM 5V Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":202800,"input":202800,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5v-turbo"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.1,"output":0.3,"cache_read":0.025},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-5.3-flash-uncensored":{"id":"z-ai/glm-5.3-flash-uncensored","name":"GLM 5.3 Flash Uncensored","description":"GLM 5.3 Flash Uncensored is an uncensored fine-tune of the efficient 320B mixture-of-experts reasoning model, built for unrestricted chat, creative writing, coding, agentic work, tool use, and long-context tasks.","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-07-29","last_updated":"2026-08-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":32768},"cost":{"input":0.2,"output":0.8,"cache_read":0.07}},"z-ai/glm-4.6":{"id":"z-ai/glm-4.6","name":"GLM 4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":65535},"cost":{"input":0.5,"output":2,"cache_read":0.1},"canonical_model_id":"zhipuai/glm-4.6"},"z-ai/glm-4.7-flash:thinking":{"id":"z-ai/glm-4.7-flash:thinking","name":"GLM 4.7 Flash Thinking","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":128000},"cost":{"input":0.07,"output":0.4,"cache_read":0.035},"canonical_model_id":"zhipuai/glm-4.7-flash"},"z-ai/glm-5.3-flash-apex":{"id":"z-ai/glm-5.3-flash-apex","name":"Apex Flash 1","description":"Apex Flash 1 is Cantina Security and Yeta's cybersecurity-focused post-train of GLM 5.3 Flash for code investigation and tool use.","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":32768},"cost":{"input":0.15,"output":0.5,"cache_read":0.075}},"z-ai/glm-5-original:thinking":{"id":"z-ai/glm-5-original:thinking","name":"GLM 5 Original Thinking","description":"GLM-5 original with extended thinking capabilities for complex reasoning.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-02-11","last_updated":"2026-02-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":128000},"cost":{"input":0.6,"output":1.9,"cache_read":0.1}},"z-ai/glm-5.3:thinking":{"id":"z-ai/glm-5.3:thinking","name":"GLM 5.3 Thinking","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.6,"output":1.1,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5.3"},"z-ai/glm-5":{"id":"z-ai/glm-5","name":"GLM 5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":128000},"cost":{"input":0.6,"output":1.9,"cache_read":0.1},"canonical_model_id":"zhipuai/glm-5"},"z-ai/GLM-4.5-Air":{"id":"z-ai/GLM-4.5-Air","name":"GLM 4.5 Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":98304},"cost":{"input":0.12,"output":0.8,"cache_read":0.06},"canonical_model_id":"zhipuai/glm-4.5-air"},"z-ai/glm-4.5v":{"id":"z-ai/glm-4.5v","name":"GLM 4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":16384},"cost":{"input":0.6,"output":1.8,"cache_read":0.3},"canonical_model_id":"zhipuai/glm-4.5v"},"z-ai/GLM-4.6-turbo:thinking":{"id":"z-ai/GLM-4.6-turbo:thinking","name":"GLM 4.6 Turbo (Thinking)","description":"GLM 4.6 Turbo with thinking mode enabled for enhanced reasoning; shows internal reasoning and supports long context.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"release_date":"2025-10-02","last_updated":"2025-10-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"input":204800,"output":131072},"cost":{"input":1,"output":3,"cache_read":0.5}},"z-ai/glm-4.7:thinking":{"id":"z-ai/glm-4.7:thinking","name":"GLM 4.7 Thinking","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":65535},"cost":{"input":0.4004,"output":1.9292,"cache_read":0.08008},"canonical_model_id":"zhipuai/glm-4.7"},"z-ai/glm-5.1:thinking":{"id":"z-ai/glm-5.1:thinking","name":"GLM 5.1 Thinking","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":131072},"cost":{"input":0.7,"output":2.5,"cache_read":0.18},"canonical_model_id":"zhipuai/glm-5.1"},"z-ai/glm-4.6v-original":{"id":"z-ai/glm-4.6v-original","name":"GLM 4.6V Original","description":"GLM-4.6V scales its context window to 128k tokens in training, and achieves SoTA performance in visual understanding among models of similar parameter scales. Integrates native Function Calling capabilities, bridging 'visual perception' and 'executable action' for multimodal agents. Direct via Z-AI (Zhipu).","family":"glm","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":24000},"cost":{"input":0.6,"output":0.9,"cache_read":0.3}},"z-ai/glm-5v-turbo:thinking":{"id":"z-ai/glm-5v-turbo:thinking","name":"GLM 5V Turbo Thinking","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":202800,"input":202800,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5v-turbo"},"z-ai/GLM-4.6-turbo":{"id":"z-ai/GLM-4.6-turbo","name":"GLM 4.6 Turbo","description":"Fast variant of GLM 4.6 for general chat, coding, and analysis with improved latency and strong reasoning.","family":"glm","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-10-02","last_updated":"2025-10-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"input":204800,"output":131072},"cost":{"input":1,"output":3,"cache_read":0.5}},"z-ai/GLM-4.5-Air:thinking":{"id":"z-ai/GLM-4.5-Air:thinking","name":"GLM 4.5 Air (Thinking)","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":98304},"cost":{"input":0.12,"output":0.8,"cache_read":0.06},"canonical_model_id":"zhipuai/glm-4.5-air"},"z-ai/glm-5.2:thinking":{"id":"z-ai/glm-5.2:thinking","name":"GLM 5.2 Thinking","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.42,"output":1.32,"cache_read":0.078},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/glm-4.7-flash":{"id":"z-ai/glm-4.7-flash","name":"GLM 4.7 Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":128000},"cost":{"input":0.07,"output":0.4,"cache_read":0.035},"canonical_model_id":"zhipuai/glm-4.7-flash"},"z-ai/glm-4.7":{"id":"z-ai/glm-4.7","name":"GLM 4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":65535},"cost":{"input":0.4004,"output":1.9292,"cache_read":0.08008},"canonical_model_id":"zhipuai/glm-4.7"},"z-ai/glm-5.3-uncensored":{"id":"z-ai/glm-5.3-uncensored","name":"GLM 5.3 Uncensored","description":"An experimental uncensored version of the full GLM 5.3 reasoning model for chat, creative writing, coding, and tool use. It may show unusual behavior or inconsistent response quality.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-09-26","last_updated":"2026-09-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":1.25,"output":2.25,"cache_read":0.3}},"z-ai/glm-5:thinking":{"id":"z-ai/glm-5:thinking","name":"GLM 5 Thinking","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":128000},"cost":{"input":0.6,"output":1.9,"cache_read":0.1},"canonical_model_id":"zhipuai/glm-5"},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.42,"output":1.32,"cache_read":0.078},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/GLM-4.5:thinking":{"id":"z-ai/GLM-4.5:thinking","name":"GLM 4.5 (Thinking)","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":0.3,"output":1.3,"cache_read":0.15},"canonical_model_id":"zhipuai/glm-4.5"},"z-ai/glm-5.1":{"id":"z-ai/glm-5.1","name":"GLM 5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":131072},"cost":{"input":0.7,"output":2.5,"cache_read":0.18},"canonical_model_id":"zhipuai/glm-5.1"},"z-ai/glm-4.6:thinking":{"id":"z-ai/glm-4.6:thinking","name":"GLM 4.6 Thinking","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":65535},"cost":{"input":0.5,"output":2,"cache_read":0.1},"canonical_model_id":"zhipuai/glm-4.6"},"z-ai/glm-4.5v:thinking":{"id":"z-ai/glm-4.5v:thinking","name":"GLM 4.5V Thinking","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":16384},"cost":{"input":0.6,"output":1.8,"cache_read":0.3},"canonical_model_id":"zhipuai/glm-4.5v"},"z-ai/glm-4.7-original":{"id":"z-ai/glm-4.7-original","name":"GLM 4.7 Original","description":"GLM-4.7 is a next-gen GLM series text model with stronger reasoning, long-context chat, and reliable tool use. Routed directly via Z-AI (Zhipu).","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":65535},"cost":{"input":0.6,"output":2.2,"cache_read":0.11}},"z-ai/glm-5-original":{"id":"z-ai/glm-5-original","name":"GLM 5 Original","description":"GLM-5 is Zhipu's latest flagship model with advanced reasoning and instruction following. Routed directly via Z-AI (Zhipu).","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-02-11","last_updated":"2026-02-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":128000},"cost":{"input":0.6,"output":1.9,"cache_read":0.1}},"z-ai/glm-5-turbo":{"id":"z-ai/glm-5-turbo","name":"GLM 5 Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":202800,"input":202800,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5-turbo"},"z-ai/glm-4.7-original:thinking":{"id":"z-ai/glm-4.7-original:thinking","name":"GLM 4.7 Original Thinking","description":"GLM-4.7 original with extended thinking capabilities for complex reasoning.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":65535},"cost":{"input":0.6,"output":2.2,"cache_read":0.11}},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.6,"output":1.1,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5.3"},"z-ai/glm-5.3-flash-cybersecurity":{"id":"z-ai/glm-5.3-flash-cybersecurity","name":"GLM 5.3 Flash Cybersecurity","description":"GLM 5.3 Flash Cybersecurity is a cybersecurity-focused variant based on the uncensored model, with provider moderation for illegal activities. It supports always-on reasoning, image understanding, tool calling, and a 1,048,576-token context window.","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-09-19","last_updated":"2026-09-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":32768},"cost":{"input":0.15,"output":0.5,"cache_read":0.075}},"z-ai/glm-latest":{"id":"z-ai/glm-latest","name":"GLM Latest","description":"Compatibility alias that routes to the newest thinking GLM model. Currently routes to GLM 5.2 Thinking.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-05-03","last_updated":"2026-05-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.6,"output":1.1,"cache_read":0.2}},"reflection/beam-1.0":{"id":"reflection/beam-1.0","name":"Beam 1.0 501B A23B","description":"Reflection's Apache 2.0 open-weight text model with 501.3B total and 23.4B active parameters, built for coding, reasoning and tool use. It supports a shared 1,048,576-token context window, up to 131,072 output tokens, JSON mode and structured output. Reasoning is always enabled with low, medium, high, xhigh and max effort; NanoGPT defaults to max. Knowledge cutoff: June 30, 2026.","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-10-16","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":1.3,"output":4.3,"cache_read":0.13}},"inference-net/schematron-v2-small":{"id":"inference-net/schematron-v2-small","name":"Schematron V2 Small","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-09-12","last_updated":"2026-09-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":4096},"cost":{"input":0.05,"output":0.23,"cache_read":0.025},"canonical_model_id":"inference-net/schematron-v2-small"},"inference-net/schematron-v2-turbo":{"id":"inference-net/schematron-v2-turbo","name":"Schematron V2 Turbo","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-09-12","last_updated":"2026-09-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.03,"output":0.15,"cache_read":0.015},"canonical_model_id":"inference-net/schematron-v2-turbo"},"thinkingmachines/inkling:thinking":{"id":"thinkingmachines/inkling:thinking","name":"Inkling Thinking","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048000,"input":1048000,"output":32768},"cost":{"input":1,"output":4.05,"cache_read":0.17},"canonical_model_id":"thinkingmachines/inkling"},"thinkingmachines/Inkling-Small":{"id":"thinkingmachines/Inkling-Small","name":"Inkling Small","description":"Multimodal MoE reasoning model (276B total, 12B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"input":524288,"output":32768},"cost":{"input":0.5,"output":1.2,"cache_read":0.1},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/inkling":{"id":"thinkingmachines/inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048000,"input":1048000,"output":32768},"cost":{"input":1,"output":4.05,"cache_read":0.17},"canonical_model_id":"thinkingmachines/inkling"},"thinkingmachines/Inkling-Small:thinking":{"id":"thinkingmachines/Inkling-Small:thinking","name":"Inkling Small Thinking","description":"Multimodal MoE reasoning model (276B total, 12B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"input":524288,"output":32768},"cost":{"input":0.5,"output":1.2,"cache_read":0.1},"canonical_model_id":"thinkingmachines/inkling-small"},"meta/muse-spark-1.3":{"id":"meta/muse-spark-1.3","name":"Muse Spark 1.3","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":943718},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.3"},"meta/muse-glimmer-30b":{"id":"meta/muse-glimmer-30b","name":"Muse Glimmer 30B","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":117964},"cost":{"input":0.35,"output":1.5,"cache_read":0.04},"canonical_model_id":"meta/muse-glimmer-30b"},"meta/muse-spark-1.1":{"id":"meta/muse-spark-1.1","name":"Muse Spark 1.1","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":65536},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.1"},"meta/muse-spark-1.2":{"id":"meta/muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":65536},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"meta/muse-spark-1.2-contributor":{"id":"meta/muse-spark-1.2-contributor","name":"Muse Spark 1.2 Contributor (Data Used for Training)","description":"A much cheaper opt-in version of Muse Spark 1.2 with the same multimodal coding and agentic capabilities. Prompts and outputs sent to this Contributor model may be used by Meta for training and to improve its products; use the standard Muse Spark 1.2 model if you do not want your data used for training.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":65536},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"meta/muse-spark-1.3-contributor":{"id":"meta/muse-spark-1.3-contributor","name":"Muse Spark 1.3 Contributor","description":"Meta's Muse Spark 1.3 Contributor is a frontier multimodal reasoning model for long-horizon coding and agentic workflows, with strong gains in computer use, browsing, professional tool use, codebase understanding, and million-token retrieval. It accepts text, images, audio, video, and files, supports tool calling and structured output, and always reasons before answering. Prompts and outputs may be used by Meta for training and to improve its products.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":943718},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"meta/muse-spark-open":{"id":"meta/muse-spark-open","name":"Muse Spark Open","description":"Muse Spark Open is an 816B total / 42B active open-weight multimodal reasoning model from Meta for coding and long-horizon agentic work, with 1M-token context.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-open"},"mlabonne/NeuralDaredevil-8B-abliterated":{"id":"mlabonne/NeuralDaredevil-8B-abliterated","name":"Neural Daredevil 8B abliterated","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"input":8192,"output":8192},"cost":{"input":0.44,"output":0.44,"cache_read":0.22}},"NeverSleep/Lumimaid-v0.2-70B":{"id":"NeverSleep/Lumimaid-v0.2-70B","name":"Lumimaid v0.2","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":1,"output":1.5,"cache_read":0.5}},"nanogpt/coding-router:low":{"id":"nanogpt/coding-router:low","name":"Coding Router Low","description":"Automatic model router for matching prompts to suitable backends and budgets","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-05-12","last_updated":"2026-05-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":0.14,"output":0.28,"cache_read":0.028}},"nanogpt/coding-router:medium":{"id":"nanogpt/coding-router:medium","name":"Coding Router Medium","description":"Automatic model router for matching prompts to suitable backends and budgets","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-05-12","last_updated":"2026-05-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":0.14,"output":0.28,"cache_read":0.028}},"nanogpt/coding-router":{"id":"nanogpt/coding-router","name":"Coding Router","description":"Automatic model router for matching prompts to suitable backends and budgets","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-05-12","last_updated":"2026-05-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":1.1,"output":2.2,"cache_read":0.11}},"nanogpt/coding-router:max":{"id":"nanogpt/coding-router:max","name":"Coding Router Max","description":"Automatic model router for matching prompts to suitable backends and budgets","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-05-12","last_updated":"2026-05-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5}},"nanogpt/coding-router:high":{"id":"nanogpt/coding-router:high","name":"Coding Router High","description":"Automatic model router for matching prompts to suitable backends and budgets","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-05-12","last_updated":"2026-05-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":1.1,"output":2.2,"cache_read":0.11}},"LatitudeGames/Wayfarer-Large-70B-Llama-3.3":{"id":"LatitudeGames/Wayfarer-Large-70B-Llama-3.3","name":"Llama 3.3 70B Wayfarer","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-02-20","last_updated":"2025-02-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":0.7,"output":0.7,"cache_read":0.35}},"VongolaChouko/Starcannon-Unleashed-12B-v1.0":{"id":"VongolaChouko/Starcannon-Unleashed-12B-v1.0","name":"Mistral Nemo Starcannon 12b v1","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"arcee-ai/trinity-large-thinking":{"id":"arcee-ai/trinity-large-thinking","name":"Trinity Large Thinking","description":"Reasoning-optimized 398B MoE agent model with extended thinking for long-horizon and multi-turn tool use","family":"trinity","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":80000},"cost":{"input":0.25,"output":0.9,"cache_read":0.125},"canonical_model_id":"arcee-ai/trinity-large-thinking"},"x-ai/grok-4.20-multi-agent":{"id":"x-ai/grok-4.20-multi-agent","name":"Grok 4.20 Multi-Agent","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"release_date":"2026-03-31","last_updated":"2026-03-31","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"input":2000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":1}},"x-ai/grok-latest":{"id":"x-ai/grok-latest","name":"Grok Latest","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-03","last_updated":"2026-05-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"input":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.5}},"x-ai/grok-4.7":{"id":"x-ai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"input":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.7"},"x-ai/grok-4.3":{"id":"x-ai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":900000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2},"canonical_model_id":"xai/grok-4.3"},"x-ai/grok-4.5":{"id":"x-ai/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"input":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.5"},"x-ai/grok-build-0.1":{"id":"x-ai/grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":230400},"cost":{"input":1,"output":2,"cache_read":0.2},"canonical_model_id":"xai/grok-build-0.1"},"x-ai/grok-4.20":{"id":"x-ai/grok-4.20","name":"Grok 4.20","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-03-31","last_updated":"2026-03-31","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"input":2000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":1}},"x-ai/grok-4.6":{"id":"x-ai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"input":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"Envoid/Llama-3.05-Nemotron-Tenyxchat-Storybreaker-70B":{"id":"Envoid/Llama-3.05-Nemotron-Tenyxchat-Storybreaker-70B","name":"Nemotron Tenyxchat Storybreaker 70b","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"Envoid/Llama-3.05-NT-Storybreaker-Ministral-70B":{"id":"Envoid/Llama-3.05-NT-Storybreaker-Ministral-70B","name":"Llama 3.05 Storybreaker Ministral 70b","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"heabsy/qwen3.8-27b-uncensored-fast":{"id":"heabsy/qwen3.8-27b-uncensored-fast","name":"Qwen 3.8 27B Uncensored Fast by Heabsy","description":"Heabsy's NVFP4 build of Qwen3.8-27B by Alibaba Cloud, with refusal removal based on huihui-ai's Huihui-Qwen3.8-27B-abliterated. Quantized and calibrated by Heabsy, with unpublished weights under the Heabsy Model License. Supports text and image input, tools, and optional reasoning capped at 16,384 tokens within the output budget. This named build is separate from Qwen 3.8 27B Uncensored.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-10-16","last_updated":"2026-10-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"input":524288,"output":235929},"cost":{"input":1,"output":3,"cache_read":0.22}},"heabsy/cyberheabsy":{"id":"heabsy/cyberheabsy","name":"CyberHeabsy","description":"A low-refusal text model for authorized security research, roleplay, and creative writing. It preserves tool calling after refusal removal, supports optional reasoning, and has a 1M-token context window.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-09-27","last_updated":"2026-09-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":1.5,"output":4.5,"cache_read":0.275}},"upstage/solar-pro-3":{"id":"upstage/solar-pro-3","name":"Solar Pro 3","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"solar-pro","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"input":131072,"output":117964},"cost":{"input":0.15,"output":0.6,"cache_read":0.015}},"upstage/solar-pro4":{"id":"upstage/solar-pro4","name":"Solar Pro 4","description":"Upstage's flagship model, specialized for agentic use","family":"solar-pro","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02","release_date":"2026-08-06","last_updated":"2026-08-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"input":524288,"output":131072},"cost":{"input":0.03,"output":0.12,"cache_read":0.006},"canonical_model_id":"upstage/solar-pro4"},"upstage/solar-mini4:thinking":{"id":"upstage/solar-mini4:thinking","name":"Solar Mini 4 Thinking","description":"Solar Mini 4 with reasoning enabled for agentic tasks and harder analysis across a 524K-token context window.","family":"solar","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"input":524288,"output":131072},"cost":{"input":0.05,"output":0.2,"cache_read":0.005}},"upstage/solar-pro4:thinking":{"id":"upstage/solar-pro4:thinking","name":"Solar Pro 4 Thinking","description":"Upstage's flagship model, specialized for agentic use","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02","release_date":"2026-08-06","last_updated":"2026-08-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"input":524288,"output":131072},"cost":{"input":0.03,"output":0.12,"cache_read":0.006},"canonical_model_id":"upstage/solar-pro4"},"upstage/solar-mini4":{"id":"upstage/solar-mini4","name":"Solar Mini 4","description":"Upstage's compact 35B-parameter mixture-of-experts model with 3B active parameters and a 524K context window. Built for fast, cost-efficient agentic tasks, with strong Korean and English support.","family":"solar","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"input":524288,"output":131072},"cost":{"input":0.05,"output":0.2,"cache_read":0.005}},"bytedance/doubao-seed-2.1-turbo":{"id":"bytedance/doubao-seed-2.1-turbo","name":"Doubao Seed 2.1 Turbo","description":"Fast, lower-cost model in the Doubao Seed 2.1 family for everyday chat, coding assistance, document work, and high-throughput productivity tasks. Supports a 256k context window and up to 128k output tokens. Note: privacy and logging guarantees may be limited.","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":128000},"cost":{"input":0.5,"output":2.5,"cache_read":0.25}},"bytedance/doubao-seed-2.1-pro":{"id":"bytedance/doubao-seed-2.1-pro","name":"Doubao Seed 2.1 Pro","description":"Higher-capability model in the Doubao Seed 2.1 family for agentic coding, long-context analysis, complex instruction following, and productivity workflows. Supports a 256k context window and up to 128k output tokens. Note: privacy and logging guarantees may be limited.","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":128000},"cost":{"input":1,"output":5,"cache_read":0.5}},"bytedance/doubao-seed-character":{"id":"bytedance/doubao-seed-character","name":"Doubao Seed Character","description":"ByteDance's character-focused Doubao Seed model for roleplay, persona consistency, dialogue, and creative character interactions. It supports text and image input with a 128k context window. Requests route through ZenMux to ByteDance; ZenMux does not publish a model-API zero-retention or training guarantee, so avoid sensitive data.","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":false,"release_date":"2026-07-18","last_updated":"2026-07-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":32768},"cost":{"input":0.15,"output":0.37,"cache_read":0.03,"cache_write":0.003}},"liquid/lfm-2.5-2.6b":{"id":"liquid/lfm-2.5-2.6b","name":"LFM2.5 2.6B","description":"Liquid AI's compact 2.6B reasoning model for agent workflows, data extraction, RAG, and long-context processing. It supports tool calling and structured output, but Liquid advises against using it for agentic coding. Warning: prompts and responses may be logged and used for model training or service improvement; do not send sensitive data.","family":"liquid","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":32768},"cost":{"input":0.1,"output":0.2,"cache_read":0.05}},"liquid/lfm-2.5-24b-a2b":{"id":"liquid/lfm-2.5-24b-a2b","name":"LFM2.5 24B A2B","description":"Liquid AI's text-only mixture-of-experts model for reasoning and tool-using agents, with 24B total and 2.45B active parameters. It always thinks before answering and supports structured output. Pair it with retrieval for knowledge-heavy tasks. Open weights use the LFM Open License v1.0, with a $10M annual-revenue commercial threshold; hosted API use is subject to separate service terms that permit retention and use of prompts and responses for model training.","family":"liquid","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-10-14","last_updated":"2026-10-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.05,"output":0.7,"cache_read":0.025}},"google/gemini-flash-latest":{"id":"google/gemini-flash-latest","name":"Gemini Flash Latest","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.041667},"canonical_model_id":"google/gemini-flash-latest"},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":131072},"cost":{"input":0.1,"output":0.45,"cache_read":0.05},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemini-3.1-pro-preview-low":{"id":"google/gemini-3.1-pro-preview-low","name":"Gemini 3.1 Pro (Preview Low)","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-02-21","last_updated":"2026-02-21","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":0.375}},"google/gemini-3.5-flash-thinking":{"id":"google/gemini-3.5-flash-thinking","name":"Gemini 3.5 Flash Thinking","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"cache_write":0.083333},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemma-4-26b-a4b-it:thinking":{"id":"google/gemma-4-26b-a4b-it:thinking","name":"Gemma 4 26B A4B Thinking","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":131072},"cost":{"input":0.13,"output":0.4,"cache_read":0.065},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemini-flash-lite-latest":{"id":"google/gemini-flash-lite-latest","name":"Gemini Flash Lite Latest","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":0.08333},"canonical_model_id":"google/gemini-flash-lite-latest"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.6-flash"},"google/diffusiongemma":{"id":"google/diffusiongemma","name":"DiffusionGemma","description":"DiffusionGemma is a high-speed diffusion-based version of Gemma 4 26B A4B. It supports optional reasoning and a 262,144-token context window.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","xhigh"]}],"tool_call":false,"structured_output":false,"release_date":"2026-09-19","last_updated":"2026-09-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.05,"output":0.15,"cache_read":0.025}},"google/gemma-4-26b-a4b-it":{"id":"google/gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":131072},"cost":{"input":0.12,"output":0.38,"cache_read":0.06},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemma-4-31b-it:thinking":{"id":"google/gemma-4-31b-it:thinking","name":"Gemma 4 31B Thinking","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":131072},"cost":{"input":0.1,"output":0.35,"cache_read":0.05},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro (Preview)","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":0.375},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.1-pro-preview-high":{"id":"google/gemini-3.1-pro-preview-high","name":"Gemini 3.1 Pro (Preview High)","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-02-21","last_updated":"2026-02-21","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":0.375}},"google/gemma4-31b-splituntied":{"id":"google/gemma4-31b-splituntied","name":"Gemma 4 31B Split-Untied","description":"Blazed-Forge's Split-Untied is a text-only Gemma 4 31B community finetune with an untied BF16 output head, built for creative writing, roleplay, expressive dialogue, and tool use.","family":"gemma","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.3,"cache_read":0.05}},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"cache_write":0.083333},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemma-4-26b-a4b-it-cybersecurity":{"id":"google/gemma-4-26b-a4b-it-cybersecurity","name":"Gemma 4 26B A4B Cybersecurity","description":"Gemma 4 26B A4B Cybersecurity is a cybersecurity-focused variant based on the uncensored model, with provider moderation for illegal activities. It supports optional reasoning, image understanding, tool calling, and a 262,144-token context window.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-09-19","last_updated":"2026-09-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1056,"output":0.3344,"cache_read":0.0528}},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.7-flash"},"google/gemini-3.1-pro-preview-customtools":{"id":"google/gemini-3.1-pro-preview-customtools","name":"Gemini 3.1 Pro (Preview Custom Tools)","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":0.375},"canonical_model_id":"google/gemini-3.1-pro-preview-customtools"},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash (Preview)","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-pro-latest":{"id":"google/gemini-pro-latest","name":"Gemini Pro Latest","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-03-29","last_updated":"2026-03-29","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":0.375}},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-3-flash-preview-thinking":{"id":"google/gemini-3-flash-preview-thinking","name":"Gemini 3 Flash Thinking","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-4-argon":{"id":"google/gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":0.1875},"canonical_model_id":"google/gemini-4-argon"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.1-flash-lite"},"TEE/gemma-4-31b-it":{"id":"TEE/gemma-4-31b-it","name":"Gemma 4 31B IT TEE","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":262144},"cost":{"input":0.15,"output":0.46,"cache_read":0.075},"canonical_model_id":"google/gemma-4-31b-it"},"TEE/qwen3.8-27b":{"id":"TEE/qwen3.8-27b","name":"Qwen3.8 27B TEE","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":262144},"cost":{"input":0.4,"output":3,"cache_read":0.15},"canonical_model_id":"alibaba/qwen3.8-27b"},"TEE/nemotron-3.5-lightning":{"id":"TEE/nemotron-3.5-lightning","name":"Nvidia Nemotron 3.5 Lightning TEE","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.08,"output":0.2,"cache_read":0.04},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"TEE/glm-5.3-flash":{"id":"TEE/glm-5.3-flash","name":"GLM 5.3 Flash TEE","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"TEE/qwen3.5-27b":{"id":"TEE/qwen3.5-27b","name":"Qwen3.5 27B TEE","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.3,"output":2.4,"cache_read":0.15},"canonical_model_id":"alibaba/qwen3.5-27b"},"TEE/muse-glimmer-30b":{"id":"TEE/muse-glimmer-30b","name":"Muse Glimmer 30B TEE","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":131072},"cost":{"input":0.35,"output":1.5,"cache_read":0.04},"canonical_model_id":"meta/muse-glimmer-30b"},"TEE/kimi-k3":{"id":"TEE/kimi-k3","name":"Kimi K3 TEE","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":65535},"cost":{"input":3,"output":15,"cache_read":1.5},"canonical_model_id":"moonshotai/kimi-k3"},"TEE/deepseek-v4.1-flash":{"id":"TEE/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash TEE","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":0.65,"output":1.45,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"TEE/llama3-3-70b":{"id":"TEE/llama3-3-70b","name":"Llama 3.3 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-07-03","last_updated":"2025-07-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":1.75,"output":2.75,"cache_read":1.75}},"TEE/kimi-k2.6":{"id":"TEE/kimi-k2.6","name":"Kimi K2.6 TEE","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":1.5,"output":5.25,"cache_read":0.375},"canonical_model_id":"moonshotai/kimi-k2.6"},"TEE/gemma-4-26b-a4b-uncensored":{"id":"TEE/gemma-4-26b-a4b-uncensored","name":"Gemma 4 26B A4B Uncensored TEE","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-05-23","last_updated":"2026-05-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":65536},"cost":{"input":0.15,"output":0.7,"cache_read":0.075}},"TEE/gemma4-31b:thinking":{"id":"TEE/gemma4-31b:thinking","name":"Gemma 4 31B Thinking TEE","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-05-02","last_updated":"2026-05-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":131072},"cost":{"input":0.4,"output":1,"cache_read":0.4}},"TEE/gemma4-31b":{"id":"TEE/gemma4-31b","name":"Gemma 4 31B","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-04-04","last_updated":"2026-04-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":131072},"cost":{"input":0.4,"output":1,"cache_read":0.4}},"TEE/qwen3.6-35b-a3b":{"id":"TEE/qwen3.6-35b-a3b","name":"Qwen3.6 35B A3B TEE","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":262144},"cost":{"input":0.2,"output":1.27,"cache_read":0.1},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"TEE/glm-5.2:thinking":{"id":"TEE/glm-5.2:thinking","name":"GLM 5.2 Thinking TEE","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.7},"canonical_model_id":"zhipuai/glm-5.2"},"TEE/qwen3.5-397b-a17b":{"id":"TEE/qwen3.5-397b-a17b","name":"Qwen3.5 397B A17B TEE","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.55,"output":3.5,"cache_read":0.275},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"TEE/glm-5.2":{"id":"TEE/glm-5.2","name":"GLM 5.2 TEE","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.7},"canonical_model_id":"zhipuai/glm-5.2"},"TEE/glm-5.1-thinking":{"id":"TEE/glm-5.1-thinking","name":"GLM 5.1 Thinking TEE","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"input":202752,"output":65535},"cost":{"input":0.7,"output":2.5,"cache_read":0.18},"canonical_model_id":"zhipuai/glm-5.1"},"TEE/glm-5.1":{"id":"TEE/glm-5.1","name":"GLM 5.1 TEE","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"input":202752,"output":65535},"cost":{"input":0.7,"output":2.5,"cache_read":0.18},"canonical_model_id":"zhipuai/glm-5.1"},"TEE/qwen2.5-vl-72b-instruct":{"id":"TEE/qwen2.5-vl-72b-instruct","name":"Qwen2.5 VL 72B TEE","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-02-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":8192},"cost":{"input":0.7,"output":0.7,"cache_read":0.35}},"TEE/qwen3.6-27b":{"id":"TEE/qwen3.6-27b","name":"Qwen3.6 27B TEE","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.32,"output":2.7,"cache_read":0.16},"canonical_model_id":"alibaba/qwen3.6-27b"},"TEE/deepseek-v3.2":{"id":"TEE/deepseek-v3.2","name":"DeepSeek V3.2 TEE","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"input":164000,"output":65536},"cost":{"input":0.5,"output":1,"cache_read":0.25},"canonical_model_id":"deepseek/deepseek-v3.2"},"TEE/gpt-oss-120b":{"id":"TEE/gpt-oss-120b","name":"GPT-OSS 120B TEE","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":16384},"cost":{"input":2,"output":2,"cache_read":2},"canonical_model_id":"openai/gpt-oss-120b"},"TEE/glm-5.3":{"id":"TEE/glm-5.3","name":"GLM 5.3 TEE","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"TEE/kimi-k2.7-code":{"id":"TEE/kimi-k2.7-code","name":"Kimi K2.7 Code TEE","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"EVA-UNIT-01/EVA-Qwen2.5-72B-v0.2":{"id":"EVA-UNIT-01/EVA-Qwen2.5-72B-v0.2","name":"EVA-Qwen2.5-72B-v0.2","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-09-25","last_updated":"2025-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.799,"output":0.799,"cache_read":0.3995}},"EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.0":{"id":"EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.0","name":"EVA Llama 3.33 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-07-26","last_updated":"2025-07-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":2.006,"output":2.006,"cache_read":1.003}},"EVA-UNIT-01/EVA-Qwen2.5-32B-v0.2":{"id":"EVA-UNIT-01/EVA-Qwen2.5-32B-v0.2","name":"EVA-Qwen2.5-32B-v0.2","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-07-26","last_updated":"2025-07-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.799,"output":0.799,"cache_read":0.3995}},"EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1":{"id":"EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1","name":"EVA-LLaMA-3.33-70B-v0.1","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-09-25","last_updated":"2025-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":2.006,"output":2.006,"cache_read":1.003}},"nothingiisreal/L3.1-70B-Celeste-V0.1-BF16":{"id":"nothingiisreal/L3.1-70B-Celeste-V0.1-BF16","name":"Llama 3.1 70B Celeste v0.1","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"aisingapore/Gemma-SEA-LION-v4-27B-IT":{"id":"aisingapore/Gemma-SEA-LION-v4-27B-IT","name":"Gemma SEA-LION v4 27B","description":"Gemma 3 27B tuned by AI Singapore for Southeast Asian languages and instruction following","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":128000},"cost":{"input":0.24,"output":0.48},"canonical_model_id":"aisingapore/gemma-sea-lion-v4-27b-it"},"MarinaraSpaghetti/NemoMix-Unleashed-12B":{"id":"MarinaraSpaghetti/NemoMix-Unleashed-12B","name":"NemoMix 12B Unleashed","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":8192},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"pamanseau/OpenReasoning-Nemotron-32B":{"id":"pamanseau/OpenReasoning-Nemotron-32B","name":"OpenReasoning Nemotron 32B","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.05}},"huihui-ai/DeepSeek-R1-Distill-Qwen-32B-abliterated":{"id":"huihui-ai/DeepSeek-R1-Distill-Qwen-32B-abliterated","name":"DeepSeek R1 Qwen Abliterated","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-01-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":1.4,"output":1.4,"cache_read":0.7}},"huihui-ai/Qwen2.5-32B-Instruct-abliterated":{"id":"huihui-ai/Qwen2.5-32B-Instruct-abliterated","name":"Qwen 2.5 32B Abliterated","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-01-06","last_updated":"2025-01-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":8192},"cost":{"input":0.7,"output":0.7,"cache_read":0.35}},"huihui-ai/Llama-3.3-70B-Instruct-abliterated":{"id":"huihui-ai/Llama-3.3-70B-Instruct-abliterated","name":"Llama 3.3 70B Instruct abliterated","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-08-08","last_updated":"2025-08-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":0.7,"output":0.7,"cache_read":0.35}},"huihui-ai/DeepSeek-R1-Distill-Llama-70B-abliterated":{"id":"huihui-ai/DeepSeek-R1-Distill-Llama-70B-abliterated","name":"DeepSeek R1 Llama 70B Abliterated","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-01-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.7,"output":0.7,"cache_read":0.35}},"Gryphe/MythoMax-L2-13b":{"id":"Gryphe/MythoMax-L2-13b","name":"MythoMax 13B","description":"Llama 2 merge combining MythoLogic and Huginn for creative writing and roleplay","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2023-08-10","last_updated":"2023-08-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"input":4096,"output":3686},"cost":{"input":0.1003,"output":0.1003,"cache_read":0.05015},"canonical_model_id":"gryphe/mythomax-l2-13b"},"moondream/moondream3-preview":{"id":"moondream/moondream3-preview","name":"Moondream 3 Preview","description":"Moondream 3 Preview is the original 9B mixture-of-experts vision-language checkpoint with 2B active parameters, for visual question answering, captioning, OCR, and visual reasoning. It accepts text or one image with optional reasoning, a 32,000-token context, and up to 4,096 output tokens.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"release_date":"2026-10-16","last_updated":"2026-10-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"input":32000,"output":4096},"cost":{"input":0.3,"output":2.5}},"moondream/moondream3.1-9b-a2b":{"id":"moondream/moondream3.1-9b-a2b","name":"Moondream 3.1 9B A2B","description":"Moondream 3.1 is the successor to Moondream 3 Preview: a distinct 9B mixture-of-experts vision-language checkpoint with 2B active parameters, for visual question answering, captioning, OCR, and visual reasoning. It accepts text or one image with optional reasoning, a 32,000-token context, and up to 4,096 output tokens.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"release_date":"2026-10-16","last_updated":"2026-10-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"input":32000,"output":4096},"cost":{"input":0.3,"output":2.5}},"ibm-granite/granite-4.2-8b":{"id":"ibm-granite/granite-4.2-8b","name":"Granite 4.2 8B","description":"IBM Granite 4.2 8B is an Apache 2.0-licensed dense model with native step-by-step reasoning and specialized training for agentic work. It can plan before acting, sequence tools, navigate codebases, work in terminals, and verify results across coding, search, mathematics, science, and complex instruction-following tasks.","family":"granite","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-31","last_updated":"2026-08-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":117964},"cost":{"input":0.1,"output":0.15,"cache_read":0.05}},"TheDrummer/skyfall-36b-v2":{"id":"TheDrummer/skyfall-36b-v2","name":"TheDrummer Skyfall 36B V2","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-06-30","release_date":"2025-03-10","last_updated":"2025-03-10","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":29491},"cost":{"input":0.55,"output":0.8,"cache_read":0.25},"canonical_model_id":"thedrummer/skyfall-36b-v2"},"TheDrummer/Artemis-v1.1":{"id":"TheDrummer/Artemis-v1.1","name":"TheDrummer/Artemis v1.1","description":"TheDrummer's Artemis v1.1 is a Gemma 4 31B fine-tune for creative writing, expressive dialogue, and roleplay, with optional thinking and a 262K context window.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-09-06","last_updated":"2026-09-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"TheDrummer/Anubis-70B-v1":{"id":"TheDrummer/Anubis-70B-v1","name":"Anubis 70B v1","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":16384},"cost":{"input":0.31,"output":0.31,"cache_read":0.155}},"TheDrummer/Anubis-70B-v1.1":{"id":"TheDrummer/Anubis-70B-v1.1","name":"Anubis 70B v1.1","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"input":32000,"output":16384},"cost":{"input":0.31,"output":0.31,"cache_read":0.155}},"TheDrummer/Cydonia-24B-v4.3":{"id":"TheDrummer/Cydonia-24B-v4.3","name":"The Drummer Cydonia 24B v4.3","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-12-25","last_updated":"2025-12-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.12,"output":0.15,"cache_read":0.06}},"TheDrummer/Magidonia-24B-v4.3":{"id":"TheDrummer/Magidonia-24B-v4.3","name":"The Drummer Magidonia 24B v4.3","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-12-25","last_updated":"2025-12-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":32768},"cost":{"input":0.1003,"output":0.1207,"cache_read":0.05015}},"TheDrummer/Cydonia-24B-v4.1":{"id":"TheDrummer/Cydonia-24B-v4.1","name":"The Drummer Cydonia 24B v4.1","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-04-30","release_date":"2025-09-27","last_updated":"2025-09-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":117964},"cost":{"input":0.35,"output":0.55,"cache_read":0.16},"canonical_model_id":"thedrummer/cydonia-24b-v4.1"},"TheDrummer/UnslopNemo-12B-v4.1":{"id":"TheDrummer/UnslopNemo-12B-v4.1","name":"UnslopNemo 12b v4","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"input":8192,"output":26214},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"TheDrummer/Cydonia-24B-v2":{"id":"TheDrummer/Cydonia-24B-v2","name":"The Drummer Cydonia 24B v2","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-02-17","last_updated":"2025-02-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":32768},"cost":{"input":0.1003,"output":0.1207,"cache_read":0.05015}},"TheDrummer/Rocinante-12B-v1.1":{"id":"TheDrummer/Rocinante-12B-v1.1","name":"Rocinante 12b","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.408,"output":0.595,"cache_read":0.204}},"TheDrummer/Cydonia-24B-v4":{"id":"TheDrummer/Cydonia-24B-v4","name":"The Drummer Cydonia 24B v4","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":32768},"cost":{"input":0.2006,"output":0.2414,"cache_read":0.1003}},"TheDrummer/orion-26b-a4b-v1.1":{"id":"TheDrummer/orion-26b-a4b-v1.1","name":"Orion 26B A4B v1.1","description":"TheDrummer's Gemma 4 26B A4B fine-tune for creative writing, roleplay, and expressive dialogue. Supports optional thinking with a 65,536-token context window and up to 8,192 output tokens. Text input only.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":false,"release_date":"2026-10-16","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":8192},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"deepseek-ai/DeepSeek-V3.1":{"id":"deepseek-ai/DeepSeek-V3.1","name":"DeepSeek V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2025-07-26","last_updated":"2025-07-26","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":0.2,"output":0.7,"cache_read":0.1}},"deepseek-ai/deepseek-v3.2-exp-thinking":{"id":"deepseek-ai/deepseek-v3.2-exp-thinking","name":"DeepSeek V3.2 Exp Thinking","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"input":163840,"output":65536},"cost":{"input":0.28,"output":0.42,"cache_read":0.14}},"deepseek-ai/DeepSeek-R1-0528":{"id":"deepseek-ai/DeepSeek-R1-0528","name":"DeepSeek R1 0528","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"input":163840,"output":32768},"cost":{"input":0.5,"output":2.15,"cache_read":0.35}},"deepseek-ai/DeepSeek-V3.1-Terminus":{"id":"deepseek-ai/DeepSeek-V3.1-Terminus","name":"DeepSeek V3.1 Terminus","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2025-08-02","last_updated":"2025-08-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":0.25,"output":0.7,"cache_read":0.125}},"deepseek-ai/deepseek-v3.2-exp":{"id":"deepseek-ai/deepseek-v3.2-exp","name":"DeepSeek V3.2 Exp","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"input":163840,"output":65536},"cost":{"input":0.28,"output":0.42,"cache_read":0.14}},"deepseek-ai/DeepSeek-V3.1:thinking":{"id":"deepseek-ai/DeepSeek-V3.1:thinking","name":"DeepSeek V3.1 Thinking","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek-thinking","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":0.2,"output":0.7,"cache_read":0.1}},"deepseek-ai/DeepSeek-V3.1-Terminus:thinking":{"id":"deepseek-ai/DeepSeek-V3.1-Terminus:thinking","name":"DeepSeek V3.1 Terminus (Thinking)","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek-thinking","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2024-01-01","last_updated":"2025-09-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":0.25,"output":0.7,"cache_read":0.125}},"stepfun-ai/step-3.5-flash-2603":{"id":"stepfun-ai/step-3.5-flash-2603","name":"Step 3.5 Flash 2603","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.1,"output":0.3,"cache_read":0.05},"canonical_model_id":"stepfun/step-3.5-flash-2603"},"stepfun-ai/step-3.5-flash":{"id":"stepfun-ai/step-3.5-flash","name":"Step 3.5 Flash","description":"StepFun flash lane for quick multimodal reasoning and coding assistance","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.1,"output":0.3,"cache_read":0.05},"canonical_model_id":"stepfun/step-3.5-flash"},"MiniMaxAI/MiniMax-M1-80k":{"id":"MiniMaxAI/MiniMax-M1-80k","name":"MiniMax M1 80K","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-01-08","last_updated":"2025-06-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":131072},"cost":{"input":0.6052,"output":2.4225,"cache_read":0.3026}},"fireworks/ember-1":{"id":"fireworks/ember-1","name":"Ember 1","description":"Specialized model from Fireworks built on Kimi K3, producing shorter reasoning traces with approximately 40% fewer tokens while maintaining comparable quality","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"fireworks/ember-1"},"mistralai/ministral-8b-2512":{"id":"mistralai/ministral-8b-2512","name":"Ministral 8B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.15,"output":0.15,"cache_read":0.075},"canonical_model_id":"mistral/ministral-8b-2512"},"mistralai/mistral-large-4":{"id":"mistralai/mistral-large-4","name":"Mistral Large 4","description":"Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"input":524288,"output":262144},"cost":{"input":0.68,"output":2.09,"cache_read":0.07},"canonical_model_id":"mistral/mistral-large-4"},"mistralai/mistral-small-4-119b-2603:thinking":{"id":"mistralai/mistral-small-4-119b-2603:thinking","name":"Mistral Small 4 119B Thinking","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.4,"output":1.4,"cache_read":0.2}},"mistralai/mistral-medium-3.5":{"id":"mistralai/mistral-medium-3.5","name":"Mistral Medium 3.5","description":"Mistral Medium 3.5 is a 128B dense open-weights flagship model for instruction-following, reasoning, coding, long-horizon agentic work, tool use, structured output, and multimodal prompts. It supports a 256k context window and configurable reasoning effort.","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":32768},"cost":{"input":1.5,"output":7.5,"cache_read":0.75}},"mistralai/mistral-small-24b-instruct-2501":{"id":"mistralai/mistral-small-24b-instruct-2501","name":"Mistral Small 24B","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-01-30","last_updated":"2025-01-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":8192},"cost":{"input":0.1155,"output":0.3465},"canonical_model_id":"mistral/mistral-small-24b-instruct-2501"},"mistralai/mixtral-8x22b-instruct-v0.1":{"id":"mistralai/mixtral-8x22b-instruct-v0.1","name":"Mixtral 8x22B","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mixtral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":52428},"cost":{"input":2,"output":6,"cache_read":0.2}},"mistralai/mistral-saba":{"id":"mistralai/mistral-saba","name":"Mistral Saba","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-02-17","last_updated":"2025-02-17","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"input":32768,"output":26214},"cost":{"input":0.1989,"output":0.595,"cache_read":0.09945},"canonical_model_id":"mistral/mistral-saba"},"mistralai/mistral-medium-3.1":{"id":"mistralai/mistral-medium-3.1","name":"Mistral Medium 3.1","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-06-30","release_date":"2025-08-13","last_updated":"2025-08-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.4,"output":2,"cache_read":0.2},"canonical_model_id":"mistral/mistral-medium-3.1"},"mistralai/mistral-small-3.2-24b-instruct":{"id":"mistralai/mistral-small-3.2-24b-instruct","name":"Mistral Small 3.2 24B (2506)","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":0.2,"output":0.4,"cache_read":0.1},"canonical_model_id":"mistral/mistral-small-3.2-24b-instruct"},"mistralai/mistral-small-4-119b-2603":{"id":"mistralai/mistral-small-4-119b-2603","name":"Mistral Small 4 119B","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.4,"output":1.4,"cache_read":0.2}},"mistralai/mistral-large":{"id":"mistralai/mistral-large","name":"Mistral Large 2411","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-11-30","release_date":"2024-02-26","last_updated":"2024-02-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":102400},"cost":{"input":2.006,"output":6.001,"cache_read":0.2},"canonical_model_id":"mistral/mistral-large"},"mistralai/mistral-medium-3.5:thinking":{"id":"mistralai/mistral-medium-3.5:thinking","name":"Mistral Medium 3.5 Thinking","description":"Mistral Medium 3.5 with reasoning enabled by default (reasoning_effort=high), for complex coding, agentic, and multi-step reasoning prompts.","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":32768},"cost":{"input":1.5,"output":7.5,"cache_read":0.75}},"mistralai/devstral-small-2505":{"id":"mistralai/devstral-small-2505","name":"Mistral Devstral Small 2505","description":"OpenHands+Devstral is 100% local 100% open, and is SOTA for the category on SWE-Bench Verified: 46.8% accuracy.","family":"devstral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-08-02","last_updated":"2025-08-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":8192},"cost":{"input":0.06,"output":0.06,"cache_read":0.03}},"mistralai/devstral-2-123b-instruct-2512":{"id":"mistralai/devstral-2-123b-instruct-2512","name":"Devstral 2 123B","description":"Mistral coding agent model for repository tasks and software engineering workflows","family":"devstral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.4,"output":1.4,"cache_read":0.2}},"mistralai/mistral-medium-3":{"id":"mistralai/mistral-medium-3","name":"Mistral Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.4,"output":2,"cache_read":0.2},"canonical_model_id":"mistral/mistral-medium-3"},"mistralai/ministral-14b-instruct-2512":{"id":"mistralai/ministral-14b-instruct-2512","name":"Ministral 3 14B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.05}},"mistralai/ministral-14b-2512":{"id":"mistralai/ministral-14b-2512","name":"Ministral 14B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.2,"output":0.2,"cache_read":0.1},"canonical_model_id":"mistral/ministral-14b-2512"},"mistralai/mistral-small-3.1-24b-instruct":{"id":"mistralai/mistral-small-3.1-24b-instruct","name":"Mistral Small 3.1 24B (2503)","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-03-17","last_updated":"2025-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":102400},"cost":{"input":0.1,"output":0.3,"cache_read":0.05},"canonical_model_id":"mistral/mistral-small-3.1-24b-instruct"},"mistralai/ministral-3b-2512":{"id":"mistralai/ministral-3b-2512","name":"Ministral 3B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.1,"output":0.1,"cache_read":0.05},"canonical_model_id":"mistral/ministral-3b-2512"},"mistralai/mistral-nemo-instruct-2407":{"id":"mistralai/mistral-nemo-instruct-2407","name":"Mistral Nemo","description":"12B parameter model with multilingual support.","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.1003,"output":0.1207,"cache_read":0.05015}},"mistralai/codestral-2508":{"id":"mistralai/codestral-2508","name":"Codestral 2508","description":"Mistral code model for low-latency completion, fill-in-the-middle, and code generation","family":"codestral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":32768},"cost":{"input":0.3,"output":0.9,"cache_read":0.15},"canonical_model_id":"mistral/codestral-2508"},"sakana/fugu-max":{"id":"sakana/fugu-max","name":"Fugu Max","description":"Multi-agent model for routing expert agents across complex analytical tasks","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"sakana/fugu-max"},"sakana/fugu-ultra":{"id":"sakana/fugu-ultra","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":16384},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"sakana/fugu-ultra"},"sakana/fugu-ultra-v1.1":{"id":"sakana/fugu-ultra-v1.1","name":"Fugu Ultra v1.1","description":"Sakana AI's upgraded Fugu Ultra release with stronger coding, agentic task execution, and advanced reasoning through dynamic orchestration of frontier models.","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":16384},"cost":{"input":5,"output":30,"cache_read":0.5}},"inclusionai/ling-3.0-flash":{"id":"inclusionai/ling-3.0-flash","name":"Ling 3.0 Flash","description":"Hybrid-linear MoE reasoning model with 124B total and 5.1B active parameters for efficient agents","family":"ling","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-23","last_updated":"2026-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.075,"output":0.22,"cache_read":0.015},"canonical_model_id":"inclusionai/ling-3.0-flash"},"inclusionai/ling-3.1-flash":{"id":"inclusionai/ling-3.1-flash","name":"Ling 3.1 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.075,"output":0.22,"cache_read":0.015},"canonical_model_id":"inclusionai/ling-3.1-flash"},"inclusionai/ling-3.0-flash-vl":{"id":"inclusionai/ling-3.0-flash-vl","name":"Ling 3.0 Flash VL","description":"Native multimodal hybrid MoE model for image and video understanding, reasoning, and visual agents","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.06,"output":0.18,"cache_read":0.012},"canonical_model_id":"inclusionai/ling-3.0-flash-vl"},"inclusionai/ling-3.0-flash:thinking":{"id":"inclusionai/ling-3.0-flash:thinking","name":"Ling 3.0 Flash Thinking","description":"Hybrid-linear MoE reasoning model with 124B total and 5.1B active parameters for efficient agents","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-23","last_updated":"2026-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.075,"output":0.22,"cache_read":0.015},"canonical_model_id":"inclusionai/ling-3.0-flash"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":943718},"cost":{"input":2,"output":10,"cache_read":0.2},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.7-code-highspeed":{"id":"moonshotai/kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code High-Speed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":1.9,"output":8,"cache_read":0.32},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.5,"output":2.6,"cache_read":0.125},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2.5:thinking":{"id":"moonshotai/kimi-k2.5:thinking","name":"Kimi K2.5 Thinking","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.375,"output":2,"cache_read":0.07},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/kimi-k2-thinking":{"id":"moonshotai/kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Thinking Kimi model for slower research passes, planning, and hard technical questions","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":98304},"cost":{"input":0.6,"output":2.5,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"moonshotai/kimi-k2.5":{"id":"moonshotai/kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.375,"output":2,"cache_read":0.07},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/kimi-k2-instruct":{"id":"moonshotai/kimi-k2-instruct","name":"Kimi K2 Instruct","description":"Non-thinking Kimi K2 MoE instruction model for coding and tool-using agents","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":8192},"cost":{"input":0.4,"output":1.8,"cache_read":0.2},"canonical_model_id":"moonshotai/kimi-k2-instruct"},"moonshotai/kimi-k2.6:thinking":{"id":"moonshotai/kimi-k2.6:thinking","name":"Kimi K2.6 Thinking","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.5,"output":2.6,"cache_read":0.125},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2-instruct-0711":{"id":"moonshotai/kimi-k2-instruct-0711","name":"Kimi K2 0711","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.4,"output":1.8,"cache_read":0.2}},"moonshotai/kimi-latest":{"id":"moonshotai/kimi-latest","name":"Kimi Latest","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-03","last_updated":"2026-05-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":943718},"cost":{"input":2,"output":10,"cache_read":0.2}},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.6712,"output":3.35,"cache_read":0.18},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"moonshotai/Kimi-K2-Instruct-0905":{"id":"moonshotai/Kimi-K2-Instruct-0905","name":"Kimi K2 0905","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2025-09-25","last_updated":"2025-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":100352},"cost":{"input":0.4,"output":1.8,"cache_read":0.2}},"THUDM/GLM-Z1-9B-0414":{"id":"THUDM/GLM-Z1-9B-0414","name":"GLM Z1 9B 0414","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm-z","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-04-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"input":32000,"output":8000},"cost":{"input":0.2,"output":0.2,"cache_read":0.1}},"THUDM/GLM-4-9B-0414":{"id":"THUDM/GLM-4-9B-0414","name":"GLM 4 9B 0414","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-04-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"input":32000,"output":8000},"cost":{"input":0.2,"output":0.2,"cache_read":0.1}},"THUDM/GLM-4-32B-0414":{"id":"THUDM/GLM-4-32B-0414","name":"GLM 4 32B 0414","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-04-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":0.2,"output":0.2,"cache_read":0.1}},"nvidia/nemotron-3-nano-30b-a3b":{"id":"nvidia/nemotron-3-nano-30b-a3b","name":"Nvidia Nemotron 3 Nano 30B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":235929},"cost":{"input":0.17,"output":0.68,"cache_read":0.085},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"nvidia/nemotron-3.5-lightning":{"id":"nvidia/nemotron-3.5-lightning","name":"Nvidia Nemotron 3.5 Lightning","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":65536},"cost":{"input":0.05,"output":0.2,"cache_read":0.01},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/Llama-3.3-Nemotron-Super-49B-v1":{"id":"nvidia/Llama-3.3-Nemotron-Super-49B-v1","name":"Nvidia Nemotron Super 49B","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-08-08","last_updated":"2025-08-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":0.15,"output":0.15,"cache_read":0.075},"canonical_model_id":"nvidia/llama-3.3-nemotron-super-49b-v1"},"nvidia/nemotron-3-super-120b-a12b":{"id":"nvidia/nemotron-3-super-120b-a12b","name":"Nvidia Nemotron 3 Super 120B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-03-01","last_updated":"2026-03-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.05,"output":0.25,"cache_read":0.025},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"nvidia/nemotron-3.5-super-vl":{"id":"nvidia/nemotron-3.5-super-vl","name":"Nvidia Nemotron 3.5 Super VL","description":"NVIDIA’s open-weight 120B model (12B active) for reasoning, coding, tool use, document and GUI understanding, and video understanding. Text, images and video in; text out. Served in NVFP4 with a 262,144-token shared context window. NanoGPT currently limits responses to 16,384 tokens while separate hosted output limits remain unpublished. OpenMDW 1.1 license.","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.15,"output":0.5,"cache_read":0.02}},"nvidia/nemotron-3-ultra-550b-a55b":{"id":"nvidia/nemotron-3-ultra-550b-a55b","name":"Nvidia Nemotron 3 Ultra 550B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":65536},"cost":{"input":0.5,"output":2.5,"cache_read":0.25},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/nemotron-3-super-120b-a12b:thinking":{"id":"nvidia/nemotron-3-super-120b-a12b:thinking","name":"Nvidia Nemotron 3 Super 120B Thinking","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-03-01","last_updated":"2026-03-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.05,"output":0.25,"cache_read":0.025},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"nvidia/nemotron-3-ultra-550b-a55b:thinking":{"id":"nvidia/nemotron-3-ultra-550b-a55b:thinking","name":"Nvidia Nemotron 3 Ultra 550B Thinking","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":65536},"cost":{"input":0.5,"output":2.5,"cache_read":0.25},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/nemotron-3.5-content-safety":{"id":"nvidia/nemotron-3.5-content-safety","name":"Nemotron 3.5 Content Safety","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.05,"output":0.15,"cache_read":0.025},"canonical_model_id":"nvidia/nemotron-3.5-content-safety"},"nvidia/Llama-3.1-Nemotron-70B-Instruct-HF":{"id":"nvidia/Llama-3.1-Nemotron-70B-Instruct-HF","name":"Nvidia Nemotron 70b","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-04-15","last_updated":"2025-04-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.357,"output":0.408,"cache_read":0.1785},"canonical_model_id":"nvidia/llama-3.1-nemotron-70b-instruct"},"nvidia/nemotron-3.5-lightning:thinking":{"id":"nvidia/nemotron-3.5-lightning:thinking","name":"Nvidia Nemotron 3.5 Lightning Thinking","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":65536},"cost":{"input":0.05,"output":0.2,"cache_read":0.01},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"xiaomi/mimo-v2.5-pro:thinking":{"id":"xiaomi/mimo-v2.5-pro:thinking","name":"MiMo V2.5 Pro Thinking","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036,"cache_write":0},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"xiaomi/mimo-v2.6-pro":{"id":"xiaomi/mimo-v2.6-pro","name":"MiMo V2.6 Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036,"cache_write":0},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"xiaomi/mimo-v2.5":{"id":"xiaomi/mimo-v2.5","name":"MiMo V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028,"cache_write":0},"canonical_model_id":"xiaomi/mimo-v2.5"},"xiaomi/mimo-v2.6-flash-uncensored:thinking":{"id":"xiaomi/mimo-v2.6-flash-uncensored:thinking","name":"MiMo V2.6 Flash Uncensored Thinking","description":"MiMo V2.6 Flash Uncensored with maximum thinking enabled. Supports a 1M-token context window and tool calling.","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-09-26","last_updated":"2026-09-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.5,"output":1.5,"cache_read":0.1995}},"xiaomi/mimo-v2.6-pro-ultraspeed":{"id":"xiaomi/mimo-v2.6-pro-ultraspeed","name":"MiMo V2.6 Pro UltraSpeed","description":"MiMo pro model for strong multimodal reasoning and agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":4.35,"output":8.7,"cache_read":0.036,"cache_write":0},"canonical_model_id":"xiaomi/mimo-v2.6-pro-ultraspeed"},"xiaomi/mimo-v2.5:thinking":{"id":"xiaomi/mimo-v2.5:thinking","name":"MiMo V2.5 Thinking","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028,"cache_write":0},"canonical_model_id":"xiaomi/mimo-v2.5"},"xiaomi/mimo-v2.5-pro":{"id":"xiaomi/mimo-v2.5-pro","name":"MiMo V2.5 Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036,"cache_write":0},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"xiaomi/mimo-v2.6-flash":{"id":"xiaomi/mimo-v2.6-flash","name":"MiMo V2.6 Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028,"cache_write":0},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"xiaomi/mimo-v2.6-flash-abliterated":{"id":"xiaomi/mimo-v2.6-flash-abliterated","name":"MiMo V2.6 Flash Abliterated","description":"A MiMo V2.6 Flash finetune with refusal-direction ablation, image input, a 1M-token context window, separate reasoning output, and tool calling.","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-09-25","last_updated":"2026-09-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.5,"output":1.5,"cache_read":0.275}},"xiaomi/mimo-v2.6-flash-uncensored":{"id":"xiaomi/mimo-v2.6-flash-uncensored","name":"MiMo V2.6 Flash Uncensored","description":"A text-only, lower-refusal MiMo V2.6 Flash finetune served by Heabsy with a 1M-token context window, separate reasoning output, and tool calling.","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-09-25","last_updated":"2026-09-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.5,"output":1.5,"cache_read":0.1995}},"undi95/remm-slerp-l2-13b":{"id":"undi95/remm-slerp-l2-13b","name":"ReMM SLERP 13B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-06-30","release_date":"2023-07-22","last_updated":"2023-07-22","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":6144,"input":6144,"output":4096},"cost":{"input":0.799,"output":1.207,"cache_read":0.3995},"canonical_model_id":"undi95/remm-slerp-l2-13b"},"Salesforce/Llama-xLAM-2-70b-fc-r":{"id":"Salesforce/Llama-xLAM-2-70b-fc-r","name":"Llama-xLAM-2 70B fc-r","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-04-13","last_updated":"2025-04-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":2.5,"output":2.5,"cache_read":1.25}},"minimax/minimax-latest":{"id":"minimax/minimax-latest","name":"MiniMax Latest","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"release_date":"2026-05-03","last_updated":"2026-05-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"input":512000,"output":80000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06}},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"input":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.15},"canonical_model_id":"minimax/MiniMax-M2.5"},"minimax/minimax-m2.7-turbo":{"id":"minimax/minimax-m2.7-turbo","name":"MiniMax M2.7 Turbo","description":"Efficient MiniMax model for quick assistance, coding, and routine automation","family":"minimax-m2.7","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"input":204800,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.3}},"minimax/minimax-01":{"id":"minimax/minimax-01","name":"MiniMax 01","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-01-15","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000192,"input":1000192,"output":16384},"cost":{"input":0.1394,"output":1.122,"cache_read":0.0697}},"minimax/minimax-m2-her":{"id":"minimax/minimax-m2-her","name":"MiniMax M2-her","description":"MiniMax M2 variant tuned for conversational and character-driven agent interactions","family":"minimax","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-01-23","last_updated":"2026-01-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":65532,"input":65532,"output":2048},"cost":{"input":0.302,"output":1.207,"cache_read":0.151},"canonical_model_id":"minimax/MiniMax-M2-Her"},"minimax/minimax-m2.7":{"id":"minimax/minimax-m2.7","name":"MiniMax M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"input":204800,"output":131072},"cost":{"input":0.315,"output":1.26,"cache_read":0.1575},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/minimax-m3:thinking":{"id":"minimax/minimax-m3:thinking","name":"MiniMax M3 Thinking","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"input":512000,"output":80000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"input":512000,"output":80000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"minimax/minimax-m2.1":{"id":"minimax/minimax-m2.1","name":"MiniMax M2.1","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":131072},"cost":{"input":0.33,"output":1.32,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.1"},"minimax/minimax-m2":{"id":"minimax/minimax-m2","name":"MiniMax M2","description":"Efficient open MiniMax model built for coding agents and tool-heavy workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":131072},"cost":{"input":0.17,"output":1.53,"cache_read":0.085},"canonical_model_id":"minimax/MiniMax-M2"},"inflatebot/MN-12B-Mag-Mell-R1":{"id":"inflatebot/MN-12B-Mag-Mell-R1","name":"Mag Mell R1","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"soob3123/Veiled-Calla-12B":{"id":"soob3123/Veiled-Calla-12B","name":"Veiled Calla 12B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-04-13","last_updated":"2025-04-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":8192},"cost":{"input":0.3,"output":0.3,"cache_read":0.15}},"soob3123/amoral-gemma3-27B-v2":{"id":"soob3123/amoral-gemma3-27B-v2","name":"Amoral Gemma3 27B v2","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-05-23","last_updated":"2025-05-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":8192},"cost":{"input":0.3,"output":0.3,"cache_read":0.15}},"stepfun/step-5-preview":{"id":"stepfun/step-5-preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":1000000},"cost":{"input":1,"output":2.7,"cache_read":0.05},"canonical_model_id":"stepfun/step-5-preview"},"stepfun/step-3.7-flash:thinking":{"id":"stepfun/step-3.7-flash:thinking","name":"Step 3.7 Flash Thinking","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":256000},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"Sao10K/L3.1-70B-Hanami-x1":{"id":"Sao10K/L3.1-70B-Hanami-x1","name":"Llama 3.1 70B Hanami","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"Sao10K/L3.1-70B-Euryale-v2.2":{"id":"Sao10K/L3.1-70B-Euryale-v2.2","name":"Llama 3.1 70B Euryale","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":20480,"input":20480,"output":16384},"cost":{"input":0.306,"output":0.357,"cache_read":0.153}},"Sao10K/L3.3-70B-Euryale-v2.3":{"id":"Sao10K/L3.3-70B-Euryale-v2.3","name":"Llama 3.3 70B Euryale","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":20480,"input":20480,"output":16384},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"Sao10K/L3-8B-Stheno-v3.2":{"id":"Sao10K/L3-8B-Stheno-v3.2","name":"Sao10K Stheno 8b","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-11-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.2006,"output":0.2006,"cache_read":0.1003}},"inception/mercury-2.5-preview":{"id":"inception/mercury-2.5-preview","name":"Mercury 2.5 Preview","description":"Mercury 2.5 Preview is Inception's latest and most intelligent diffusion language model. Instead of generating tokens strictly one at a time, it produces and refines multiple tokens in parallel, reaching up to 1,107 tokens per second on standard GPUs. It delivers a 10+ point intelligence gain over Mercury 2, with tunable reasoning, parallel tool calls, schema-aligned JSON output, and a 260K context window. It is built for latency-sensitive production work such as search agents, voice pipelines, customer support, rapid coding iteration, and coding subagents.","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":260000,"input":260000,"output":65536},"cost":{"input":0.04,"output":0.15,"cache_read":0.004}},"ornith-ai/ornith-1.5-35b-a3b":{"id":"ornith-ai/ornith-1.5-35b-a3b","name":"Ornith 1.5 35B","description":"Ornith 1.5 35B A3B is an open-weight mixture-of-experts model for agentic coding, tool use, image understanding, and long-context work. This variant disables thinking for faster direct responses.","family":"ornith","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-07-29","last_updated":"2026-08-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.05}},"ornith-ai/ornith-1.5-35b-a3b:thinking":{"id":"ornith-ai/ornith-1.5-35b-a3b:thinking","name":"Ornith 1.5 35B Thinking","description":"Ornith 1.5 35B A3B is an open-weight mixture-of-experts model for agentic coding, reasoning, tool use, image understanding, and long-context work. This variant enables thinking by default.","family":"ornith","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-07-29","last_updated":"2026-08-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.05}},"amazon/nova-lite-v1":{"id":"amazon/nova-lite-v1","name":"Amazon Nova Lite 1.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"input":300000,"output":5120},"cost":{"input":0.0595,"output":0.238,"cache_read":0.02975},"canonical_model_id":"amazon/nova-lite-v1"},"amazon/nova-2-lite-v1":{"id":"amazon/nova-2-lite-v1","name":"Amazon Nova 2 Lite","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":65535},"cost":{"input":0.51,"output":4.25,"cache_read":0.255},"canonical_model_id":"amazon/nova-2-lite-v1"},"amazon/nova-pro-v1":{"id":"amazon/nova-pro-v1","name":"Amazon Nova Pro 1.0","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"input":300000,"output":32000},"cost":{"input":0.799,"output":3.196,"cache_read":0.3995},"canonical_model_id":"amazon/nova-pro-v1"},"Doctor-Shotgun/MS3.2-24B-Magnum-Diamond":{"id":"Doctor-Shotgun/MS3.2-24B-Magnum-Diamond","name":"MS3.2 24B Magnum Diamond","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":32768},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"aion-labs/aion-2.0":{"id":"aion-labs/aion-2.0","name":"AionLabs: Aion-2.0","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.8,"output":1.6,"cache_read":0.2},"canonical_model_id":"aion-labs/aion-2.0"},"aion-labs/aion-rp-llama-3.1-8b":{"id":"aion-labs/aion-rp-llama-3.1-8b","name":"Llama 3.1 8b (uncensored)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12-31","release_date":"2025-02-04","last_updated":"2025-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":0.8,"output":1.6,"cache_read":0.4},"canonical_model_id":"aion-labs/aion-rp-llama-3.1-8b"},"aion-labs/aion-3.0":{"id":"aion-labs/aion-3.0","name":"AionLabs: Aion 3.0","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-07","last_updated":"2026-07-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":3,"output":6,"cache_read":0.75},"canonical_model_id":"aion-labs/aion-3.0"},"aion-labs/aion-3.5":{"id":"aion-labs/aion-3.5","name":"AionLabs: Aion 3.5","description":"A GLM-family collaborative generation model tuned for immersive roleplay and storytelling, with stronger narrative structure, tension, conflict, and nuanced mature themes.","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":3,"output":6,"cache_read":0.75}},"aion-labs/aion-3.5-mini":{"id":"aion-labs/aion-3.5-mini","name":"AionLabs: Aion 3.5 Mini","description":"A GLM-family collaborative generation model tuned for immersive roleplay and storytelling, with stronger narrative structure, tension, conflict, and nuanced mature themes.","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.7,"output":1.4,"cache_read":0.18}},"aion-labs/aion-3.0-mini":{"id":"aion-labs/aion-3.0-mini","name":"AionLabs: Aion 3.0 Mini","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-07","last_updated":"2026-07-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.7,"output":1.4,"cache_read":0.18},"canonical_model_id":"aion-labs/aion-3.0-mini"},"qwen/qwen3.5-flash":{"id":"qwen/qwen3.5-flash","name":"Qwen3.5 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":991808,"input":991808,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.5-flash"},"qwen/qwen3.8-max:thinking":{"id":"qwen/qwen3.8-max:thinking","name":"Qwen3.8 Max Thinking","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":991000,"input":991000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"qwen/qwen3-vl-235b-a22b-instruct":{"id":"qwen/qwen3-vl-235b-a22b-instruct","name":"Qwen3 VL 235B A22B Instruct","description":"Qwen vision-language instruct model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.3,"output":1.9,"cache_read":0.15},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":65536},"cost":{"input":2.5,"output":7.5,"cache_read":0.5,"cache_write":3.125},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1001536,"input":1001536,"output":32768},"cost":{"input":0.15,"output":0.7,"cache_read":0.04},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3-vl-235b-a22b-thinking":{"id":"qwen/qwen3-vl-235b-a22b-thinking","name":"Qwen3 VL 235B A22B Thinking","description":"Qwen vision-language thinking model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-thinking"},"qwen/qwen3.8-27b-kiwen":{"id":"qwen/qwen3.8-27b-kiwen","name":"Qwen 3.8 27B Kiwen","description":"Qwen 3.8 27B Kiwen is a creative finetune served by Aoru in NVFP4 with a 262,144-token context window. It supports image understanding, tool calling, and optional reasoning.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.6,"cache_read":0.05}},"qwen/qwen3.5-27b":{"id":"qwen/qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":260096,"input":260096,"output":65536},"cost":{"input":0.27,"output":2.16,"cache_read":0.135},"canonical_model_id":"alibaba/qwen3.5-27b"},"qwen/qwen3.5-omni-plus":{"id":"qwen/qwen3.5-omni-plus","name":"Qwen3.5 Omni Plus","description":"Qwen3.5 Omni Plus is Qwen's stronger general multimodal model. We verified live support for text prompts, images, audio files, and direct video URLs on Alibaba's chat-completions-compatible API. Alibaba describes Plus as a comprehensive evolution of Qwen3 Omni with support for over 10 hours of audio input.","family":"qwen3.5","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-03-30","last_updated":"2026-03-30","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"input":983616,"output":65536}},"qwen/qwen3.7-flash:thinking":{"id":"qwen/qwen3.7-flash:thinking","name":"Qwen3.7 Flash Thinking","description":"Lightweight multimodal Qwen model for high-throughput text, image, and video tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"input":983616,"output":65536},"cost":{"input":0.03,"output":0.13,"cache_read":0.006,"cache_write":0.038},"canonical_model_id":"alibaba/qwen3.7-flash"},"qwen/qwen3-235b-a22b-instruct-2507":{"id":"qwen/qwen3-235b-a22b-instruct-2507","name":"Qwen 3 235b A22B 2507","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.13,"output":0.5,"cache_read":0.065},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"qwen/qwen-max":{"id":"qwen/qwen-max","name":"Qwen 2.5 Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-03","last_updated":"2025-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"input":32000,"output":8192},"cost":{"input":1.5997,"output":6.392,"cache_read":0.79985},"canonical_model_id":"alibaba/qwen-max"},"qwen/qwen3-next-80b-a3b-thinking":{"id":"qwen/qwen3-next-80b-a3b-thinking","name":"Qwen3 Next 80B A3B (Thinking)","description":"Efficient Qwen thinking model for local reasoning, math, and coding agents","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":32768},"cost":{"input":0.15,"output":0.65,"cache_read":0.075},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-thinking"},"qwen/qwen3.8-max":{"id":"qwen/qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":991000,"input":991000,"output":65536},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"qwen/qwen3-coder-next":{"id":"qwen/qwen3-coder-next","name":"Qwen3 Coder Next","description":"Open-weight Qwen coding model for agents, repository edits, and multi-turn tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.250251,"output":0.80293,"cache_read":0.079764},"canonical_model_id":"alibaba/qwen3-coder-next"},"qwen/qwen3-coder":{"id":"qwen/qwen3-coder","name":"Qwen 3 Coder 480B","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"input":262000,"output":65536},"cost":{"input":0.13,"output":0.5,"cache_read":0.065}},"qwen/qwen3.5-35b-a3b:thinking":{"id":"qwen/qwen3.5-35b-a3b:thinking","name":"Qwen3.5 35B A3B Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":260096,"input":260096,"output":65536},"cost":{"input":0.225,"output":1.8,"cache_read":0.1125},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"qwen/qwen3.5-plus":{"id":"qwen/qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"input":983616,"output":65536},"cost":{"input":0.4,"output":2.4,"cache_read":0.04},"canonical_model_id":"alibaba/qwen3.5-plus"},"qwen/qwen3.8-27b-swift":{"id":"qwen/qwen3.8-27b-swift","name":"Qwen 3.8 27B Swift","description":"Qwen 3.8 27B Swift is a finetune for fast responses, served by Aoru in NVFP4 with a 262,144-token context window. It supports image understanding, tool calling, and optional reasoning.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.6,"cache_read":0.05}},"qwen/qwen3.8-27b-fimi":{"id":"qwen/qwen3.8-27b-fimi","name":"Qwen 3.8 27B Fimi","description":"Qwen 3.8 27B Fimi is a creative finetune served by Aoru in NVFP4 with a 262,144-token context window. It supports image understanding, tool calling, and optional reasoning.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.6,"cache_read":0.05}},"qwen/qwen3-32b":{"id":"qwen/qwen3-32b","name":"Qwen 3 32b","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":41000,"input":41000,"output":32768},"cost":{"input":0.1,"output":0.3,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3-32b"},"qwen/qwen3.8-27b-kimiko":{"id":"qwen/qwen3.8-27b-kimiko","name":"Qwen 3.8 27B Kimiko","description":"Qwen 3.8 27B Kimiko is a creative finetune served by Aoru in NVFP4 with a 262,144-token context window. It supports image understanding, tool calling, and optional reasoning.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.6,"cache_read":0.05}},"qwen/qwen-plus":{"id":"qwen/qwen-plus","name":"Qwen Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":995904,"input":995904,"output":32768},"cost":{"input":0.3995,"output":1.2002,"cache_read":0.19975},"canonical_model_id":"alibaba/qwen-plus"},"qwen/qwen3.7-flash":{"id":"qwen/qwen3.7-flash","name":"Qwen3.7 Flash","description":"Lightweight multimodal Qwen model for high-throughput text, image, and video tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":991808,"input":991808,"output":65536},"cost":{"input":0.03,"output":0.13,"cache_read":0.006,"cache_write":0.038},"canonical_model_id":"alibaba/qwen3.7-flash"},"qwen/qwen3-max":{"id":"qwen/qwen3-max","name":"Qwen3 Max","description":"Flagship Qwen3 model for coding agents, complex reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":32768},"cost":{"input":1.2002,"output":6.001,"cache_read":0.6001},"canonical_model_id":"alibaba/qwen3-max"},"qwen/qwen3.8-27b-obliterated:thinking":{"id":"qwen/qwen3.8-27b-obliterated:thinking","name":"Qwen 3.8 27B Obliterated Thinking","description":"Qwen 3.8 27B Obliterated with thinking enabled for more deliberate creative work, coding, multimodal analysis, tool use, and long-context problem solving.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-07-29","last_updated":"2026-08-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"input":524288,"output":32768},"cost":{"input":0.25,"output":1.75,"cache_read":0.225}},"qwen/qwen3.8-27b-antislop":{"id":"qwen/qwen3.8-27b-antislop","name":"Qwen 3.8 27B Antislop","description":"Qwen 3.8 27B Antislop is a creative finetune served by Aoru in NVFP4 with a 262,144-token context window. It supports image understanding, tool calling, and optional reasoning.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.6,"cache_read":0.05}},"qwen/qwen-turbo":{"id":"qwen/qwen-turbo","name":"Qwen Turbo","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2024-11-01","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":8192},"cost":{"input":0.04998,"output":0.2006,"cache_read":0.02499},"canonical_model_id":"alibaba/qwen-turbo"},"qwen/qwen3-coder-30b-a3b-instruct":{"id":"qwen/qwen3-coder-30b-a3b-instruct","name":"Qwen3 Coder 30B A3B Instruct","description":"Smaller Qwen coder for efficient local agents and repo-level fixes","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"qwen/qwen3.8-27b:thinking":{"id":"qwen/qwen3.8-27b:thinking","name":"Qwen3.8 27B Thinking","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1001536,"input":1001536,"output":32768},"cost":{"input":0.15,"output":0.7,"cache_read":0.04},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3.8-27b-obliterated":{"id":"qwen/qwen3.8-27b-obliterated","name":"Qwen 3.8 27B Obliterated","description":"Qwen 3.8 27B Obliterated is an open-weight multimodal model LoRA-tuned for fewer refusals across chat, coding, reasoning, tool use, and long-context work.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-07-29","last_updated":"2026-08-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"input":524288,"output":32768},"cost":{"input":0.25,"output":1.75,"cache_read":0.225}},"qwen/qwen3.8-omni-flash":{"id":"qwen/qwen3.8-omni-flash","name":"Qwen3.8 Omni Flash","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":991808,"input":991808,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-omni-flash"},"qwen/qwen3.8-27b-uncensored":{"id":"qwen/qwen3.8-27b-uncensored","name":"Qwen 3.8 27B Uncensored","description":"Qwen 3.8 27B Uncensored is an NVFP4 open-weight multimodal model LoRA-tuned for fewer refusals across chat, coding, reasoning, tool use, and long-context work.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-07-29","last_updated":"2026-08-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1010000,"input":1010000,"output":32768},"cost":{"input":1,"output":3,"cache_read":0.22}},"qwen/qwen3.7-max:thinking":{"id":"qwen/qwen3.7-max:thinking","name":"Qwen3.7 Max Thinking","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":65536},"cost":{"input":2.5,"output":7.5,"cache_read":0.5,"cache_write":3.125},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen3-235b-a22b":{"id":"qwen/qwen3-235b-a22b","name":"Qwen 3 235b A22B","description":"Large open Qwen MoE for multilingual reasoning, coding, and tool use","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.3,"output":0.5,"cache_read":0.15},"canonical_model_id":"alibaba/qwen3-235b-a22b"},"qwen/qwen3.5-122b-a10b":{"id":"qwen/qwen3.5-122b-a10b","name":"Qwen3.5 122B A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.437,"output":3.496,"cache_read":0.103788},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"qwen/qwen3.8-27b-uncensored:thinking":{"id":"qwen/qwen3.8-27b-uncensored:thinking","name":"Qwen 3.8 27B Uncensored Thinking","description":"Qwen 3.8 27B Uncensored with thinking enabled for more deliberate creative work, coding, multimodal analysis, tool use, and long-context problem solving.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-07-29","last_updated":"2026-08-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1010000,"input":1010000,"output":32768},"cost":{"input":1,"output":3,"cache_read":0.22}},"qwen/qwen3.5-omni-flash":{"id":"qwen/qwen3.5-omni-flash","name":"Qwen3.5 Omni Flash","description":"Qwen3.5 Omni Flash is Qwen's fast multimodal model. We verified live support for text prompts, images, audio files, and direct video URLs on Alibaba's chat-completions-compatible API. Alibaba describes Flash as a fully evolved version of Qwen3 Omni with audio input support across 60+ languages.","family":"qwen3.5","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-03-30","last_updated":"2026-03-30","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":49152,"input":49152,"output":16384}},"qwen/qwen3.6-35b-a3b":{"id":"qwen/qwen3.6-35b-a3b","name":"Qwen3.6 35B A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.112,"output":0.8,"cache_read":0.056},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"qwen/qwen3-next-80b-a3b-instruct":{"id":"qwen/qwen3-next-80b-a3b-instruct","name":"Qwen3 Next 80B A3B (Instruct)","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":1.1,"cache_read":0.07},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"qwen/qwen3-max-2026-01-23":{"id":"qwen/qwen3-max-2026-01-23","name":"Qwen3 Max 2026-01-23","description":"Qwen3 Max is Alibaba's flagship Qwen 3 reasoning model with native tool use (web search, web extractor, code interpreter) and a 256K context window.","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-01-26","last_updated":"2026-01-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":32768},"cost":{"input":1.2002,"output":6.001,"cache_read":0.6001}},"qwen/qwen3.8-27b-fable":{"id":"qwen/qwen3.8-27b-fable","name":"Qwen 3.8 27B Fable","description":"Qwen 3.8 27B Fable is an open-weight multimodal creative finetune for expressive dialogue, long-form storytelling, character work, and roleplay.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-08-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"input":524288,"output":32768},"cost":{"input":0.25,"output":1.5,"cache_read":0.125}},"qwen/qwen3.8-27b-hemmingway":{"id":"qwen/qwen3.8-27b-hemmingway","name":"Qwen 3.8 27B Hemingway","description":"Qwen 3.8 27B Hemingway is an open-weight NVFP4 multimodal creative finetune for long-form prose, character dialogue, storytelling, and roleplay.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.25,"output":1.5,"cache_read":0.125}},"qwen/qwen3.6-flash":{"id":"qwen/qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":991808,"input":991808,"output":65536},"cost":{"input":0.19,"output":1.16,"cache_read":0.02,"cache_write":0.24},"canonical_model_id":"alibaba/qwen3.6-flash"},"qwen/qwen3-coder-flash":{"id":"qwen/qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":0.3,"output":1.5,"cache_read":0.15},"canonical_model_id":"alibaba/qwen3-coder-flash"},"qwen/qwen3.5-plus:thinking":{"id":"qwen/qwen3.5-plus:thinking","name":"Qwen3.5 Plus Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"input":983616,"output":65536},"cost":{"input":0.4,"output":2.4,"cache_read":0.04},"canonical_model_id":"alibaba/qwen3.5-plus"},"qwen/qwen3.8-27b-darkidol":{"id":"qwen/qwen3.8-27b-darkidol","name":"Qwen 3.8 27B DarkIdol","description":"Qwen 3.8 27B DarkIdol is a creative finetune served by Aoru in NVFP4 with a 262,144-token context window. It supports image understanding, tool calling, and optional reasoning.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.6,"cache_read":0.05}},"qwen/qwen3.5-9b":{"id":"qwen/qwen3.5-9b","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":81920}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.05,"output":0.15,"cache_read":0.025},"canonical_model_id":"alibaba/qwen3.5-9b"},"qwen/qwen3.5-122b-a10b:thinking":{"id":"qwen/qwen3.5-122b-a10b:thinking","name":"Qwen3.5 122B A10B Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.437,"output":3.496,"cache_read":0.103788},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"qwen/qwen3.5-397b-a17b:thinking":{"id":"qwen/qwen3.5-397b-a17b:thinking","name":"Qwen3.5 397B A17B Thinking","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.6,"output":3.6,"cache_read":0.3},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"qwen/qwen3.8-max-prime":{"id":"qwen/qwen3.8-max-prime","name":"Qwen3.8 Max Prime","description":"High-throughput edition of Qwen3.8 Max for coding, professional work, multimodal understanding, and long-running agent workflows","family":"qwen3.8-max","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":131072},"cost":{"input":4,"output":12,"cache_read":0.5},"canonical_model_id":"alibaba/qwen3.8-max-prime"},"qwen/qwen3.8-flash":{"id":"qwen/qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":991808,"input":991808,"output":131072},"cost":{"input":0.14,"output":0.42,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen/qwen3.8-27b-cybersecurity":{"id":"qwen/qwen3.8-27b-cybersecurity","name":"Qwen 3.8 27B Cybersecurity","description":"Qwen 3.8 27B Cybersecurity is a cybersecurity-focused variant based on the uncensored model, with provider moderation for illegal activities. It supports optional reasoning, image understanding, tool calling, and a 262,144-token context window.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-09-19","last_updated":"2026-09-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.6,"cache_read":0.05}},"qwen/qwen3.8-27b-novelist":{"id":"qwen/qwen3.8-27b-novelist","name":"Qwen 3.8 27B Novelist","description":"Qwen 3.8 27B Novelist is a creative finetune served by Aoru in NVFP4 with a 262,144-token context window. It supports image understanding, tool calling, and optional reasoning.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.6,"cache_read":0.05}},"qwen/qwen-long":{"id":"qwen/qwen-long","name":"Qwen Long 10M","description":"Alibaba's huge context window model. Takes in up to 10 million tokens, which is equivalent to dozens of books.","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-08-01","last_updated":"2024-08-01","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":10000000,"input":10000000,"output":8192},"cost":{"input":0.1003,"output":0.408,"cache_read":0.05015}},"qwen/qwen3.5-35b-a3b":{"id":"qwen/qwen3.5-35b-a3b","name":"Qwen3.5 35B A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":260096,"input":260096,"output":65536},"cost":{"input":0.225,"output":1.8,"cache_read":0.1125},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"qwen/qwen3.6-max-preview":{"id":"qwen/qwen3.6-max-preview","name":"Qwen3.6 Max Preview","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":245760,"input":245760,"output":65536},"cost":{"input":1.04,"output":6.24,"cache_read":0.52},"canonical_model_id":"alibaba/qwen3.6-max-preview"},"qwen/qwen3-30b-a3b":{"id":"qwen/qwen3-30b-a3b","name":"Qwen3 30B A3B","description":"Sparse MoE Qwen model with 3B active parameters for efficient chat and reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":41000,"input":41000,"output":32768},"cost":{"input":0.1,"output":0.3,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3-30b-a3b"},"qwen/qwen3.5-397b-a17b":{"id":"qwen/qwen3.5-397b-a17b","name":"Qwen3.5 397B A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.6,"output":3.6,"cache_read":0.3},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"qwen/qwen3-8b":{"id":"qwen/qwen3-8b","name":"Qwen 3 8B","description":"Qwen 3 8B is a 8B model. Supports switching between thinking and non thinking: trigger thinking with /think and /no_think anywhere in a prompt or system message to toggle chain-of-thought reasoning.","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":41000,"input":41000,"output":32768},"cost":{"input":0.47,"output":0.47,"cache_read":0.235}},"qwen/qwen3.5-27b:thinking":{"id":"qwen/qwen3.5-27b:thinking","name":"Qwen3.5 27B Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":260096,"input":260096,"output":65536},"cost":{"input":0.27,"output":2.16,"cache_read":0.135},"canonical_model_id":"alibaba/qwen3.5-27b"},"qwen/qwen3.8-27b-queen":{"id":"qwen/qwen3.8-27b-queen","name":"Qwen 3.8 27B Queen","description":"Qwen 3.8 27B Queen is an open-weight roleplay finetune with image understanding, tool calling, optional reasoning, and a 262,144-token context window.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-09-09","last_updated":"2026-09-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"input":524288,"output":32768},"cost":{"input":0.25,"output":1.5,"cache_read":0.125}},"qwen/qwen3.8-27b-synthia":{"id":"qwen/qwen3.8-27b-synthia","name":"Qwen 3.8 27B Synthia","description":"Qwen 3.8 27B Synthia is a text-only roleplay finetune served by Aoru in NVFP4 with a 262,144-token context window.","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.6,"cache_read":0.05}},"qwen/qwen3-30b-a3b-instruct-2507":{"id":"qwen/qwen3-30b-a3b-instruct-2507","name":"Qwen3 30B A3B Instruct 2507","description":"Qwen3-30B-A3B-Instruct-2507 is a 30.5B-parameter mixture-of-experts language model from Qwen, with 3.3B active parameters per inference. Significant improvements in general capabilities, including instruction following, logical reasoning, text comprehension, mathematics, science, coding and tool usage.","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-02-20","last_updated":"2025-02-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":32768},"cost":{"input":0.2,"output":0.5,"cache_read":0.1}},"qwen/qwen2.5-coder-32b-instruct":{"id":"qwen/qwen2.5-coder-32b-instruct","name":"Qwen 2.5 Coder 32b","description":"Open coding-focused Qwen model for code generation, repair, and repository reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2024-11-12","last_updated":"2024-11-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"input":32000,"output":8192},"cost":{"input":0.2006,"output":0.2006,"cache_read":0.1003},"canonical_model_id":"alibaba/qwen2.5-coder-32b-instruct"},"qwen/qwen3.7-plus:thinking":{"id":"qwen/qwen3.7-plus:thinking","name":"Qwen3.7 Plus Thinking","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"input":983616,"output":65536},"cost":{"input":0.4,"output":1.6,"cache_read":0.08,"cache_write":0.5},"canonical_model_id":"alibaba/qwen3.7-plus"},"qwen/qwen-2.5-72b-instruct":{"id":"qwen/qwen-2.5-72b-instruct","name":"Qwen2.5 72B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2025-07-03","last_updated":"2025-07-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":8192},"cost":{"input":0.357,"output":0.408,"cache_read":0.1785}},"qwen/qwen3.6-35b-a3b:thinking":{"id":"qwen/qwen3.6-35b-a3b:thinking","name":"Qwen3.6 35B A3B Thinking","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.112,"output":0.8,"cache_read":0.056},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"qwen/qwen3.6-27b":{"id":"qwen/qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.203,"output":2.24,"cache_read":0.1015},"canonical_model_id":"alibaba/qwen3.6-27b"},"qwen/qwen3.6-plus":{"id":"qwen/qwen3.6-plus","name":"Qwen 3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":991808,"input":991808,"output":65536},"cost":{"input":0.325,"output":1.95,"cache_read":0.0325,"cache_write":0.40625},"canonical_model_id":"alibaba/qwen3.6-plus"},"qwen/qwen3.6-27b:thinking":{"id":"qwen/qwen3.6-27b:thinking","name":"Qwen3.6 27B Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.203,"output":2.24,"cache_read":0.1015},"canonical_model_id":"alibaba/qwen3.6-27b"},"qwen/qwen3-14b":{"id":"qwen/qwen3-14b","name":"Qwen 3 14b","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":41000,"input":41000,"output":32768},"cost":{"input":0.08,"output":0.24,"cache_read":0.04}},"qwen/qwen3.7-plus":{"id":"qwen/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":991808,"input":991808,"output":65536},"cost":{"input":0.4,"output":1.6,"cache_read":0.08,"cache_write":0.5},"canonical_model_id":"alibaba/qwen3.7-plus"},"qwen/qwen3.5-flash:thinking":{"id":"qwen/qwen3.5-flash:thinking","name":"Qwen3.5 Flash Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":991808,"input":991808,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.5-flash"},"qwen/qwen3.8-max-0902":{"id":"qwen/qwen3.8-max-0902","name":"Qwen3.8 Max 0902","description":"2026-09-02 upgraded snapshot of Qwen3.8 Max with stronger coding, collaborative agents, and multimodal document understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":991808,"input":991808,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max-0902"},"failspy/Meta-Llama-3-70B-Instruct-abliterated-v3.5":{"id":"failspy/Meta-Llama-3-70B-Instruct-abliterated-v3.5","name":"Llama 3 70B abliterated","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-07-26","last_updated":"2025-07-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"input":8192,"output":8192},"cost":{"input":0.7,"output":0.7,"cache_read":0.35}},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT 5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-3.5-turbo":{"id":"openai/gpt-3.5-turbo","name":"GPT-3.5 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"input":16385,"output":4096},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"openai/gpt-3.5-turbo"},"openai/gpt-terra-latest":{"id":"openai/gpt-terra-latest","name":"GPT Terra Latest","description":"Compatibility alias that routes to GPT 5.6 Terra, the latest supported GPT Terra model.","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5}},"openai/gpt-6-astra-pro":{"id":"openai/gpt-6-astra-pro","name":"GPT 6 Astra Pro","description":"GPT 6 Astra in Pro reasoning mode. Uses additional model work for difficult tasks, with higher latency and token usage at the same per-token rates. Reasoning effort remains independently configurable.","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5}},"openai/o3-pro-2025-06-10":{"id":"openai/o3-pro-2025-06-10","name":"OpenAI o3-pro (2025-06-10)","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2024-01-01","last_updated":"2025-06-10","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":100000},"cost":{"input":22,"output":88,"cache_read":11}},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT 5.4 Nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-5.2-codex":{"id":"openai/gpt-5.2-codex","name":"GPT 5.2 Codex","description":"Code-specialist GPT for repository edits, reviews, and long-running software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-codex"},"openai/gpt-5.1-codex":{"id":"openai/gpt-5.1-codex","name":"GPT 5.1 Codex","description":"Codex GPT for repository edits, code review, and practical software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex"},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-chat-latest":{"id":"openai/gpt-chat-latest","name":"GPT Chat Latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-03","last_updated":"2026-05-03","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5}},"openai/gpt-5.6-sol-pro":{"id":"openai/gpt-5.6-sol-pro","name":"GPT 5.6 Sol Pro","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT 5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"openai/o4-mini":{"id":"openai/o4-mini","name":"OpenAI o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o4-mini"},"openai/o3-mini":{"id":"openai/o3-mini","name":"OpenAI o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT 5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT 4.1 Nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"input":1047576,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT 5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"openai/o1":{"id":"openai/o1","name":"OpenAI o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":100000},"cost":{"input":15,"output":60,"cache_read":7.5},"canonical_model_id":"openai/o1"},"openai/gpt-latest":{"id":"openai/gpt-latest","name":"GPT Latest","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-03-29","last_updated":"2026-03-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5}},"openai/gpt-5-pro":{"id":"openai/gpt-5-pro","name":"GPT 5 Pro","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":15,"output":120,"cache_read":1.5},"canonical_model_id":"openai/gpt-5-pro"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT 6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-4o-2024-08-06":{"id":"openai/gpt-4o-2024-08-06","name":"GPT-4o (2024-08-06)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-09","release_date":"2024-08-06","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-08-06"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT 6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"openai/gpt-6-astra"},"openai/gpt-luna-latest":{"id":"openai/gpt-luna-latest","name":"GPT Luna Latest","description":"Compatibility alias that routes to GPT 5.6 Luna, the latest supported GPT Luna model.","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125}},"openai/gpt-5.6-luna-pro":{"id":"openai/gpt-5.6-luna-pro","name":"GPT 5.6 Luna Pro","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT 5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":16384},"cost":{"input":0.2,"output":0.3},"canonical_model_id":"openai/gpt-oss-20b"},"openai/gpt-oss-safeguard-20b":{"id":"openai/gpt-oss-safeguard-20b","name":"GPT OSS Safeguard 20B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":0.075,"output":0.3},"canonical_model_id":"openai/gpt-oss-safeguard-20b"},"openai/o3-mini-high":{"id":"openai/o3-mini-high","name":"OpenAI o3-mini (High)","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2024-01-01","last_updated":"2025-01-31","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55}},"openai/gpt-sol-latest":{"id":"openai/gpt-sol-latest","name":"GPT Sol Latest","description":"Compatibility alias that routes to GPT 5.6 Sol, the latest supported GPT Sol model.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5}},"openai/gpt-6-sol-pro":{"id":"openai/gpt-6-sol-pro","name":"GPT 6 Sol Pro","description":"GPT-6 Sol Pro uses the same underlying model as GPT-6 Sol with Pro reasoning mode enabled for higher-quality responses on complex tasks.","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5}},"openai/gpt-astra-latest":{"id":"openai/gpt-astra-latest","name":"GPT Astra Latest","description":"Compatibility alias that routes to GPT 6 Astra, the latest supported GPT Astra model.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5}},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT 5.4 Mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT 5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.1-codex-max":{"id":"openai/gpt-5.1-codex-max","name":"GPT 5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":2.5,"output":20,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.1-codex-max"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT 5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT 5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT 4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"input":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-4o-2024-11-20":{"id":"openai/gpt-4o-2024-11-20","name":"GPT-4o (2024-11-20)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-09","release_date":"2024-11-20","last_updated":"2024-11-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-11-20"},"openai/o3-mini-low":{"id":"openai/o3-mini-low","name":"OpenAI o3-mini (Low)","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-01-31","last_updated":"2025-01-31","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55}},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT 4.1 Mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"input":1047576,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-5.6-terra-pro":{"id":"openai/gpt-5.6-terra-pro","name":"GPT 5.6 Terra Pro","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT 6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-6.1-sol-pro":{"id":"openai/gpt-6.1-sol-pro","name":"GPT 6.1 Sol Pro","description":"GPT-6.1 Sol Pro uses the same underlying model as GPT-6.1 Sol with Pro reasoning mode enabled for higher-quality responses on complex tasks.","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5}},"openai/o4-mini-high":{"id":"openai/o4-mini-high","name":"OpenAI o4-mini high","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2025-12-04","last_updated":"2025-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55}},"openai/gpt-6-luna-pro":{"id":"openai/gpt-6-luna-pro","name":"GPT 6 Luna Pro","description":"GPT-6 Luna Pro uses the same underlying model as GPT-6 Luna with Pro reasoning mode enabled for higher-quality responses on complex tasks.","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125}},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT 5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-4-turbo":{"id":"openai/gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":4096},"cost":{"input":10,"output":30},"canonical_model_id":"openai/gpt-4-turbo"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":0.35,"output":0.75},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-5.1-codex-mini":{"id":"openai/gpt-5.1-codex-mini","name":"GPT 5.1 Codex Mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5.1-codex-mini"},"openai/o3":{"id":"openai/o3","name":"OpenAI o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":1},"canonical_model_id":"openai/o3"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT 5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT 5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-5.1-2025-11-13":{"id":"openai/gpt-5.1-2025-11-13","name":"GPT-5.1 (2025-11-13)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2024-01-01","last_updated":"2025-11-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125}},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT 6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-6-sol"},"openai/o1-pro":{"id":"openai/o1-pro","name":"OpenAI o1 Pro","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-pro","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2023-09","release_date":"2025-03-19","last_updated":"2025-03-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":100000},"cost":{"input":150,"output":600,"cache_read":75},"canonical_model_id":"openai/o1-pro"},"microsoft/wizardlm-2-8x22b":{"id":"microsoft/wizardlm-2-8x22b","name":"WizardLM-2 8x22B","description":"Microsoft WizardLM instruction-tuned Mixtral MoE for multilingual dialogue and complex tasks","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2024-04-15","last_updated":"2024-04-15","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":8192},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465},"canonical_model_id":"microsoft/wizardlm-2-8x22b"},"NousResearch/hermes-3-llama-3.1-70b":{"id":"NousResearch/hermes-3-llama-3.1-70b","name":"Hermes 3 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"nousresearch","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-18","last_updated":"2024-08-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":8192},"cost":{"input":0.408,"output":0.408,"cache_read":0.204},"canonical_model_id":"nousresearch/hermes-3-llama-3.1-70b"},"NousResearch/hermes-4-405b":{"id":"NousResearch/hermes-4-405b","name":"Hermes 4 Large","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"hermes","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.3,"output":1.2,"cache_read":0.15},"canonical_model_id":"nousresearch/hermes-4-405b"},"NousResearch/hermes-4-405b:thinking":{"id":"NousResearch/hermes-4-405b:thinking","name":"Hermes 4 Large (Thinking)","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"hermes","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.3,"output":1.2,"cache_read":0.15},"canonical_model_id":"nousresearch/hermes-4-405b"},"ReadyArt/MS3.2-The-Omega-Directive-24B-Unslop-v2.0":{"id":"ReadyArt/MS3.2-The-Omega-Directive-24B-Unslop-v2.0","name":"Omega Directive 24B Unslop v2.0","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":32768},"cost":{"input":0.5,"output":0.5,"cache_read":0.25}}}},"abliteration-ai":{"id":"abliteration-ai","env":["ABLIT_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.abliteration.ai/v1","name":"abliteration.ai","doc":"https://docs.abliteration.ai/models","models":{"abliterated-model-large-v2":{"id":"abliterated-model-large-v2","name":"Abliterated Model Large V2","description":"GLM-5.3 model abliterated and finetuned for cyber, ML red teaming, and agent testing","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-29","last_updated":"2026-08-31","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":999990},"cost":{"input":5,"output":5,"cache_read":0.5}},"abliterated-model":{"id":"abliterated-model","name":"Abliterated Model","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]},{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-01-06","last_updated":"2026-07-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":150000,"input":150000,"output":8192},"cost":{"input":3,"output":3,"cache_read":0.3}},"abliterated-model-large":{"id":"abliterated-model-large","name":"Abliterated Model Large","description":"GLM-5.2 model abliterated and finetuned for cyber, ML red teaming, and agent testing","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]},{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-25","last_updated":"2026-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":999990},"cost":{"input":5,"output":5,"cache_read":0.5}}}},"crof":{"id":"crof","env":["CROF_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://crof.ai/v1","name":"CrofAI","doc":"https://crof.ai/docs","models":{"gemma-4-31b-it":{"id":"gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.1,"output":0.3,"cache_read":0.02},"canonical_model_id":"google/gemma-4-31b-it"},"qwen3.8-27b":{"id":"qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.2,"output":1.5,"cache_read":0.03},"canonical_model_id":"alibaba/qwen3.8-27b"},"kimi-k3-eco":{"id":"kimi-k3-eco","name":"Kimi K3 Eco","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":1,"output":4,"cache_read":0.1},"canonical_model_id":"moonshotai/kimi-k3"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM 5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.07,"output":0.22,"cache_read":0.01},"canonical_model_id":"zhipuai/glm-5.3-flash"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash (New)","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.08,"output":0.1,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":262144},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":2,"output":8,"cache_read":0.25},"canonical_model_id":"moonshotai/kimi-k3"},"deepseek-v4-flash-vision-exp":{"id":"deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.08,"output":0.2,"cache_read":0.007},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.5,"output":1.99,"cache_read":0.05},"canonical_model_id":"moonshotai/kimi-k2.6"},"greg-2-super":{"id":"greg-2-super","name":"Greg 2 Super","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-06-14","last_updated":"2026-06-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":229376,"output":229376},"cost":{"input":1.5,"output":5,"cache_read":0.25}},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro (0813)","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.35,"output":0.8,"cache_read":0.01},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"mimo-v2.5-pro":{"id":"mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.4,"output":0.8,"cache_read":0.003,"tiers":[{"input":2,"output":6,"cache_read":0.4,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.4}},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"greg-rp":{"id":"greg-rp","name":"Greg (Roleplay)","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":229376,"output":229376},"cost":{"input":0.1,"output":0.3,"cache_read":0.02}},"qwen3.5-9b":{"id":"qwen3.5-9b","name":"Qwen3.5 9B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-13","last_updated":"2026-03-13","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.04,"output":0.15,"cache_read":0.008}},"qwen3.5-397b-a17b":{"id":"qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.35,"output":1.75,"cache_read":0.07},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.3,"output":1.05,"cache_read":0.05},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":202752},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.45,"output":2.15,"cache_read":0.08,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.1"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.35,"output":0.8,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4-pro"},"qwen3.6-27b":{"id":"qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.2,"output":1.5,"cache_read":0.04},"canonical_model_id":"alibaba/qwen3.6-27b"},"greg-2-ultra":{"id":"greg-2-ultra","name":"Greg 2 Ultra","description":"Flagship model for demanding analysis, coding, and production agent workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-06-14","last_updated":"2026-06-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":229376,"output":229376},"cost":{"input":3,"output":10,"cache_read":0.5}},"deepseek-v3.2":{"id":"deepseek-v3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":163840,"output":163840},"cost":{"input":0.18,"output":0.35,"cache_read":0.04}},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.4,"output":1.4,"cache_read":0.06},"canonical_model_id":"zhipuai/glm-5.3"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.55,"output":2.25,"cache_read":0.05},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"greg-1-mini":{"id":"greg-1-mini","name":"Greg 1 Mini","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":229376,"output":229376},"cost":{"input":0.07,"output":0.15,"cache_read":0.01}},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.12,"output":0.21,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4-flash"}}},"standardcompute":{"id":"standardcompute","env":["STANDARDCOMPUTE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.stdcmpt.com/v1","name":"Standard Compute","doc":"https://docs.standardcompute.com/models","models":{"standardcompute":{"id":"standardcompute","name":"Standard Compute","description":"Flat-rate smart-routing gateway: one model id, each request routed across the customer's enabled models from a curated ~1M-context catalog (Claude, GPT, Gemini, DeepSeek, GLM, Qwen, Kimi, MiniMax, Grok, MiMo) or pinned to a user-selected model","family":"auto","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-03-01","last_updated":"2026-10-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0,"output":0}}}},"cloudferro-sherlock":{"id":"cloudferro-sherlock","env":["CLOUDFERRO_SHERLOCK_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api-sherlock.cloudferro.com/openai/v1/","name":"CloudFerro Sherlock","doc":"https://docs.sherlock.cloudferro.com/","models":{"meta-llama/Llama-3.3-70B-Instruct":{"id":"meta-llama/Llama-3.3-70B-Instruct","name":"Llama 3.3 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10-09","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":70000,"output":70000},"cost":{"input":2.92,"output":2.92}},"MiniMaxAI/MiniMax-M2.5":{"id":"MiniMaxAI/MiniMax-M2.5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196000,"input":180000,"output":16000},"cost":{"input":0.3,"output":1.2}},"zai-org/GLM-5.3":{"id":"zai-org/GLM-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.34,"output":4.48},"canonical_model_id":"zhipuai/glm-5.3"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"OpenAI GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-28","last_updated":"2025-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":131000},"cost":{"input":2.92,"output":2.92},"canonical_model_id":"openai/gpt-oss-120b"},"speakleash/Bielik-11B-v3.0-Instruct":{"id":"speakleash/Bielik-11B-v3.0-Instruct","name":"Bielik 11B v3.0 Instruct","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03","release_date":"2025-03-13","last_updated":"2025-03-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":32000},"cost":{"input":0.67,"output":0.67}}}},"anthropic":{"id":"anthropic","env":["ANTHROPIC_API_KEY"],"npm":"@ai-sdk/anthropic","name":"Anthropic","doc":"https://docs.anthropic.com/en/docs/about-claude/models","models":{"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"claude-opus-4-5":{"id":"claude-opus-4-5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"claude-sonnet-4-5":{"id":"claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":8,"output":40,"cache_read":0.4,"cache_write":10},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"claude-fable-5-1":{"id":"claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"claude-opus-4-5-20251101":{"id":"claude-opus-4-5-20251101","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-07","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5}},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"claude-sonnet-4-5-20250929":{"id":"claude-sonnet-4-5-20250929","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75}},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-29","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5}},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-04","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"claude-haiku-4-5-20251001":{"id":"claude-haiku-4-5-20251001","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25}},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75}},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-14","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}}}},"tinfoil":{"id":"tinfoil","env":["TINFOIL_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://inference.tinfoil.sh/v1","name":"Tinfoil","doc":"https://docs.tinfoil.sh","models":{"gpt-oss-safeguard-120b":{"id":"gpt-oss-safeguard-120b","name":"gpt-oss-safeguard-120b","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-safeguard-120b"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":4,"output":20,"cache_read":0.8},"canonical_model_id":"moonshotai/kimi-k3"},"llama3-3-70b":{"id":"llama3-3-70b","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":4096},"cost":{"input":1.75,"output":2.75},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"gemma4-31b":{"id":"gemma4-31b","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.4,"output":1},"canonical_model_id":"google/gemma-4-31b-it"},"glm-5-3":{"id":"glm-5-3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.8,"output":5.75,"cache_read":0.45},"canonical_model_id":"zhipuai/glm-5.3"},"deepseek-v4-1-flash":{"id":"deepseek-v4-1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"status":"beta","cost":{"input":0.65,"output":1.45,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"nomic-embed-text":{"id":"nomic-embed-text","name":"Nomic Embed Text v1.5","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2024-02","last_updated":"2024-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":768},"cost":{"input":0.05,"output":0}},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"gpt-oss-120b","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-120b"}}},"llama":{"id":"llama","env":["LLAMA_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.llama.com/compat/v1/","name":"Llama","doc":"https://llama.developer.meta.com/docs/models","models":{"llama-4-maverick-17b-128e-instruct-fp8":{"id":"llama-4-maverick-17b-128e-instruct-fp8","name":"Llama-4-Maverick-17B-128E-Instruct-FP8","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0,"output":0}},"groq-llama-4-maverick-17b-128e-instruct":{"id":"groq-llama-4-maverick-17b-128e-instruct","name":"Groq-Llama-4-Maverick-17B-128E-Instruct","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0,"output":0}},"llama-4-scout-17b-16e-instruct-fp8":{"id":"llama-4-scout-17b-16e-instruct-fp8","name":"Llama-4-Scout-17B-16E-Instruct-FP8","description":"Open multimodal Llama model for long-context analysis and efficient agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0,"output":0}},"cerebras-llama-4-maverick-17b-128e-instruct":{"id":"cerebras-llama-4-maverick-17b-128e-instruct","name":"Cerebras-Llama-4-Maverick-17B-128E-Instruct","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0,"output":0}},"llama-3.3-70b-instruct":{"id":"llama-3.3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0,"output":0}},"llama-3.3-8b-instruct":{"id":"llama-3.3-8b-instruct","name":"Llama-3.3-8B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0,"output":0}},"cerebras-llama-4-scout-17b-16e-instruct":{"id":"cerebras-llama-4-scout-17b-16e-instruct","name":"Cerebras-Llama-4-Scout-17B-16E-Instruct","description":"Open multimodal Llama model for long-context analysis and efficient agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0,"output":0}}}},"cohere":{"id":"cohere","env":["COHERE_API_KEY"],"npm":"@ai-sdk/cohere","name":"Cohere","doc":"https://docs.cohere.com/docs/models","models":{"command-r-08-2024":{"id":"command-r-08-2024","name":"Command R","description":"Cohere retrieval model for long-context chat and enterprise RAG workflows","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"cohere/command-r-08-2024"},"north-mini-code-1-0":{"id":"north-mini-code-1-0","name":"North Mini Code","description":"Cohere coding model for practical software engineering and agentic edits","family":"north","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-09-23","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://api.cohere.ai/compatibility/v1"},"cost":{"input":0,"output":0},"canonical_model_id":"cohere/north-mini-code-1-0"},"command-a-translate-08-2025":{"id":"command-a-translate-08-2025","name":"Command A Translate","description":"Translation model for multilingual conversion, localization, and cross-language workflows","family":"command-a","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2025-08-28","last_updated":"2025-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8000,"output":8000},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-a-translate-08-2025"},"tiny-aya-fire":{"id":"tiny-aya-fire","name":"Tiny Aya Fire","description":"Compact multilingual model specialized for South Asian languages","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-02-17","last_updated":"2026-02-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8000,"output":8000},"canonical_model_id":"cohere/tiny-aya-fire"},"command-r7b-arabic-02-2025":{"id":"command-r7b-arabic-02-2025","name":"Command R7B Arabic","description":"Open Command R model optimized for Arabic enterprise chat, RAG, and cultural knowledge","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2025-02-27","last_updated":"2025-02-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.0375,"output":0.15},"canonical_model_id":"cohere/command-r7b-arabic-02-2025"},"tiny-aya-earth":{"id":"tiny-aya-earth","name":"Tiny Aya Earth","description":"Compact multilingual model specialized for West Asian and African languages","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-02-17","last_updated":"2026-02-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8000,"output":8000},"canonical_model_id":"cohere/tiny-aya-earth"},"command-a-plus-05-2026":{"id":"command-a-plus-05-2026","name":"Command A Plus","description":"Cohere's stronger command model for multilingual agents and enterprise workflows","family":"command-a","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04-01","release_date":"2026-05-20","last_updated":"2026-06-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":64000},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-a-plus-05-2026"},"command-a-03-2025":{"id":"command-a-03-2025","name":"Command A","description":"Cohere command model for multilingual enterprise agents, tools, and chat","family":"command-a","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2025-03-13","last_updated":"2025-03-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8000},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-a-03-2025"},"c4ai-aya-vision-32b":{"id":"c4ai-aya-vision-32b","name":"Aya Vision 32B","description":"Open multilingual vision model for OCR, visual reasoning, and image question answering","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-03-04","last_updated":"2025-05-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":16000,"output":4000},"canonical_model_id":"cohere/c4ai-aya-vision-32b"},"tiny-aya-global":{"id":"tiny-aya-global","name":"Tiny Aya Global","description":"Compact multilingual model balanced across 70 languages and regions","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-02-17","last_updated":"2026-02-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8000,"output":8000},"canonical_model_id":"cohere/tiny-aya-global"},"north-small-translate-09-2026":{"id":"north-small-translate-09-2026","name":"North Small Translate","description":"Open-weight translation model for more than 50 languages and locale variants","family":"north","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-09-09","last_updated":"2026-09-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16000},"cost":{"input":0,"output":0},"canonical_model_id":"cohere/north-small-translate-1-0"},"command-r7b-12-2024":{"id":"command-r7b-12-2024","name":"Command R7B","description":"Cohere retrieval model for long-context chat and enterprise RAG workflows","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-12-02","last_updated":"2024-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.0375,"output":0.15},"canonical_model_id":"cohere/command-r7b-12-2024"},"command-r-plus-08-2024":{"id":"command-r-plus-08-2024","name":"Command R+","description":"Cohere's RAG workhorse for long-context enterprise search and tool use","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-r-plus-08-2024"},"command-a-vision-07-2025":{"id":"command-a-vision-07-2025","name":"Command A Vision","description":"Cohere vision model for multilingual document analysis, OCR, and image understanding","family":"command-a","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-06-01","release_date":"2025-07-31","last_updated":"2025-07-31","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8000},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-a-vision-07-2025"},"tiny-aya-water":{"id":"tiny-aya-water","name":"Tiny Aya Water","description":"Compact multilingual model specialized for European and Asia-Pacific languages","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-02-17","last_updated":"2026-02-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8000,"output":8000},"canonical_model_id":"cohere/tiny-aya-water"},"command-a-reasoning-08-2025":{"id":"command-a-reasoning-08-2025","name":"Command A Reasoning","description":"Cohere reasoning model for multilingual enterprise agents, tools, and complex workflows","family":"command-a","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1}],"tool_call":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32000},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-a-reasoning-08-2025"},"c4ai-aya-expanse-32b":{"id":"c4ai-aya-expanse-32b","name":"Aya Expanse 32B","description":"Open multilingual model optimized for generation across 23 languages","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-10-24","last_updated":"2024-10-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"canonical_model_id":"cohere/c4ai-aya-expanse-32b"}}},"deepseek":{"id":"deepseek","env":["DEEPSEEK_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.deepseek.com","name":"DeepSeek","doc":"https://api-docs.deepseek.com/quick_start/pricing","models":{"deepseek-v4-flash-vision-exp":{"id":"deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"status":"deprecated","cost":{"input":0.15,"output":0.6,"reasoning":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek-flash":{"id":"deepseek-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":0.15,"output":0.6,"reasoning":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":0.66,"output":1.98,"reasoning":1.98,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"status":"deprecated","cost":{"input":0.15,"output":0.6,"reasoning":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash"}}},"baseten":{"id":"baseten","env":["BASETEN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://inference.baseten.co/v1","name":"Baseten","doc":"https://docs.baseten.co/inference/model-apis/overview","models":{"thinkingmachines/inkling-small":{"id":"thinkingmachines/inkling-small","name":"Inkling Small","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":32768},"cost":{"input":0.5,"output":1.2,"cache_read":0.1},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/inkling":{"id":"thinkingmachines/inkling","name":"Inkling","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":32768},"cost":{"input":1,"output":4.05},"canonical_model_id":"thinkingmachines/inkling"},"deepseek-ai/DeepSeek-V3.1":{"id":"deepseek-ai/DeepSeek-V3.1","name":"DeepSeek V3.1","description":"Legacy model retained for compatibility with older integrations","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-08-25","last_updated":"2025-08-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":131000},"status":"deprecated","cost":{"input":0.5,"output":1.5}},"deepseek-ai/DeepSeek-V4-Flash-0731":{"id":"deepseek-ai/DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.13,"output":0.26,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek-ai/DeepSeek-V4-Pro-0813":{"id":"deepseek-ai/DeepSeek-V4-Pro-0813","name":"DeepSeek V4 Pro 0813","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":1.32,"output":3.96},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek-ai/DeepSeek-V4.1-Flash":{"id":"deepseek-ai/DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":32768},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek-ai/DeepSeek-V4.1-Flash-Fast":{"id":"deepseek-ai/DeepSeek-V4.1-Flash-Fast","name":"DeepSeek V4.1 Flash Fast","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":32768},"cost":{"input":0.6,"output":2.4},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek-ai/DeepSeek-V4-Pro":{"id":"deepseek-ai/DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":1.74,"output":3.48,"cache_read":0.145},"canonical_model_id":"deepseek/deepseek-v4-pro"},"MiniMaxAI/MiniMax-M2.5":{"id":"MiniMaxAI/MiniMax-M2.5","name":"MiniMax-M2.5","description":"Legacy model retained for compatibility with older integrations","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2026-01","release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204000,"output":204000},"status":"deprecated","cost":{"input":0.3,"output":1.2}},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.95,"output":4,"cache_read":0.16}},"moonshotai/Kimi-K3":{"id":"moonshotai/Kimi-K3","name":"Kimi K3","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":3,"output":15},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/Kimi-K2.7-Code":{"id":"moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"moonshotai/Kimi-K2.5":{"id":"moonshotai/Kimi-K2.5","name":"Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-12","release_date":"2026-01-30","last_updated":"2026-02-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.6,"output":3,"cache_read":0.12}},"zai-org/GLM-5.1":{"id":"zai-org/GLM-5.1","name":"GLM 5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202800,"output":202800},"cost":{"input":1.3,"output":4.3,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":1.4,"output":4.4,"cache_read":0.3},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-4.7":{"id":"zai-org/GLM-4.7","name":"GLM 4.7","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":200000},"cost":{"input":0.6,"output":2.2,"cache_read":0.12}},"zai-org/GLM-5.2-Fast":{"id":"zai-org/GLM-5.2-Fast","name":"GLM 5.2 Fast","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":2.1,"output":6.6,"cache_read":0.21},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-5.3-Fast":{"id":"zai-org/GLM-5.3-Fast","name":"GLM 5.3 Fast","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":2.1,"output":6.6},"canonical_model_id":"zhipuai/glm-5.3"},"zai-org/GLM-5":{"id":"zai-org/GLM-5","name":"GLM 5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-01","release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202800,"output":202800},"cost":{"input":0.95,"output":3.15,"cache_read":0.2}},"zai-org/GLM-5.3-Flash":{"id":"zai-org/GLM-5.3-Flash","name":"GLM 5.3 Flash","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/GLM-5.3":{"id":"zai-org/GLM-5.3","name":"GLM 5.3","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":1.4,"output":4.4,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.3"},"nvidia/Nemotron-120B-A12B":{"id":"nvidia/Nemotron-120B-A12B","name":"Nemotron Super","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-02","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202800,"output":202800},"cost":{"input":0.3,"output":0.75,"cache_read":0.06},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B":{"id":"nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B","name":"Nemotron Ultra","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202800,"output":202800},"cost":{"input":0.6,"output":2.4,"cache_read":0.12},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"OpenAI GPT 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-08","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128072,"output":128072},"cost":{"input":0.1,"output":0.5}}}},"nan":{"id":"nan","env":["NAN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.nan.builders/v1","name":"NaN","doc":"https://nan.builders/docs/models","models":{"qwen-image-2.1":{"id":"qwen-image-2.1","name":"Qwen-Image-2.1","description":"Unified text-to-image generation and image editing model with native RGBA transparency and reference-image editing","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-09-14","last_updated":"2026-09-21","modalities":{"input":["text"],"output":["image"]},"open_weights":true,"limit":{"context":8192,"output":0},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen-image-2.1"},"glm5.3-flash":{"id":"glm5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"gemma4":{"id":"gemma4","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"qwen3.6":{"id":"qwen3.6","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"mimo-v2.6-flash":{"id":"mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3.8-flash"},"glm5.3":{"id":"glm5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-5.3"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-v4.1-flash"}}},"stepfun-ai-step-plan":{"id":"stepfun-ai-step-plan","env":["STEPFUN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.stepfun.ai/step_plan/v1","name":"StepFun Step Plan (Global)","doc":"https://platform.stepfun.ai/docs/en/step-plan/integrations/reasoning-api","models":{"step-5-preview":{"id":"step-5-preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":65536},"canonical_model_id":"stepfun/step-5-preview"},"step-3.5-flash-2603":{"id":"step-3.5-flash-2603","name":"Step 3.5 Flash 2603","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"canonical_model_id":"stepfun/step-3.5-flash-2603"},"step-3.5-flash":{"id":"step-3.5-flash","name":"Step 3.5 Flash","description":"StepFun flash lane for quick multimodal reasoning and coding assistance","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"canonical_model_id":"stepfun/step-3.5-flash"},"step-3.7-flash":{"id":"step-3.7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"canonical_model_id":"stepfun/step-3.7-flash"}}},"nearai":{"id":"nearai","env":["NEARAI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://cloud-api.near.ai/v1","name":"NEAR AI Cloud","doc":"https://docs.near.ai/","models":{"anthropic/claude-haiku-4-5":{"id":"anthropic/claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-sonnet-4-5":{"id":"anthropic/claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-opus-5-5":{"id":"anthropic/claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-fable-5-1":{"id":"anthropic/claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-opus-4-8":{"id":"anthropic/claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-opus-4-6":{"id":"anthropic/claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-haiku-5-5":{"id":"anthropic/claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-sonnet-4-6":{"id":"anthropic/claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-sonnet-5-5":{"id":"anthropic/claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-opus-4-7":{"id":"anthropic/claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v3.2":{"id":"deepseek/deepseek-v3.2","name":"DeepSeek V3.2","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":64000},"cost":{"input":1.1,"output":1.1,"cache_read":0.55},"canonical_model_id":"deepseek/deepseek-v3.2"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.08,"output":0.5,"cache_read":0.012},"canonical_model_id":"zhipuai/glm-5.3-flash"},"black-forest-labs/FLUX.2-klein-4B":{"id":"black-forest-labs/FLUX.2-klein-4B","name":"FLUX.2 Klein 4B","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-01-14","last_updated":"2026-01-14","modalities":{"input":["text"],"output":["image"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":1,"output":1}},"x-ai/grok-4.7":{"id":"x-ai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.7"},"x-ai/grok-4.6":{"id":"x-ai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"input_audio":1},"canonical_model_id":"google/gemini-2.5-flash"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"input_audio":0.3},"canonical_model_id":"google/gemini-2.5-flash-lite"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite"},"Qwen/Qwen3-Reranker-0.6B":{"id":"Qwen/Qwen3-Reranker-0.6B","name":"Qwen3 Reranker 0.6B","description":"Reranking model for improving retrieval quality in search and recommendation systems","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-03","last_updated":"2025-06-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":1024},"cost":{"input":0.01,"output":0.01}},"Qwen/Qwen3.8-27B":{"id":"Qwen/Qwen3.8-27B","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.04,"output":1.35,"cache_read":0.018},"canonical_model_id":"alibaba/qwen3.8-27b"},"Qwen/Qwen3-VL-30B-A3B-Instruct":{"id":"Qwen/Qwen3-VL-30B-A3B-Instruct","name":"Qwen3-VL 30B-A3B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":8192},"cost":{"input":0.15,"output":0.55,"cache_read":0.03}},"Qwen/Qwen3-Embedding-0.6B":{"id":"Qwen/Qwen3-Embedding-0.6B","name":"Qwen3 Embedding 0.6B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-03","last_updated":"2025-06-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":1024},"cost":{"input":0.01,"output":0.01}},"Qwen/Qwen3.6-35B-A3B-FP8":{"id":"Qwen/Qwen3.6-35B-A3B-FP8","name":"Qwen 3.6 35B A3B FP8","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.17,"output":1.1,"cache_read":0.056},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3.3,"output":16.5,"cache_read":0.33},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.81,"output":3.85,"cache_read":0.41},"canonical_model_id":"moonshotai/kimi-k2.6"},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":2.8,"output":7.5},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen3.5-397b-a17b":{"id":"qwen/qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.5,"output":3.3,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/whisper-large-v3":{"id":"openai/whisper-large-v3","name":"Whisper Large v3","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"whisper","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2023-11-06","last_updated":"2023-11-06","modalities":{"input":["audio"],"output":["text"]},"open_weights":true,"limit":{"context":448,"output":448},"cost":{"input":0.01,"output":0.01}},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"openai/o4-mini":{"id":"openai/o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.275},"canonical_model_id":"openai/o4-mini"},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1},"canonical_model_id":"openai/gpt-6-astra"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01},"canonical_model_id":"openai/gpt-6-luna"},"openai/o3":{"id":"openai/o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2},"canonical_model_id":"openai/gpt-6-sol"}}},"wandb":{"id":"wandb","env":["WANDB_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.inference.wandb.ai/v1","name":"CoreWeave","doc":"https://docs.wandb.ai/inference","models":{"meta-llama/Llama-3.1-8B-Instruct":{"id":"meta-llama/Llama-3.1-8B-Instruct","name":"Llama 3.1 8B","description":"Efficient conversational model optimized for responsive multilingual chatbot interactions.","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.22,"output":0.22,"cache_read":0.22},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"meta-llama/Llama-3.3-70B-Instruct":{"id":"meta-llama/Llama-3.3-70B-Instruct","name":"Llama 3.3 70B","description":"Multilingual model excelling in conversational tasks, detailed instruction-following, and coding.","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-01","last_updated":"2024-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0.71,"output":0.71,"cache_read":0.71},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"google/gemma-4-31B-it":{"id":"google/gemma-4-31B-it","name":"Gemma 4 31B","description":"Gemma 4 31B Dense is designed for advanced reasoning, agentic workflows, and longer context and is natively trained on 140+ languages.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.1,"output":0.34,"cache_read":0.1},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemma-4-26B-A4B-it":{"id":"google/gemma-4-26B-A4B-it","name":"Gemma 4 26B A4B","description":"Gemma 4 26B A4B is a multimodal MoE model with LoRA support and function calling for agentic workflows.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.1,"output":0.3,"cache_read":0.05},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"Qwen/Qwen3.8-27B":{"id":"Qwen/Qwen3.8-27B","name":"Qwen3.8 27B","description":"Qwen3.8-27B is a dense multimodal model suited for coding, research, vision, and long-running agent tasks.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.4,"output":3,"cache_read":0.15},"canonical_model_id":"alibaba/qwen3.8-27b"},"Qwen/Qwen3.6-35B-A3B":{"id":"Qwen/Qwen3.6-35B-A3B","name":"Qwen3.6 35B A3B","description":"Qwen3.6-35B-A3B is an MoE multimodal model with 262K context optimized for agentic coding workflows.","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-15","last_updated":"2026-04-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.25,"output":1.25,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"ibm-granite/granite-4.2-8b":{"id":"ibm-granite/granite-4.2-8b","name":"Granite 4.2 8B","description":"Granite 4.2 8B is an instruct model capable of enhanced tool calling, instruction following, and chat capabilities.","family":"granite","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-24","last_updated":"2026-08-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.1,"output":0.15,"cache_read":0.05}},"deepseek-ai/DeepSeek-V3.1":{"id":"deepseek-ai/DeepSeek-V3.1","name":"DeepSeek V3.1","description":"A large hybrid model that supports both thinking and non-thinking modes via prompt templates.","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":161000,"output":161000},"cost":{"input":0.55,"output":1.65,"cache_read":0.55},"canonical_model_id":"deepseek/deepseek-v3.1"},"deepseek-ai/DeepSeek-V4-Flash-0731":{"id":"deepseek-ai/DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731","description":"DeepSeek V4-Flash-0731 is an MoE model great for coding, reasoning, and agentic workloads.","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.13,"output":0.28,"cache_read":0.07},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek-ai/DeepSeek-V4-Pro-0813":{"id":"deepseek-ai/DeepSeek-V4-Pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4-Pro-0813 is a 1.6T-parameter MoE model excelling at advanced reasoning, coding, and complex agentic workloads.","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.31,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek-ai/DeepSeek-V4.1-Flash":{"id":"deepseek-ai/DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash is a multimodal MoE model for coding, reasoning, and agentic workloads with long contexts.","family":"deepseek","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.15,"output":0.65,"cache_read":0.002},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"MiniMaxAI/MiniMax-M3":{"id":"MiniMaxAI/MiniMax-M3","name":"MiniMax M3","description":"MiniMax M3 is a multimodal MoE model with 23B active parameters optimized for coding and agentic workflows.","family":"minimax-m3","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.23,"output":0.96,"cache_read":0.05},"canonical_model_id":"minimax/MiniMax-M3"},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi K2.6","description":"Kimi K2.6 is a multimodal Mixture-of-Experts language model featuring 32 billion activated parameters and a total of 1 trillion parameters.","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.65,"output":3.41,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/Kimi-K2.7-Code":{"id":"moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Kimi K2.7 Code is a 1T-parameter MoE model with 32B active parameters purpose-built for long-horizon agentic coding and software engineering.","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.71,"output":3.5,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM 5.2","description":"GLM-5.2 is a Mixture-of-Experts language model featuring 40 billion activated parameters and a total of 744 billion parameters.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-16","last_updated":"2026-06-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.62,"output":2.42,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-5.3-Flash":{"id":"zai-org/GLM-5.3-Flash","name":"GLM 5.3 Flash","description":"GLM-5.3-Flash is a natively multimodal model with 320B total parameters and 18B active parameters.","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.15,"output":0.5,"cache_read":0.02},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/GLM-5.3":{"id":"zai-org/GLM-5.3","name":"GLM 5.3","description":"GLM-5.3 is a 744B-parameter MoE model built for advanced reasoning, software engineering, and long-horizon agentic tasks.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.2,"output":4,"cache_read":0.19},"canonical_model_id":"zhipuai/glm-5.3"},"nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B":{"id":"nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B","name":"Nemotron 3.5 Super VL","description":"Nemotron 3.5 Super VL is a multimodal MoE model built for visual understanding, reasoning, and agentic workflows.","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.15,"output":0.75,"cache_read":0.02},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B":{"id":"nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B","name":"Nemotron 3.5 Lightning","description":"Nemotron 3.5 Lightning is an MoE model built for fast, reliable agentic tasks across use cases such as financial services, cybersecurity, telecom, and retail.","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.07,"output":0.2,"cache_read":0.04},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B":{"id":"nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B","name":"Nemotron 3 Ultra","description":"Nemotron 3 Ultra is a powerful MoE model designed for long-running agents across coding, deep research, and enterprise automation.","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":2.15,"cache_read":0.1},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"gpt-oss-20b","description":"Lower latency Mixture-of-Experts model trained on OpenAI's Harmony response format with reasoning capabilities.","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.03,"output":0.13,"cache_read":0.03},"canonical_model_id":"openai/gpt-oss-20b"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"gpt-oss-120b","description":"Efficient Mixture-of-Experts model designed for high-reasoning, agentic and general-purpose use cases.","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.03,"output":0.17,"cache_read":0.03},"canonical_model_id":"openai/gpt-oss-120b"}}},"subconscious":{"id":"subconscious","env":["SUBCONSCIOUS_API_KEY"],"npm":"@ai-sdk/anthropic","api":"https://api.subconscious.dev/v1","name":"Subconscious","doc":"https://docs.subconscious.dev","models":{"subconscious/deepseek-v4.1-flash-marathon":{"id":"subconscious/deepseek-v4.1-flash-marathon","name":"DeepSeek V4.1 Flash Marathon","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":5000000,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"subconscious/glm-5.3-marathon":{"id":"subconscious/glm-5.3-marathon","name":"GLM-5.3 Marathon","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":5000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"}}},"zeldoc":{"id":"zeldoc","env":["ZELDOC_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.zeldoc.ai/v1","name":"Zeldoc","doc":"https://docs.zeldoc.ai","models":{"zdev":{"id":"zdev","name":"ZDev","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0}}}},"databricks":{"id":"databricks","env":["DATABRICKS_HOST","DATABRICKS_TOKEN"],"npm":"@ai-sdk/openai-compatible","api":"https://${DATABRICKS_HOST}/ai-gateway/mlflow/v1","name":"Databricks","doc":"https://docs.databricks.com/aws/en/machine-learning/foundation-models/","models":{"databricks-claude-opus-4-5":{"id":"databricks-claude-opus-4-5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"databricks-gpt-5-6-terra":{"id":"databricks-gpt-5-6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.6-terra"},"databricks-gemini-3-5-flash":{"id":"databricks-gemini-3-5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.5-flash"},"databricks-kimi-k2-7-code":{"id":"databricks-kimi-k2-7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"databricks-glm-5-2":{"id":"databricks-glm-5-2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"databricks-gemini-3-1-flash-lite":{"id":"databricks-gemini-3-1-flash-lite","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite-preview"},"databricks-gpt-5-mini":{"id":"databricks-gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"databricks-gemini-3-flash":{"id":"databricks-gemini-3-flash","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"input_audio":1},"canonical_model_id":"google/gemini-3-flash-preview"},"databricks-claude-opus-4-7":{"id":"databricks-claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":30,"output":150,"cache_read":3,"cache_write":37.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"databricks-gpt-oss-20b":{"id":"databricks-gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.05,"output":0.2}},"databricks-gpt-5-4-mini":{"id":"databricks-gpt-5-4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":1.5,"output":9,"cache_read":0.15},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"databricks-gemini-3-pro":{"id":"databricks-gemini-3-pro","name":"Gemini 3 Pro Preview","description":"Preview Gemini flagship for complex reasoning, coding, and rich multimodal prompts","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3-pro-preview"},"databricks-gpt-5-2":{"id":"databricks-gpt-5-2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"databricks-claude-haiku-4-5":{"id":"databricks-claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"databricks-gemini-3-1-pro":{"id":"databricks-gemini-3-1-pro","name":"Gemini 3.1 Pro Preview Custom Tools","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview-customtools"},"databricks-claude-opus-4-6":{"id":"databricks-claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":30,"output":150,"cache_read":3,"cache_write":37.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"databricks-gpt-5-6-sol":{"id":"databricks-gpt-5-6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.6-sol"},"databricks-claude-opus-4-1":{"id":"databricks-claude-opus-4-1","name":"Claude Opus 4.1 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1"},"databricks-gpt-oss-120b":{"id":"databricks-gpt-oss-120b","name":"GPT OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.072,"output":0.28}},"databricks-gemini-2-5-pro":{"id":"databricks-gemini-2-5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro"},"databricks-gemini-2-5-flash":{"id":"databricks-gemini-2-5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"input_audio":1},"canonical_model_id":"google/gemini-2.5-flash"},"databricks-claude-sonnet-4-5":{"id":"databricks-claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"databricks-gpt-5-4":{"id":"databricks-gpt-5-4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":5,"output":30,"cache_read":0.5},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"databricks-gpt-5-4-nano":{"id":"databricks-gpt-5-4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"databricks-claude-sonnet-4-6":{"id":"databricks-claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"databricks-gpt-5-6-luna":{"id":"databricks-gpt-5-6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1,"output":6,"cache_read":0.1,"tiers":[{"input":2,"output":9,"cache_read":0.2,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":2,"output":9,"cache_read":0.2}},"canonical_model_id":"openai/gpt-5.6-luna"},"databricks-claude-sonnet-4":{"id":"databricks-claude-sonnet-4","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"databricks-gpt-5-1":{"id":"databricks-gpt-5-1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"databricks-gpt-5-nano":{"id":"databricks-gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"databricks-gpt-5":{"id":"databricks-gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"databricks-gpt-5-5":{"id":"databricks-gpt-5-5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":12.5,"output":75,"cache_read":1.25},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"}}},"umans-ai-coding-plan":{"id":"umans-ai-coding-plan","env":["UMANS_AI_CODING_PLAN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.code.umans.ai/v1","name":"Umans AI Coding Plan","doc":"https://app.umans.ai/offers/code/docs","models":{"umans-deepseek-v4.1-flash":{"id":"umans-deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393215},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"umans-glm-5.3-flash":{"id":"umans-glm-5.3-flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131071},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"umans-flash":{"id":"umans-flash","name":"Umans Flash","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"umans-deepseek-v4-flash-0731":{"id":"umans-deepseek-v4-flash-0731","name":"DeepSeek V4 Flash","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393215},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"umans-kimi-k3":{"id":"umans-kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k3"},"umans-glm-5.3":{"id":"umans-glm-5.3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131071},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"umans-qwen3.6-35b-a3b":{"id":"umans-qwen3.6-35b-a3b","name":"Qwen3.6 35B A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"umans-coder":{"id":"umans-coder","name":"Umans Coder","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131071},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"}}},"kuae-cloud-coding-plan":{"id":"kuae-cloud-coding-plan","env":["KUAE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://coding-plan-endpoint.kuaecloud.net/v1","name":"KUAE Cloud Coding Plan","doc":"https://docs.mthreads.com/kuaecloud/kuaecloud-doc-online/coding_plan/","models":{"GLM-4.7":{"id":"GLM-4.7","name":"GLM-4.7","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}}}},"umans-ai":{"id":"umans-ai","env":["UMANS_AI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.code.umans.ai/v1","name":"Umans AI","doc":"https://app.umans.ai/offers/code/docs/orgs","models":{"umans-deepseek-v4.1-flash":{"id":"umans-deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393215},"cost":{"input":0.15,"output":0.6,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"umans-glm-5.3-flash":{"id":"umans-glm-5.3-flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131071},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"umans-flash":{"id":"umans-flash","name":"Umans Flash","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.15,"output":1,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"umans-deepseek-v4-flash-0731":{"id":"umans-deepseek-v4-flash-0731","name":"DeepSeek V4 Flash","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393215},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"umans-kimi-k3":{"id":"umans-kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"umans-glm-5.3":{"id":"umans-glm-5.3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131071},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"umans-coder":{"id":"umans-coder","name":"Umans Coder","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131071},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"}}},"siliconflow":{"id":"siliconflow","env":["SILICONFLOW_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.siliconflow.com/v1","name":"SiliconFlow","doc":"https://cloud.siliconflow.com/models","models":{"ByteDance-Seed/Seed-OSS-36B-Instruct":{"id":"ByteDance-Seed/Seed-OSS-36B-Instruct","name":"ByteDance-Seed/Seed-OSS-36B-Instruct","description":"Tool-capable chat model for instruction following and agentic application workflows","family":"seed","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-04","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.21,"output":0.57}},"nex-agi/Nex-N2-Pro":{"id":"nex-agi/Nex-N2-Pro","name":"Nex-N2-Pro","description":"Open agentic MoE model (397B total, 17B active) for coding, tool use, and research workflows","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.5,"output":2.5,"cache_read":0.25},"canonical_model_id":"nex-agi/nex-n2-pro"},"tencent/Hunyuan-A13B-Instruct":{"id":"tencent/Hunyuan-A13B-Instruct","name":"tencent/Hunyuan-A13B-Instruct","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"hunyuan","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-06-30","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":131000},"cost":{"input":0.14,"output":0.57}},"tencent/Hy3":{"id":"tencent/Hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":192000,"output":262144},"cost":{"input":0.132,"output":0.528,"cache_read":0.033},"canonical_model_id":"tencent/hy3"},"meituan-longcat/LongCat-2.0":{"id":"meituan-longcat/LongCat-2.0","name":"LongCat-2.0","description":"Meituan LongCat-2.0, a reasoning model with tool calling and a 1M-token context window","family":"longcat","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1049000,"output":131072},"cost":{"input":0.75,"output":2.95,"cache_read":0.015},"canonical_model_id":"meituan/longcat-2.0"},"google/gemma-4-12B-it":{"id":"google/gemma-4-12B-it","name":"Gemma 4 12B IT","description":"Compact Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"google/gemma-4-12b-it"},"google/gemma-4-31B-it":{"id":"google/gemma-4-31B-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.13,"output":0.4},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemma-4-26B-A4B-it":{"id":"google/gemma-4-26B-A4B-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.12,"output":0.4},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"Qwen/Qwen3-VL-30B-A3B-Instruct":{"id":"Qwen/Qwen3-VL-30B-A3B-Instruct","name":"Qwen/Qwen3-VL-30B-A3B-Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-05","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.29,"output":1}},"Qwen/Qwen3-VL-8B-Instruct":{"id":"Qwen/Qwen3-VL-8B-Instruct","name":"Qwen/Qwen3-VL-8B-Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-15","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.18,"output":0.68}},"Qwen/Qwen3-VL-32B-Thinking":{"id":"Qwen/Qwen3-VL-32B-Thinking","name":"Qwen/Qwen3-VL-32B-Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-21","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.2,"output":1.5}},"Qwen/Qwen3-30B-A3B-Instruct-2507":{"id":"Qwen/Qwen3-30B-A3B-Instruct-2507","name":"Qwen/Qwen3-30B-A3B-Instruct-2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-30","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.09,"output":0.3}},"Qwen/Qwen3.5-27B":{"id":"Qwen/Qwen3.5-27B","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.25,"output":2},"canonical_model_id":"alibaba/qwen3.5-27b"},"Qwen/Qwen3.6-35B-A3B":{"id":"Qwen/Qwen3.6-35B-A3B","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.2,"output":1.6},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"Qwen/Qwen3-14B":{"id":"Qwen/Qwen3-14B","name":"Qwen/Qwen3-14B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-30","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":131000},"cost":{"input":0.07,"output":0.28}},"Qwen/Qwen3-VL-30B-A3B-Thinking":{"id":"Qwen/Qwen3-VL-30B-A3B-Thinking","name":"Qwen/Qwen3-VL-30B-A3B-Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-11","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.29,"output":1}},"Qwen/Qwen3-8B":{"id":"Qwen/Qwen3-8B","name":"Qwen/Qwen3-8B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-30","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":131000},"cost":{"input":0.06,"output":0.06}},"Qwen/Qwen2.5-72B-Instruct":{"id":"Qwen/Qwen2.5-72B-Instruct","name":"Qwen/Qwen2.5-72B-Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-09-18","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":33000,"output":4000},"cost":{"input":0.59,"output":0.59}},"Qwen/Qwen3-32B":{"id":"Qwen/Qwen3-32B","name":"Qwen/Qwen3-32B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-30","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":131000},"cost":{"input":0.14,"output":0.57}},"Qwen/Qwen3-Coder-30B-A3B-Instruct":{"id":"Qwen/Qwen3-Coder-30B-A3B-Instruct","name":"Qwen/Qwen3-Coder-30B-A3B-Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-01","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.07,"output":0.28}},"Qwen/Qwen2.5-7B-Instruct":{"id":"Qwen/Qwen2.5-7B-Instruct","name":"Qwen/Qwen2.5-7B-Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-09-18","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":33000,"output":4000},"cost":{"input":0.05,"output":0.05}},"Qwen/Qwen3.5-35B-A3B":{"id":"Qwen/Qwen3.5-35B-A3B","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.24,"output":1.8},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"Qwen/Qwen3.5-122B-A10B":{"id":"Qwen/Qwen3.5-122B-A10B","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.26,"output":2.08},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"Qwen/Qwen3.5-9B":{"id":"Qwen/Qwen3.5-9B","name":"Qwen/Qwen3.5-9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-03","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.1,"output":0.15}},"Qwen/Qwen3.5-397B-A17B":{"id":"Qwen/Qwen3.5-397B-A17B","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.39,"output":2.34},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"Qwen/Qwen3.8-2.4T-A95B":{"id":"Qwen/Qwen3.8-2.4T-A95B","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1049000,"output":131000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"Qwen/Qwen3-VL-32B-Instruct":{"id":"Qwen/Qwen3-VL-32B-Instruct","name":"Qwen/Qwen3-VL-32B-Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-21","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.2,"output":0.6}},"Qwen/Qwen3-Coder-480B-A35B-Instruct":{"id":"Qwen/Qwen3-Coder-480B-A35B-Instruct","name":"Qwen/Qwen3-Coder-480B-A35B-Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-31","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.25,"output":1}},"Qwen/Qwen3.6-27B":{"id":"Qwen/Qwen3.6-27B","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.3,"output":3.2},"canonical_model_id":"alibaba/qwen3.6-27b"},"deepseek-ai/DeepSeek-V3.1":{"id":"deepseek-ai/DeepSeek-V3.1","name":"deepseek-ai/DeepSeek-V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-25","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":164000,"output":164000},"cost":{"input":0.27,"output":1}},"deepseek-ai/DeepSeek-V4-Flash-0731":{"id":"deepseek-ai/DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.22,"output":0.66,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek-ai/DeepSeek-R1":{"id":"deepseek-ai/DeepSeek-R1","name":"deepseek-ai/DeepSeek-R1","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":164000,"output":164000},"cost":{"input":0.5,"output":2.18}},"deepseek-ai/DeepSeek-V4-Pro-0813":{"id":"deepseek-ai/DeepSeek-V4-Pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek-ai/DeepSeek-V4-Flash":{"id":"deepseek-ai/DeepSeek-V4-Flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.13,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek-ai/DeepSeek-V4-Pro":{"id":"deepseek-ai/DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.50162,"output":3.135,"cache_read":0.135},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek-ai/DeepSeek-V3.2":{"id":"deepseek-ai/DeepSeek-V3.2","name":"deepseek-ai/DeepSeek-V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-03","last_updated":"2025-12-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":164000,"output":164000},"cost":{"input":0.27,"output":0.42,"cache_read":0.135}},"deepseek-ai/DeepSeek-V3":{"id":"deepseek-ai/DeepSeek-V3","name":"deepseek-ai/DeepSeek-V3","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-12-26","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":164000,"output":164000},"cost":{"input":0.25,"output":1}},"deepseek-ai/DeepSeek-V3.1-Terminus":{"id":"deepseek-ai/DeepSeek-V3.1-Terminus","name":"deepseek-ai/DeepSeek-V3.1-Terminus","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-29","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":164000,"output":164000},"cost":{"input":0.27,"output":1}},"deepseek-ai/DeepSeek-V3.2-Exp":{"id":"deepseek-ai/DeepSeek-V3.2-Exp","name":"deepseek-ai/DeepSeek-V3.2-Exp","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-10","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":164000,"output":164000},"cost":{"input":0.27,"output":0.41}},"deepseek-ai/DeepSeek-V4-Flash-Vision-Exp":{"id":"deepseek-ai/DeepSeek-V4-Flash-Vision-Exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.44,"output":1.32,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"stepfun-ai/Step-3.5-Flash":{"id":"stepfun-ai/Step-3.5-Flash","name":"stepfun-ai/Step-3.5-Flash","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","family":"step","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-11","last_updated":"2026-02-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.1,"output":0.3}},"MiniMaxAI/MiniMax-M3":{"id":"MiniMaxAI/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"MiniMaxAI/MiniMax-M2.5":{"id":"MiniMaxAI/MiniMax-M2.5","name":"MiniMaxAI/MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-06-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":197000,"output":131000},"cost":{"input":0.3,"output":1.2,"cache_read":0.03}},"inclusionAI/Ling-flash-2.0":{"id":"inclusionAI/Ling-flash-2.0","name":"inclusionAI/Ling-flash-2.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-18","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":131000},"cost":{"input":0.14,"output":0.57}},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"moonshotai/Kimi-K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-21","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.77,"output":3.4,"cache_read":0.14}},"moonshotai/Kimi-K3":{"id":"moonshotai/Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262000},"cost":{"input":2.7,"output":13.5,"cache_read":0.27},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/Kimi-K2.7-Code":{"id":"moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.85916,"output":3.8,"cache_read":0.17993},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"moonshotai/Kimi-K2.5":{"id":"moonshotai/Kimi-K2.5","name":"moonshotai/Kimi-K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.45,"output":2.25,"cache_read":0.07}},"zai-org/GLM-5.1":{"id":"zai-org/GLM-5.1","name":"zai-org/GLM-5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-04-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":205000,"output":131000},"cost":{"input":1.19,"output":3.74,"cache_read":0.6,"cache_write":0}},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1049000,"output":262000},"cost":{"input":1.302,"output":4.092,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-4.5-Air":{"id":"zai-org/GLM-4.5-Air","name":"zai-org/GLM-4.5-Air","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-air","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-28","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":131000},"cost":{"input":0.14,"output":0.86}},"zai-org/GLM-5":{"id":"zai-org/GLM-5","name":"zai-org/GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-06-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":205000,"output":205000},"cost":{"input":0.95,"output":2.55,"cache_read":0.2}},"zai-org/GLM-5.3-Flash":{"id":"zai-org/GLM-5.3-Flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1049000,"output":262000},"cost":{"input":0.15,"output":0.5,"cache_read":0.03,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/GLM-5V-Turbo":{"id":"zai-org/GLM-5V-Turbo","name":"zai-org/GLM-5V-Turbo","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24,"cache_write":0}},"zai-org/GLM-5.3":{"id":"zai-org/GLM-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1049000,"output":262000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"openai/gpt-oss-20b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-13","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":8000},"cost":{"input":0.04,"output":0.18}},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"openai/gpt-oss-120b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-13","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":8000},"cost":{"input":0.05,"output":0.45}}}},"minimax-coding-plan":{"id":"minimax-coding-plan","env":["MINIMAX_API_KEY"],"npm":"@ai-sdk/anthropic","api":"https://api.minimax.io/anthropic/v1","name":"MiniMax Token Plan (minimax.io)","doc":"https://platform.minimax.io/docs/token-plan/intro","models":{"MiniMax-M3":{"id":"MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-25","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"MiniMax-M2.1":{"id":"MiniMax-M2.1","name":"MiniMax-M2.1","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"MiniMax-M3.1-Flash-Preview":{"id":"MiniMax-M3.1-Flash-Preview","name":"MiniMax-M3.1-Flash-Preview","description":"Frontier multimodal coding model with 1M context window and tunable thinking depth","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-27","last_updated":"2026-09-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":512000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"minimax/MiniMax-M3.1-Flash-Preview"},"MiniMax-M2.5":{"id":"MiniMax-M2.5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"MiniMax-M2.7":{"id":"MiniMax-M2.7","name":"MiniMax-M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"MiniMax-M2.7-highspeed":{"id":"MiniMax-M2.7-highspeed","name":"MiniMax-M2.7-highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"MiniMax-M2":{"id":"MiniMax-M2","name":"MiniMax-M2","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0}},"MiniMax-M2.5-highspeed":{"id":"MiniMax-M2.5-highspeed","name":"MiniMax-M2.5-highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-13","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}}}},"alibaba-coding-plan":{"id":"alibaba-coding-plan","env":["ALIBABA_CODING_PLAN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://coding-intl.dashscope.aliyuncs.com/v1","name":"Alibaba Coding Plan","doc":"https://www.alibabacloud.com/help/en/model-studio/coding-plan","models":{"qwen3-coder-next":{"id":"qwen3-coder-next","name":"Qwen3 Coder Next","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3.5-plus":{"id":"qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"glm-5":{"id":"glm-5","name":"GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-11","last_updated":"2026-02-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":16384},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3-max-2026-01-23":{"id":"qwen3-max-2026-01-23","name":"Qwen3 Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-23","last_updated":"2026-01-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3-coder-plus":{"id":"qwen3-coder-plus","name":"Qwen3 Coder Plus","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"MiniMax-M2.5":{"id":"MiniMax-M2.5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"input":196601,"output":24576},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"glm-4.7":{"id":"glm-4.7","name":"GLM-4.7","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":16384},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3.6-plus":{"id":"qwen3.6-plus","name":"Qwen3.6 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.7-plus"}}},"lilac":{"id":"lilac","env":["LILAC_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.getlilac.com/v1","name":"Lilac","doc":"https://docs.getlilac.com/inference/models","models":{"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262100,"output":262100},"cost":{"input":0.11,"output":0.35},"canonical_model_id":"google/gemma-4-31b-it"},"minimaxai/minimax-m3":{"id":"minimaxai/minimax-m3","name":"MiniMax M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax-m3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.28,"output":1.1,"cache_read":0.05},"canonical_model_id":"minimax/MiniMax-M3"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.7,"output":3.5,"cache_read":0.2},"canonical_model_id":"moonshotai/kimi-k2.6"},"zai-org/glm-5.2":{"id":"zai-org/glm-5.2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":524288},"cost":{"input":0.9,"output":3,"cache_read":0.27},"canonical_model_id":"zhipuai/glm-5.2"}}},"moonshotai-cn":{"id":"moonshotai-cn","env":["MOONSHOT_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.moonshot.cn/v1","name":"Moonshot AI (China)","doc":"https://platform.moonshot.cn/docs/api/chat","models":{"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16}},"kimi-k2.7-code-highspeed":{"id":"kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code HighSpeed","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3},"canonical_model_id":"moonshotai/kimi-k3"}}},"bothub":{"id":"bothub","env":["BOTHUB_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://openai.bothub.ru/v1","name":"Bothub","doc":"https://bothub.ru/models","models":{"gemma-4-31b-it:free":{"id":"gemma-4-31b-it:free","name":"Gemma 4 31B IT (free)","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemma-4-31b-it"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.12,"output":0.44},"canonical_model_id":"zhipuai/glm-5.3-flash"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.1,"output":0.28},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"nemotron-3-ultra-550b-a55b:free":{"id":"nemotron-3-ultra-550b-a55b:free","name":"Nemotron 3 Ultra (free)","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]}],"tool_call":true,"interleaved":true,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.61,"output":4.84},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.06,"output":0.37},"canonical_model_id":"openai/gpt-5.6-luna"},"muse-spark-1.3-contributor":{"id":"muse-spark-1.3-contributor","name":"Muse Spark 1.3 Contributor","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.1,"output":0.2},"canonical_model_id":"meta/muse-spark-1.3"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.72,"output":5.41},"canonical_model_id":"zhipuai/glm-5.3"}}},"xiaomi-token-plan-cn":{"id":"xiaomi-token-plan-cn","env":["XIAOMI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://token-plan-cn.xiaomimimo.com/v1","name":"Xiaomi Token Plan (China)","doc":"https://platform.xiaomimimo.com/#/docs","models":{"mimo-v2.6-pro":{"id":"mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"mimo-v2.5":{"id":"mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.5"},"mimo-v2.5-tts-voicedesign":{"id":"mimo-v2.5-tts-voicedesign","name":"MiMo-V2.5-TTS-VoiceDesign","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mimo","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["audio"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0,"output":0}},"mimo-v2.5-tts":{"id":"mimo-v2.5-tts","name":"MiMo-V2.5-TTS","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mimo","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["audio"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0,"output":0}},"mimo-v2-pro":{"id":"mimo-v2-pro","name":"MiMo-V2-Pro","description":"Earlier MiMo Pro model for multimodal agents, reasoning, and code tasks","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2-pro"},"mimo-v2-tts":{"id":"mimo-v2-tts","name":"MiMo-V2-TTS","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mimo","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["audio"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0,"output":0}},"mimo-v2.5-pro":{"id":"mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"mimo-v2.6-flash":{"id":"mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"mimo-v2.5-tts-voiceclone":{"id":"mimo-v2.5-tts-voiceclone","name":"MiMo-V2.5-TTS-VoiceClone","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mimo","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["audio"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0,"output":0}}}},"privatemode-ai":{"id":"privatemode-ai","env":["PRIVATEMODE_API_KEY","PRIVATEMODE_ENDPOINT"],"npm":"@ai-sdk/openai-compatible","api":"http://localhost:8080/v1","name":"Privatemode AI","doc":"https://docs.privatemode.ai/api/overview","models":{"glm-flash-latest":{"id":"glm-flash-latest","name":"GLM Flash (latest)","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"beta","cost":{"input":0.2311,"output":0.7511,"cache_read":0.0578},"canonical_model_id":"zhipuai/glm-5.3-flash"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"beta","cost":{"input":0.2311,"output":0.7511,"cache_read":0.0578},"canonical_model_id":"zhipuai/glm-5.3-flash"},"whisper-large-v3":{"id":"whisper-large-v3","name":"Whisper large-v3","description":"Open Whisper checkpoint for robust multilingual transcription and captioning","family":"whisper","attachment":true,"reasoning":false,"tool_call":false,"release_date":"2024-10-01","last_updated":"2024-10-01","modalities":{"input":["audio"],"output":["text"]},"open_weights":true,"limit":{"context":448,"output":4096},"cost":{"input":0.01618,"output":0},"canonical_model_id":"openai/whisper-large-v3"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":262144},"status":"deprecated","cost":{"input":1.791,"output":8.9436,"cache_read":0.1733},"canonical_model_id":"moonshotai/kimi-k2.6"},"deepseek-ocr-2":{"id":"deepseek-ocr-2","name":"DeepSeek OCR 2","description":"High-accuracy OCR model for extracting text from documents, screenshots, receipts, and natural scenes","attachment":true,"reasoning":false,"tool_call":false,"release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8192},"status":"beta","cost":{"input":0.8897,"output":1.4675,"cache_read":0.0924},"canonical_model_id":"deepseek/deepseek-ocr-2"},"qwen3-embedding-4b":{"id":"qwen3-embedding-4b","name":"Qwen3-Embedding 4B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-06","release_date":"2025-06-06","last_updated":"2025-06-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":2560},"cost":{"input":0.1502,"output":0}},"voxtral-mini-3b":{"id":"voxtral-mini-3b","name":"Voxtral Mini 3B","description":"Speech-to-text model for audio transcription, translation, and audio understanding","family":"voxtral","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-07","last_updated":"2025-07","modalities":{"input":["audio"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":32000},"cost":{"input":0.00462,"output":0}},"kimi-latest":{"id":"kimi-latest","name":"Kimi (latest)","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":262144},"status":"deprecated","cost":{"input":1.791,"output":8.9436,"cache_read":0.1733},"canonical_model_id":"moonshotai/kimi-k2.6"},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"gpt-oss-120b","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.2311,"output":0.7511,"cache_read":0.0462},"canonical_model_id":"openai/gpt-oss-120b"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"beta","cost":{"input":1.791,"output":6.6326,"cache_read":0.1733},"canonical_model_id":"zhipuai/glm-5.3"},"glm-latest":{"id":"glm-latest","name":"GLM (latest)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"beta","cost":{"input":1.791,"output":6.6326,"cache_read":0.1733},"canonical_model_id":"zhipuai/glm-5.3"}}},"llmgateway-providers":{"id":"llmgateway-providers","env":["LLMGATEWAY_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.llmgateway.io/v1","name":"LLM Gateway","doc":"https://llmgateway.io/docs","models":{"entrim/glm-5.3-flash":{"id":"entrim/glm-5.3-flash","name":"GLM-5.3 Flash (entrim)","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.1,"output":0.35,"cache_read":0.0175},"canonical_model_id":"zhipuai/glm-5.3-flash"},"entrim/deepseek-v4.1-flash":{"id":"entrim/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash (entrim)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.2,"output":0.6,"cache_read":0.005},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"entrim/glm-5.3":{"id":"entrim/glm-5.3","name":"GLM-5.3 (entrim)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.5,"output":2,"cache_read":0.15},"canonical_model_id":"zhipuai/glm-5.3"},"consensusprotocol/gemma-4-31b-it":{"id":"consensusprotocol/gemma-4-31b-it","name":"Gemma 4 31B IT (Consensus Protocol)","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.1,"output":0.25,"cache_read":0.01},"canonical_model_id":"google/gemma-4-31b-it"},"consensusprotocol/Qwen3.8-27B":{"id":"consensusprotocol/Qwen3.8-27B","name":"Qwen3.8 27B (Consensus Protocol)","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":32768},"cost":{"input":0.08,"output":0.35,"cache_read":0.05}},"consensusprotocol/glm-5.3-flash":{"id":"consensusprotocol/glm-5.3-flash","name":"GLM-5.3 Flash (Consensus Protocol)","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.1,"output":0.25,"cache_read":0.01},"canonical_model_id":"zhipuai/glm-5.3-flash"},"consensusprotocol/deepseek-v4.1-flash":{"id":"consensusprotocol/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash (Consensus Protocol)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.15,"output":0.55,"cache_read":0.005},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"consensusprotocol/gpt-oss-20b":{"id":"consensusprotocol/gpt-oss-20b","name":"GPT OSS 20B (Consensus Protocol)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.04,"output":0.19,"cache_read":0.01},"canonical_model_id":"openai/gpt-oss-20b"},"consensusprotocol/mimo-v2.6-flash":{"id":"consensusprotocol/mimo-v2.6-flash","name":"MiMo V2.6 Flash (Consensus Protocol)","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.12,"output":0.25,"cache_read":0.0025},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"consensusprotocol/minimax-m3":{"id":"consensusprotocol/minimax-m3","name":"MiniMax M3 (Consensus Protocol)","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.28,"output":1.1,"cache_read":0.05},"canonical_model_id":"minimax/MiniMax-M3"},"consensusprotocol/deepseek-v4-flash":{"id":"consensusprotocol/deepseek-v4-flash","name":"DeepSeek V4 Flash (Consensus Protocol)","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.1,"output":0.2,"cache_read":0.005},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepinfra/mimo-v2.6-pro":{"id":"deepinfra/mimo-v2.6-pro","name":"MiMo V2.6 Pro (DeepInfra)","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"deepinfra/gemma-4-31b-it":{"id":"deepinfra/gemma-4-31b-it","name":"Gemma 4 31B IT (DeepInfra)","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.2,"output":0.4},"canonical_model_id":"google/gemma-4-31b-it"},"deepinfra/qwen3-vl-235b-a22b-instruct":{"id":"deepinfra/qwen3-vl-235b-a22b-instruct","name":"Qwen3 VL 235B A22B Instruct (DeepInfra)","description":"Qwen vision-language instruct model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.2,"output":0.88,"cache_read":0.11},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"deepinfra/muse-glimmer-30b":{"id":"deepinfra/muse-glimmer-30b","name":"Muse Glimmer 30B (DeepInfra)","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.3,"output":1.2,"cache_read":0.04},"canonical_model_id":"meta/muse-glimmer-30b"},"deepinfra/deepseek-v4.1-flash":{"id":"deepinfra/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash (DeepInfra)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.2,"output":0.6,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepinfra/ling-3.0-flash":{"id":"deepinfra/ling-3.0-flash","name":"InclusionAI Ling 3.0 Flash (DeepInfra)","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-02","last_updated":"2026-08-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.06,"output":0.18,"cache_read":0.012}},"deepinfra/qwen3-vl-30b-a3b-instruct":{"id":"deepinfra/qwen3-vl-30b-a3b-instruct","name":"Qwen3 VL 30B A3B Instruct (DeepInfra)","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-10-05","last_updated":"2025-10-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.15,"output":0.6}},"deepinfra/gemma-4-26b-a4b-it":{"id":"deepinfra/gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT (DeepInfra)","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.07,"output":0.34},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"deepinfra/ling-3.0-flash-vl":{"id":"deepinfra/ling-3.0-flash-vl","name":"Ling 3.0 Flash VL (DeepInfra)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.06,"output":0.18,"cache_read":0.012}},"deepinfra/granite-4.2-8b":{"id":"deepinfra/granite-4.2-8b","name":"Granite 4.2 8B (DeepInfra)","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"granite","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":117964},"cost":{"input":0.06,"output":0.25,"cache_read":0.015}},"deepinfra/nemotron-3-ultra-550b":{"id":"deepinfra/nemotron-3-ultra-550b","name":"Nemotron 3 Ultra 550B (DeepInfra)","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","family":"nemotron","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":2.2,"cache_read":0.1}},"deepinfra/qwen3.5-9b":{"id":"deepinfra/qwen3.5-9b","name":"Qwen3.5 9B (DeepInfra)","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.1,"output":0.15},"canonical_model_id":"alibaba/qwen3.5-9b"},"deepinfra/inkling":{"id":"deepinfra/inkling","name":"Inkling (DeepInfra)","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":262144},"cost":{"input":0.95,"output":4.05,"cache_read":0.16},"canonical_model_id":"thinkingmachines/inkling"},"deepinfra/mimo-v2.6-flash":{"id":"deepinfra/mimo-v2.6-flash","name":"MiMo V2.6 Flash (DeepInfra)","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"deepinfra/deepseek-v4-pro":{"id":"deepinfra/deepseek-v4-pro","name":"DeepSeek V4 Pro (DeepInfra)","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":64000},"cost":{"input":1.3,"output":2.6,"cache_read":0.1},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepinfra/deepseek-v3.2":{"id":"deepinfra/deepseek-v3.2","name":"DeepSeek V3.2 (DeepInfra)","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":160000,"output":65536},"cost":{"input":0.26,"output":0.38,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepinfra/deepseek-v4-flash":{"id":"deepinfra/deepseek-v4-flash","name":"DeepSeek V4 Flash (DeepInfra)","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":0.08,"output":0.18,"cache_read":0.016},"canonical_model_id":"deepseek/deepseek-v4-flash"},"cerebras/gemma-4-31b-it":{"id":"cerebras/gemma-4-31b-it","name":"Gemma 4 31B IT (Cerebras)","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.99,"output":1.49},"canonical_model_id":"google/gemma-4-31b-it"},"cerebras/qwen3-235b-a22b-instruct-2507":{"id":"cerebras/qwen3-235b-a22b-instruct-2507","name":"Qwen3 235B A22B Instruct 2507 (Cerebras)","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":8192},"cost":{"input":0.6,"output":1.2},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"cerebras/llama-3.3-70b-instruct":{"id":"cerebras/llama-3.3-70b-instruct","name":"Llama 3.3 70B Instruct (Cerebras)","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.85,"output":1.2},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"cerebras/glm-4.7":{"id":"cerebras/glm-4.7","name":"GLM-4.7 (Cerebras)","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":2.25,"output":2.75},"canonical_model_id":"zhipuai/glm-4.7"},"cerebras/gpt-oss-120b":{"id":"cerebras/gpt-oss-120b","name":"GPT OSS 120B (Cerebras)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.35,"output":0.75},"canonical_model_id":"openai/gpt-oss-120b"},"groq/gpt-oss-20b":{"id":"groq/gpt-oss-20b","name":"GPT OSS 20B (Groq)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32766},"cost":{"input":0.1,"output":0.5},"canonical_model_id":"openai/gpt-oss-20b"},"groq/gpt-oss-120b":{"id":"groq/gpt-oss-120b","name":"GPT OSS 120B (Groq)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32766},"cost":{"input":0.15,"output":0.75},"canonical_model_id":"openai/gpt-oss-120b"},"scx-ai-gp/glm-5.3-flash":{"id":"scx-ai-gp/glm-5.3-flash","name":"GLM-5.3 Flash (SCX.ai)","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.088,"output":0.25,"cache_read":0.025},"canonical_model_id":"zhipuai/glm-5.3-flash"},"scx-ai-gp/glm-5.2-fast":{"id":"scx-ai-gp/glm-5.2-fast","name":"GLM-5.2 Turbo (SCX.ai)","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":2.156,"output":6.776,"cache_read":0.429},"canonical_model_id":"zhipuai/glm-5.2"},"scx-ai-gp/qwen3.8-max":{"id":"scx-ai-gp/qwen3.8-max","name":"Qwen3.8 Max (SCX.ai)","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":1.54,"output":4.631,"cache_read":0.198,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"scx-ai-gp/kimi-k3":{"id":"scx-ai-gp/kimi-k3","name":"Kimi K3 (SCX.ai)","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":3.135,"output":15.675,"cache_read":0.319},"canonical_model_id":"moonshotai/kimi-k3"},"scx-ai-gp/deepseek-v4.1-flash":{"id":"scx-ai-gp/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash (SCX.ai)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.01},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"scx-ai-gp/glm-5.2":{"id":"scx-ai-gp/glm-5.2","name":"GLM-5.2 (SCX.ai)","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.605,"output":2.123,"cache_read":0.154},"canonical_model_id":"zhipuai/glm-5.2"},"scx-ai-gp/glm-5.3":{"id":"scx-ai-gp/glm-5.3","name":"GLM-5.3 (SCX.ai)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.924,"output":2.904,"cache_read":0.1716},"canonical_model_id":"zhipuai/glm-5.3"},"scx-ai-gp/kimi-k2.7-code":{"id":"scx-ai-gp/kimi-k2.7-code","name":"Kimi K2.7 Code (SCX.ai)","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.737,"output":3.08,"cache_read":0.143},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"scx-ai-gp/glm-5.3-fast":{"id":"scx-ai-gp/glm-5.3-fast","name":"GLM 5.3 Fast (SCX.ai)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":2.8,"output":8.8,"cache_read":0.56},"canonical_model_id":"zhipuai/glm-5.3"},"zai/glm-4.6v":{"id":"zai/glm-4.6v","name":"GLM-4.6V (Z AI)","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16000},"cost":{"input":0.3,"output":0.9,"cache_read":0.05},"canonical_model_id":"zhipuai/glm-4.6v"},"zai/glm-4.5":{"id":"zai/glm-4.5","name":"GLM-4.5 (Z AI)","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":98304},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5"},"zai/glm-5.3-flash":{"id":"zai/glm-5.3-flash","name":"GLM-5.3 Flash (Z AI)","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai/glm-4.6":{"id":"zai/glm-4.6","name":"GLM-4.6 (Z AI)","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.6"},"zai/glm-4.5-x":{"id":"zai/glm-4.5-x","name":"GLM-4.5 X (Z AI)","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000},"cost":{"input":2.2,"output":8.9,"cache_read":0.45}},"zai/glm-5":{"id":"zai/glm-5","name":"GLM-5 (Z AI)","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202800,"output":131100},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"zai/glm-4.5-airx":{"id":"zai/glm-4.5-airx","name":"GLM-4.5 AirX (Z AI)","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000},"cost":{"input":1.1,"output":4.5,"cache_read":0.22}},"zai/glm-4.5v":{"id":"zai/glm-4.5v","name":"GLM-4.5V (Z AI)","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16000},"cost":{"input":0.6,"output":1.8,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5v"},"zai/glm-4-32b-0414-128k":{"id":"zai/glm-4-32b-0414-128k","name":"GLM-4 32B (0414-128k) (Z AI)","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000},"cost":{"input":0.1,"output":0.1}},"zai/glm-4.6v-flashx":{"id":"zai/glm-4.6v-flashx","name":"GLM-4.6V FlashX (Z AI)","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16000},"cost":{"input":0.04,"output":0.4,"cache_read":0.004}},"zai/glm-4.7":{"id":"zai/glm-4.7","name":"GLM-4.7 (Z AI)","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.7"},"zai/glm-5.2":{"id":"zai/glm-5.2","name":"GLM-5.2 (Z AI)","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"zai/glm-5.1":{"id":"zai/glm-5.1","name":"GLM-5.1 (Z AI)","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"zai/glm-4.7-flashx":{"id":"zai/glm-4.7-flashx","name":"GLM-4.7 FlashX (Z AI)","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.07,"output":0.4,"cache_read":0.01},"canonical_model_id":"zhipuai/glm-4.7-flashx"},"zai/glm-4.5-air":{"id":"zai/glm-4.5-air","name":"GLM-4.5 Air (Z AI)","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":98304},"cost":{"input":0.2,"output":1.1,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-4.5-air"},"zai/glm-5.3":{"id":"zai/glm-5.3","name":"GLM-5.3 (Z AI)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"luminal/deepseek-v4.1-flash":{"id":"luminal/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash (luminal)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.135,"output":0.54,"cache_read":0.0027},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"aws-bedrock/claude-haiku-4-5":{"id":"aws-bedrock/claude-haiku-4-5","name":"Claude Haiku 4.5 (AWS Bedrock)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"aws-bedrock/kimi-k3":{"id":"aws-bedrock/kimi-k3","name":"Kimi K3 (AWS Bedrock)","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"moonshotai/kimi-k3"},"aws-bedrock/llama-4-maverick-17b-instruct":{"id":"aws-bedrock/llama-4-maverick-17b-instruct","name":"Llama 4 Maverick 17B Instruct (AWS Bedrock)","description":"Open multimodal Llama for strong reasoning with efficient everyday serving","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":2048},"cost":{"input":0.24,"output":0.97},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"aws-bedrock/claude-sonnet-4-5":{"id":"aws-bedrock/claude-sonnet-4-5","name":"Claude Sonnet 4.5 (AWS Bedrock)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":63999},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"aws-bedrock/claude-opus-5-5":{"id":"aws-bedrock/claude-opus-5-5","name":"Claude Opus 5.5 (AWS Bedrock)","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"aws-bedrock/claude-fable-5-1":{"id":"aws-bedrock/claude-fable-5-1","name":"Claude Fable 5.1 (AWS Bedrock)","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"aws-bedrock/llama-4-scout-17b-instruct":{"id":"aws-bedrock/llama-4-scout-17b-instruct","name":"Llama 4 Scout 17B Instruct (AWS Bedrock)","description":"Open Llama with long-context vision for efficient multimodal agents","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":2048},"cost":{"input":0.17,"output":0.66},"canonical_model_id":"meta/llama-4-scout-17b-instruct"},"aws-bedrock/claude-opus-4-1-20250805":{"id":"aws-bedrock/claude-opus-4-1-20250805","name":"Claude Opus 4.1 (AWS Bedrock)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":31999},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1-20250805"},"aws-bedrock/claude-opus-4-5-20251101":{"id":"aws-bedrock/claude-opus-4-5-20251101","name":"Claude Opus 4.5 (AWS Bedrock)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":31999},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-01","last_updated":"2025-11-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"aws-bedrock/claude-opus-5":{"id":"aws-bedrock/claude-opus-5","name":"Claude Opus 5 (AWS Bedrock)","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"aws-bedrock/claude-fable-5":{"id":"aws-bedrock/claude-fable-5","name":"Claude Fable 5 (AWS Bedrock)","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"aws-bedrock/claude-opus-4-8":{"id":"aws-bedrock/claude-opus-4-8","name":"Claude Opus 4.8 (AWS Bedrock)","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"aws-bedrock/claude-sonnet-4-5-20250929":{"id":"aws-bedrock/claude-sonnet-4-5-20250929","name":"Claude Sonnet 4.5 (2025-09-29) (AWS Bedrock)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":63999},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"aws-bedrock/claude-sonnet-5":{"id":"aws-bedrock/claude-sonnet-5","name":"Claude Sonnet 5 (AWS Bedrock)","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"aws-bedrock/claude-opus-4-6":{"id":"aws-bedrock/claude-opus-4-6","name":"Claude Opus 4.6 (AWS Bedrock)","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"aws-bedrock/grok-4-3":{"id":"aws-bedrock/grok-4-3","name":"Grok 4.3 (AWS Bedrock)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"aws-bedrock/claude-haiku-4-5-20251001":{"id":"aws-bedrock/claude-haiku-4-5-20251001","name":"Claude Haiku 4.5 (2025-10-01) (AWS Bedrock)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"aws-bedrock/grok-4-6":{"id":"aws-bedrock/grok-4-6","name":"Grok 4.6 (AWS Bedrock)","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"aws-bedrock/claude-haiku-5-5":{"id":"aws-bedrock/claude-haiku-5-5","name":"Claude Haiku 5.5 (AWS Bedrock)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"anthropic/claude-haiku-5-5"},"aws-bedrock/claude-sonnet-4-6":{"id":"aws-bedrock/claude-sonnet-4-6","name":"Claude Sonnet 4.6 (AWS Bedrock)","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":63999},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"aws-bedrock/claude-sonnet-5-5":{"id":"aws-bedrock/claude-sonnet-5-5","name":"Claude Sonnet 5.5 (AWS Bedrock)","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"aws-bedrock/grok-4-7":{"id":"aws-bedrock/grok-4-7","name":"Grok 4.7 (AWS Bedrock)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":524288},"cost":{"input":2,"output":6,"cache_read":0.5}},"aws-bedrock/claude-opus-4-7":{"id":"aws-bedrock/claude-opus-4-7","name":"Claude Opus 4.7 (AWS Bedrock)","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"aws-bedrock/llama-3.1-70b-instruct":{"id":"aws-bedrock/llama-3.1-70b-instruct","name":"Llama 3.1 70B Instruct (AWS Bedrock)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":2048},"cost":{"input":0.72,"output":0.72}},"google-ai-studio/gemini-3.6-flash":{"id":"google-ai-studio/gemini-3.6-flash","name":"Gemini 3.6 Flash (Google AI Studio)","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.6-flash"},"google-ai-studio/gemini-3.5-flash-lite":{"id":"google-ai-studio/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite (Google AI Studio)","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google-ai-studio/gemini-3.1-pro-preview":{"id":"google-ai-studio/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro (Preview) (Google AI Studio)","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google-ai-studio/gemini-3.5-flash":{"id":"google-ai-studio/gemini-3.5-flash","name":"Gemini 3.5 Flash (Google AI Studio)","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.5-flash"},"google-ai-studio/gemini-3.7-flash":{"id":"google-ai-studio/gemini-3.7-flash","name":"Gemini 3.7 Flash (Google AI Studio)","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.7-flash"},"google-ai-studio/gemini-3-flash-preview":{"id":"google-ai-studio/gemini-3-flash-preview","name":"Gemini 3 Flash (Preview) (Google AI Studio)","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.5,"output":3,"cache_read":0.05},"canonical_model_id":"google/gemini-3-flash-preview"},"google-ai-studio/gemini-pro-latest":{"id":"google-ai-studio/gemini-pro-latest","name":"Gemini Pro Latest (Google AI Studio)","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-27","last_updated":"2026-02-27","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2}},"google-ai-studio/gemini-3.8-flash":{"id":"google-ai-studio/gemini-3.8-flash","name":"Gemini 3.8 Flash (Google AI Studio)","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.8-flash"},"google-ai-studio/gemini-4-argon":{"id":"google-ai-studio/gemini-4-argon","name":"Gemini 4 Argon (Google AI Studio)","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":0.375},"canonical_model_id":"google/gemini-4-argon"},"google-ai-studio/gemini-3.1-flash-lite":{"id":"google-ai-studio/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite (Google AI Studio)","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.1-flash-lite"},"anthropic/claude-haiku-4-5":{"id":"anthropic/claude-haiku-4-5","name":"Claude Haiku 4.5 (Anthropic)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-sonnet-4-5":{"id":"anthropic/claude-sonnet-4-5","name":"Claude Sonnet 4.5 (Anthropic)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":63999},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-opus-5-5":{"id":"anthropic/claude-opus-5-5","name":"Claude Opus 5.5 (Anthropic)","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-fable-5-1":{"id":"anthropic/claude-fable-5-1","name":"Claude Fable 5.1 (Anthropic)","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-opus-4-5-20251101":{"id":"anthropic/claude-opus-4-5-20251101","name":"Claude Opus 4.5 (Anthropic)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":31999},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-01","last_updated":"2025-11-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5 (Anthropic)","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5 (Anthropic)","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-opus-4-8":{"id":"anthropic/claude-opus-4-8","name":"Claude Opus 4.8 (Anthropic)","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-sonnet-4-5-20250929":{"id":"anthropic/claude-sonnet-4-5-20250929","name":"Claude Sonnet 4.5 (2025-09-29) (Anthropic)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":63999},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5 (Anthropic)","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-opus-4-6":{"id":"anthropic/claude-opus-4-6","name":"Claude Opus 4.6 (Anthropic)","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-haiku-4-5-20251001":{"id":"anthropic/claude-haiku-4-5-20251001","name":"Claude Haiku 4.5 (2025-10-01) (Anthropic)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"anthropic/claude-haiku-5-5":{"id":"anthropic/claude-haiku-5-5","name":"Claude Haiku 5.5 (Anthropic)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-sonnet-4-6":{"id":"anthropic/claude-sonnet-4-6","name":"Claude Sonnet 4.6 (Anthropic)","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":63999},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-sonnet-5-5":{"id":"anthropic/claude-sonnet-5-5","name":"Claude Sonnet 5.5 (Anthropic)","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-opus-4-7":{"id":"anthropic/claude-opus-4-7","name":"Claude Opus 4.7 (Anthropic)","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash (DeepSeek)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":393216},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro (DeepSeek)","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":393216},"cost":{"input":0.435,"output":0.87,"cache_read":0.003625},"canonical_model_id":"deepseek/deepseek-v4-pro"},"runpod/kimi-k3":{"id":"runpod/kimi-k3","name":"Kimi K3 (Runpod)","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"runware/gemma-4-31b-it":{"id":"runware/gemma-4-31b-it","name":"Gemma 4 31B IT (Runware)","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.102,"output":0.297,"cache_read":0.012},"canonical_model_id":"google/gemma-4-31b-it"},"runware/glm-5.3-flash":{"id":"runware/glm-5.3-flash","name":"GLM-5.3 Flash (Runware)","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"runware/kimi-k3":{"id":"runware/kimi-k3","name":"Kimi K3 (Runware)","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"runware/deepseek-v4.1-flash":{"id":"runware/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash (Runware)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.01},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"runware/kimi-k2.6":{"id":"runware/kimi-k2.6","name":"Kimi K2.6 (Runware)","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.6,"output":3.05,"cache_read":0.13},"canonical_model_id":"moonshotai/kimi-k2.6"},"runware/glm-5.2":{"id":"runware/glm-5.2","name":"GLM-5.2 (Runware)","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":128000},"cost":{"input":0.8,"output":2.55,"cache_read":0.16},"canonical_model_id":"zhipuai/glm-5.2"},"runware/deepseek-v4-pro":{"id":"runware/deepseek-v4-pro","name":"DeepSeek V4 Pro (Runware)","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.961,"output":1.922,"cache_read":0.079},"canonical_model_id":"deepseek/deepseek-v4-pro"},"runware/gpt-oss-120b":{"id":"runware/gpt-oss-120b","name":"GPT OSS 120B (Runware)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.032,"output":0.14,"cache_read":0.032},"canonical_model_id":"openai/gpt-oss-120b"},"runware/glm-5.3":{"id":"runware/glm-5.3","name":"GLM-5.3 (Runware)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5.3"},"runware/deepseek-v4-flash":{"id":"runware/deepseek-v4-flash","name":"DeepSeek V4 Flash (Runware)","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.076,"output":0.153,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash"},"tencent/glm-5v-turbo":{"id":"tencent/glm-5v-turbo","name":"GLM-5V Turbo (Tencent Cloud)","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5v-turbo"},"tencent/kimi-k3":{"id":"tencent/kimi-k3","name":"Kimi K3 (Tencent Cloud)","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"tencent/glm-5":{"id":"tencent/glm-5","name":"GLM-5 (Tencent Cloud)","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"tencent/kimi-k2.7-code-highspeed":{"id":"tencent/kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code Highspeed (Tencent Cloud)","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"tencent/kimi-k2.6":{"id":"tencent/kimi-k2.6","name":"Kimi K2.6 (Tencent Cloud)","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.858,"output":3.566,"cache_read":0.145},"canonical_model_id":"moonshotai/kimi-k2.6"},"tencent/minimax-m2.7":{"id":"tencent/minimax-m2.7","name":"MiniMax M2.7 (Tencent Cloud)","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7"},"tencent/mimo-v2.5-pro":{"id":"tencent/mimo-v2.5-pro","name":"MiMo V2.5 Pro (Tencent Cloud)","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036,"tiers":[{"input":2,"output":6,"cache_read":0.4,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.4}},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"tencent/minimax-m3":{"id":"tencent/minimax-m3","name":"MiniMax M3 (Tencent Cloud)","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"tencent/glm-5.2":{"id":"tencent/glm-5.2","name":"GLM-5.2 (Tencent Cloud)","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"tencent/hy3":{"id":"tencent/hy3","name":"Hy3 (Tencent Cloud)","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.132,"output":0.528,"cache_read":0.033},"canonical_model_id":"tencent/hy3"},"tencent/hy-mt2-plus":{"id":"tencent/hy-mt2-plus","name":"Hy-MT2 Plus (Tencent Cloud)","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":4096},"cost":{"input":0.074,"output":0.295}},"tencent/glm-5.1":{"id":"tencent/glm-5.1","name":"GLM-5.1 (Tencent Cloud)","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"tencent/glm-5-turbo":{"id":"tencent/glm-5-turbo","name":"GLM-5 Turbo (Tencent Cloud)","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5-turbo"},"tencent/deepseek-v4-pro":{"id":"tencent/deepseek-v4-pro","name":"DeepSeek V4 Pro (Tencent Cloud)","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":0.435,"output":0.87,"cache_read":0.00363},"canonical_model_id":"deepseek/deepseek-v4-pro"},"tencent/hy4-preview":{"id":"tencent/hy4-preview","name":"Hy4 Preview (Tencent Cloud)","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"},"tencent/kimi-k2.7-code":{"id":"tencent/kimi-k2.7-code","name":"Kimi K2.7 Code (Tencent Cloud)","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"tencent/deepseek-v4-flash":{"id":"tencent/deepseek-v4-flash","name":"DeepSeek V4 Flash (Tencent Cloud)","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"meta-contributor/muse-spark-1.2-contributor":{"id":"meta-contributor/muse-spark-1.2-contributor","name":"Muse Spark 1.2 Contributor (Meta Contributor)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-06","last_updated":"2026-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"meta-contributor/muse-spark-1.3-contributor":{"id":"meta-contributor/muse-spark-1.3-contributor","name":"Muse Spark 1.3 Contributor (Meta Contributor)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"novita/glm-4.6v":{"id":"novita/glm-4.6v","name":"GLM-4.6V (NovitaAI)","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16000},"cost":{"input":0.3,"output":0.9,"cache_read":0.055},"canonical_model_id":"zhipuai/glm-4.6v"},"novita/gemma-4-31b-it":{"id":"novita/gemma-4-31b-it","name":"Gemma 4 31B IT (NovitaAI)","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.14,"output":0.4},"canonical_model_id":"google/gemma-4-31b-it"},"novita/qwen3-vl-235b-a22b-instruct":{"id":"novita/qwen3-vl-235b-a22b-instruct","name":"Qwen3 VL 235B A22B Instruct (NovitaAI)","description":"Qwen vision-language instruct model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.3,"output":1.5},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"novita/qwen3.7-max":{"id":"novita/qwen3.7-max","name":"Qwen3.7 Max (NovitaAI)","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":1.25,"output":3.75,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.7-max"},"novita/mimo-v2.5":{"id":"novita/mimo-v2.5","name":"MiMo V2.5 (NovitaAI)","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.168,"output":0.336,"cache_read":0.0034,"tiers":[{"input":0.8,"output":4,"cache_read":0.16,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.8,"output":4,"cache_read":0.16}},"canonical_model_id":"xiaomi/mimo-v2.5"},"novita/qwen3.8-27b":{"id":"novita/qwen3.8-27b","name":"Qwen3.8 27B (NovitaAI)","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.42,"output":3,"cache_read":0.085},"canonical_model_id":"alibaba/qwen3.8-27b"},"novita/qwen3-vl-235b-a22b-thinking":{"id":"novita/qwen3-vl-235b-a22b-thinking","name":"Qwen3 VL 235B A22B Thinking (NovitaAI)","description":"Qwen vision-language thinking model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.98,"output":3.95},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-thinking"},"novita/qwen3.8-2.4t-a95b":{"id":"novita/qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B (NovitaAI)","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"novita/glm-5.3-flash":{"id":"novita/glm-5.3-flash","name":"GLM-5.3 Flash (NovitaAI)","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"novita/glm-4.6":{"id":"novita/glm-4.6","name":"GLM-4.6 (NovitaAI)","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.55,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.6"},"novita/qwen3-235b-a22b-instruct-2507":{"id":"novita/qwen3-235b-a22b-instruct-2507","name":"Qwen3 235B A22B Instruct 2507 (NovitaAI)","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.09,"output":0.58},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"novita/qwen3.8-max":{"id":"novita/qwen3.8-max","name":"Qwen3.8 Max (NovitaAI)","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-max"},"novita/kimi-k3":{"id":"novita/kimi-k3","name":"Kimi K3 (NovitaAI)","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"novita/llama-4-maverick-17b-instruct":{"id":"novita/llama-4-maverick-17b-instruct","name":"Llama 4 Maverick 17B Instruct (NovitaAI)","description":"Open multimodal Llama for strong reasoning with efficient everyday serving","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":8192},"cost":{"input":0.27,"output":0.85},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"novita/glm-5":{"id":"novita/glm-5","name":"GLM-5 (NovitaAI)","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202800,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"novita/deepseek-v4.1-flash":{"id":"novita/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash (NovitaAI)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"novita/minimax-m2.5":{"id":"novita/minimax-m2.5","name":"MiniMax M2.5 (NovitaAI)","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131100},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5"},"novita/kimi-k2.6":{"id":"novita/kimi-k2.6","name":"Kimi K2.6 (NovitaAI)","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.8,"output":3.4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"novita/qwen3-max":{"id":"novita/qwen3-max","name":"Qwen3 Max (NovitaAI)","description":"Flagship Qwen3 model for coding agents, complex reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.845,"output":3.38},"canonical_model_id":"alibaba/qwen3-max"},"novita/glm-4.5v":{"id":"novita/glm-4.5v","name":"GLM-4.5V (NovitaAI)","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":16000},"cost":{"input":0.6,"output":1.8,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5v"},"novita/llama-4-scout-17b-instruct":{"id":"novita/llama-4-scout-17b-instruct","name":"Llama 4 Scout 17B Instruct (NovitaAI)","description":"Open Llama with long-context vision for efficient multimodal agents","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.18,"output":0.59},"canonical_model_id":"meta/llama-4-scout-17b-instruct"},"novita/qwen3-235b-a22b-fp8":{"id":"novita/qwen3-235b-a22b-fp8","name":"Qwen3 235B A22B FP8 (NovitaAI)","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":40960,"output":20000},"cost":{"input":0.2,"output":0.8}},"novita/qwen3-coder-480b-a35b-instruct":{"id":"novita/qwen3-coder-480b-a35b-instruct","name":"Qwen3 Coder 480B A35B Instruct (NovitaAI)","description":"Open Qwen coding heavyweight for repository reasoning and agentic engineering","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.38,"output":1.55},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"novita/qwen3-coder-30b-a3b-instruct":{"id":"novita/qwen3-coder-30b-a3b-instruct","name":"Qwen3 Coder 30B A3B Instruct (NovitaAI)","description":"Smaller Qwen coder for efficient local agents and repo-level fixes","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":160000,"output":32768},"cost":{"input":0.07,"output":0.27},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"novita/ling-3.0-flash":{"id":"novita/ling-3.0-flash","name":"InclusionAI Ling 3.0 Flash (NovitaAI)","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-02","last_updated":"2026-08-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.06,"output":0.18,"cache_read":0.012}},"novita/qwen3-vl-30b-a3b-instruct":{"id":"novita/qwen3-vl-30b-a3b-instruct","name":"Qwen3 VL 30B A3B Instruct (NovitaAI)","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-10-05","last_updated":"2025-10-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.2,"output":0.7}},"novita/ling-3.1-flash":{"id":"novita/ling-3.1-flash","name":"Ling 3.1 Flash (NovitaAI)","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"inclusionai/ling-3.1-flash"},"novita/gemma-4-26b-a4b-it":{"id":"novita/gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT (NovitaAI)","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.13,"output":0.4},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"novita/llama-3-70b-instruct":{"id":"novita/llama-3-70b-instruct","name":"Llama 3 70B Instruct (NovitaAI)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2024-04-18","last_updated":"2024-04-18","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8000},"cost":{"input":0.51,"output":0.74}},"novita/qwen3-235b-a22b-thinking-2507":{"id":"novita/qwen3-235b-a22b-thinking-2507","name":"Qwen3 235B A22B Thinking 2507 (NovitaAI)","description":"Tool-capable chat model for instruction following and agentic application workflows","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-07-25","last_updated":"2025-07-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.3,"output":3}},"novita/qwen3.5-122b-a10b":{"id":"novita/qwen3.5-122b-a10b","name":"Qwen3.5 122B A10B (NovitaAI)","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.4,"output":3.2},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"novita/llama-3.3-70b-instruct":{"id":"novita/llama-3.3-70b-instruct","name":"Llama 3.3 70B Instruct (NovitaAI)","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":120000},"cost":{"input":0.135,"output":0.4},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"novita/qwen3.6-35b-a3b":{"id":"novita/qwen3.6-35b-a3b","name":"Qwen3.6 35B A3B (NovitaAI)","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":64000},"cost":{"input":0.248,"output":1.485},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"novita/qwen3-next-80b-a3b-instruct":{"id":"novita/qwen3-next-80b-a3b-instruct","name":"Qwen3 Next 80B A3B Instruct (NovitaAI)","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":1.5},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"novita/minimax-m2.7":{"id":"novita/minimax-m2.7","name":"MiniMax M2.7 (NovitaAI)","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131100},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7"},"novita/mimo-v2.5-pro":{"id":"novita/mimo-v2.5-pro","name":"MiMo V2.5 Pro (NovitaAI)","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.522,"output":1.044,"cache_read":0.0043,"tiers":[{"input":2,"output":6,"cache_read":0.4,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.4}},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"novita/glm-4.7":{"id":"novita/glm-4.7","name":"GLM-4.7 (NovitaAI)","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":128000},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.7"},"novita/qwen3.8-flash":{"id":"novita/qwen3.8-flash","name":"Qwen3.8 Flash (NovitaAI)","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-flash"},"novita/qwen35-397b-a17b":{"id":"novita/qwen35-397b-a17b","name":"Qwen3.5 397B A17B (NovitaAI)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"qwen3.5","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":64000},"cost":{"input":0.6,"output":3.6}},"novita/glm-5.2":{"id":"novita/glm-5.2","name":"GLM-5.2 (NovitaAI)","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"novita/ernie-4.5-vl-424b-a47b":{"id":"novita/ernie-4.5-vl-424b-a47b","name":"ERNIE 4.5 VL 424B A47B (NovitaAI)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ernie","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-06-30","last_updated":"2025-06-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":123000,"output":16000},"cost":{"input":0.42,"output":1.25}},"novita/hy3":{"id":"novita/hy3","name":"Hy3 (NovitaAI)","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":192000,"output":262144},"cost":{"input":0.14,"output":0.58,"cache_read":0.035},"canonical_model_id":"tencent/hy3"},"novita/kimi-k2":{"id":"novita/kimi-k2","name":"Kimi K2 (NovitaAI)","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":131072},"cost":{"input":0.57,"output":2.3}},"novita/glm-5.1":{"id":"novita/glm-5.1","name":"GLM-5.1 (NovitaAI)","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1.38,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"novita/step-3.7-flash":{"id":"novita/step-3.7-flash","name":"Step 3.7 Flash (NovitaAI)","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"novita/llama-3.2-3b-instruct":{"id":"novita/llama-3.2-3b-instruct","name":"Llama 3.2 3B Instruct (NovitaAI)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2024-09-18","last_updated":"2024-09-18","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":32000},"cost":{"input":0.03,"output":0.05}},"novita/deepseek-v3.2":{"id":"novita/deepseek-v3.2","name":"DeepSeek V3.2 (NovitaAI)","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":65536},"cost":{"input":0.269,"output":0.4,"cache_read":0.1345},"canonical_model_id":"deepseek/deepseek-v3.2"},"novita/glm-5.3":{"id":"novita/glm-5.3","name":"GLM-5.3 (NovitaAI)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"novita/kimi-k2.7-code":{"id":"novita/kimi-k2.7-code","name":"Kimi K2.7 Code (NovitaAI)","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"novita/minimax-m2.1":{"id":"novita/minimax-m2.1","name":"MiniMax M2.1 (NovitaAI)","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.1"},"novita/deepseek-v4-flash":{"id":"novita/deepseek-v4-flash","name":"DeepSeek V4 Flash (NovitaAI)","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":393216},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"embercloud/glm-4.5":{"id":"embercloud/glm-4.5","name":"GLM-4.5 (EmberCloud)","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":96000},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5"},"embercloud/qwen3-coder-next":{"id":"embercloud/qwen3-coder-next","name":"Qwen3 Coder Next (EmberCloud)","description":"Open-weight Qwen coding model for agents, repository edits, and multi-turn tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.108,"output":0.675,"cache_read":0.06},"canonical_model_id":"alibaba/qwen3-coder-next"},"embercloud/glm-5":{"id":"embercloud/glm-5","name":"GLM-5 (EmberCloud)","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":203000,"output":131000},"cost":{"input":0.72,"output":2.3,"cache_read":0.144},"canonical_model_id":"zhipuai/glm-5"},"embercloud/kimi-k2.5":{"id":"embercloud/kimi-k2.5","name":"Kimi K2.5 (EmberCloud)","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.405,"output":1.98,"cache_read":0.225},"canonical_model_id":"moonshotai/kimi-k2.5"},"embercloud/glm-4.7-flash":{"id":"embercloud/glm-4.7-flash","name":"GLM-4.7 Flash (EmberCloud)","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131000},"cost":{"input":0.06,"output":0.4,"cache_read":0.01},"canonical_model_id":"zhipuai/glm-4.7-flash"},"embercloud/glm-4.7":{"id":"embercloud/glm-4.7","name":"GLM-4.7 (EmberCloud)","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131000},"cost":{"input":0.38,"output":1.98,"cache_read":0.19},"canonical_model_id":"zhipuai/glm-4.7"},"embercloud/glm-5.2":{"id":"embercloud/glm-5.2","name":"GLM-5.2 (EmberCloud)","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":203000,"output":131000},"cost":{"input":1.26,"output":3.96,"cache_read":0.234},"canonical_model_id":"zhipuai/glm-5.2"},"embercloud/glm-5.1":{"id":"embercloud/glm-5.1","name":"GLM-5.1 (EmberCloud)","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":203000,"output":131000},"cost":{"input":0.931,"output":2.93,"cache_read":0.173},"canonical_model_id":"zhipuai/glm-5.1"},"embercloud/glm-4.5-air":{"id":"embercloud/glm-4.5-air","name":"GLM-4.5 Air (EmberCloud)","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":96000},"cost":{"input":0.13,"output":0.85,"cache_read":0.025},"canonical_model_id":"zhipuai/glm-4.5-air"},"perplexity/sonar":{"id":"perplexity/sonar","name":"Sonar (Perplexity)","description":"Fast web-grounded Sonar for current answers, citations, and lightweight retrieval","family":"sonar","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":130000,"output":4096},"cost":{"input":0.25,"output":2.5,"cache_write":0.25},"canonical_model_id":"perplexity/sonar"},"azure-ai-foundry/grok-4-1-fast-reasoning":{"id":"azure-ai-foundry/grok-4-1-fast-reasoning","name":"Grok 4.1 Fast Reasoning (Azure AI Foundry)","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":0.2,"output":0.5}},"azure-ai-foundry/grok-4-1-fast-non-reasoning":{"id":"azure-ai-foundry/grok-4-1-fast-non-reasoning","name":"Grok 4.1 Fast Non-Reasoning (Azure AI Foundry)","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":0.2,"output":0.5}},"azure-ai-foundry/grok-4-3":{"id":"azure-ai-foundry/grok-4-3","name":"Grok 4.3 (Azure AI Foundry)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":20000,"output":8192},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"meta/muse-spark-1.3":{"id":"meta/muse-spark-1.3","name":"Muse Spark 1.3 (Meta)","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.3"},"meta/muse-spark-1.1":{"id":"meta/muse-spark-1.1","name":"Muse Spark 1.1 (Meta)","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.1"},"meta/muse-spark-1.2":{"id":"meta/muse-spark-1.2","name":"Muse Spark 1.2 (Meta)","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"meta/muse-wonder-1.0":{"id":"meta/muse-wonder-1.0","name":"Muse Wonder 1.0 (Meta)","description":"Muse Wonder is a frontier multimodal reasoning model from Meta for personal and professional agents, long-horizon coding, and computer use. It combines Active Memory, which carries relevant context across conversations, with Active Focus, which keeps it working through blockers toward a goal.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":4,"output":20,"cache_read":0.2},"canonical_model_id":"meta/muse-wonder-1.0"},"azure/gpt-5.4":{"id":"azure/gpt-5.4","name":"GPT-5.4 (Azure)","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.4"},"azure/gpt-5.4-pro":{"id":"azure/gpt-5.4-pro","name":"GPT-5.4 Pro (Azure)","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180},"canonical_model_id":"openai/gpt-5.4-pro"},"azure/gpt-5.4-nano":{"id":"azure/gpt-5.4-nano","name":"GPT-5.4 Nano (Azure)","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"azure/gpt-5.2-codex":{"id":"azure/gpt-5.2-codex","name":"GPT-5.2 Codex (Azure)","description":"Code-specialist GPT for repository edits, reviews, and long-running software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-codex"},"azure/gpt-5.1-codex":{"id":"azure/gpt-5.1-codex","name":"GPT-5.1 Codex (Azure)","description":"Codex GPT for repository edits, code review, and practical software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":272000},"cost":{"input":1.25,"output":10},"canonical_model_id":"openai/gpt-5.1-codex"},"azure/gpt-4o":{"id":"azure/gpt-4o","name":"GPT-4o (Azure)","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"azure/gpt-5-mini":{"id":"azure/gpt-5-mini","name":"GPT-5 Mini (Azure)","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"azure/gpt-5.3-codex":{"id":"azure/gpt-5.3-codex","name":"GPT-5.3 Codex (Azure)","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"azure/gpt-5-nano":{"id":"azure/gpt-5-nano","name":"GPT-5 Nano (Azure)","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"azure/gpt-6.1-sol":{"id":"azure/gpt-6.1-sol","name":"GPT-6.1 Sol (Azure)","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"openai/gpt-6.1-sol"},"azure/gpt-6-astra":{"id":"azure/gpt-6-astra","name":"GPT-6 Astra (Azure)","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"openai/gpt-6-astra"},"azure/gpt-5.1":{"id":"azure/gpt-5.1","name":"GPT-5.1 (Azure)","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"azure/gpt-5.4-mini":{"id":"azure/gpt-5.4-mini","name":"GPT-5.4 Mini (Azure)","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"azure/gpt-5.6-luna":{"id":"azure/gpt-5.6-luna","name":"GPT-5.6 Luna (Azure)","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25},"canonical_model_id":"openai/gpt-5.6-luna"},"azure/gpt-5.2":{"id":"azure/gpt-5.2","name":"GPT-5.2 (Azure)","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"azure/gpt-5.5":{"id":"azure/gpt-5.5","name":"GPT-5.5 (Azure)","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"azure/gpt-4.1":{"id":"azure/gpt-4.1","name":"GPT-4.1 (Azure)","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"azure/gpt-4.1-mini":{"id":"azure/gpt-4.1-mini","name":"GPT-4.1 Mini (Azure)","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"azure/gpt-6-luna":{"id":"azure/gpt-6-luna","name":"GPT-6 Luna (Azure)","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"openai/gpt-6-luna"},"azure/gpt-5.6-terra":{"id":"azure/gpt-5.6-terra","name":"GPT-5.6 Terra (Azure)","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.6-terra"},"azure/gpt-oss-120b":{"id":"azure/gpt-oss-120b","name":"GPT OSS 120B (Azure)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-120b"},"azure/gpt-5.1-codex-mini":{"id":"azure/gpt-5.1-codex-mini","name":"GPT-5.1 Codex mini (Azure)","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5.1-codex-mini"},"azure/gpt-5":{"id":"azure/gpt-5","name":"GPT-5 (Azure)","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"azure/gpt-5.6-sol":{"id":"azure/gpt-5.6-sol","name":"GPT-5.6 Sol (Azure)","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5},"canonical_model_id":"openai/gpt-5.6-sol"},"azure/gpt-6-sol":{"id":"azure/gpt-6-sol","name":"GPT-6 Sol (Azure)","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-6-sol"},"alibaba/qwen-flash":{"id":"alibaba/qwen-flash","name":"Qwen Flash (Alibaba Cloud)","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32000},"cost":{"input":0.05,"output":0.4,"cache_read":0.01,"cache_write":0.0625},"canonical_model_id":"alibaba/qwen-flash"},"alibaba/qwen3.7-max":{"id":"alibaba/qwen3.7-max","name":"Qwen3.7 Max (Alibaba Cloud)","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"output":65536},"cost":{"input":2.5,"output":7.5,"cache_read":0.5,"cache_write":3.125},"canonical_model_id":"alibaba/qwen3.7-max"},"alibaba/qwen3-vl-plus":{"id":"alibaba/qwen3-vl-plus","name":"Qwen3 VL Plus (Alibaba Cloud)","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.2,"output":1.6,"cache_read":0.04,"cache_write":0.25},"canonical_model_id":"alibaba/qwen3-vl-plus"},"alibaba/qwen3.5-27b":{"id":"alibaba/qwen3.5-27b","name":"Qwen3.5 27B (Alibaba Cloud)","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.3,"output":2.4},"canonical_model_id":"alibaba/qwen3.5-27b"},"alibaba/qwen-max":{"id":"alibaba/qwen-max","name":"Qwen Max (Alibaba Cloud)","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-03","last_updated":"2025-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":8192},"cost":{"input":1.6,"output":6.4},"canonical_model_id":"alibaba/qwen-max"},"alibaba/qwen3.8-max":{"id":"alibaba/qwen3.8-max","name":"Qwen3.8 Max (Alibaba Cloud)","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"alibaba/kimi-k3":{"id":"alibaba/kimi-k3","name":"Kimi K3 (Alibaba Cloud)","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"alibaba/glm-5":{"id":"alibaba/glm-5","name":"GLM-5 (Alibaba Cloud)","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":16384},"cost":{"input":0.573,"output":2.58},"canonical_model_id":"zhipuai/glm-5"},"alibaba/deepseek-v4.1-flash":{"id":"alibaba/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash (Alibaba Cloud)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"alibaba/qwen-plus":{"id":"alibaba/qwen-plus","name":"Qwen Plus (Alibaba Cloud)","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32000},"cost":{"input":0.4,"output":1.2,"cache_read":0.08,"cache_write":0.5},"canonical_model_id":"alibaba/qwen-plus"},"alibaba/qwen3.7-flash":{"id":"alibaba/qwen3.7-flash","name":"Qwen3.7 Flash (Alibaba Cloud)","description":"Lightweight multimodal Qwen model for high-throughput text, image, and video tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"input":991808,"output":65536},"cost":{"input":0.03,"output":0.13,"cache_read":0.006,"cache_write":0.0375},"canonical_model_id":"alibaba/qwen3.7-flash"},"alibaba/qwen3.5-122b-a10b":{"id":"alibaba/qwen3.5-122b-a10b","name":"Qwen3.5 122B A10B (Alibaba Cloud)","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.4,"output":3.2},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"alibaba/kimi-k2.5":{"id":"alibaba/kimi-k2.5","name":"Kimi K2.5 (Alibaba Cloud)","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":0.574,"output":3.011},"canonical_model_id":"moonshotai/kimi-k2.5"},"alibaba/qwen3.6-35b-a3b":{"id":"alibaba/qwen3.6-35b-a3b","name":"Qwen3.6 35B A3B (Alibaba Cloud)","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.375,"output":2.25},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"alibaba/qwen3.6-flash":{"id":"alibaba/qwen3.6-flash","name":"Qwen3.6 Flash (Alibaba Cloud)","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.05,"cache_write":0.3125},"canonical_model_id":"alibaba/qwen3.6-flash"},"alibaba/qwen3-coder-flash":{"id":"alibaba/qwen3-coder-flash","name":"Qwen3 Coder Flash (Alibaba Cloud)","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":997952,"output":65536},"cost":{"input":0.3,"output":1.5,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"alibaba/qwen3-coder-flash"},"alibaba/qwen3.8-flash":{"id":"alibaba/qwen3.8-flash","name":"Qwen3.8 Flash (Alibaba Cloud)","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"alibaba/qwen35-397b-a17b":{"id":"alibaba/qwen35-397b-a17b","name":"Qwen3.5 397B A17B (Alibaba Cloud)","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.5","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.6,"output":3.6}},"alibaba/qwen3.5-35b-a3b":{"id":"alibaba/qwen3.5-35b-a3b","name":"Qwen3.5 35B A3B (Alibaba Cloud)","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.25,"output":2},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"alibaba/glm-5.2":{"id":"alibaba/glm-5.2","name":"GLM-5.2 (Alibaba Cloud)","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.28},"canonical_model_id":"zhipuai/glm-5.2"},"alibaba/deepseek-v4-pro":{"id":"alibaba/deepseek-v4-pro","name":"DeepSeek V4 Pro (Alibaba Cloud)","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":2.4,"output":4.8,"cache_read":0.2},"canonical_model_id":"deepseek/deepseek-v4-pro"},"alibaba/qwen3.6-plus":{"id":"alibaba/qwen3.6-plus","name":"Qwen3.6 Plus (Alibaba Cloud)","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625,"tiers":[{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5}},"canonical_model_id":"alibaba/qwen3.6-plus"},"alibaba/qwen-plus-latest":{"id":"alibaba/qwen-plus-latest","name":"Qwen Plus Latest (Alibaba Cloud)","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2024-09-09","last_updated":"2024-09-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32000},"cost":{"input":0.4,"output":1.2,"cache_read":0.08,"cache_write":0.5}},"alibaba/glm-5.3":{"id":"alibaba/glm-5.3","name":"GLM-5.3 (Alibaba Cloud)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.28},"canonical_model_id":"zhipuai/glm-5.3"},"alibaba/qwen3.7-plus":{"id":"alibaba/qwen3.7-plus","name":"Qwen3.7 Plus (Alibaba Cloud)","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"output":65536},"cost":{"input":0.4,"output":1.6,"cache_read":0.08,"cache_write":0.5},"canonical_model_id":"alibaba/qwen3.7-plus"},"alibaba/deepseek-v4-flash":{"id":"alibaba/deepseek-v4-flash","name":"DeepSeek V4 Flash (Alibaba Cloud)","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":0.2,"output":0.4,"cache_read":0.04},"canonical_model_id":"deepseek/deepseek-v4-flash"},"baidu/glm-5":{"id":"baidu/glm-5","name":"GLM-5 (Baidu)","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"baidu/deepseek-v4.1-flash":{"id":"baidu/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash (Baidu)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"baidu/kimi-k2.6":{"id":"baidu/kimi-k2.6","name":"Kimi K2.6 (Baidu)","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"baidu/glm-5.2":{"id":"baidu/glm-5.2","name":"GLM-5.2 (Baidu)","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"baidu/glm-5.1":{"id":"baidu/glm-5.1","name":"GLM-5.1 (Baidu)","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"baidu/deepseek-v4-pro":{"id":"baidu/deepseek-v4-pro","name":"DeepSeek V4 Pro (Baidu)","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.32,"output":3.96,"cache_read":0.042},"canonical_model_id":"deepseek/deepseek-v4-pro"},"baidu/glm-5.3":{"id":"baidu/glm-5.3","name":"GLM-5.3 (Baidu)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"baidu/deepseek-v4-flash":{"id":"baidu/deepseek-v4-flash","name":"DeepSeek V4 Flash (Baidu)","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.44,"output":1.32,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash"},"gonka24/minimax-m2.7":{"id":"gonka24/minimax-m2.7","name":"MiniMax M2.7 (Gonka24)","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131100},"cost":{"input":0.08,"output":0.32,"cache_read":0.017},"canonical_model_id":"minimax/MiniMax-M2.7"},"reka-ai/reka-edge-2603":{"id":"reka-ai/reka-edge-2603","name":"Reka Edge 2603 (reka-ai)","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"reka","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-09","last_updated":"2026-10-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":16384},"cost":{"input":0.1,"output":0.1}},"reka-ai/deepseek-v4-pro":{"id":"reka-ai/deepseek-v4-pro","name":"DeepSeek V4 Pro (reka-ai)","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":1.2,"output":3.3,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-v4-pro"},"reka-ai/glm-5.3":{"id":"reka-ai/glm-5.3","name":"GLM-5.3 (reka-ai)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":1.17,"output":3.96,"cache_read":0.234},"canonical_model_id":"zhipuai/glm-5.3"},"bytedance/seed-1-6-flash-250715":{"id":"bytedance/seed-1-6-flash-250715","name":"Seed 1.6 Flash (250715) (ByteDance)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-07-26","last_updated":"2025-07-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.07,"output":0.3,"cache_read":0.015}},"bytedance/seed-2-0-code-preview-260328":{"id":"bytedance/seed-2-0-code-preview-260328","name":"Seed 2.0 Code Preview (260328) (ByteDance)","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-28","last_updated":"2026-03-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.5,"output":3,"cache_read":0.1}},"bytedance/seed-1-6-250915":{"id":"bytedance/seed-1-6-250915","name":"Seed 1.6 (250915) (ByteDance)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.25,"output":2,"cache_read":0.05}},"bytedance/seed-2-0-mini-260428":{"id":"bytedance/seed-2-0-mini-260428","name":"Seed 2.0 Mini (260428) (ByteDance)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.1,"output":0.4,"cache_read":0.02}},"bytedance/seed-2-0-pro-260328":{"id":"bytedance/seed-2-0-pro-260328","name":"Seed 2.0 Pro (260328) (ByteDance)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-28","last_updated":"2026-03-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.5,"output":3,"cache_read":0.1}},"bytedance/seed-1-8-251228":{"id":"bytedance/seed-1-8-251228","name":"Seed 1.8 (251228) (ByteDance)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-18","last_updated":"2025-12-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.25,"output":2,"cache_read":0.05}},"bytedance/glm-4.7":{"id":"bytedance/glm-4.7","name":"GLM-4.7 (ByteDance)","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.7"},"bytedance/seed-1-6-250615":{"id":"bytedance/seed-1-6-250615","name":"Seed 1.6 (250615) (ByteDance)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-06-25","last_updated":"2025-06-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.25,"output":2,"cache_read":0.05}},"bytedance/glm-5.2":{"id":"bytedance/glm-5.2","name":"GLM-5.2 (ByteDance)","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":128000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"bytedance/seed-2-0-lite-260428":{"id":"bytedance/seed-2-0-lite-260428","name":"Seed 2.0 Lite (260428) (ByteDance)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.25,"output":2,"cache_read":0.05}},"bytedance/deepseek-v4-pro":{"id":"bytedance/deepseek-v4-pro","name":"DeepSeek V4 Pro (ByteDance)","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro"},"bytedance/deepseek-v3.2":{"id":"bytedance/deepseek-v3.2","name":"DeepSeek V3.2 (ByteDance)","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.28,"output":0.42,"cache_read":0.056},"canonical_model_id":"deepseek/deepseek-v3.2"},"bytedance/gpt-oss-120b":{"id":"bytedance/gpt-oss-120b","name":"GPT OSS 120B (ByteDance)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"cost":{"input":0.1,"output":0.5,"cache_read":0.02},"canonical_model_id":"openai/gpt-oss-120b"},"bytedance/deepseek-v4-flash":{"id":"bytedance/deepseek-v4-flash","name":"DeepSeek V4 Flash (ByteDance)","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.44,"output":1.32,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash"},"sciforium/deepseek-v4.1-flash":{"id":"sciforium/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash (sciforium)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.246,"output":0.944,"cache_read":0.012},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"xai/grok-4-5":{"id":"xai/grok-4-5","name":"Grok 4.5 (xAI)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.3}},"xai/grok-build-0-1":{"id":"xai/grok-build-0-1","name":"Grok Build 0.1 (xAI)","description":"Grok coding model for agentic engineering, edits, and codebase workflows","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-05-20","last_updated":"2026-05-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.2,"tiers":[{"input":2,"output":4,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2,"output":4,"cache_read":0.4}}},"xai/grok-4":{"id":"xai/grok-4","name":"Grok 4 (xAI)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-07-09","last_updated":"2025-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":3,"output":15,"cache_read":0.75}},"xai/grok-4-20-beta-0309-non-reasoning":{"id":"xai/grok-4-20-beta-0309-non-reasoning","name":"Grok 4.20 Beta Non-Reasoning (0309) (xAI)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":2,"output":6,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"xai/grok-4-3":{"id":"xai/grok-4-3","name":"Grok 4.3 (xAI)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"xai/grok-4-20-beta-0309-reasoning":{"id":"xai/grok-4-20-beta-0309-reasoning","name":"Grok 4.20 Beta Reasoning (0309) (xAI)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":2,"output":6,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"xai/grok-4-6":{"id":"xai/grok-4-6","name":"Grok 4.6 (xAI)","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"xai/grok-4-7":{"id":"xai/grok-4-7","name":"Grok 4.7 (xAI)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5}},"ranoai/deepseek-v4-flash":{"id":"ranoai/deepseek-v4-flash","name":"DeepSeek V4 Flash (RanoAI)","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"canopywave/kimi-k3":{"id":"canopywave/kimi-k3","name":"Kimi K3 (CanopyWave)","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"canopywave/kimi-k2.6":{"id":"canopywave/kimi-k2.6","name":"Kimi K2.6 (CanopyWave)","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"canopywave/glm-5.2":{"id":"canopywave/glm-5.2","name":"GLM-5.2 (CanopyWave)","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32768},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"canopywave/deepseek-v4-pro":{"id":"canopywave/deepseek-v4-pro","name":"DeepSeek V4 Pro (CanopyWave)","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":1.74,"output":3.48,"cache_read":0.01},"canonical_model_id":"deepseek/deepseek-v4-pro"},"canopywave/deepseek-v4-flash":{"id":"canopywave/deepseek-v4-flash","name":"DeepSeek V4 Flash (CanopyWave)","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":0.14,"output":0.28,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v4-flash"},"fireworks/glm-5.3-flash":{"id":"fireworks/glm-5.3-flash","name":"GLM-5.3 Flash (Fireworks AI)","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"fireworks/kimi-k3":{"id":"fireworks/kimi-k3","name":"Kimi K3 (Fireworks AI)","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1040384,"output":1040384},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"fireworks/deepseek-v4.1-flash":{"id":"fireworks/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash (Fireworks AI)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.22,"output":0.66,"cache_read":0.007},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"fireworks/kimi-k3-fast":{"id":"fireworks/kimi-k3-fast","name":"Kimi K3 Fast (Fireworks AI)","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1040384,"output":1040384},"cost":{"input":4.5,"output":22.5,"cache_read":0.45},"canonical_model_id":"moonshotai/kimi-k3"},"fireworks/glm-5.3":{"id":"fireworks/glm-5.3","name":"GLM-5.3 (Fireworks AI)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"fireworks/deepseek-v4-flash":{"id":"fireworks/deepseek-v4-flash","name":"DeepSeek V4 Flash (Fireworks AI)","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.22,"output":0.66,"cache_read":0.007},"canonical_model_id":"deepseek/deepseek-v4-flash"},"sakana/fugu-max":{"id":"sakana/fugu-max","name":"Fugu Max (Sakana AI)","description":"Multi-agent model for routing expert agents across complex analytical tasks","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":2,"output":6,"cache_read":0.25}},"sakana/fugu-ultra-v2.0":{"id":"sakana/fugu-ultra-v2.0","name":"Fugu Ultra v2.0 (Sakana AI)","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":5,"output":30,"cache_read":0.5}},"sakana/fugu-ultra":{"id":"sakana/fugu-ultra","name":"Fugu Ultra (Sakana AI)","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"sakana/fugu-ultra"},"scx-ai/qwen3-32b":{"id":"scx-ai/qwen3-32b","name":"Qwen3 32B (SCX.ai (Turbo))","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0.36,"output":0.87},"canonical_model_id":"alibaba/qwen3-32b"},"scx-ai/minimax-m2.7":{"id":"scx-ai/minimax-m2.7","name":"MiniMax M2.7 (SCX.ai (Turbo))","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":196608},"cost":{"input":0.48,"output":1.79,"cache_read":0.05},"canonical_model_id":"minimax/MiniMax-M2.7"},"scx-ai/gpt-oss-120b":{"id":"scx-ai/gpt-oss-120b","name":"GPT OSS 120B (SCX.ai (Turbo))","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.17,"output":0.55},"canonical_model_id":"openai/gpt-oss-120b"},"together-ai/qwen3.8-2.4t-a95b":{"id":"together-ai/qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B (Together AI)","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1010000,"output":909000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"together-ai/glm-5.3-flash":{"id":"together-ai/glm-5.3-flash","name":"GLM-5.3 Flash (Together AI)","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943717},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"together-ai/muse-glimmer-30b":{"id":"together-ai/muse-glimmer-30b","name":"Muse Glimmer 30B (Together AI)","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.35,"output":1.5,"cache_read":0.04},"canonical_model_id":"meta/muse-glimmer-30b"},"together-ai/kimi-k3":{"id":"together-ai/kimi-k3","name":"Kimi K3 (Together AI)","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":1000000},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"together-ai/deepseek-v4.1-flash":{"id":"together-ai/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash (Together AI)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"together-ai/glm-4.7":{"id":"together-ai/glm-4.7","name":"GLM-4.7 (Together AI)","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":128000},"cost":{"input":0.45,"output":2},"canonical_model_id":"zhipuai/glm-4.7"},"together-ai/minimax-m3":{"id":"together-ai/minimax-m3","name":"MiniMax M3 (Together AI)","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"together-ai/deepseek-v4-pro":{"id":"together-ai/deepseek-v4-pro","name":"DeepSeek V4 Pro (Together AI)","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":163840},"cost":{"input":1.32,"output":3.96,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-v4-pro"},"together-ai/gpt-oss-120b":{"id":"together-ai/gpt-oss-120b","name":"GPT OSS 120B (Together AI)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-120b"},"together-ai/glm-5.3":{"id":"together-ai/glm-5.3","name":"GLM-5.3 (Together AI)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943717},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"together-ai/deepseek-v4-flash":{"id":"together-ai/deepseek-v4-flash","name":"DeepSeek V4 Flash (Together AI)","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":163840},"cost":{"input":0.14,"output":0.28,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v4-flash"},"xiaomi/mimo-v2.6-pro":{"id":"xiaomi/mimo-v2.6-pro","name":"MiMo V2.6 Pro (Xiaomi)","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"xiaomi/mimo-v2.6-flash":{"id":"xiaomi/mimo-v2.6-flash","name":"MiMo V2.6 Flash (Xiaomi)","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"quartz/gemini-3.1-pro-preview":{"id":"quartz/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro (Preview) (Quartz)","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax M2.5 (MiniMax)","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131100},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5"},"minimax/minimax-m2.1-lightning":{"id":"minimax/minimax-m2.1-lightning","name":"MiniMax M2.1 Lightning (MiniMax)","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":196608,"output":131072},"cost":{"input":0.12,"output":0.48}},"minimax/minimax-text-01":{"id":"minimax/minimax-text-01","name":"MiniMax Text 01 (MiniMax)","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-01-15","last_updated":"2025-01-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.2,"output":1.1}},"minimax/minimax-m2.7":{"id":"minimax/minimax-m2.7","name":"MiniMax M2.7 (MiniMax)","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131100},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax M3 (MiniMax)","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.12},"canonical_model_id":"minimax/MiniMax-M3"},"minimax/minimax-m2.7-highspeed":{"id":"minimax/minimax-m2.7-highspeed","name":"MiniMax M2.7 Highspeed (MiniMax)","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131100},"cost":{"input":0.6,"output":2.4,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"minimax/minimax-m2.5-highspeed":{"id":"minimax/minimax-m2.5-highspeed","name":"MiniMax M2.5 Highspeed (MiniMax)","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-13","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131100},"cost":{"input":0.6,"output":2.4,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5-highspeed"},"minimax/minimax-m2.1":{"id":"minimax/minimax-m2.1","name":"MiniMax M2.1 (MiniMax)","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":131072},"cost":{"input":0.27,"output":1.1},"canonical_model_id":"minimax/MiniMax-M2.1"},"minimax/minimax-m2":{"id":"minimax/minimax-m2","name":"MiniMax M2 (MiniMax)","description":"Efficient open MiniMax model built for coding agents and tool-heavy workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":131072},"cost":{"input":0.2,"output":1,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2"},"inference.net/glm-5.3-flash":{"id":"inference.net/glm-5.3-flash","name":"GLM-5.3 Flash (Inference.net)","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":128000},"cost":{"input":0.09,"output":0.28,"cache_read":0.02},"canonical_model_id":"zhipuai/glm-5.3-flash"},"inference.net/llama-3.2-11b-instruct":{"id":"inference.net/llama-3.2-11b-instruct","name":"Llama 3.2 11B Instruct (Inference.net)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000},"cost":{"input":0.07,"output":0.33}},"inference.net/glm-5.3":{"id":"inference.net/glm-5.3","name":"GLM-5.3 (Inference.net)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.9,"output":3,"cache_read":0.15},"canonical_model_id":"zhipuai/glm-5.3"},"azure-anthropic/claude-opus-5-5":{"id":"azure-anthropic/claude-opus-5-5","name":"Claude Opus 5.5 (Azure Anthropic)","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"azure-anthropic/claude-fable-5-1":{"id":"azure-anthropic/claude-fable-5-1","name":"Claude Fable 5.1 (Azure Anthropic)","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"azure-anthropic/claude-opus-5":{"id":"azure-anthropic/claude-opus-5","name":"Claude Opus 5 (Azure Anthropic)","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"azure-anthropic/claude-fable-5":{"id":"azure-anthropic/claude-fable-5","name":"Claude Fable 5 (Azure Anthropic)","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"azure-anthropic/claude-opus-4-8":{"id":"azure-anthropic/claude-opus-4-8","name":"Claude Opus 4.8 (Azure Anthropic)","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"azure-anthropic/claude-sonnet-5":{"id":"azure-anthropic/claude-sonnet-5","name":"Claude Sonnet 5 (Azure Anthropic)","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"azure-anthropic/claude-opus-4-6":{"id":"azure-anthropic/claude-opus-4-6","name":"Claude Opus 4.6 (Azure Anthropic)","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"azure-anthropic/claude-sonnet-5-5":{"id":"azure-anthropic/claude-sonnet-5-5","name":"Claude Sonnet 5.5 (Azure Anthropic)","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"azure-anthropic/claude-opus-4-7":{"id":"azure-anthropic/claude-opus-4-7","name":"Claude Opus 4.7 (Azure Anthropic)","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"mistral/mistral-large-latest":{"id":"mistral/mistral-large-latest","name":"Mistral Large Latest (Mistral AI)","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-11","release_date":"2024-11-01","last_updated":"2025-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":262144},"cost":{"input":4,"output":12},"canonical_model_id":"mistral/mistral-large-latest"},"mistral/ministral-8b-2512":{"id":"mistral/ministral-8b-2512","name":"Ministral 8B (Mistral AI)","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.15,"output":0.15}},"mistral/mistral-large-4":{"id":"mistral/mistral-large-4","name":"Mistral Large 4 (Mistral AI)","description":"Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":262144},"cost":{"input":1.36,"output":4.18,"cache_read":0.14},"canonical_model_id":"mistral/mistral-large-4"},"mistral/devstral-2512":{"id":"mistral/devstral-2512","name":"Devstral 2 (Mistral AI)","description":"Mistral's coding-agent model for repository work, terminal tasks, and software fixes","family":"devstral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.4,"output":2},"canonical_model_id":"mistral/devstral-2512"},"mistral/mistral-medium-3-5":{"id":"mistral/mistral-medium-3-5","name":"Mistral Medium 3.5 (Mistral AI)","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-01","last_updated":"2026-05-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":1.5,"output":7.5}},"mistral/mistral-small-2603":{"id":"mistral/mistral-small-2603","name":"Mistral Small 4 (Mistral AI)","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"mistral/mistral-small-2603"},"mistral/mistral-large-2512":{"id":"mistral/mistral-large-2512","name":"Mistral Large 3 (Mistral AI)","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"mistral/mistral-large-2512"},"mistral/ministral-14b-2512":{"id":"mistral/ministral-14b-2512","name":"Ministral 14B (Mistral AI)","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.2,"output":0.2}},"mistral/mistral-small-2506":{"id":"mistral/mistral-small-2506","name":"Mistral Small 3.2 (Mistral AI)","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-03","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"mistral/mistral-small-2506"},"mistral/ministral-3b-2512":{"id":"mistral/ministral-3b-2512","name":"Ministral 3B (Mistral AI)","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":131072},"cost":{"input":0.1,"output":0.1}},"mistral/glm-5.3":{"id":"mistral/glm-5.3","name":"GLM-5.3 (Mistral AI)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.3"},"mistral/codestral-2508":{"id":"mistral/codestral-2508","name":"Codestral (Mistral AI)","description":"Mistral coding model for code completion, generation, and developer workflows","family":"codestral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.3,"output":0.9}},"vertex-anthropic/claude-haiku-4-5":{"id":"vertex-anthropic/claude-haiku-4-5","name":"Claude Haiku 4.5 (Vertex AI (Anthropic))","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"vertex-anthropic/claude-sonnet-4-5":{"id":"vertex-anthropic/claude-sonnet-4-5","name":"Claude Sonnet 4.5 (Vertex AI (Anthropic))","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":63999},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"vertex-anthropic/claude-opus-4-5-20251101":{"id":"vertex-anthropic/claude-opus-4-5-20251101","name":"Claude Opus 4.5 (Vertex AI (Anthropic))","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":31999},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-01","last_updated":"2025-11-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"vertex-anthropic/claude-sonnet-5":{"id":"vertex-anthropic/claude-sonnet-5","name":"Claude Sonnet 5 (Vertex AI (Anthropic))","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"vertex-anthropic/claude-opus-4-6":{"id":"vertex-anthropic/claude-opus-4-6","name":"Claude Opus 4.6 (Vertex AI (Anthropic))","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"vertex-anthropic/claude-sonnet-4-6":{"id":"vertex-anthropic/claude-sonnet-4-6","name":"Claude Sonnet 4.6 (Vertex AI (Anthropic))","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":63999},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"vertex-anthropic/claude-opus-4-7":{"id":"vertex-anthropic/claude-opus-4-7","name":"Claude Opus 4.7 (Vertex AI (Anthropic))","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"vertex-openai/qwen3-235b-a22b-instruct-2507":{"id":"vertex-openai/qwen3-235b-a22b-instruct-2507","name":"Qwen3 235B A22B Instruct 2507 (Vertex AI (OpenAI-compatible))","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.22,"output":0.88},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"vertex-openai/qwen3-next-80b-a3b-thinking":{"id":"vertex-openai/qwen3-next-80b-a3b-thinking","name":"Qwen3 Next 80B A3B Thinking (Vertex AI (OpenAI-compatible))","description":"Efficient Qwen thinking model for local reasoning, math, and coding agents","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":1.2},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-thinking"},"vertex-openai/glm-5":{"id":"vertex-openai/glm-5","name":"GLM-5 (Vertex AI (OpenAI-compatible))","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":32768},"cost":{"input":1,"output":3.2,"cache_read":0.1},"canonical_model_id":"zhipuai/glm-5"},"vertex-openai/qwen3-coder-480b-a35b-instruct":{"id":"vertex-openai/qwen3-coder-480b-a35b-instruct","name":"Qwen3 Coder 480B A35B Instruct (Vertex AI (OpenAI-compatible))","description":"Open Qwen coding heavyweight for repository reasoning and agentic engineering","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.22,"output":1.8,"cache_read":0.022},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"vertex-openai/kimi-k2-thinking":{"id":"vertex-openai/kimi-k2-thinking","name":"Kimi K2 Thinking (Vertex AI (OpenAI-compatible))","description":"Thinking Kimi model for slower research passes, planning, and hard technical questions","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.6,"output":2.5,"cache_read":0.06},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"vertex-openai/qwen3-next-80b-a3b-instruct":{"id":"vertex-openai/qwen3-next-80b-a3b-instruct","name":"Qwen3 Next 80B A3B Instruct (Vertex AI (OpenAI-compatible))","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":1.2},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"vertex-openai/glm-4.7":{"id":"vertex-openai/glm-4.7","name":"GLM-4.7 (Vertex AI (OpenAI-compatible))","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":128000},"cost":{"input":0.6,"output":2.2},"canonical_model_id":"zhipuai/glm-4.7"},"vertex-openai/grok-4-20-non-reasoning":{"id":"vertex-openai/grok-4-20-non-reasoning","name":"Grok 4.20 Non-Reasoning (Vertex AI (OpenAI-compatible))","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"vertex-openai/grok-4-6":{"id":"vertex-openai/grok-4-6","name":"Grok 4.6 (Vertex AI (OpenAI-compatible))","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"vertex-openai/grok-4-20-reasoning":{"id":"vertex-openai/grok-4-20-reasoning","name":"Grok 4.20 Reasoning (Vertex AI (OpenAI-compatible))","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"vertex-openai/deepseek-v3.2":{"id":"vertex-openai/deepseek-v3.2","name":"DeepSeek V3.2 (Vertex AI (OpenAI-compatible))","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":65536},"cost":{"input":0.56,"output":1.68,"cache_read":0.056},"canonical_model_id":"deepseek/deepseek-v3.2"},"google-vertex/gemini-3.6-flash":{"id":"google-vertex/gemini-3.6-flash","name":"Gemini 3.6 Flash (Google Vertex AI)","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.6-flash"},"google-vertex/gemini-3.5-flash-lite":{"id":"google-vertex/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite (Google Vertex AI)","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google-vertex/gemini-3.1-pro-preview":{"id":"google-vertex/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro (Preview) (Google Vertex AI)","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google-vertex/gemini-3.5-flash":{"id":"google-vertex/gemini-3.5-flash","name":"Gemini 3.5 Flash (Google Vertex AI)","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.5-flash"},"google-vertex/gemini-3.7-flash":{"id":"google-vertex/gemini-3.7-flash","name":"Gemini 3.7 Flash (Google Vertex AI)","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.7-flash"},"google-vertex/gemini-3-flash-preview":{"id":"google-vertex/gemini-3-flash-preview","name":"Gemini 3 Flash (Preview) (Google Vertex AI)","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.5,"output":3,"cache_read":0.05},"canonical_model_id":"google/gemini-3-flash-preview"},"google-vertex/gemini-3.8-flash":{"id":"google-vertex/gemini-3.8-flash","name":"Gemini 3.8 Flash (Google Vertex AI)","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.08333}},"google-vertex/gemini-4-argon":{"id":"google-vertex/gemini-4-argon","name":"Gemini 4 Argon (Google Vertex AI)","description":"Gemini multimodal model for text, image, audio, video, and document tasks","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-30","last_updated":"2026-09-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":0.375}},"google-vertex/gemini-3.1-flash-lite":{"id":"google-vertex/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite (Google Vertex AI)","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.1-flash-lite"},"aws-mantle/gpt-6-astra":{"id":"aws-mantle/gpt-6-astra","name":"GPT-6 Astra (AWS Mantle)","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"openai/gpt-6-astra"},"aws-mantle/gpt-5.6-luna":{"id":"aws-mantle/gpt-5.6-luna","name":"GPT-5.6 Luna (AWS Mantle)","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":921600,"output":128000},"cost":{"input":0.22,"output":1.32,"cache_read":0.022,"cache_write":0.275},"canonical_model_id":"openai/gpt-5.6-luna"},"aws-mantle/gpt-5.6-terra":{"id":"aws-mantle/gpt-5.6-terra","name":"GPT-5.6 Terra (AWS Mantle)","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":921600,"output":128000},"cost":{"input":2.2,"output":13.2,"cache_read":0.22,"cache_write":2.75},"canonical_model_id":"openai/gpt-5.6-terra"},"aws-mantle/gpt-5.6-sol":{"id":"aws-mantle/gpt-5.6-sol","name":"GPT-5.6 Sol (AWS Mantle)","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":921600,"output":128000},"cost":{"input":4.4,"output":22,"cache_read":0.44,"cache_write":5.5},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4 (OpenAI)","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT-5.4 Pro (OpenAI)","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180},"canonical_model_id":"openai/gpt-5.4-pro"},"openai/gpt-3.5-turbo":{"id":"openai/gpt-3.5-turbo","name":"GPT-3.5 Turbo (OpenAI)","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"output":4096},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"openai/gpt-3.5-turbo"},"openai/gpt-4o-transcribe":{"id":"openai/gpt-4o-transcribe","name":"GPT-4o Transcribe (OpenAI)","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-03-20","last_updated":"2025-03-20","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":false,"limit":{"context":16000,"output":2000},"cost":{"input":2.5,"output":10}},"openai/gpt-5.5-pro":{"id":"openai/gpt-5.5-pro","name":"GPT-5.5 Pro (OpenAI)","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.5-pro"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 Nano (OpenAI)","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o (OpenAI)","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini (OpenAI)","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"openai/gpt-5.2-pro":{"id":"openai/gpt-5.2-pro","name":"GPT-5.2 Pro (OpenAI)","description":"Higher-accuracy GPT-5.2 variant for tougher reasoning and review workflows","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":272000},"cost":{"input":21,"output":168},"canonical_model_id":"openai/gpt-5.2-pro"},"openai/o4-mini":{"id":"openai/o4-mini","name":"o4 Mini (OpenAI)","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.275},"canonical_model_id":"openai/o4-mini"},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3 Mini (OpenAI)","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"openai/gpt-4":{"id":"openai/gpt-4","name":"GPT-4 (OpenAI)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-11","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8192},"cost":{"input":30,"output":60},"canonical_model_id":"openai/gpt-4"},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT-5.3 Codex (OpenAI)","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1 Nano (OpenAI)","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano (OpenAI)","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"openai/o1":{"id":"openai/o1","name":"o1 (OpenAI)","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":15,"output":60,"cache_read":7.5},"canonical_model_id":"openai/o1"},"openai/gpt-5-pro":{"id":"openai/gpt-5-pro","name":"GPT-5 Pro (OpenAI)","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":272000},"cost":{"input":15,"output":120},"canonical_model_id":"openai/gpt-5-pro"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol (OpenAI)","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra (OpenAI)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-03","last_updated":"2026-09-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5}},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1 (OpenAI)","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o Mini (OpenAI)","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 Mini (OpenAI)","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna (OpenAI)","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2 (OpenAI)","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5 (OpenAI)","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1 (OpenAI)","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 Mini (OpenAI)","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna (OpenAI)","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-4o-mini-transcribe":{"id":"openai/gpt-4o-mini-transcribe","name":"GPT-4o Mini Transcribe (OpenAI)","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-03-20","last_updated":"2025-03-20","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":false,"limit":{"context":16000,"output":2000},"cost":{"input":1.25,"output":5}},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra (OpenAI)","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-4-turbo":{"id":"openai/gpt-4-turbo","name":"GPT-4 Turbo (OpenAI)","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":10,"output":30},"canonical_model_id":"openai/gpt-4-turbo"},"openai/o3":{"id":"openai/o3","name":"o3 (OpenAI)","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5 (OpenAI)","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol (OpenAI)","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol (OpenAI)","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-6-sol"},"moonshot/kimi-k3":{"id":"moonshot/kimi-k3","name":"Kimi K3 (Moonshot AI)","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshot/kimi-k2.7-code-highspeed":{"id":"moonshot/kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code Highspeed (Moonshot AI)","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"moonshot/kimi-k2.6":{"id":"moonshot/kimi-k2.6","name":"Kimi K2.6 (Moonshot AI)","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshot/kimi-k2.5":{"id":"moonshot/kimi-k2.5","name":"Kimi K2.5 (Moonshot AI)","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.6,"output":3,"cache_read":0.1},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshot/kimi-k2.7-code":{"id":"moonshot/kimi-k2.7-code","name":"Kimi K2.7 Code (Moonshot AI)","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"}}},"above":{"id":"above","env":["ABOVE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.above.dev/v1","name":"above.dev","doc":"https://above.dev/docs","models":{"mimo-v2.6-pro":{"id":"mimo-v2.6-pro","name":"MiMo V2.6 Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.5077,"output":1.0154,"cache_read":0.0042},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.165,"output":0.55,"cache_read":0.0319},"canonical_model_id":"zhipuai/glm-5.3-flash"},"glm-5.2-fast":{"id":"glm-5.2-fast","name":"GLM 5.2 Fast","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":2.31,"output":7.26,"cache_read":0.231},"canonical_model_id":"zhipuai/glm-5.2"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen 3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":2.2,"output":6.6,"cache_read":0.275},"canonical_model_id":"alibaba/qwen3.8-max"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.165,"output":0.66,"reasoning":0.66,"cache_read":0.0033},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"mimo-v2.6-pro-ultraspeed":{"id":"mimo-v2.6-pro-ultraspeed","name":"MiMo V2.6 Pro UltraSpeed","description":"MiMo pro model for strong multimodal reasoning and agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":5.0769,"output":10.1538,"cache_read":0.0423},"canonical_model_id":"xiaomi/mimo-v2.6-pro-ultraspeed"},"mimo-v2.6-flash":{"id":"mimo-v2.6-flash","name":"MiMo V2.6 Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.1692,"output":0.3385,"cache_read":0.0034},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"glm-5.2":{"id":"glm-5.2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.54,"output":4.84,"cache_read":0.154},"canonical_model_id":"zhipuai/glm-5.2"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.726,"output":2.178,"reasoning":2.178,"cache_read":0.0242},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"status":"deprecated","cost":{"input":0.165,"output":0.66,"reasoning":0.66,"cache_read":0.0033},"canonical_model_id":"deepseek/deepseek-v4.1-flash"}}},"kilo":{"id":"kilo","env":["KILO_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.kilo.ai/api/gateway","name":"Kilo Gateway","doc":"https://kilo.ai","models":{"sao10k/l3-lunaris-8b":{"id":"sao10k/l3-lunaris-8b","name":"Sao10K: Llama 3 8B Lunaris","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2024-08-13","last_updated":"2024-08-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":7372},"cost":{"input":0.04,"output":0.05}},"sao10k/l3.3-euryale-70b":{"id":"sao10k/l3.3-euryale-70b","name":"Sao10K: Llama 3.3 Euryale 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2024-12-18","last_updated":"2024-12-18","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"cost":{"input":0.65,"output":0.75}},"sao10k/l3.1-euryale-70b":{"id":"sao10k/l3.1-euryale-70b","name":"Sao10K: Llama 3.1 Euryale 70B v2.2","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2024-08-28","last_updated":"2024-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"cost":{"input":0.85,"output":0.85}},"stealth/claude-opus-4.6":{"id":"stealth/claude-opus-4.6","name":"Stealth: Claude Opus 4.6 (20% off)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"reasoning":0,"cache_read":0.4,"cache_write":5}},"stealth/claude-opus-4.7":{"id":"stealth/claude-opus-4.7","name":"Stealth: Claude Opus 4.7 (20% off)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"reasoning":0,"cache_read":0.4,"cache_write":5}},"stealth/claude-opus-4.8":{"id":"stealth/claude-opus-4.8","name":"Stealth: Claude Opus 4.8 (20% off)","description":"Your prompts and completions may be retained and used to train or improve the provider's services. This third-party-served variant of Claude Opus 4.8 is offered at 20% lower cost than standard Claude Opus 4.8 pricing and is not served by Anthropic or Kilo Code.","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"reasoning":0,"cache_read":0.4,"cache_write":5}},"stealth/glyph-cluster":{"id":"stealth/glyph-cluster","name":"Stealth: Glyph Cluster (free)","description":"Your prompts and completions may be retained and used to train or improve the provider's services. Glyph Cluster is a reasoning model for coding and long-context analysis, served through Vercel AI Gateway during its stealth period at no cost. It supports function calling and streaming, takes text input only, and does not support structured outputs. Zero Data Retention is not available for this model.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0,"output":0,"reasoning":0,"cache_read":0}},"stealth/cat-jam":{"id":"stealth/cat-jam","name":"Stealth: Cat Jam (free)","description":"Your prompts and completions may be retained and used to train or improve the provider's services. Cat Jam is a reasoning model for coding and agentic workflows, combining strong coding capabilities with fast, low-latency inference, served through Vercel AI Gateway during its stealth period at no cost. It supports function calling, structured outputs, and streaming, and takes text input only. Zero Data Retention is not available for this model.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"reasoning":0,"cache_read":0}},"stealth/claude-sonnet-4.6":{"id":"stealth/claude-sonnet-4.6","name":"Stealth: Claude Sonnet 4.6 (20% off)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":2.4,"output":12,"reasoning":0,"cache_read":0.24,"cache_write":3}},"stealth/qwen3.6-plus":{"id":"stealth/qwen3.6-plus","name":"Stealth: Qwen3.6 Plus (50% off)","description":"Your prompts and completions may be retained and used to train or improve the provider's services. This third-party-served variant of Qwen3.6 Plus is offered at 50% lower cost than standard Qwen3.6 Plus pricing and is not served by Alibaba or Kilo Code. Note: a surcharge applies to long-context workloads exceeding 256K input tokens.","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.25,"output":1.5,"reasoning":0,"cache_read":0.025,"cache_write":0.3125}},"bytedance-seed/seed-1.6-flash":{"id":"bytedance-seed/seed-1.6-flash","name":"ByteDance Seed: Seed 1.6 Flash (retires Nov 11)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.075,"output":0.3}},"bytedance-seed/seed-2.0-lite":{"id":"bytedance-seed/seed-2.0-lite","name":"Seed 2.0 Lite","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.25,"output":2},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"bytedance-seed/seed-2-1-turbo":{"id":"bytedance-seed/seed-2-1-turbo","name":"ByteDance Seed: Seed 2.1 Turbo","description":"Seed 2.1 Turbo is a multimodal model from ByteDance Seed for coding and long-horizon agent workflows. It is suited for end-to-end software delivery, multi-step task execution, and understanding visual and...","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":235929},"cost":{"input":0.5,"output":2.5}},"bytedance-seed/seed-2.0-mini":{"id":"bytedance-seed/seed-2.0-mini","name":"Seed 2.0 Mini","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.1,"output":0.4},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"bytedance-seed/seed-2.0-code":{"id":"bytedance-seed/seed-2.0-code","name":"Seed 2.0 Code","description":"Seed 2.0 Code is a model from ByteDance Seed optimized for agentic coding. It is suited for frontend development, multilingual programming tasks, and coding-agent workflows in tools such as Claude...","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.5,"output":3},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"bytedance-seed/seed-1.6":{"id":"bytedance-seed/seed-1.6","name":"ByteDance Seed: Seed 1.6 (retires Nov 11)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.25,"output":2}},"~moonshotai/kimi-latest":{"id":"~moonshotai/kimi-latest","name":"MoonshotAI: Kimi Latest","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.294,"output":28,"cache_read":0.284}},"poolside/laguna-s-2.1:free":{"id":"poolside/laguna-s-2.1:free","name":"Poolside: Laguna S 2.1 (free)","description":"Laguna S 2.1 is the latest coding agent model from [Poolside]( ). Laguna S 2.1 is a 118B total parameter model with 8B active parameters, scoring 70.2% on Terminal-Bench 2.1 and...","family":"laguna-s","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0}},"poolside/laguna-s-2.1":{"id":"poolside/laguna-s-2.1","name":"Poolside: Laguna S 2.1 (retires Oct 31)","description":"Laguna S 2.1 is the latest coding agent model from [Poolside]( ). Laguna S 2.1 is a 118B total parameter model with 8B active parameters, scoring 70.2% on Terminal-Bench 2.1 and...","family":"laguna-s","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.1,"output":0.2,"cache_read":0.01}},"poolside/laguna-xs-2.1:free":{"id":"poolside/laguna-xs-2.1:free","name":"Poolside: Laguna XS 2.1 (free)","description":"Laguna XS 2.1 is the latest coding agent model in the 33B-A3B category from [Poolside](https://poolside.ai/) and a step forward from their Laguna XS.2 model (released in April 2026). It combines...","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-02","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0}},"poolside/laguna-xs-2.1":{"id":"poolside/laguna-xs-2.1","name":"Poolside: Laguna XS 2.1 (retires Oct 31)","description":"Laguna XS 2.1 is the latest coding agent model in the 33B-A3B category from [Poolside](https://poolside.ai/) and a step forward from their Laguna XS.2 model (released in April 2026). It combines...","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-02","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.1,"output":0.2,"cache_read":0.05}},"prism-ml/ternary-bonsai-2-27b":{"id":"prism-ml/ternary-bonsai-2-27b","name":"PrismML: Ternary Bonsai 2 27B","description":"Bonsai 2 27B is a 27B-parameter reasoning model from PrismML derived from Qwen3.8-27B. It supports coding, mathematics, tool calling, and image understanding with a 262K-token context window. Ternary compression shrinks...","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-18","last_updated":"2026-09-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.075,"output":0.5,"cache_read":0.0375}},"anthropic/claude-opus-4.1":{"id":"anthropic/claude-opus-4.1","name":"Claude Opus 4.1 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1"},"anthropic/claude-opus-4.5":{"id":"anthropic/claude-opus-4.5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-opus-4.6":{"id":"anthropic/claude-opus-4.6","name":"Claude Opus 4.6","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude Opus 4.7","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic/claude-haiku-5.5":{"id":"anthropic/claude-haiku-5.5","name":"Claude Haiku 5.5","description":"Claude Haiku 5.5 is Anthropic's small, fast model for high-volume, cost-sensitive work such as summarization, subagents, and browser use. It succeeds Claude Haiku 4.5 with stronger coding, computer use, and...","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude Opus 4.8","description":"Claude Opus 4.8 is Anthropic's most capable generally available model in the Opus family. It supports text, image, and file inputs with text output, with reasoning support and a 1M-token...","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-haiku-4.5":{"id":"anthropic/claude-haiku-4.5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Claude Opus 5 is Anthropic’s flagship model for demanding reasoning, coding, and long-horizon agentic work. It is particularly strong at end-to-end software tasks, code review and bug finding, visual analysis...","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-sonnet-5.5":{"id":"anthropic/claude-sonnet-5.5","name":"Claude Sonnet 5.5","description":"Claude Sonnet 5.5 is Anthropic's Sonnet-class model for well-scoped everyday work, succeeding Claude Sonnet 5 as a direct upgrade. It is especially strong at building features, fixing bugs, and producing...","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-fable-5.1":{"id":"anthropic/claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude Fable 5.1 improves on Claude Fable 5 across the board, with the biggest gains in agentic coding, long-running agentic workflows, and knowledge work: long code refactors, front-end and visual...","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-sonnet-4.5":{"id":"anthropic/claude-sonnet-4.5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude Fable 5 is a Mythos-class model from Anthropic, built for autonomous knowledge work and coding. It supports text, image, and file inputs with text output, with reasoning support and...","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Sonnet 5 is Anthropic's most capable Sonnet-class model, with frontier performance across coding, agents, and professional work. It supports adaptive thinking with selectable reasoning effort levels (low, medium, high, max,...","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude Sonnet 4.6","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-5.5":{"id":"anthropic/claude-opus-5.5","name":"Claude Opus 5.5","description":"Claude Opus 5.5 is Anthropic's flagship model for demanding reasoning, coding, and long-horizon agentic work, succeeding Claude Opus 5. It is particularly strong at multi-step changes in large codebases, code...","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"nex-agi/nex-n2.5-mini":{"id":"nex-agi/nex-n2.5-mini","name":"Nex AGI: Nex-N2.5-Mini","description":"Nex-N2.5 is an agentic model built to turn goals into working, verified outcomes. Its core strength is agentic coding within a visual feedback loop: it can explore codebases, implement multi-file...","family":"agi","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":235929},"cost":{"input":0.025,"output":0.1,"cache_read":0.0025}},"nex-agi/nex-n2.5-pro":{"id":"nex-agi/nex-n2.5-pro","name":"Nex AGI: Nex-N2.5-Pro","description":"Nex-N2.5 is an agentic model built to turn goals into working, verified outcomes. Its core strength is agentic coding within a visual feedback loop: it can explore codebases, implement multi-file...","family":"agi","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":235929},"cost":{"input":0.075,"output":0.25,"cache_read":0.015}},"cohere/command-r-08-2024":{"id":"cohere/command-r-08-2024","name":"Command R","description":"Cohere retrieval model for long-context chat and enterprise RAG workflows","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"cohere/command-r-08-2024"},"cohere/command-a-plus":{"id":"cohere/command-a-plus","name":"Cohere: Command A+","description":"Command A+ is Cohere's flagship model for enterprise agentic workflows. It accepts text and image inputs with a 192K context window, supports native tool calling with strict tool schemas, structured...","family":"command-a","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":192000,"output":64000},"cost":{"input":0.3,"output":1.5,"cache_read":0.15}},"cohere/command-a":{"id":"cohere/command-a","name":"Command A","description":"Cohere command model for multilingual enterprise agents, tools, and chat","family":"command-a","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-03-13","last_updated":"2025-03-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-a"},"cohere/north-mini-code:free":{"id":"cohere/north-mini-code:free","name":"Cohere: North Mini Code (free)","description":"North Mini Code is Cohere's first agentic coding model and the debut of its North family. A sparse mixture-of-experts model with 30B total parameters and 3B active, it is optimized...","family":"north","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-17","last_updated":"2026-06-17","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":0,"output":0}},"cohere/command-r7b-12-2024":{"id":"cohere/command-r7b-12-2024","name":"Command R7B","description":"Cohere command model for multilingual enterprise agents, tools, and chat","family":"command-r","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-12-02","last_updated":"2024-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.0375,"output":0.15},"canonical_model_id":"cohere/command-r7b-12-2024"},"cohere/command-r-plus-08-2024":{"id":"cohere/command-r-plus-08-2024","name":"Command R+","description":"Cohere retrieval model for long-context chat and enterprise RAG workflows","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-r-plus-08-2024"},"deepseek/deepseek-chat-v3.1":{"id":"deepseek/deepseek-chat-v3.1","name":"DeepSeek V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":32768},"cost":{"input":0.25,"output":0.95,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-chat-v3.1"},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"DeepSeek V4 Flash 0731 is a sparse mixture-of-experts model from DeepSeek, with 13B active parameters out of 284B total. This re-post-trained revision is suited for coding, reasoning, and agent workflows.","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":0.44,"output":1.32,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash is a sparse mixture-of-experts model from DeepSeek, and the cost-efficient tier of the V4.1 family. DeepSeek reports that it exceeds V4 Pro on performance, speed, and task...","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-flash-vision-exp":{"id":"deepseek/deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"DeepSeek V4 Flash Vision Exp is an experimental vision-enabled version of [DeepSeek V4 Flash 0731](https://openrouter.ai/deepseek/deepseek-v4-flash-0731) from DeepSeek, adding image understanding while matching the base model on text capabilities including agents,...","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":0.2156,"output":0.6468,"cache_read":0.00686},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"deepseek/deepseek-v3.1-terminus":{"id":"deepseek/deepseek-v3.1-terminus","name":"DeepSeek: DeepSeek V3.1 Terminus","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-22","last_updated":"2025-09-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":163840,"output":147456},"cost":{"input":0.27,"output":1}},"deepseek/deepseek-chat":{"id":"deepseek/deepseek-chat","name":"DeepSeek Chat","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-12-01","last_updated":"2026-02-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":16384},"cost":{"input":0.32,"output":0.89},"canonical_model_id":"deepseek/deepseek-chat"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro 0813 is a large-scale mixture-of-experts model from DeepSeek. This is the GA release of DeepSeek V4 Pro.","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek/deepseek-v3.2-exp":{"id":"deepseek/deepseek-v3.2-exp","name":"DeepSeek: DeepSeek V3.2 Exp","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":163840,"output":147456},"cost":{"input":0.27,"output":0.41}},"deepseek/deepseek-chat-v3-0324":{"id":"deepseek/deepseek-chat-v3-0324","name":"DeepSeek V3 0324","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07-31","release_date":"2025-03-24","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":115200},"cost":{"input":0.29,"output":1.14,"cache_read":0.11},"canonical_model_id":"deepseek/deepseek-chat-v3-0324"},"deepseek/deepseek-r1":{"id":"deepseek/deepseek-r1","name":"DeepSeek-R1","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":16000},"cost":{"input":0.7,"output":2.5},"canonical_model_id":"deepseek/deepseek-r1"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":384000},"cost":{"input":1.6,"output":3.2,"cache_read":0.135},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-r1-0528":{"id":"deepseek/deepseek-r1-0528","name":"DeepSeek R1 0528","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":32768},"cost":{"input":0.7,"output":2.5,"cache_read":0.35},"canonical_model_id":"deepseek/deepseek-r1-0528"},"deepseek/deepseek-v3.2":{"id":"deepseek/deepseek-v3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":147456},"cost":{"input":0.259,"output":0.8,"cache_read":0.14},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048575,"output":943717},"cost":{"input":0.091,"output":0.182,"cache_read":0.0182},"canonical_model_id":"deepseek/deepseek-v4-flash"},"unbiased/pareto-26.9":{"id":"unbiased/pareto-26.9","name":"Pareto 26.9","description":"Pareto is a multimodal composite model built for research, coding, and agentic workflows, while delivering frontier-level performance across a broad range of general-purpose tasks.","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":2.5,"output":7.5,"cache_read":0.25}},"tencent/hy3-preview":{"id":"tencent/hy3-preview","name":"Hy3 preview","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.18,"output":0.6,"cache_read":0.06},"canonical_model_id":"tencent/hy3-preview"},"tencent/hunyuan-a13b-instruct":{"id":"tencent/hunyuan-a13b-instruct","name":"Tencent: Hunyuan A13B Instruct","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"hunyuan","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-07-08","last_updated":"2025-07-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":117964},"cost":{"input":0.14,"output":0.57}},"tencent/hy-mt2-30b-a3b":{"id":"tencent/hy-mt2-30b-a3b","name":"Hy-MT2-30B-A3B","description":"Hy-MT2-30B-A3B is Tencent's flagship translation model in the Hy-MT2 family. It supports 33 language pairs and five Chinese dialect and minority-language pairs, with workflows for structured, delimiter-based, contextual, glossary-based, and...","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-08-20","last_updated":"2026-08-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":4096},"cost":{"input":0.074,"output":0.295},"canonical_model_id":"tencent/hy-mt2-30b-a3b"},"tencent/hy-mt2-1.8b":{"id":"tencent/hy-mt2-1.8b","name":"Hy-MT2-1.8B","description":"Hy-MT2-1.8B is a compact 1.8B-parameter translation model from Tencent. It supports 33 language pairs and five Chinese dialect and minority-language pairs, with workflows for structured, delimiter-based, contextual, glossary-based, and style-guided...","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-08-20","last_updated":"2026-08-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":4096},"cost":{"input":0.044,"output":0.177},"canonical_model_id":"tencent/hy-mt2-1.8b"},"tencent/hy3":{"id":"tencent/hy3","name":"Hy3","description":"Hy3 is a 295B-parameter Mixture-of-Experts model from Tencent (21B active, 192 experts with top-8 routing) built for reasoning, agentic workflows, and real-world production use. It supports a configurable reasoning effort:...","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":192000,"output":128000},"cost":{"input":0.0825,"output":0.33,"cache_read":0.020625},"canonical_model_id":"tencent/hy3"},"tencent/hy-mt2-7b":{"id":"tencent/hy-mt2-7b","name":"Hy-MT2-7B","description":"Hy-MT2-7B is a 7B-parameter translation model from Tencent. It supports 33 language pairs and five Chinese dialect and minority-language pairs, with workflows for structured, delimiter-based, contextual, glossary-based, and style-guided translation.","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-08-19","last_updated":"2026-08-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":4096},"cost":{"input":0.074,"output":0.295},"canonical_model_id":"tencent/hy-mt2-7b"},"tencent/hy4-preview":{"id":"tencent/hy4-preview","name":"Hy4 preview","description":"Tencent: Hy4 preview is a mixture-of-experts model from Tencent, with 49B active parameters out of 770B total. It is designed for coding agents, complex tool-use workflows, and productivity tasks that...","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":64000},"cost":{"input":0.7506,"output":2.2509,"cache_read":0.0378},"canonical_model_id":"tencent/hy4-preview"},"anthracite-org/magnum-v4-72b":{"id":"anthracite-org/magnum-v4-72b","name":"Magnum v4 72B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":4096},"cost":{"input":2.5,"output":5}},"meta-llama/llama-4-scout":{"id":"meta-llama/llama-4-scout","name":"Meta: Llama 4 Scout","description":"Open multimodal Llama model for long-context analysis and efficient agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":327680,"output":16384},"cost":{"input":0.08,"output":0.24}},"meta-llama/llama-guard-4-12b":{"id":"meta-llama/llama-guard-4-12b","name":"Meta: Llama Guard 4 12B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-04-30","last_updated":"2025-04-30","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":163840,"output":16384},"cost":{"input":0.144,"output":0.144}},"meta-llama/llama-4-maverick":{"id":"meta-llama/llama-4-maverick","name":"Meta: Llama 4 Maverick","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.1875,"output":0.6525,"cache_read":0.05}},"meta-llama/llama-3.3-70b-instruct":{"id":"meta-llama/llama-3.3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.1,"output":0.32},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"meta-llama/llama-3.1-8b-instruct":{"id":"meta-llama/llama-3.1-8b-instruct","name":"Llama-3.1-8B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.02,"output":0.04},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"meta-llama/llama-3.2-1b-instruct":{"id":"meta-llama/llama-3.2-1b-instruct","name":"Llama 3.2 1B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":60000,"output":54000},"cost":{"input":0.027,"output":0.201},"canonical_model_id":"meta/llama-3.2-1b-instruct"},"meta-llama/llama-3.2-3b-instruct":{"id":"meta-llama/llama-3.2-3b-instruct","name":"Meta: Llama 3.2 3B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":117964},"cost":{"input":0.05,"output":0.33}},"meta-llama/llama-3.1-70b-instruct":{"id":"meta-llama/llama-3.1-70b-instruct","name":"Llama-3.1-70B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.4,"output":0.4},"canonical_model_id":"meta/llama-3.1-70b-instruct"},"~google/gemini-flash-latest":{"id":"~google/gemini-flash-latest","name":"Google: Gemini Flash Latest","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"reasoning":3.75,"cache_read":0.075,"cache_write":0.041667}},"~google/gemini-pro-latest":{"id":"~google/gemini-pro-latest","name":"Google: Gemini Pro Latest","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["audio","pdf","image","text","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":10,"reasoning":10,"cache_read":0.1,"cache_write":0.1875}},"~unbiased/pareto-latest":{"id":"~unbiased/pareto-latest","name":"Pareto Latest","description":"This model always redirects to the latest model in the Pareto family.","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":2.5,"output":7.5,"cache_read":0.25}},"perceptron/perceptron-mk1":{"id":"perceptron/perceptron-mk1","name":"Perceptron: Perceptron Mk1","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-05-12","last_updated":"2026-05-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":8192},"cost":{"input":0.15,"output":1.5}},"perceptron/perceptron-mk1.5":{"id":"perceptron/perceptron-mk1.5","name":"Perceptron: Perceptron Mk1.5","description":"Perceptron Mk1.5 is Perceptron's embodied reasoning model for physical agents. It accepts text, image, video, and audio input, and answers with text plus optional structured annotations: points, boxes, polygons, tracks,...","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-25","last_updated":"2026-09-25","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":36864,"output":8192},"cost":{"input":0.15,"output":1.5}},"z-ai/glm-4.6v":{"id":"z-ai/glm-4.6v","name":"GLM-4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.3,"output":0.9,"cache_read":0.055},"canonical_model_id":"zhipuai/glm-4.6v"},"z-ai/glm-4.5":{"id":"z-ai/glm-4.5","name":"GLM-4.5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5"},"z-ai/glm-5.3-prime":{"id":"z-ai/glm-5.3-prime","name":"Z.ai: GLM 5.3 Prime","description":"GLM-5.3-Prime is the high-speed variant of Z.ai's GLM-5.3, inheriting its full capabilities while delivering 1.5–2× the output throughput through inference acceleration. It supports text input and output with a 1M-token...","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2.8,"output":8.8,"cache_read":0.56}},"z-ai/glm-5v-turbo":{"id":"z-ai/glm-5v-turbo","name":"GLM-5V-Turbo","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5v-turbo"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"GLM-5.3-Flash is a native multimodal model from Z.ai. It is suited for efficient coding and long-horizon agent tasks. Its hybrid sparse and linear attention architecture maintains accurate long-context behavior while...","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-4.6":{"id":"z-ai/glm-4.6","name":"GLM-4.6","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.5,"output":2,"cache_read":0.1},"canonical_model_id":"zhipuai/glm-4.6"},"z-ai/glm-5":{"id":"z-ai/glm-5","name":"GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"z-ai/glm-4.5v":{"id":"z-ai/glm-4.5v","name":"GLM-4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":16384},"cost":{"input":0.6,"output":1.8,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5v"},"z-ai/glm-5.3-flashx":{"id":"z-ai/glm-5.3-flashx","name":"Z.ai: GLM 5.3 FlashX","description":"GLM-5.3-FlashX is the high-speed variant of Z.ai's GLM-5.3-Flash, a native multimodal model delivering inference speeds of up to 200 tokens/s. Built on the same hybrid sparse and linear attention architecture...","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-18","last_updated":"2026-09-18","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.37,"output":1.25,"cache_read":0.09}},"z-ai/glm-4.7-flash":{"id":"z-ai/glm-4.7-flash","name":"GLM-4.7-Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.0605,"output":0.4},"canonical_model_id":"zhipuai/glm-4.7-flash"},"z-ai/glm-4.7":{"id":"z-ai/glm-4.7","name":"GLM-4.7","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.7"},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM-5.2","description":"GLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level software engineering,...","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/glm-5.1":{"id":"z-ai/glm-5.1","name":"GLM-5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"z-ai/glm-5-turbo":{"id":"z-ai/glm-5-turbo","name":"GLM-5-Turbo","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5-turbo"},"z-ai/glm-4.5-air":{"id":"z-ai/glm-4.5-air","name":"GLM-4.5-Air","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.13,"output":0.85,"cache_read":0.025},"canonical_model_id":"zhipuai/glm-4.5-air"},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM-5.3","description":"GLM-5.3 is a large-scale reasoning model from Z.ai, built for complex software engineering and long-horizon agent tasks. It supports text input and output with a 1M-token context window, and improves...","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"reflection/beam-1.0-501b-a23b":{"id":"reflection/beam-1.0-501b-a23b","name":"Reflection: Beam 1.0 501B A23B","description":"Beam 1.0 is Reflection's open-weight reasoning model for coding and long-horizon agentic workflows. It uses a sparse mixture-of-experts architecture with 501B total and 23B active parameters per token, and a...","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-16","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.25,"output":1}},"inference-net/schematron-v2-small":{"id":"inference-net/schematron-v2-small","name":"Inference.net: Schematron V2 Small","description":"Schematron V2 Small is a 3B-parameter HTML-to-JSON extraction model from Inference.net. It prioritizes extraction quality for complex schemas and long pages. Extraction instructions must be supplied through a JSON schema...","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-09-12","last_updated":"2026-09-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":0.05,"output":0.23,"cache_read":0.05}},"inference-net/schematron-v2-turbo":{"id":"inference-net/schematron-v2-turbo","name":"Inference.net: Schematron V2 Turbo","description":"Schematron V2 Turbo is a 3B-parameter HTML-to-JSON extraction model from Inference.net. It prioritizes throughput for high-volume extraction workloads. Extraction instructions must be supplied through a JSON schema in response_format rather...","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-09-12","last_updated":"2026-09-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.03,"output":0.15,"cache_read":0.03}},"thinkingmachines/inkling-small:free":{"id":"thinkingmachines/inkling-small:free","name":"Thinking Machines: Inkling Small (free)","description":"Inkling Small is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 12B active parameters out of 276B total. It is positioned as the smaller, more efficient member of...","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/inkling-small":{"id":"thinkingmachines/inkling-small","name":"Inkling Small","description":"Inkling Small is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 12B active parameters out of 276B total. It is positioned as the smaller, more efficient member of...","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":262144},"cost":{"input":0.45,"output":1.2,"cache_read":0.1},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/inkling":{"id":"thinkingmachines/inkling","name":"Inkling","description":"Inkling is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 41B active parameters out of 975B total. It is designed for general-purpose reasoning, coding, agentic and tool-use systems,...","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":471859},"cost":{"input":0.95,"output":4.05,"cache_read":0.16},"canonical_model_id":"thinkingmachines/inkling"},"meituan/longcat-2.0":{"id":"meituan/longcat-2.0","name":"Meituan: LongCat 2.0","description":"LongCat 2.0 is a sparse mixture-of-experts language model from Meituan, with 48B active parameters out of 1.6T total. It is suited for coding, repository-level changes, long-horizon problem solving, and agentic...","family":"longcat","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-20","last_updated":"2026-07-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048756,"output":262144},"cost":{"input":0.75,"output":3,"cache_read":0.015}},"openrouter/bodybuilder":{"id":"openrouter/bodybuilder","name":"Body Builder (beta)","description":"Preview model for early access evaluation, prototyping, and compatibility testing","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-03-15","last_updated":"2026-03-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32768},"status":"beta","cost":{"input":0,"output":0}},"openrouter/free":{"id":"openrouter/free","name":"OpenRouter Free Models Router","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-01","last_updated":"2026-02-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32768},"cost":{"input":0,"output":0}},"openrouter/pareto-code":{"id":"openrouter/pareto-code","name":"Pareto Code Router","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-05-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":65536},"cost":{"input":0,"output":0}},"openrouter/auto":{"id":"openrouter/auto","name":"Auto Router","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-15","last_updated":"2026-03-15","modalities":{"input":["audio","image","pdf","text","video"],"output":["image","text"]},"open_weights":false,"limit":{"context":2000000,"output":32768},"cost":{"input":0,"output":0}},"perplexity/sonar-pro":{"id":"perplexity/sonar-pro","name":"Perplexity: Sonar Pro","description":"Advanced Sonar search model for deeper research and cited synthesis","family":"sonar-pro","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-03-07","last_updated":"2025-03-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8000},"cost":{"input":3,"output":15}},"perplexity/sonar-deep-research":{"id":"perplexity/sonar-deep-research","name":"Perplexity: Sonar Deep Research","description":"Sonar search model for current answers, retrieval, and citation-backed chat","family":"sonar-deep-research","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-03-07","last_updated":"2025-03-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":115200},"cost":{"input":2,"output":8,"reasoning":3}},"perplexity/sonar":{"id":"perplexity/sonar","name":"Perplexity: Sonar","description":"Sonar search model for current answers, retrieval, and citation-backed chat","family":"sonar","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-01-27","last_updated":"2025-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":127072,"output":114364},"cost":{"input":1,"output":1}},"perplexity/sonar-reasoning-pro":{"id":"perplexity/sonar-reasoning-pro","name":"Perplexity: Sonar Reasoning Pro","description":"Web-grounded reasoning model for multi-step research and cited answers","family":"sonar-reasoning","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-03-07","last_updated":"2025-03-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":115200},"cost":{"input":2,"output":8}},"perplexity/sonar-pro-search":{"id":"perplexity/sonar-pro-search","name":"Perplexity: Sonar Pro Search","description":"Advanced Sonar search model for deeper research and cited synthesis","family":"sonar-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-10-30","last_updated":"2025-10-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8000},"cost":{"input":3,"output":15}},"meta/muse-spark-1.3":{"id":"meta/muse-spark-1.3","name":"Muse Spark 1.3","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It is designed to keep track of information across extended tasks, work through...","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.3"},"meta/muse-glimmer-30b":{"id":"meta/muse-glimmer-30b","name":"Muse Glimmer 30B","description":"Muse Glimmer 30B is a dense, open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark and optimized for autonomous agents on consumer hardware. It is suited for long-horizon...","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.3,"output":1.2,"cache_read":0.04},"canonical_model_id":"meta/muse-glimmer-30b"},"meta/muse-wonder":{"id":"meta/muse-wonder","name":"Meta: Muse Wonder","description":"Muse Wonder is a frontier reasoning model from Meta, designed for complex personal and professional agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with...","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":4,"output":20,"cache_read":0.2}},"meta/muse-spark-1.1":{"id":"meta/muse-spark-1.1","name":"Muse Spark 1.1","description":"Muse Spark 1.1 is a multimodal reasoning model from Meta, built for agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with a 1M-token context...","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.1"},"meta/muse-spark-1.2":{"id":"meta/muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a reasoning model from Meta, designed for complex agentic tasks. It accepts text, images, video, audio, and PDF documents, returns text, and offers a 1M-token context...","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"meta/muse-spark-1.2-contributor":{"id":"meta/muse-spark-1.2-contributor","name":"Meta: Muse Spark 1.2 Contributor","description":"Muse Spark 1.2 contributor tier is a reasoning model from Meta designed for developers who want to start building at an even lower cost. It’s meaningfully cheaper than Muse Spark...","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-08-21","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"meta/muse-spark-1.3-contributor":{"id":"meta/muse-spark-1.3-contributor","name":"Meta: Muse Spark 1.3 Contributor","description":"Muse Spark 1.3 Contributor is the cost-efficient contributor tier of Meta’s multimodal reasoning model for experimentation, learning, and early-stage agentic, multi-agent, and coding workflows. It is designed to track information...","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"meta/muse-spark-open":{"id":"meta/muse-spark-open","name":"Muse Spark Open","description":"Muse Spark Open is a coding-optimized open-weight model. Trained specifically for agentic coding workflows, it delivers higher first-attempt accuracy, reliable tool calling, and deep codebase understanding across the repos developers...","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-open"},"nousresearch/hermes-3-llama-3.1-70b":{"id":"nousresearch/hermes-3-llama-3.1-70b","name":"Nous: Hermes 3 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"nousresearch","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2024-08-18","last_updated":"2024-08-18","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"cost":{"input":0.7,"output":0.7}},"nousresearch/hermes-3-llama-3.1-405b":{"id":"nousresearch/hermes-3-llama-3.1-405b","name":"Nous: Hermes 3 405B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"nousresearch","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2024-08-16","last_updated":"2024-08-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"cost":{"input":1,"output":1}},"nousresearch/hermes-4-405b":{"id":"nousresearch/hermes-4-405b","name":"Nous: Hermes 4 405B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"nousresearch","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":117964},"cost":{"input":1,"output":3}},"scaledown/summarize":{"id":"scaledown/summarize","name":"ScaleDown: Summarize","description":"Summarize is an abstractive summarization model from ScaleDown. It condenses long text and documents into a fluent, faithful rewrite rather than lifting sentences from the source, and is suited for...","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":4000},"cost":{"input":0.05,"output":0}},"scaledown/extract":{"id":"scaledown/extract","name":"ScaleDown: Extract","description":"Extract is a description-driven entity extraction model from ScaleDown. Instead of a fixed set of entity types, callers describe the fields they want in plain English through `provider.options.scaledown.entities`, and the...","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":900000},"cost":{"input":0.05,"output":0}},"~z-ai/glm-flash-latest":{"id":"~z-ai/glm-flash-latest","name":"Z.ai: GLM Flash Latest","description":"This model always redirects to the latest model in the GLM Flash family.","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.02466,"output":0.9,"cache_read":0.01125}},"~z-ai/glm-latest":{"id":"~z-ai/glm-latest","name":"Z.ai: GLM Latest","description":"This model always redirects to the latest GLM model from Z.ai.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-19","last_updated":"2026-08-19","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.0608,"output":4.4,"cache_read":0.0565}},"arcee-ai/trinity-large-thinking":{"id":"arcee-ai/trinity-large-thinking","name":"Trinity Large Thinking","description":"Reasoning-optimized 398B MoE agent model with extended thinking for long-horizon and multi-turn tool use","family":"trinity","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":80000},"cost":{"input":0.25,"output":0.8,"cache_read":0.06},"canonical_model_id":"arcee-ai/trinity-large-thinking"},"~openai/gpt-terra-latest":{"id":"~openai/gpt-terra-latest","name":"OpenAI: GPT Terra Latest","description":"This model always redirects to the latest model in the OpenAI GPT Terra family.","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5}},"~openai/gpt-luna-latest":{"id":"~openai/gpt-luna-latest","name":"OpenAI: GPT Luna Latest","description":"This model always redirects to the latest model in the OpenAI GPT Luna family.","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125}},"~openai/gpt-sol-latest":{"id":"~openai/gpt-sol-latest","name":"OpenAI: GPT Sol Latest","description":"This model always redirects to the latest model in the OpenAI GPT Sol family.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5}},"~openai/gpt-astra-latest":{"id":"~openai/gpt-astra-latest","name":"OpenAI: GPT Astra Latest ($$$$)","description":"This model always redirects to the latest model in the OpenAI GPT Astra family.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5}},"~openai/gpt-mini-latest":{"id":"~openai/gpt-mini-latest","name":"OpenAI: GPT Mini Latest","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075}},"cognitivecomputations/dolphin-mistral-24b-venice-edition":{"id":"cognitivecomputations/dolphin-mistral-24b-venice-edition","name":"Venice: Uncensored","description":"Venice Uncensored Dolphin Mistral 24B Venice Edition is a fine-tuned variant of Mistral-Small-24B-Instruct-2501, developed by dphn.ai in collaboration with Venice.ai. This model is designed as an “uncensored” instruct-tuned LLM, preserving...","family":"mistral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-07-09","last_updated":"2025-07-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.2,"output":0.9}},"thedrummer/skyfall-36b-v2":{"id":"thedrummer/skyfall-36b-v2","name":"TheDrummer: Skyfall 36B V2","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-03-10","last_updated":"2025-03-10","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":29491},"cost":{"input":0.55,"output":0.8,"cache_read":0.25}},"thedrummer/unslopnemo-12b":{"id":"thedrummer/unslopnemo-12b","name":"TheDrummer: UnslopNemo 12B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2024-11-08","last_updated":"2024-11-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1024000,"output":819200},"cost":{"input":0.4,"output":0.4}},"thedrummer/cydonia-24b-v4.1":{"id":"thedrummer/cydonia-24b-v4.1","name":"TheDrummer: Cydonia 24B V4.1","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-09-27","last_updated":"2025-09-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":117964},"cost":{"input":0.3,"output":0.5,"cache_read":0.15}},"x-ai/grok-4.20-multi-agent":{"id":"x-ai/grok-4.20-multi-agent","name":"SpaceXAI: Grok 4.20 Multi-Agent","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-03-31","last_updated":"2026-03-31","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":1800000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2}},"x-ai/grok-4.7":{"id":"x-ai/grok-4.7","name":"Grok 4.7","description":"Grok 4.7 is SpaceXAI's smartest model with frontier performance on coding, knowledge work, and STEM.","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.7"},"x-ai/grok-4.3":{"id":"x-ai/grok-4.3","name":"Grok 4.3","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":900000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2},"canonical_model_id":"xai/grok-4.3"},"x-ai/grok-4.5":{"id":"x-ai/grok-4.5","name":"Grok 4.5","description":"Grok 4.5 is SpaceXAI's smartest model with frontier performance on coding, knowledge work, and STEM.","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.3},"canonical_model_id":"xai/grok-4.5"},"x-ai/grok-build-0.1":{"id":"x-ai/grok-build-0.1","name":"Grok Build 0.1","description":"Grok coding model for agentic engineering, edits, and codebase workflows","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":230400},"cost":{"input":1,"output":2,"cache_read":0.2},"canonical_model_id":"xai/grok-build-0.1"},"x-ai/grok-4.20":{"id":"x-ai/grok-4.20","name":"SpaceXAI: Grok 4.20","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-31","last_updated":"2026-03-31","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":1800000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2}},"x-ai/grok-4.6":{"id":"x-ai/grok-4.6","name":"Grok 4.6","description":"Grok 4.6 is SpaceXAI's smartest model with frontier performance on coding, knowledge work, and STEM.","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"~anthropic/claude-opus-latest":{"id":"~anthropic/claude-opus-latest","name":"Anthropic: Claude Opus Latest","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5}},"~anthropic/claude-haiku-latest":{"id":"~anthropic/claude-haiku-latest","name":"Anthropic: Claude Haiku Latest","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125}},"~anthropic/claude-sonnet-latest":{"id":"~anthropic/claude-sonnet-latest","name":"Anthropic: Claude Sonnet Latest","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5}},"~anthropic/claude-fable-latest":{"id":"~anthropic/claude-fable-latest","name":"Anthropic: Claude Fable Latest ($$$$)","description":"This model always redirects to the latest model in the Claude Fable family.","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5}},"upstage/solar-pro-3":{"id":"upstage/solar-pro-3","name":"Upstage: Solar Pro 3","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":117964},"cost":{"input":0.15,"output":0.6,"cache_read":0.015}},"upstage/solar-pro4":{"id":"upstage/solar-pro4","name":"Upstage: Solar Pro 4","description":"Solar Pro 4 is a large language model from Upstage. It is suited for agentic workflows, office productivity, document-intensive work, and coding.","family":"solar","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06}},"upstage/solar-mini4":{"id":"upstage/solar-mini4","name":"Upstage: Solar Mini 4","description":"Solar Mini 4 is Upstage's compact, cost-efficient language model, a 35B-parameter mixture-of-experts with 3B active parameters and a 524K context window. It is built for agentic use cases where response...","family":"solar","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":131072},"cost":{"input":0.1,"output":0.4,"cache_read":0.01}},"~deepseek/deepseek-flash-latest":{"id":"~deepseek/deepseek-flash-latest","name":"DeepSeek: DeepSeek Flash Latest","description":"This model always redirects to the latest model in the DeepSeek Flash family.","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-14","last_updated":"2026-09-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.036,"output":0.6633,"cache_read":0.0054}},"~deepseek/deepseek-pro-latest":{"id":"~deepseek/deepseek-pro-latest","name":"DeepSeek: DeepSeek Pro Latest","description":"This model always redirects to the latest model in the DeepSeek Pro family.","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-14","last_updated":"2026-09-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":393216},"cost":{"input":0.24948,"output":0.74844,"cache_read":0.007938}},"~deepseek/deepseek-v4-flash-latest":{"id":"~deepseek/deepseek-v4-flash-latest","name":"DeepSeek: DeepSeek V4 Flash Latest","description":"This model always redirects to the latest model in the DeepSeek V4 Flash family.","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-01","last_updated":"2026-08-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.00441,"output":1.152,"cache_read":0.00441}},"~x-ai/grok-latest":{"id":"~x-ai/grok-latest","name":"xAI: Grok Latest","description":"This model always redirects to the latest Grok model from xAI.","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.5}},"bytedance/ui-tars-1.5-7b":{"id":"bytedance/ui-tars-1.5-7b","name":"ByteDance: UI-TARS 7B ","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":2048},"cost":{"input":0.1,"output":0.2,"cache_read":0.1}},"liquid/lfm-2.5-2.6b:free":{"id":"liquid/lfm-2.5-2.6b:free","name":"LiquidAI: LFM2.5-2.6B (free)","description":"LFM2.5-2.6B is a compact reasoning model from Liquid AI. It is suited for agent workflows, data extraction, RAG, and long-context processing. Liquid advises against using it for agentic coding or...","family":"liquid","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"output":8192},"cost":{"input":0,"output":0}},"liquid/lfm-2.5-24b-a2b":{"id":"liquid/lfm-2.5-24b-a2b","name":"LiquidAI: LFM2.5-24B-A2B","description":"LFM2.5-24B-A2B is a mixture-of-experts reasoning model from Liquid AI with 24B total and 2.45B active parameters. It always reasons before answering and is built for agents that call tools. Liquid...","family":"liquid","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.05,"output":0.7,"cache_read":0.025}},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.1,"output":0.34,"cache_read":0.1},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemini-3.1-flash-image-preview":{"id":"google/gemini-3.1-flash-image-preview","name":"Nano Banana 2 Preview","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-26","last_updated":"2026-02-26","modalities":{"input":["text","image","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":58982},"cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3.1-flash-image-preview"},"google/lyria-3-pro-preview":{"id":"google/lyria-3-pro-preview","name":"Lyria 3 Pro Preview","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"lyria","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-03-25","last_updated":"2026-03-25","modalities":{"input":["text","image"],"output":["text","audio"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"google/lyria-3-pro-preview"},"google/gemma-3-27b-it":{"id":"google/gemma-3-27b-it","name":"Gemma 3 27B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.08,"output":0.16},"canonical_model_id":"google/gemma-3-27b-it"},"google/gemini-2.5-flash-image":{"id":"google/gemini-2.5-flash-image","name":"Nano Banana","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["image","text","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":32768,"output":8192},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":0.083333},"canonical_model_id":"google/gemini-2.5-flash-image"},"google/gemma-2-27b-it":{"id":"google/gemma-2-27b-it","name":"Gemma 2 27B","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2024-07-13","last_updated":"2024-07-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":2048},"cost":{"input":0.65,"output":0.65},"canonical_model_id":"google/gemma-2-27b-it"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Gemini 3.6 Flash is a high-efficiency model from Google for coding, agentic workflows, and web and app development. It is designed to produce polished outputs with fewer unnecessary edits and...","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.375,"output":1.875,"reasoning":1.875,"cache_read":0.0375,"cache_write":0.020833},"canonical_model_id":"google/gemini-3.6-flash"},"google/gemma-4-26b-a4b-it":{"id":"google/gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.042,"output":0.22,"cache_read":0.021},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemini-3-pro-image-preview":{"id":"google/gemini-3-pro-image-preview","name":"Nano Banana Pro Preview","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-20","last_updated":"2025-11-20","modalities":{"input":["image","text","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":1,"output":6,"reasoning":6,"cache_read":0.1,"cache_write":0.1875},"canonical_model_id":"google/gemini-3-pro-image-preview"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Gemini 3.5 Flash Lite is a high-efficiency model from Google with upgraded agentic capabilities. It is suited for subagents that execute focused tasks within complex, multi-agent workflows.","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.15,"output":1.25,"reasoning":1.25,"cache_read":0.015,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemini-3.1-flash-image":{"id":"google/gemini-3.1-flash-image","name":"Nano Banana 2","description":"Gemini 3.1 Flash Image, a.k.a. \"Nano Banana 2,\" is Google’s latest state of the art image generation and editing model, delivering Pro-level visual quality at Flash speed. It combines advanced...","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["image","text","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3.1-flash-image"},"google/lyria-3-clip-preview":{"id":"google/lyria-3-clip-preview","name":"Lyria 3 Clip Preview","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"lyria","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-03-25","last_updated":"2026-03-25","modalities":{"input":["text","image"],"output":["text","audio"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"google/lyria-3-clip-preview"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1,"output":6,"reasoning":6,"cache_read":0.1,"cache_write":0.1875},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemma-3-12b-it":{"id":"google/gemma-3-12b-it","name":"Gemma 3 12B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.04,"output":0.12},"canonical_model_id":"google/gemma-3-12b-it"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":4.5,"reasoning":4.5,"cache_read":0.075,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"reasoning":10,"cache_read":0.125,"cache_write":0.375},"canonical_model_id":"google/gemini-2.5-pro"},"google/gemini-3-pro-image":{"id":"google/gemini-3-pro-image","name":"Nano Banana Pro","description":"Nano Banana Pro is Google’s most advanced image-generation and editing model, built on Gemini 3 Pro. It extends the original Nano Banana with significantly improved multimodal reasoning, real-world grounding, and...","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["image","text","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":2,"output":12,"reasoning":12,"cache_read":0.2,"cache_write":0.375},"canonical_model_id":"google/gemini-3-pro-image"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.3,"output":2.5,"reasoning":2.5,"cache_read":0.03,"cache_write":0.083333},"canonical_model_id":"google/gemini-2.5-flash"},"google/gemini-3.1-flash-lite-image":{"id":"google/gemini-3.1-flash-lite-image","name":"Nano Banana 2 Lite","description":"Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) is Google's fastest, most cost-efficient Gemini image model, built for high-velocity developer pipelines and rapid-fire visual exploration. It delivers text-to-image generation...","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["image","text","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":58982},"cost":{"input":0.25,"output":1.5},"canonical_model_id":"google/gemini-3.1-flash-lite-image"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"Gemini 3.7 Flash is a multimodal model from Google for fast agentic workflows, coding, and complex multi-step reasoning. It is designed for tasks that require responsive performance and reliable multi-step...","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"reasoning":3.75,"cache_read":0.075,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.7-flash"},"google/gemini-3.1-pro-preview-customtools":{"id":"google/gemini-3.1-pro-preview-customtools","name":"Gemini 3.1 Pro Preview Custom Tools","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"reasoning":12,"cache_read":0.2,"cache_write":0.375},"canonical_model_id":"google/gemini-3.1-pro-preview-customtools"},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"reasoning":1.5,"cache_read":0.025,"cache_write":0.041667},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Gemini 3.8 Flash is Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows.","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"reasoning":3.75,"cache_read":0.075,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemma-3-4b-it":{"id":"google/gemma-3-4b-it","name":"Gemma 3 4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.04,"output":0.05,"cache_read":0.02},"canonical_model_id":"google/gemma-3-4b-it"},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.1,"output":0.4,"reasoning":0.4,"cache_read":0.01,"cache_write":0.083333},"canonical_model_id":"google/gemini-2.5-flash-lite"},"google/gemini-2.5-pro-preview":{"id":"google/gemini-2.5-pro-preview","name":"Gemini 2.5 Pro Preview 06-05","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01-31","release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["pdf","image","text","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"reasoning":10,"cache_read":0.125,"cache_write":0.375},"canonical_model_id":"google/gemini-2.5-pro-preview"},"google/gemini-3.1-flash-lite-preview":{"id":"google/gemini-3.1-flash-lite-preview","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.125,"output":0.75,"reasoning":0.75,"cache_read":0.0125,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.1-flash-lite-preview"},"google/gemini-nano-banana-2.1":{"id":"google/gemini-nano-banana-2.1","name":"Nano Banana 2.1","description":"Nano Banana 2.1 (Gemini Nano Banana 2.1) is Google's image generation and editing model on the Flash tier, succeeding Nano Banana 2 and Nano Banana Pro. It improves product recontextualization,...","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["image","text","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":58982},"cost":{"input":1.5,"output":7.5},"canonical_model_id":"google/gemini-nano-banana-2.1"},"google/gemini-4-argon":{"id":"google/gemini-4-argon","name":"Gemini 4 Argon","description":"Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across...","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":10,"reasoning":10,"cache_read":0.1,"cache_write":0.1875},"canonical_model_id":"google/gemini-4-argon"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.125,"output":0.75,"reasoning":0.75,"cache_read":0.0125,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.1-flash-lite"},"writer/palmyra-x5":{"id":"writer/palmyra-x5","name":"Writer: Palmyra X5","description":"General-purpose chat model for instruction following, writing, and analysis","family":"palmyra","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-01-21","last_updated":"2026-01-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1040000,"output":8192},"cost":{"input":0.6,"output":6}},"moondream/moondream3-preview":{"id":"moondream/moondream3-preview","name":"Moondream: Moondream 3 Preview","description":"Moondream 3 Preview is a vision-language model from Moondream with 9B total parameters and 2B active (mixture-of-experts). It handles visual question answering, captioning, OCR, and visual reasoning over images, with...","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":4096},"cost":{"input":0.3,"output":2.5}},"moondream/moondream3.1-9b-a2b":{"id":"moondream/moondream3.1-9b-a2b","name":"Moondream: Moondream 3.1","description":"Moondream 3.1 is a vision-language model from Moondream, the successor to Moondream 3 Preview, with 9B total parameters and 2B active (mixture-of-experts). It handles visual question answering, captioning, OCR, and...","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":4096},"cost":{"input":0.3,"output":2.5}},"ibm-granite/granite-4.0-h-micro":{"id":"ibm-granite/granite-4.0-h-micro","name":"IBM: Granite 4.0 Micro","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"granite","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-10-20","last_updated":"2025-10-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":117900},"cost":{"input":0.017,"output":0.112}},"ibm-granite/granite-4.2-8b":{"id":"ibm-granite/granite-4.2-8b","name":"IBM: Granite 4.2 8B","description":"Granite 4.2 8B is a dense reasoning model from IBM. It is suited for mathematics, code generation, multilingual dialogue, and agentic workflows that need multi-step reasoning. It supports full, low-effort,...","family":"granite","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-31","last_updated":"2026-08-31","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":117964},"cost":{"input":0.06,"output":0.25,"cache_read":0.015}},"fireworks/ember-1":{"id":"fireworks/ember-1","name":"Fireworks: Ember-1","description":"Ember-1 is a specialized reasoning model from Fireworks Research, built on [Kimi K3](https://openrouter.ai/moonshotai/kimi-k3). It is designed to make every token go further: it produces shorter reasoning traces, using roughly 40%...","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-24","last_updated":"2026-09-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":3,"output":15,"cache_read":0.3}},"mistralai/mistral-nemo":{"id":"mistralai/mistral-nemo","name":"Mistral Nemo","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.15,"output":0.15,"cache_read":0.015},"canonical_model_id":"mistral/mistral-nemo"},"mistralai/ministral-8b-2512":{"id":"mistralai/ministral-8b-2512","name":"Ministral 3 8B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.15,"output":0.15,"cache_read":0.015},"canonical_model_id":"mistral/ministral-8b-2512"},"mistralai/mistral-small-24b-instruct-2501":{"id":"mistralai/mistral-small-24b-instruct-2501","name":"Mistral Small 3","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-01-30","last_updated":"2025-01-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"cost":{"input":0.05,"output":0.08},"canonical_model_id":"mistral/mistral-small-24b-instruct-2501"},"mistralai/devstral-2512":{"id":"mistralai/devstral-2512","name":"Devstral 2","description":"Devstral 2 is a state-of-the-art open-source model by Mistral AI specializing in agentic coding. It is a 123B-parameter dense transformer model supporting a 256K context window. Devstral 2 supports exploring...","family":"devstral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.4,"output":2,"cache_read":0.04},"canonical_model_id":"mistral/devstral-2512"},"mistralai/mistral-saba":{"id":"mistralai/mistral-saba","name":"Saba","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-02-17","last_updated":"2025-02-17","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":26214},"cost":{"input":0.2,"output":0.6,"cache_read":0.02},"canonical_model_id":"mistral/mistral-saba"},"mistralai/mistral-medium-3-5":{"id":"mistralai/mistral-medium-3-5","name":"Mistral Medium 3.5","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":209715},"cost":{"input":1.5,"output":7.5},"canonical_model_id":"mistral/mistral-medium-3-5"},"mistralai/mistral-medium-3.1":{"id":"mistralai/mistral-medium-3.1","name":"Mistral Medium 3.1","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06-30","release_date":"2025-08-13","last_updated":"2025-08-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":104857},"cost":{"input":0.4,"output":2,"cache_read":0.04},"canonical_model_id":"mistral/mistral-medium-3.1"},"mistralai/mistral-small-3.2-24b-instruct":{"id":"mistralai/mistral-small-3.2-24b-instruct","name":"Mistral Small 3.2 24B","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["image","text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":0.1,"output":0.3,"cache_read":0.01},"canonical_model_id":"mistral/mistral-small-3.2-24b-instruct"},"mistralai/mistral-large":{"id":"mistralai/mistral-large","name":"Mistral Large","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11-30","release_date":"2024-02-26","last_updated":"2024-02-26","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":102400},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"mistral/mistral-large"},"mistralai/mistral-small-2603":{"id":"mistralai/mistral-small-2603","name":"Mistral Small 4","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"mistral/mistral-small-2603"},"mistralai/mistral-medium-3":{"id":"mistralai/mistral-medium-3","name":"Mistral Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":104857},"cost":{"input":0.4,"output":2,"cache_read":0.04},"canonical_model_id":"mistral/mistral-medium-3"},"mistralai/voxtral-small-24b-2507":{"id":"mistralai/voxtral-small-24b-2507","name":"Voxtral Small 24B 2507","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"voxtral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":26214},"cost":{"input":0.1,"output":0.3,"cache_read":0.01},"canonical_model_id":"mistral/voxtral-small-24b-2507"},"mistralai/mistral-large-2512":{"id":"mistralai/mistral-large-2512","name":"Mistral Large 3","description":"Mistral Large 3 2512 is Mistral’s most capable model to date, featuring a sparse mixture-of-experts architecture with 41B active parameters (675B total), and released under the Apache 2.0 license.","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.5,"output":1.5,"cache_read":0.05},"canonical_model_id":"mistral/mistral-large-2512"},"mistralai/mistral-large-2407":{"id":"mistralai/mistral-large-2407","name":"Mistral Large 2407","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-03-31","release_date":"2024-11-19","last_updated":"2024-11-19","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":104857},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"mistral/mistral-large-2407"},"mistralai/ministral-14b-2512":{"id":"mistralai/ministral-14b-2512","name":"Ministral 3 14B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.2,"output":0.2,"cache_read":0.02},"canonical_model_id":"mistral/ministral-14b-2512"},"mistralai/mistral-large-4-0":{"id":"mistralai/mistral-large-4-0","name":"Mistral: Mistral Large 4 (50% off)","description":"Mistral Large 4 is a frontier multimodal (text and image input) model from Mistral AI built for reasoning, coding, and agentic workloads. It offers a 512K-token context window with up...","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":262144},"cost":{"input":0.68,"output":2.09,"cache_read":0.07}},"mistralai/mistral-small-3.1-24b-instruct":{"id":"mistralai/mistral-small-3.1-24b-instruct","name":"Mistral Small 3.1 24B","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-03-17","last_updated":"2025-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":102400},"cost":{"input":0.351,"output":0.555},"canonical_model_id":"mistral/mistral-small-3.1-24b-instruct"},"mistralai/ministral-3b-2512":{"id":"mistralai/ministral-3b-2512","name":"Ministral 3 3B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":104857},"cost":{"input":0.1,"output":0.1,"cache_read":0.01},"canonical_model_id":"mistral/ministral-3b-2512"},"mistralai/mixtral-8x22b-instruct":{"id":"mistralai/mixtral-8x22b-instruct","name":"Mixtral 8x22B Instruct","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-01-31","release_date":"2024-04-17","last_updated":"2024-04-17","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":52428},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"mistral/mixtral-8x22b-instruct"},"mistralai/codestral-2508":{"id":"mistralai/codestral-2508","name":"Codestral 25.08","description":"Mistral coding model for code completion, generation, and developer workflows","family":"codestral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":204800},"cost":{"input":0.3,"output":0.9,"cache_read":0.03},"canonical_model_id":"mistral/codestral-2508"},"sakana/fugu-max":{"id":"sakana/fugu-max","name":"Fugu Max","description":"Fugu Max is the cost-performance model in Sakana AI's Fugu family. Rather than a single monolithic model, Fugu is a learned multi-agent orchestration system: a language model trained to route...","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"sakana/fugu-max"},"sakana/fugu-ultra-v2":{"id":"sakana/fugu-ultra-v2","name":"Fugu Ultra v2","description":"Fugu Ultra v2 is the higher-performance model in Sakana AI's Fugu family. Rather than a single monolithic model, Fugu is a learned multi-agent orchestration system: a language model trained to...","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-08-28","release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"sakana/fugu-ultra-v2"},"sakana/fugu-ultra":{"id":"sakana/fugu-ultra","name":"Fugu Ultra","description":"Fugu Ultra is the higher-performance model in Sakana AI's Fugu family. Rather than a single monolithic model, Fugu is a learned multi-agent orchestration system: a language model trained to route...","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"sakana/fugu-ultra"},"sakana/sakana-namazu":{"id":"sakana/sakana-namazu","name":"Sakana Namazu","description":"Sakana Namazu is a Japanese-specialized reasoning model from Sakana AI, based on Kimi K2.6 with additional training for Japanese language and business contexts. It is suited for Japanese instruction following,...","family":"sakana-namazu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.95,"output":4,"cache_read":0.15},"canonical_model_id":"sakana/sakana-namazu"},"inclusionai/ling-3.0-flash":{"id":"inclusionai/ling-3.0-flash","name":"inclusionAI: Ling 3.0 Flash","description":"*Ling-3.0-flash* is a *124B-parameter Mixture-of-Experts (MoE) model*, with approximately *5.1B parameters activated per token*. The model is designed with *token efficiency and production-scale agentic inference* as key priorities, enabling developers...","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-23","last_updated":"2026-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.06,"output":0.18,"cache_read":0.012}},"inclusionai/ling-3.1-flash":{"id":"inclusionai/ling-3.1-flash","name":"inclusionAI: Ling 3.1 Flash","description":"Ling 3.1 Flash is a hybrid reasoning mixture-of-experts model from inclusionAI, with 25B active parameters out of 560B total.","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-02","last_updated":"2026-10-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":235929},"cost":{"input":0.3,"output":0.9,"cache_read":0.06}},"inclusionai/ling-3.0-flash-vl":{"id":"inclusionai/ling-3.0-flash-vl","name":"inclusionAI: Ling 3.0 Flash VL","description":"Ling 3.0 Flash VL builds on Ling 3.0 Flash (124B total / 5.5B active MoE from InclusionAI), further strengthening its language capabilities while adding native visual perception and advanced visual...","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.06,"output":0.18,"cache_read":0.012}},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Kimi K3 is a 2.8T parameter open-weight multimodal reasoning model from Moonshot AI. It is suited for complex coding, knowledge work, and long-horizon agentic workflows, and is particularly strong at...","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.65,"output":3.41,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2-thinking":{"id":"moonshotai/kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Kimi reasoning model for long-horizon research, planning, and tool use","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":0.6,"output":2.5,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"moonshotai/kimi-k2.5":{"id":"moonshotai/kimi-k2.5","name":"Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.6,"output":3},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/kimi-k2-0905":{"id":"moonshotai/kimi-k2-0905","name":"Kimi K2 Instruct 0905","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":0.6,"output":2.5},"canonical_model_id":"moonshotai/kimi-k2-0905"},"moonshotai/kimi-k2":{"id":"moonshotai/kimi-k2","name":"Kimi K2 0711","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-12-31","release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.57,"output":2.3},"canonical_model_id":"moonshotai/kimi-k2"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"MoonshotAI: Kimi K2.7 Code is a coding-focused model in Moonshot AI's Kimi K2 family, built to complete end-to-end programming tasks reliably over long contexts. It uses a native multimodal mixture-of-experts...","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.6712,"output":3.35,"cache_read":0.18},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"kilo-auto/small":{"id":"kilo-auto/small","name":"Auto Small","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"1970-01-01","last_updated":"1970-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.05,"output":0.4,"reasoning":0,"cache_read":0.005}},"kilo-auto/efficient":{"id":"kilo-auto/efficient","name":"Auto Efficient","description":"Routes each request to the cheapest model that gets the job done, based on continuously benchmarked accuracy and cost.","family":"auto","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"1970-01-01","last_updated":"1970-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.325,"output":1.95,"reasoning":0,"cache_read":0.0325,"cache_write":0.40625}},"kilo-auto/free":{"id":"kilo-auto/free","name":"Auto Free","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"1970-01-01","last_updated":"1970-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32768},"cost":{"input":0,"output":0,"reasoning":0,"cache_read":0,"cache_write":0}},"kilo-auto/frontier":{"id":"kilo-auto/frontier","name":"Auto Frontier","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"1970-01-01","last_updated":"1970-01-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"reasoning":0,"cache_read":0.5,"cache_write":6.25}},"kilo-auto/balanced":{"id":"kilo-auto/balanced","name":"Auto Balanced","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"1970-01-01","last_updated":"1970-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.325,"output":1.95,"reasoning":0,"cache_read":0.0325,"cache_write":0.40625}},"rekaai/reka-flash-3":{"id":"rekaai/reka-flash-3","name":"Reka Flash 3","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"reka","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"output":58982},"cost":{"input":0.1,"output":0.2}},"rekaai/reka-edge":{"id":"rekaai/reka-edge","name":"Reka Edge","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"reka","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-20","last_updated":"2026-03-20","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":14745},"cost":{"input":0.1,"output":0.1}},"nvidia/nemotron-3.5-super-vl:free":{"id":"nvidia/nemotron-3.5-super-vl:free","name":"NVIDIA: Nemotron 3.5 Super VL (free)","description":"NVIDIA Nemotron 3.5 Super VL is an open multimodal mixture-of-experts model from NVIDIA, with 12B active parameters out of 120B total. It takes text, images, documents, GUI screenshots, and video... **Terms of service** For NVIDIA free endpoints (Super/Ultra/etc): Trial use only - do not submit personal or confidential data. Your use is logged for security purposes and to improve NVIDIA products and services. The logged session data for improvement purposes is not linked to your identity or any persistent identifier. For more information about our data processing practices, see our [Privacy Policy](https://www.nvidia.com/en-us/about-nvidia/privacy-policy/). By interacting with this endpoint, you consent to our collection, recording, and use of such information and the [NVIDIA API Trial Terms of Service](https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf).","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0}},"nvidia/nemotron-3-nano-30b-a3b":{"id":"nvidia/nemotron-3-nano-30b-a3b","name":"Nemotron 3 Nano 30B A3B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.05,"output":0.2},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"nvidia/nemotron-3.5-content-safety:free":{"id":"nvidia/nemotron-3.5-content-safety:free","name":"NVIDIA: Nemotron 3.5 Content Safety (free)","description":"NVIDIA Nemotron 3.5 Content Safety is a compact 4B-parameter multimodal guardrail model from NVIDIA, fine-tuned from Google Gemma-3-4B. It moderates both inputs to and responses from LLMs and VLMs, accepting... **Terms of service** For NVIDIA free endpoints (Super/Ultra/etc): Trial use only - do not submit personal or confidential data. Your use is logged for security purposes and to improve NVIDIA products and services. The logged session data for improvement purposes is not linked to your identity or any persistent identifier. For more information about our data processing practices, see our [Privacy Policy](https://www.nvidia.com/en-us/about-nvidia/privacy-policy/). By interacting with this endpoint, you consent to our collection, recording, and use of such information and the [NVIDIA API Trial Terms of Service](https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf).","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-content-safety"},"nvidia/nemotron-3.5-lightning":{"id":"nvidia/nemotron-3.5-lightning","name":"Nemotron 3.5 Lightning 30B A3B","description":"NVIDIA Nemotron 3.5 Lightning is an open mixture-of-experts model from NVIDIA, with 3B active parameters out of 30B total. It is suited for high-throughput agentic workloads and specialized tasks that...","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.025,"output":0.12,"cache_read":0.0125},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning:free":{"id":"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning:free","name":"NVIDIA: Nemotron 3 Nano Omni (free)","description":"Open Nemotron omni model combining reasoning with text, vision, and audio","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning"},"nvidia/nemotron-3-super-120b-a12b":{"id":"nvidia/nemotron-3-super-120b-a12b","name":"Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.08,"output":0.45},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"nvidia/nemotron-3.5-super-vl":{"id":"nvidia/nemotron-3.5-super-vl","name":"NVIDIA: Nemotron 3.5 Super VL","description":"NVIDIA Nemotron 3.5 Super VL is an open multimodal mixture-of-experts model from NVIDIA, with 12B active parameters out of 120B total. It takes text, images, documents, GUI screenshots, and video...","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":235929},"cost":{"input":0.1,"output":0.4,"cache_read":0.08}},"nvidia/nemotron-3-ultra-550b-a55b:free":{"id":"nvidia/nemotron-3-ultra-550b-a55b:free","name":"NVIDIA: Nemotron 3 Ultra (free)","description":"NVIDIA Nemotron 3 Ultra is an open frontier-reasoning and orchestration model from NVIDIA, with 55B active parameters out of 550B total (MoE). Built on a hybrid Transformer-Mamba mixture-of-experts architecture, it... **Terms of service** For NVIDIA free endpoints (Super/Ultra/etc): Trial use only - do not submit personal or confidential data. Your use is logged for security purposes and to improve NVIDIA products and services. The logged session data for improvement purposes is not linked to your identity or any persistent identifier. For more information about our data processing practices, see our [Privacy Policy](https://www.nvidia.com/en-us/about-nvidia/privacy-policy/). By interacting with this endpoint, you consent to our collection, recording, and use of such information and the [NVIDIA API Trial Terms of Service](https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf).","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/nemotron-3-ultra-550b-a55b":{"id":"nvidia/nemotron-3-ultra-550b-a55b","name":"Nemotron 3 Ultra 550B A55B","description":"NVIDIA Nemotron 3 Ultra is an open frontier-reasoning and orchestration model from NVIDIA, with 55B active parameters out of 550B total (MoE). Built on a hybrid Transformer-Mamba mixture-of-experts architecture, it...","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202800,"output":182520},"cost":{"input":0.4,"output":1.76,"cache_read":0.08},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/nemotron-3-super-120b-a12b:free":{"id":"nvidia/nemotron-3-super-120b-a12b:free","name":"NVIDIA: Nemotron 3 Super (free)","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"nvidia/nemotron-3.5-content-safety":{"id":"nvidia/nemotron-3.5-content-safety","name":"Nemotron 3.5 Content Safety","description":"NVIDIA Nemotron 3.5 Content Safety is a compact 4B-parameter multimodal guardrail model from NVIDIA, fine-tuned from Google Gemma-3-4B. It moderates both inputs to and responses from LLMs and VLMs, accepting...","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.2,"output":0.2},"canonical_model_id":"nvidia/nemotron-3.5-content-safety"},"nvidia/nemotron-3.5-lightning:free":{"id":"nvidia/nemotron-3.5-lightning:free","name":"NVIDIA: Nemotron 3.5 Lightning (free)","description":"NVIDIA Nemotron 3.5 Lightning is an open mixture-of-experts model from NVIDIA, with 3B active parameters out of 30B total. It is suited for high-throughput agentic workloads and specialized tasks that... **Terms of service** For NVIDIA free endpoints (Super/Ultra/etc): Trial use only - do not submit personal or confidential data. Your use is logged for security purposes and to improve NVIDIA products and services. The logged session data for improvement purposes is not linked to your identity or any persistent identifier. For more information about our data processing practices, see our [Privacy Policy](https://www.nvidia.com/en-us/about-nvidia/privacy-policy/). By interacting with this endpoint, you consent to our collection, recording, and use of such information and the [NVIDIA API Trial Terms of Service](https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf).","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"xiaomi/mimo-v2.6-pro":{"id":"xiaomi/mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"MiMo-V2.6-Pro is the flagship foundation model developed by Xiaomi. Built at a scale of over 1T parameters, it is designed to push the ceiling of capability for the most demanding...","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.43,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"xiaomi/mimo-v2.5":{"id":"xiaomi/mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.003,"tiers":[{"input":0.8,"output":4,"cache_read":0.16,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.8,"output":4,"cache_read":0.16}},"canonical_model_id":"xiaomi/mimo-v2.5"},"xiaomi/mimo-v2.6-pro-ultraspeed":{"id":"xiaomi/mimo-v2.6-pro-ultraspeed","name":"MiMo-V2.6-Pro-UltraSpeed","description":"MiMo-V2.6-Pro-UltraSpeed is the fast speed edition of Xiaomi's flagship foundation model, MiMo-V2.6-Pro. Built from the same 1T MiMo-V2.6-Pro checkpoint, it matches the original model in quality while delivering roughly 10x...","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":4.35,"output":8.7,"cache_read":0.036},"canonical_model_id":"xiaomi/mimo-v2.6-pro-ultraspeed"},"xiaomi/mimo-v2.5-pro":{"id":"xiaomi/mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.004,"tiers":[{"input":2,"output":6,"cache_read":0.4,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.4}},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"xiaomi/mimo-v2.6-flash":{"id":"xiaomi/mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo-V2.6-Flash is an open-source foundation model developed by Xiaomi. Built on a Mixture-of-Experts architecture with 309B total parameters and 15B activated per token, it employs a hybrid attention mechanism for...","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.1,"output":0.28,"cache_read":0.05},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"undi95/remm-slerp-l2-13b":{"id":"undi95/remm-slerp-l2-13b","name":"ReMM SLERP 13B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2023-07-22","last_updated":"2023-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":6144,"output":5529},"cost":{"input":0.35,"output":0.65}},"gryphe/mythomax-l2-13b":{"id":"gryphe/mythomax-l2-13b","name":"MythoMax 13B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2023-07-02","last_updated":"2023-07-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":4096,"output":3686},"cost":{"input":0.08,"output":0.11}},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":198000,"output":32768},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5"},"minimax/minimax-01":{"id":"minimax/minimax-01","name":"MiniMax: MiniMax-01","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-01-15","last_updated":"2025-01-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000192,"output":900172},"cost":{"input":0.2,"output":1.1}},"minimax/minimax-m2-her":{"id":"minimax/minimax-m2-her","name":"MiniMax-M2 Her","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-01-23","last_updated":"2026-01-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"output":2048},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2-Her"},"minimax/minimax-m2.7":{"id":"minimax/minimax-m2.7","name":"MiniMax-M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/minimax-m1":{"id":"minimax/minimax-m1","name":"MiniMax: MiniMax M1","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":40000},"cost":{"input":0.4,"output":2.2}},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":512000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"minimax/minimax-m2.1":{"id":"minimax/minimax-m2.1","name":"MiniMax-M2.1","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.1"},"minimax/minimax-m2":{"id":"minimax/minimax-m2","name":"MiniMax-M2","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2"},"mancer/weaver":{"id":"mancer/weaver","name":"Mancer: Weaver (alpha)","description":"An attempt to recreate Claude-style verbosity, but don't expect the same level of coherence or memory. Meant for use in roleplay/narrative situations.","family":"alpha","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2023-08-02","last_updated":"2023-08-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8000,"output":6000},"cost":{"input":0.4,"output":0.75}},"stepfun/step-5-preview":{"id":"stepfun/step-5-preview","name":"Step 5 Preview","description":"Step 5 Preview is StepFun's flagship model for agentic work, built on a sparse Mixture-of-Experts architecture (27B active / 600B total parameters). It performs strongly in software engineering and professional...","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":64000},"cost":{"input":1,"output":2.7,"cache_read":0.1},"canonical_model_id":"stepfun/step-5-preview"},"stepfun/step-3.5-flash":{"id":"stepfun/step-3.5-flash","name":"Step 3.5 Flash","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"stepfun/step-3.5-flash"},"stepfun/step-3.7-flash":{"id":"stepfun/step-3.7-flash","name":"Step 3.7 Flash","description":"Step 3.7 Flash is StepFun's latest high-efficiency multimodal Mixture-of-Experts model. It pairs a 196B-parameter language backbone with a vision encoder for native image and video understanding, activating roughly 11B parameters...","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":230400},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"dots-studio/dots-3-note-preview:free":{"id":"dots-studio/dots-3-note-preview:free","name":"Dots Studio: Dots3-Note Preview (free)","description":"Dots3-Note Preview is an open-weight mixture-of-experts model from Dots Studio, with 16B active parameters out of 280B total. It is the lightest model in the Dots 3 family and is...","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":512000,"output":460800},"cost":{"input":0,"output":0}},"inception/mercury-2.5":{"id":"inception/mercury-2.5","name":"Inception: Mercury 2.5","description":"Mercury 2.5 is the fastest reasoning LLM, and the latest diffusion LLM (dLLM) from Inception. Instead of generating tokens sequentially, Mercury 2.5 produces and refines multiple tokens in parallel, achieving...","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":260000,"output":65536},"cost":{"input":0.2,"output":0.75,"cache_read":0.02}},"inception/mercury-2":{"id":"inception/mercury-2","name":"Inception: Mercury 2","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-04","last_updated":"2026-03-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":50000},"cost":{"input":0.25,"output":0.75,"cache_read":0.025}},"amazon/nova-lite-v1":{"id":"amazon/nova-lite-v1","name":"Amazon: Nova Lite 1.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":5120},"cost":{"input":0.06,"output":0.24}},"amazon/nova-2-lite-v1":{"id":"amazon/nova-2-lite-v1","name":"Amazon: Nova 2 Lite","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.3,"output":2.5}},"amazon/nova-pro-v1":{"id":"amazon/nova-pro-v1","name":"Amazon: Nova Pro 1.0","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":5120},"cost":{"input":0.8,"output":3.2}},"amazon/nova-premier-v1":{"id":"amazon/nova-premier-v1","name":"Amazon: Nova Premier 1.0","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-10-31","last_updated":"2025-10-31","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32000},"cost":{"input":2.5,"output":12.5,"cache_read":0.625}},"amazon/nova-micro-v1":{"id":"amazon/nova-micro-v1","name":"Amazon: Nova Micro 1.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-micro","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":5120},"cost":{"input":0.035,"output":0.14}},"relace/relace-search":{"id":"relace/relace-search","name":"Relace: Relace Search","description":"Tool-capable chat model for instruction following and agentic application workflows","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":1,"output":3}},"relace/relace-apply-3":{"id":"relace/relace-apply-3","name":"Relace: Relace Apply 3","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2025-09-26","last_updated":"2025-09-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.85,"output":1.25}},"aion-labs/aion-2.0":{"id":"aion-labs/aion-2.0","name":"AionLabs: Aion-2.0","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.8,"output":1.6,"cache_read":0.2}},"aion-labs/aion-rp-llama-3.1-8b":{"id":"aion-labs/aion-rp-llama-3.1-8b","name":"AionLabs: Aion-RP 1.0 (8B)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-02-04","last_updated":"2025-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":29491},"cost":{"input":0.8,"output":1.6}},"aion-labs/aion-3.0":{"id":"aion-labs/aion-3.0","name":"AionLabs: Aion-3.0","description":"Aion-3.0 is a multi-model roleplaying and storytelling system from AionLabs, built on the GLM family of models. It uses a collaborative generation process in which multiple specialized models each contribute...","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-07","last_updated":"2026-07-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":3,"output":6,"cache_read":0.75}},"aion-labs/aion-3.5":{"id":"aion-labs/aion-3.5","name":"AionLabs: Aion 3.5","description":"Aion 3.5 is a multi-model roleplaying and storytelling system from AionLabs, built on the GLM family of models. It uses a collaborative generation process in which multiple specialized models each...","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":3,"output":6,"cache_read":0.75}},"aion-labs/aion-3.5-mini":{"id":"aion-labs/aion-3.5-mini","name":"AionLabs: Aion 3.5 Mini","description":"Aion 3.5 Mini is a multi-model roleplaying and storytelling system from AionLabs, built on the GLM family of models. It is the smaller, lower-cost sibling of Aion 3.5 and uses...","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.7,"output":1.4,"cache_read":0.18}},"aion-labs/aion-3.0-mini":{"id":"aion-labs/aion-3.0-mini","name":"AionLabs: Aion-3.0-Mini","description":"Aion-3.0 Mini is a multi-model roleplaying and storytelling system from AionLabs, built on the DeepSeek family of models. It uses a collaborative generation process in which multiple specialized models each...","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-07","last_updated":"2026-07-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.7,"output":1.4,"cache_read":0.18}},"qwen/qwen3-235b-a22b-2507":{"id":"qwen/qwen3-235b-a22b-2507","name":"Qwen: Qwen3 235B A22B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":16384},"cost":{"input":0.09,"output":0.55}},"qwen/qwen3-vl-235b-a22b-instruct":{"id":"qwen/qwen3-vl-235b-a22b-instruct","name":"Qwen3 VL 235B A22B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.21,"output":1.9,"cache_read":0.1},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":1.475,"output":4.425,"cache_read":0.295,"cache_write":1.84375},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Qwen3.8 27B is an open-weight dense vision-language model from Qwen. It is suited for coding, professional workflows, research, multimodal interaction, and long-running agent tasks, with flexible thinking that can be...","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.425,"output":2.55,"cache_read":0.085,"cache_write":0.53125},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3.8-2.4t-a95b":{"id":"qwen/qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"qwen/qwen3.5-27b":{"id":"qwen/qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":81920},"cost":{"input":0.195,"output":1.56},"canonical_model_id":"alibaba/qwen3.5-27b"},"qwen/qwen3-next-80b-a3b-thinking":{"id":"qwen/qwen3-next-80b-a3b-thinking","name":"Qwen3-Next 80B-A3B (Thinking)","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.15,"output":1.2},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-thinking"},"qwen/qwen3-coder-next":{"id":"qwen/qwen3-coder-next","name":"Qwen3 Coder Next","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.12,"output":0.8,"cache_read":0.07},"canonical_model_id":"alibaba/qwen3-coder-next"},"qwen/qwen3-coder":{"id":"qwen/qwen3-coder","name":"Qwen: Qwen3 Coder 480B A35B","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.3,"output":1,"cache_read":0.1}},"qwen/qwen3-32b":{"id":"qwen/qwen3-32b","name":"Qwen3 32B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":16384},"cost":{"input":0.08,"output":0.28},"canonical_model_id":"alibaba/qwen3-32b"},"qwen/qwen-plus":{"id":"qwen/qwen-plus","name":"Qwen Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.26,"output":0.78,"cache_read":0.052,"cache_write":0.325},"canonical_model_id":"alibaba/qwen-plus"},"qwen/qwen3.7-flash":{"id":"qwen/qwen3.7-flash","name":"Qwen3.7 Flash","description":"Qwen3.7 Flash is a vision-language reasoning model from Alibaba. It is suited for multimodal agents, visual coding, search, and computer interaction, with strengths in object recognition, spatial understanding, and real-world...","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":991808,"output":65536},"cost":{"input":0.03,"output":0.13,"cache_read":0.006,"cache_write":0.038},"canonical_model_id":"alibaba/qwen3.7-flash"},"qwen/qwen3-coder-30b-a3b-instruct":{"id":"qwen/qwen3-coder-30b-a3b-instruct","name":"Qwen3-Coder 30B-A3B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.07,"output":0.28},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"qwen/qwen3.8-omni-flash":{"id":"qwen/qwen3.8-omni-flash","name":"Qwen3.8 Omni Flash","description":"Qwen3.8 Omni Flash is an omni-modal reasoning model from Alibaba, the first Qwen model built around agentic capabilities with native audio-video understanding. It is suited for audio-video analysis and summarization,...","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-omni-flash"},"qwen/qwen3-vl-30b-a3b-instruct":{"id":"qwen/qwen3-vl-30b-a3b-instruct","name":"Qwen3 VL 30B A3B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-04","last_updated":"2025-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"alibaba/qwen3-vl-30b-a3b-instruct"},"qwen/qwen3-235b-a22b-thinking-2507":{"id":"qwen/qwen3-235b-a22b-thinking-2507","name":"Qwen: Qwen3 235B A22B Thinking 2507","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-07-25","last_updated":"2025-07-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.45,"output":3.5}},"qwen/qwen3.5-122b-a10b":{"id":"qwen/qwen3.5-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.26,"output":2.08},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"qwen/qwen3.6-35b-a3b":{"id":"qwen/qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.15,"output":1,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"qwen/qwen3-next-80b-a3b-instruct":{"id":"qwen/qwen3-next-80b-a3b-instruct","name":"Qwen3-Next 80B-A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.09,"output":1.1},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"qwen/qwen3-vl-30b-a3b-thinking":{"id":"qwen/qwen3-vl-30b-a3b-thinking","name":"Qwen: Qwen3 VL 30B A3B Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":235929},"cost":{"input":0.29,"output":1}},"qwen/qwen3.6-flash":{"id":"qwen/qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.1875,"output":1.125,"cache_write":0.234375},"canonical_model_id":"alibaba/qwen3.6-flash"},"qwen/qwen3-coder-flash":{"id":"qwen/qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.195,"output":0.975,"cache_read":0.039,"cache_write":0.24375},"canonical_model_id":"alibaba/qwen3-coder-flash"},"qwen/qwen-2.5-coder-32b-instruct":{"id":"qwen/qwen-2.5-coder-32b-instruct","name":"Qwen2.5 Coder 32B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2024-11-11","last_updated":"2024-11-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":29491},"cost":{"input":0.66,"output":1}},"qwen/qwen3.5-flash-02-23":{"id":"qwen/qwen3.5-flash-02-23","name":"Qwen: Qwen3.5-Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.5","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-25","last_updated":"2026-02-25","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.065,"output":0.26}},"qwen/qwen3.5-9b":{"id":"qwen/qwen3.5-9b","name":"Qwen3.5 9B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32768},"cost":{"input":0.1,"output":0.15},"canonical_model_id":"alibaba/qwen3.5-9b"},"qwen/qwen3.8-max-prime":{"id":"qwen/qwen3.8-max-prime","name":"Qwen 3.8 Max Prime","description":"Qwen3.8 Max Prime is a higher-throughput variant of Qwen3.8 Max from Alibaba's Qwen team, served as a separate SKU at a higher price point. It accepts text, image, and video...","family":"qwen3.8-max","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":4,"output":12,"cache_read":0.5},"canonical_model_id":"alibaba/qwen3.8-max-prime"},"qwen/qwen3.5-plus-20260420":{"id":"qwen/qwen3.5-plus-20260420","name":"Qwen: Qwen3.5 Plus 2026-04-20","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.5","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.3,"output":1.8,"cache_write":0.375}},"qwen/qwen3.8-flash":{"id":"qwen/qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen3.8 Flash is a multimodal reasoning model from Alibaba. It is suited for coding assistance, agentic workflows, visual understanding, document and codebase analysis, desktop interaction, chart analysis, and long-video analysis.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen/qwen3.5-35b-a3b":{"id":"qwen/qwen3.5-35b-a3b","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":0.1625,"output":1.3},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"qwen/qwen3-30b-a3b":{"id":"qwen/qwen3-30b-a3b","name":"Qwen3 30B A3B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":16384},"cost":{"input":0.12,"output":0.5},"canonical_model_id":"alibaba/qwen3-30b-a3b"},"qwen/qwen3.5-397b-a17b":{"id":"qwen/qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.39,"output":2.34},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"qwen/qwen3-vl-8b-instruct":{"id":"qwen/qwen3-vl-8b-instruct","name":"Qwen: Qwen3 VL 8B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-14","last_updated":"2025-10-14","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":235929},"cost":{"input":0.25,"output":0.75,"cache_read":0.12}},"qwen/qwen3-30b-a3b-instruct-2507":{"id":"qwen/qwen3-30b-a3b-instruct-2507","name":"Qwen: Qwen3 30B A3B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-29","last_updated":"2025-07-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":235929},"cost":{"input":0.1,"output":0.3}},"qwen/qwen2.5-vl-72b-instruct":{"id":"qwen/qwen2.5-vl-72b-instruct","name":"Qwen: Qwen2.5 VL 72B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-02-01","last_updated":"2025-02-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":115200},"cost":{"input":0.8,"output":1,"cache_read":0.4}},"qwen/qwen-2.5-7b-instruct":{"id":"qwen/qwen-2.5-7b-instruct","name":"Qwen: Qwen2.5 7B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-10-16","last_updated":"2024-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":29491},"cost":{"input":0.1,"output":0.2}},"qwen/qwen3.5-plus-02-15":{"id":"qwen/qwen3.5-plus-02-15","name":"Qwen: Qwen3.5 Plus 2026-02-15","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.5","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.26,"output":1.56}},"qwen/qwen-2.5-72b-instruct":{"id":"qwen/qwen-2.5-72b-instruct","name":"Qwen2.5 72B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-09-19","last_updated":"2024-09-19","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":16384},"cost":{"input":0.36,"output":0.4}},"qwen/qwen3.6-27b":{"id":"qwen/qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.45,"output":2.7},"canonical_model_id":"alibaba/qwen3.6-27b"},"qwen/qwen3.6-plus":{"id":"qwen/qwen3.6-plus","name":"Qwen3.6 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.325,"output":1.95,"cache_write":0.40625},"canonical_model_id":"alibaba/qwen3.6-plus"},"qwen/qwen3-14b":{"id":"qwen/qwen3-14b","name":"Qwen: Qwen3 14B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":40960,"output":16384},"cost":{"input":0.12,"output":0.24}},"qwen/qwen3.7-plus":{"id":"qwen/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Qwen3.7-Plus is a cost-effective model in Alibaba's Qwen3.7 series. It supports text and image input with text output, building on the series' text capabilities with a comprehensive upgrade to its...","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.32,"output":1.28,"cache_read":0.064,"cache_write":0.4},"canonical_model_id":"alibaba/qwen3.7-plus"},"qwen/qwen3.8-max-0902":{"id":"qwen/qwen3.8-max-0902","name":"Qwen3.8 Max 0902","description":"Qwen3.8 Max 0902 is an updated snapshot of Qwen3.8 Max from Alibaba's Qwen team. It is a 2.4-trillion-parameter mixture-of-experts model that accepts text, image, and video input and returns text,...","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max-0902"},"morph/morph-v3-large":{"id":"morph/morph-v3-large","name":"Morph: Morph V3 Large","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"morph","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-07-07","last_updated":"2025-07-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.9,"output":1.9}},"morph/morph-v3-fast":{"id":"morph/morph-v3-fast","name":"Morph: Morph V3 Fast","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"morph","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-07-07","last_updated":"2025-07-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":81920,"output":38000},"cost":{"input":0.8,"output":1.2}},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.4-image-2":{"id":"openai/gpt-5.4-image-2","name":"GPT-5.4 Image 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":false,"structured_output":true,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["image","text","pdf"],"output":["image","text"]},"open_weights":false,"limit":{"context":272000,"output":128000},"cost":{"input":8,"output":15,"cache_read":2},"canonical_model_id":"openai/gpt-5.4-image-2"},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT-5.4 Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180},"canonical_model_id":"openai/gpt-5.4-pro"},"openai/gpt-audio":{"id":"openai/gpt-audio","name":"OpenAI: GPT Audio","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text","audio","pdf"],"output":["text","audio"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10}},"openai/gpt-3.5-turbo":{"id":"openai/gpt-3.5-turbo","name":"GPT-3.5-turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"output":4096},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"openai/gpt-3.5-turbo"},"openai/gpt-6-astra-pro":{"id":"openai/gpt-6-astra-pro","name":"OpenAI: GPT-6 Astra Pro ($$$$)","description":"GPT-6 Astra Pro is the same underlying model as [GPT-6 Astra](https://openrouter.ai/openai/gpt-6-astra), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5}},"openai/gpt-5.5-pro":{"id":"openai/gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180},"canonical_model_id":"openai/gpt-5.5-pro"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-4o-2024-05-13":{"id":"openai/gpt-4o-2024-05-13","name":"GPT-4o (2024-05-13)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-05-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":5,"output":15},"canonical_model_id":"openai/gpt-4o-2024-05-13"},"openai/gpt-4o-mini-2024-07-18":{"id":"openai/gpt-4o-mini-2024-07-18","name":"OpenAI: GPT-4o-mini (2024-07-18)","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075}},"openai/gpt-5.2-codex":{"id":"openai/gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-codex"},"openai/gpt-5.1-codex":{"id":"openai/gpt-5.1-codex","name":"GPT-5.1 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.13},"canonical_model_id":"openai/gpt-5.1-codex"},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-chat-latest":{"id":"openai/gpt-chat-latest","name":"OpenAI: GPT Chat Latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-05-05","last_updated":"2026-05-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5}},"openai/gpt-audio-mini":{"id":"openai/gpt-audio-mini","name":"OpenAI: GPT Audio Mini","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text","audio","pdf"],"output":["text","audio"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.6,"output":2.4}},"openai/gpt-5.6-sol-pro":{"id":"openai/gpt-5.6-sol-pro","name":"GPT-5.6 Sol","description":"GPT-5.6 Sol Pro is the same underlying model as [GPT-5.6 Sol](https://openrouter.ai/openai/gpt-5.6-sol), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"openai/gpt-5.2-pro":{"id":"openai/gpt-5.2-pro","name":"GPT-5.2 Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":21,"output":168},"canonical_model_id":"openai/gpt-5.2-pro"},"openai/o4-mini":{"id":"openai/o4-mini","name":"o4-mini","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.275},"canonical_model_id":"openai/o4-mini"},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3-mini","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"openai/gpt-4":{"id":"openai/gpt-4","name":"GPT-4","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-11","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":8191,"output":4096},"cost":{"input":30,"output":60},"canonical_model_id":"openai/gpt-4"},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1 nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"openai/o1":{"id":"openai/o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":15,"output":60,"cache_read":7.5},"canonical_model_id":"openai/o1"},"openai/gpt-5-pro":{"id":"openai/gpt-5-pro","name":"GPT-5 Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":15,"output":120},"canonical_model_id":"openai/gpt-5-pro"},"openai/gpt-3.5-turbo-instruct":{"id":"openai/gpt-3.5-turbo-instruct","name":"OpenAI: GPT-3.5 Turbo Instruct","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2023-09-28","last_updated":"2023-09-28","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":4095,"output":3685},"cost":{"input":1.5,"output":2}},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"GPT-6.1 Sol is an upgrade to GPT-6 Sol from OpenAI, positioned below the flagship GPT-6 Astra in the GPT-6 series. It is suited for agentic coding, computer use, document-heavy professional...","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-4o-2024-08-06":{"id":"openai/gpt-4o-2024-08-06","name":"GPT-4o (2024-08-06)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-08-06","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-08-06"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's flagship model for demanding end-to-end work. It is suited for advanced analysis, software engineering, deep research, scientific work, and document creation, with particular strengths in long-horizon...","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"openai/gpt-6-astra"},"openai/gpt-5.6-luna-pro":{"id":"openai/gpt-5.6-luna-pro","name":"GPT-5.6 Luna","description":"GPT-5.6 Luna Pro is the same underlying model as [GPT-5.6 Luna](https://openrouter.ai/openai/gpt-5.6-luna), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-5-image-mini":{"id":"openai/gpt-5-image-mini","name":"GPT-5 Image Mini","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-10-16","last_updated":"2025-10-16","modalities":{"input":["pdf","image","text"],"output":["image","text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":2.5,"output":2,"cache_read":0.25},"canonical_model_id":"openai/gpt-5-image-mini"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"openai/o3-pro":{"id":"openai/o3-pro","name":"o3-pro","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-06-10","last_updated":"2025-06-10","modalities":{"input":["text","pdf","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":20,"output":80},"canonical_model_id":"openai/o3-pro"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.018,"output":0.09,"cache_read":0.009},"canonical_model_id":"openai/gpt-oss-20b"},"openai/gpt-oss-safeguard-20b":{"id":"openai/gpt-oss-safeguard-20b","name":"GPT OSS Safeguard 20B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.075,"output":0.3,"cache_read":0.0375},"canonical_model_id":"openai/gpt-oss-safeguard-20b"},"openai/o3-mini-high":{"id":"openai/o3-mini-high","name":"OpenAI: o3 Mini High","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2025-02-12","last_updated":"2025-02-12","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55}},"openai/gpt-3.5-turbo-16k":{"id":"openai/gpt-3.5-turbo-16k","name":"OpenAI: GPT-3.5 Turbo 16k","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2023-08-28","last_updated":"2023-08-28","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"output":4096},"cost":{"input":3,"output":4}},"openai/gpt-5.2-chat":{"id":"openai/gpt-5.2-chat","name":"OpenAI: GPT-5.2 Chat","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2025-12-10","last_updated":"2025-12-10","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"openai/gpt-6-sol-pro":{"id":"openai/gpt-6-sol-pro","name":"OpenAI: GPT-6 Sol Pro","description":"GPT-6 Sol Pro is the same underlying model as [GPT-6 Sol](https://openrouter.ai/openai/gpt-6-sol), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5}},"openai/gpt-5-image":{"id":"openai/gpt-5-image","name":"GPT-5 Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-10-01","release_date":"2025-10-14","last_updated":"2025-10-14","modalities":{"input":["image","text","pdf"],"output":["image","text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":10,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-5-image"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"GPT-5.6 Luna is a fast, cost-efficient model in OpenAI's GPT-5.6 series. It is suited for high-volume, latency-sensitive tasks such as chat, classification, and lightweight agentic workflows, providing capable reasoning for...","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.1-codex-max":{"id":"openai/gpt-5.1-codex-max","name":"GPT-5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex-max"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-4o-2024-11-20":{"id":"openai/gpt-4o-2024-11-20","name":"GPT-4o (2024-11-20)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-11-20","last_updated":"2024-11-20","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-11-20"},"openai/gpt-3.5-turbo-0613":{"id":"openai/gpt-3.5-turbo-0613","name":"OpenAI: GPT-3.5 Turbo (older v0613)","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":4095,"output":3685},"cost":{"input":1,"output":2}},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-5.6-terra-pro":{"id":"openai/gpt-5.6-terra-pro","name":"GPT-5.6 Terra","description":"GPT-5.6 Terra Pro is the same underlying model as [GPT-5.6 Terra](https://openrouter.ai/openai/gpt-5.6-terra), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, positioned below GPT-6 Sol. It is suited for high-volume and latency-sensitive workloads such as chat, classification, and lightweight agentic...","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-6.1-sol-pro":{"id":"openai/gpt-6.1-sol-pro","name":"OpenAI: GPT-6.1 Sol Pro","description":"GPT-6.1 Sol Pro is the same underlying model as [GPT-6.1 Sol](https://openrouter.ai/openai/gpt-6.1-sol), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. **Cost note:** pro mode spends far more...","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5}},"openai/o4-mini-high":{"id":"openai/o4-mini-high","name":"OpenAI: o4 Mini High","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.275}},"openai/gpt-6-luna-pro":{"id":"openai/gpt-6-luna-pro","name":"OpenAI: GPT-6 Luna Pro","description":"GPT-6 Luna Pro is the same underlying model as [GPT-6 Luna](https://openrouter.ai/openai/gpt-6-luna), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125}},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"GPT-5.6 Terra is a balanced model in OpenAI's GPT-5.6 series, positioned between the flagship Sol tier and the cost-efficient Luna tier. It is suited for everyday coding, reasoning, and agentic...","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-4-turbo":{"id":"openai/gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":10,"output":30},"canonical_model_id":"openai/gpt-4-turbo"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.03,"output":0.15,"cache_read":0.015},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-5.1-codex-mini":{"id":"openai/gpt-5.1-codex-mini","name":"GPT-5.1 Codex mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.03},"canonical_model_id":"openai/gpt-5.1-codex-mini"},"openai/o3":{"id":"openai/o3","name":"o3","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"GPT-5.6 Sol is the flagship model in OpenAI's GPT-5.6 series. It is suited for complex reasoning, coding, and agentic workflows, and is particularly strong at command-line and multi-step coding tasks...","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"GPT-6 Sol is the cost-efficient high-end model in OpenAI's GPT-6 series, positioned below the flagship GPT-6 Astra and above the fast GPT-6 Luna tier. It is suited for demanding professional...","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-6-sol"},"openai/o1-pro":{"id":"openai/o1-pro","name":"o1-pro","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":false,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2025-03-19","last_updated":"2025-03-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":150,"output":600},"canonical_model_id":"openai/o1-pro"},"microsoft/phi-4":{"id":"microsoft/phi-4","name":"Microsoft: Phi 4","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","family":"phi","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-01-10","last_updated":"2025-01-10","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":14745},"cost":{"input":0.056,"output":0.112}},"microsoft/wizardlm-2-8x22b":{"id":"microsoft/wizardlm-2-8x22b","name":"WizardLM-2 8x22B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2024-04-16","last_updated":"2024-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":65535,"output":8000},"cost":{"input":0.62,"output":0.62}}}},"venice":{"id":"venice","env":["VENICE_API_KEY"],"npm":"venice-ai-sdk-provider","name":"Venice AI","doc":"https://docs.venice.ai","models":{"qwen-3-8-2-4t-a95b":{"id":"qwen-3-8-2-4t-a95b","name":"Qwen 3.8 2.4T","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":2.5,"output":7.5,"cache_read":0.3125},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"openai-gpt-56-luna":{"id":"openai-gpt-56-luna","name":"GPT-5.6 Luna","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"grok-4-5":{"id":"grok-4-5","name":"Grok 4.5","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-07","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":32000},"cost":{"input":2.27,"output":6.8,"cache_read":0.34,"tiers":[{"input":4.53,"output":13.6,"cache_read":0.68,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4.53,"output":13.6,"cache_read":0.68}},"canonical_model_id":"xai/grok-4.5"},"aion-labs-aion-3-5":{"id":"aion-labs-aion-3-5","name":"Aion 3.5","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":3.75,"output":7.5,"cache_read":0.9375}},"kimi-k3-fast-api":{"id":"kimi-k3-fast-api","name":"Kimi K3 Fast","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":4.5,"output":22.5,"cache_read":0.45},"canonical_model_id":"moonshotai/kimi-k3"},"qwen3-6-27b":{"id":"qwen3-6-27b","name":"Qwen 3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-24","last_updated":"2026-06-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0.325,"output":3.25},"canonical_model_id":"alibaba/qwen3.6-27b"},"hermes-3-llama-3.1-405b":{"id":"hermes-3-llama-3.1-405b","name":"Hermes 3 Llama 3.1 405b","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"hermes","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2025-09-25","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":1.1,"output":3},"canonical_model_id":"nousresearch/hermes-3-llama-3.1-405b"},"claude-opus-5-5-fast":{"id":"claude-opus-5-5-fast","name":"Claude Opus 5.5 Fast","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-26","last_updated":"2026-09-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":8,"output":40,"cache_read":0.4,"cache_write":10},"canonical_model_id":"anthropic/claude-opus-5-5"},"kimi-k2-7-code":{"id":"kimi-k2-7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-13","last_updated":"2026-06-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0.75,"output":3.5,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"google-gemma-3-27b-it":{"id":"google-gemma-3-27b-it","name":"Google Gemma 3 27B Instruct","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-04","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":198000,"output":16384},"cost":{"input":0.12,"output":0.2},"canonical_model_id":"google/gemma-3-27b-it"},"qwen-3-7-max":{"id":"qwen-3-7-max","name":"Qwen 3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-05-22","last_updated":"2026-06-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":2.7,"output":8.05,"cache_read":0.27,"cache_write":3.35},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen-3-8-max":{"id":"qwen-3-8-max","name":"Qwen 3.8 Max","description":"Preview Qwen flagship for million-token multimodal reasoning and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-07-22","last_updated":"2026-07-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2.5,"output":7.5,"cache_read":0.3125,"cache_write":3.125},"canonical_model_id":"alibaba/qwen3.8-max-preview"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-08-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32768},"cost":{"input":0.13,"output":0.26,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"venice-uncensored-role-play":{"id":"venice-uncensored-role-play","name":"Venice Role Play Uncensored","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"venice","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-02-20","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.5,"output":2}},"grok-build-0-1":{"id":"grok-build-0-1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":65536},"cost":{"input":1,"output":2,"cache_read":0.2,"tiers":[{"input":2,"output":4,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2,"output":4,"cache_read":0.4}},"canonical_model_id":"xai/grok-build-0.1"},"qwen3-235b-a22b-instruct-2507":{"id":"qwen3-235b-a22b-instruct-2507","name":"Qwen 3 235B A22B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-29","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.75},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"openai-gpt-6-luna":{"id":"openai-gpt-6-luna","name":"GPT-6 Luna","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":3.75,"output":18.75,"cache_read":0.375},"canonical_model_id":"moonshotai/kimi-k3"},"openai-gpt-54-mini":{"id":"openai-gpt-54-mini","name":"GPT-5.4 Mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-27","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"qwen-3-8-flash":{"id":"qwen-3-8-flash","name":"Qwen 3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.14,"output":0.49,"cache_read":0.014},"canonical_model_id":"alibaba/qwen3.8-flash"},"olafangensan-glm-4.7-flash-heretic":{"id":"olafangensan-glm-4.7-flash-heretic","name":"GLM 4.7 Flash Heretic","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-02-04","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":24000},"cost":{"input":0.07,"output":0.4,"cache_read":0.035}},"xiaomi-mimo-v2-6-flash":{"id":"xiaomi-mimo-v2-6-flash","name":"MiMo-V2.6-Flash","description":"MiMo flash model for fast multimodal assistance and agent workflows","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.175,"output":0.35,"cache_read":0.00375},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"deepseek-v4-flash-0731-fast":{"id":"deepseek-v4-flash-0731-fast","name":"DeepSeek V4 Flash 0731 Fast","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-08-09","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32768},"cost":{"input":0.35,"output":0.7,"cache_read":0.0875},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"claude-opus-4-5":{"id":"claude-opus-4-5","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-12-06","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":198000,"output":32768},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"zai-org-glm-5-2":{"id":"zai-org-glm-5-2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-16","last_updated":"2026-06-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"claude-opus-4-8-fast":{"id":"claude-opus-4-8-fast","name":"Claude Opus 4.8 Fast","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-opus-4-8"},"z-ai-glm-5-turbo":{"id":"z-ai-glm-5-turbo","name":"GLM 5 Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-15","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32768},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5-turbo"},"zai-org-glm-4.6":{"id":"zai-org-glm-4.6","name":"GLM 4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2024-04-01","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":198000,"output":16384},"cost":{"input":0.43,"output":1.75,"cache_read":0.08},"canonical_model_id":"zhipuai/glm-4.6"},"muse-wonder":{"id":"muse-wonder","name":"Muse Wonder","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-10-12","last_updated":"2026-10-15","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":5,"output":25,"cache_read":0.25}},"openai-gpt-54-pro":{"id":"openai-gpt-54-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.4-pro"},"aion-labs-aion-3-0":{"id":"aion-labs-aion-3-0","name":"Aion 3.0","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32768},"cost":{"input":3.75,"output":7.5,"cache_read":0.9375},"canonical_model_id":"aion-labs/aion-3.0"},"claude-sonnet-4-5":{"id":"claude-sonnet-4-5","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-01-15","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":198000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-18","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"kimi-k2-5":{"id":"kimi-k2-5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2024-04","release_date":"2026-01-27","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0.56,"output":3.5,"cache_read":0.22},"canonical_model_id":"moonshotai/kimi-k2.5"},"claude-fable-5-1":{"id":"claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-08-29","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"gemini-3-7-flash":{"id":"gemini-3-7-flash","name":"Gemini 3.7 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.9375,"output":4.6875,"cache_read":0.09375},"canonical_model_id":"google/gemini-3.7-flash"},"grok-4-20":{"id":"grok-4-20","name":"Grok 4.20","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-03-12","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":128000},"cost":{"input":1.42,"output":2.83,"cache_read":0.23,"tiers":[{"input":2.83,"output":5.67,"cache_read":0.45,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.83,"output":5.67,"cache_read":0.45}}},"openai-gpt-56-sol-pro":{"id":"openai-gpt-56-sol-pro","name":"GPT-5.6 Sol Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"seed-2-1-turbo":{"id":"seed-2-1-turbo","name":"Seed 2.1 Turbo","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-28","last_updated":"2026-07-24","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":65536},"cost":{"input":0.625,"output":3.125,"cache_read":0.125},"canonical_model_id":"bytedance-seed/seed-2.1-turbo"},"z-ai-glm-5v-turbo":{"id":"z-ai-glm-5v-turbo","name":"GLM 5V Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32768},"cost":{"input":1.5,"output":5,"cache_read":0.3},"canonical_model_id":"zhipuai/glm-5v-turbo"},"openai-gpt-55-pro":{"id":"openai-gpt-55-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-24","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.5-pro"},"qwen-3-7-plus":{"id":"qwen-3-7-plus","name":"Qwen 3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.5,"output":2,"cache_read":0.05,"cache_write":0.625,"tiers":[{"input":1.5,"output":6,"cache_read":0.15,"cache_write":1.875,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1.5,"output":6,"cache_read":0.15,"cache_write":1.875}},"canonical_model_id":"alibaba/qwen3.7-plus"},"qwen3-235b-a22b-thinking-2507":{"id":"qwen3-235b-a22b-thinking-2507","name":"Qwen 3 235B A22B Thinking 2507","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2025-04-29","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.45,"output":3.5}},"openai-gpt-61-sol":{"id":"openai-gpt-61-sol","name":"GPT-6.1 Sol","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"zai-org-glm-4.7-flash":{"id":"zai-org-glm-4.7-flash","name":"GLM 4.7 Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-29","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.06,"output":0.4,"cache_read":0.01},"canonical_model_id":"zhipuai/glm-4.7-flash"},"openai-gpt-61-sol-ultrafast":{"id":"openai-gpt-61-sol-ultrafast","name":"GPT-6.1 Sol Ultrafast","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-10-08","last_updated":"2026-10-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":12,"output":60,"cache_read":0.6,"cache_write":15,"tiers":[{"input":24,"output":90,"cache_read":1.2,"cache_write":30,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":24,"output":90,"cache_read":1.2,"cache_write":30}}},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-23","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"openai-gpt-6-astra":{"id":"openai-gpt-6-astra","name":"GPT-6 Astra","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-05","last_updated":"2026-09-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"minimax-m27":{"id":"minimax-m27","name":"MiniMax M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":198000,"output":32768},"cost":{"input":0.375,"output":1.5,"cache_read":0.06875},"canonical_model_id":"minimax/MiniMax-M2.7"},"mercury-2-5":{"id":"mercury-2-5","name":"Mercury 2.5","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-08","last_updated":"2026-09-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":260000,"output":65536},"cost":{"input":0.25,"output":0.9375,"cache_read":0.025},"canonical_model_id":"inception/mercury-2.5"},"qwen3-next-80b":{"id":"qwen3-next-80b","name":"Qwen 3 Next 80b","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2025-04-29","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":0.35,"output":1.9}},"minimax-m25":{"id":"minimax-m25","name":"MiniMax M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":198000,"output":32768},"cost":{"input":0.27,"output":0.95,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5"},"qwen3-6-35b-a3b":{"id":"qwen3-6-35b-a3b","name":"Qwen 3.6 35B A3B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-20","last_updated":"2026-07-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0.1,"output":1},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"grok-4-20-multi-agent":{"id":"grok-4-20-multi-agent","name":"Grok 4.20 Multi-Agent","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"release_date":"2026-03-12","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":128000},"cost":{"input":1.42,"output":2.83,"cache_read":0.23,"tiers":[{"input":2.83,"output":5.67,"cache_read":0.45,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.83,"output":5.67,"cache_read":0.45}}},"zai-org-glm-4.7":{"id":"zai-org-glm-4.7","name":"GLM 4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-24","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":198000,"output":16384},"cost":{"input":0.55,"output":2.65,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.7"},"qwen3-5-9b":{"id":"qwen3-5-9b","name":"Qwen 3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-05","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32768},"cost":{"input":0.1,"output":0.15},"canonical_model_id":"alibaba/qwen3.5-9b"},"qwen3-vl-235b-a22b":{"id":"qwen3-vl-235b-a22b","name":"Qwen3 VL 235B","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-01-16","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.21,"output":1.9,"cache_read":0.1}},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-10","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"qwen3-5-35b-a3b":{"id":"qwen3-5-35b-a3b","name":"Qwen 3.5 35B A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-25","last_updated":"2026-06-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":0.15,"output":1,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32768},"cost":{"input":1.65,"output":4.95,"cache_read":0.165},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"openai-gpt-56-terra":{"id":"openai-gpt-56-terra","name":"GPT-5.6 Terra","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"llama-3.3-70b":{"id":"llama-3.3-70b","name":"Llama 3.3 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"release_date":"2025-04-06","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.7,"output":2.8}},"openai-gpt-4o-mini-2024-07-18":{"id":"openai-gpt-4o-mini-2024-07-18","name":"GPT-4o Mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2026-02-28","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"mistral-small-3-2-24b-instruct":{"id":"mistral-small-3-2-24b-instruct","name":"Mistral Small 3.2 24B Instruct","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2026-01-15","last_updated":"2026-06-11","modalities":{"input":["image","text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":0.09375,"output":0.25},"canonical_model_id":"mistral/mistral-small-3.2-24b-instruct"},"inkling":{"id":"inkling","name":"Inkling","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-16","last_updated":"2026-07-17","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":65536},"cost":{"input":1.25,"output":5.0625,"cache_read":0.2125},"canonical_model_id":"thinkingmachines/inkling"},"z-ai-glm-5-3":{"id":"z-ai-glm-5-3","name":"GLM 5.3","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-18","last_updated":"2026-08-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.75,"output":5.5,"cache_read":0.325},"canonical_model_id":"zhipuai/glm-5.3"},"google-gemma-4-26b-a4b-it":{"id":"google-gemma-4-26b-a4b-it","name":"Google Gemma 4 26B A4B Instruct","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-06-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.13,"output":0.4,"cache_read":0.05},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"kimi-k2-6":{"id":"kimi-k2-6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0.75,"output":3.5,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"openai-gpt-6-astra-pro":{"id":"openai-gpt-6-astra-pro","name":"GPT-6 Astra Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-05","last_updated":"2026-09-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}}},"openai-gpt-54":{"id":"openai-gpt-54","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":131072},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"gemma-4-uncensored":{"id":"gemma-4-uncensored","name":"Gemma 4 Uncensored","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-04-13","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.1625,"output":0.5}},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"abliteration-abliterated-model-large-v2":{"id":"abliteration-abliterated-model-large-v2","name":"Abliterated Large V2","description":"Flagship model for demanding analysis, coding, and production agent workflows","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-10-01","last_updated":"2026-10-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":3,"output":5,"cache_read":0.3}},"minimax-m3-preview":{"id":"minimax-m3-preview","name":"MiniMax M3 Preview","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax-m3","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"release_date":"2026-06-12","last_updated":"2026-06-13","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":65536},"cost":{"input":0.3,"output":1.2,"cache_read":0.06}},"openai-gpt-oss-120b":{"id":"openai-gpt-oss-120b","name":"OpenAI GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-11-06","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.07,"output":0.3},"canonical_model_id":"openai/gpt-oss-120b"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-29","last_updated":"2026-07-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"deepseek-v4-1-flash":{"id":"deepseek-v4-1-flash","name":"DeepSeek V4.1 Flash","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.0075},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"gemini-3-8-flash":{"id":"gemini-3-8-flash","name":"Gemini 3.8 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.9375,"output":4.6875,"cache_read":0.09375},"canonical_model_id":"google/gemini-3.8-flash"},"qwen-3-6-plus":{"id":"qwen-3-6-plus","name":"Qwen 3.6 Plus Uncensored","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-06","last_updated":"2026-06-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.625,"output":3.75,"cache_read":0.0625,"cache_write":0.78,"tiers":[{"input":2.5,"output":7.5,"cache_read":0.0625,"cache_write":0.78,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2.5,"output":7.5,"cache_read":0.0625,"cache_write":0.78}},"canonical_model_id":"alibaba/qwen3.6-plus"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"openai-gpt-6-sol":{"id":"openai-gpt-6-sol","name":"GPT-6 Sol","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"qwen-3-8-27b":{"id":"qwen-3-8-27b","name":"Qwen 3.8 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-17","last_updated":"2026-08-18","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.45,"output":3.2},"canonical_model_id":"alibaba/qwen3.8-27b"},"openai-gpt-53-codex":{"id":"openai-gpt-53-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-24","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"aion-labs-aion-3-0-mini":{"id":"aion-labs-aion-3-0-mini","name":"Aion 3.0 Mini","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32768},"cost":{"input":0.875,"output":1.75,"cache_read":0.225},"canonical_model_id":"aion-labs/aion-3.0-mini"},"grok-4-3":{"id":"grok-4-3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-18","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32000},"cost":{"input":1.42,"output":2.83,"cache_read":0.23,"tiers":[{"input":2.83,"output":5.67,"cache_read":0.45,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.83,"output":5.67,"cache_read":0.45}},"canonical_model_id":"xai/grok-4.3"},"aion-labs-aion-3-5-mini":{"id":"aion-labs-aion-3-5-mini","name":"Aion 3.5 Mini","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.875,"output":1.75,"cache_read":0.225}},"openai-gpt-56-terra-pro":{"id":"openai-gpt-56-terra-pro","name":"GPT-5.6 Terra Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"gemini-3-flash-preview":{"id":"gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-19","last_updated":"2026-06-11","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":65536},"cost":{"input":0.7,"output":3.75,"cache_read":0.07},"canonical_model_id":"google/gemini-3-flash-preview"},"mercury-2":{"id":"mercury-2","name":"Mercury 2","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-20","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":50000},"cost":{"input":0.3125,"output":0.9375,"cache_read":0.03125},"canonical_model_id":"inception/mercury-2"},"grok-4-6":{"id":"grok-4-6","name":"Grok 4.6","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-10","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":200000},"cost":{"input":2.27,"output":6.8,"cache_read":0.57,"tiers":[{"input":4.53,"output":13.6,"cache_read":1.13,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4.53,"output":13.6,"cache_read":1.13}},"canonical_model_id":"xai/grok-4.6"},"zai-org-glm-5-1":{"id":"zai-org-glm-5-1","name":"GLM 5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":80000},"cost":{"input":1.54,"output":4.84,"cache_read":0.286},"canonical_model_id":"zhipuai/glm-5.1"},"xiaomi-mimo-v2-5":{"id":"xiaomi-mimo-v2-5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-06-11","last_updated":"2026-06-11","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":0.4,"output":2,"cache_read":0.08},"canonical_model_id":"xiaomi/mimo-v2.5"},"openai-gpt-4o-2024-11-20":{"id":"openai-gpt-4o-2024-11-20","name":"GPT-4o","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2026-02-28","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-11-20"},"openai-gpt-52":{"id":"openai-gpt-52","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-13","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":272000,"output":65536},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"gemini-3-6-flash":{"id":"gemini-3-6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-09","last_updated":"2026-07-21","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.9375,"output":4.6875,"cache_read":0.09375},"canonical_model_id":"google/gemini-3.6-flash"},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"gemini-3-1-pro-preview":{"id":"gemini-3-1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-06-11","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":2.5,"output":15,"cache_read":0.5,"cache_write":0.5,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"cache_write":0.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5,"cache_write":0.5}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32768},"cost":{"input":1.65,"output":3.301,"cache_read":0.33},"canonical_model_id":"deepseek/deepseek-v4-pro"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"claude-opus-5-fast":{"id":"claude-opus-5-fast","name":"Claude Opus 5 Fast","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-23","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-opus-5"},"openai-gpt-55":{"id":"openai-gpt-55","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":131072},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"openai-gpt-56-sol":{"id":"openai-gpt-56-sol","name":"GPT-5.6 Sol","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"qwen3-coder-480b-a35b-instruct-turbo":{"id":"qwen3-coder-480b-a35b-instruct-turbo","name":"Qwen 3 Coder 480B Turbo","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-01-27","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0.35,"output":1.5,"cache_read":0.04}},"z-ai-glm-5-3-flash":{"id":"z-ai-glm-5-3-flash","name":"GLM 5.3 Flash","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-26","last_updated":"2026-09-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"zai-org-glm-5":{"id":"zai-org-glm-5","name":"GLM 5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-11","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":198000,"output":32000},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"grok-4-7":{"id":"grok-4-7","name":"Grok 4.7","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-16","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":200000},"cost":{"input":2.27,"output":6.8,"cache_read":0.57,"tiers":[{"input":4.53,"output":13.6,"cache_read":1.13,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4.53,"output":13.6,"cache_read":1.13}},"canonical_model_id":"xai/grok-4.7"},"deepseek-v3.2":{"id":"deepseek-v3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-04","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":160000,"output":32768},"cost":{"input":0.33,"output":0.48,"cache_read":0.16},"canonical_model_id":"deepseek/deepseek-v3.2"},"gemini-3-5-flash-lite":{"id":"gemini-3-5-flash-lite","name":"Gemini 3.5 Flash-Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-09","last_updated":"2026-07-21","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.375,"output":3.125,"cache_read":0.0375},"canonical_model_id":"google/gemini-3.5-flash-lite"},"hy4-preview":{"id":"hy4-preview","name":"Hy4 Preview","description":"Preview model for early access evaluation, prototyping, and compatibility testing","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-10-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":64000},"cost":{"input":1.0425,"output":3.12625,"cache_read":0.0525},"canonical_model_id":"tencent/hy4-preview"},"gemini-3-5-flash":{"id":"gemini-3-5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-22","last_updated":"2026-06-11","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":1.55,"output":9.45,"cache_read":0.155,"cache_write":0.086},"canonical_model_id":"google/gemini-3.5-flash"},"google-gemma-4-31b-it":{"id":"google-gemma-4-31b-it","name":"Google Gemma 4 31B Instruct","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-03","last_updated":"2026-06-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.12,"output":0.36,"cache_read":0.09},"canonical_model_id":"google/gemma-4-31b-it"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"venice-uncensored-1-2":{"id":"venice-uncensored-1-2","name":"Venice Uncensored 1.2","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"venice","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-04-01","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.2,"output":0.9}},"nvidia-nemotron-3-5-super-vl-120b-a12b":{"id":"nvidia-nemotron-3-5-super-vl-120b-a12b","name":"NVIDIA Nemotron 3.5 Super VL 120B","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-16","last_updated":"2026-10-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.25,"output":1.25,"cache_read":0.125},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"qwen3-5-397b-a17b":{"id":"qwen3-5-397b-a17b","name":"Qwen 3.5 397B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-16","last_updated":"2026-06-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.75,"output":4.5},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"llama-3.2-3b":{"id":"llama-3.2-3b","name":"Llama 3.2 3B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-10-03","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"meta/llama-3.2-3b"},"openai-gpt-56-luna-pro":{"id":"openai-gpt-56-luna-pro","name":"GPT-5.6 Luna Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"nvidia-nemotron-3-ultra-550b-a55b":{"id":"nvidia-nemotron-3-ultra-550b-a55b","name":"NVIDIA Nemotron 3 Ultra","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32768},"cost":{"input":0.625,"output":3.125,"cache_read":0.1875},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"muse-spark-open":{"id":"muse-spark-open","name":"Muse Spark Open","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.5625,"output":5.3125,"cache_read":0.1875},"canonical_model_id":"meta/muse-spark-open"},"gemini-4-argon":{"id":"gemini-4-argon","name":"Gemini 4 Argon","description":"Gemini multimodal model for text, image, audio, video, and document tasks","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-14","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":2.5,"output":12.5,"cache_read":0.125},"canonical_model_id":"google/gemini-4-argon"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash 0423","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32768},"cost":{"input":0.138,"output":0.275,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"nvidia-nemotron-3-nano-30b-a3b":{"id":"nvidia-nemotron-3-nano-30b-a3b","name":"NVIDIA Nemotron 3 Nano 30B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01-27","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.075,"output":0.3},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"}}},"alibaba-token-plan-cn":{"id":"alibaba-token-plan-cn","env":["ALIBABA_TOKEN_PLAN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://token-plan.cn-beijing.maas.aliyuncs.com/compatible-mode/v1","name":"Alibaba Token Plan (China)","doc":"https://www.alibabacloud.com/help/zh/model-studio/token-plan-overview","models":{"happyhorse-1.1-r2v":{"id":"happyhorse-1.1-r2v","name":"HappyHorse 1.1 Reference-to-Video","description":"Video model for reference-guided video generation","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-07-17","last_updated":"2026-07-17","modalities":{"input":["image","text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":0,"output":0}},"qwen3.7-max":{"id":"qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.7-max"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.8-max"},"happyhorse-1.1-t2v":{"id":"happyhorse-1.1-t2v","name":"HappyHorse 1.1 Text-to-Video","description":"Video model for prompt-driven text-to-video generation","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-07-17","last_updated":"2026-07-17","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":0,"output":0}},"qwen-image-2.0":{"id":"qwen-image-2.0","name":"Qwen Image 2.0","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":8192,"output":0},"cost":{"input":0,"output":0}},"glm-5":{"id":"glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":16384},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"qwen3.8-max-preview":{"id":"qwen3.8-max-preview","name":"Qwen3.8 Max Preview","description":"Preview Qwen flagship for million-token multimodal reasoning and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-19","last_updated":"2026-07-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.8-max-preview"},"qwen-image-2.0-pro":{"id":"qwen-image-2.0-pro","name":"Qwen Image 2.0 Pro","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":8192,"output":0},"cost":{"input":0,"output":0}},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.6"},"wan2.7-image":{"id":"wan2.7-image","name":"Wan2.7 Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":8192,"output":0},"cost":{"input":0,"output":0}},"wan2.7-image-pro":{"id":"wan2.7-image-pro","name":"Wan2.7 Image Pro","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":8192,"output":0},"cost":{"input":0,"output":0}},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.5"},"happyhorse-1.1-i2v":{"id":"happyhorse-1.1-i2v","name":"HappyHorse 1.1 Image-to-Video","description":"Video model for image-to-video generation","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-07-17","last_updated":"2026-07-17","modalities":{"input":["image","text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":0,"output":0}},"qwen3.6-flash":{"id":"qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":131072}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.6-flash"},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"MiniMax-M2.5":{"id":"MiniMax-M2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"input":196601,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"minimax/MiniMax-M2.5"},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.8-flash"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.1"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4-pro"},"qwen3.6-plus":{"id":"qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":131072}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.6-plus"},"deepseek-v3.2":{"id":"deepseek-v3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-03","last_updated":"2025-12-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0,"output":0}},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.7-plus"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4-flash"}}},"ai21":{"id":"ai21","env":["AI21_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.ai21.com/studio/v1","name":"AI21 Labs","doc":"https://docs.ai21.com/docs/jamba-foundation-models","models":{"jamba-large":{"id":"jamba-large","name":"Jamba Large","description":"AI21's hybrid SSM-Transformer long-context model for enterprise agents and grounded generation","family":"jamba","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08-22","release_date":"2025-07-01","last_updated":"2025-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":4096},"cost":{"input":2,"output":8},"canonical_model_id":"ai21/jamba-large"},"jamba-mini":{"id":"jamba-mini","name":"Jamba Mini","description":"AI21's efficient, lightweight hybrid SSM-Transformer model for a wide range of tasks","family":"jamba","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08-22","release_date":"2026-01-01","last_updated":"2026-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":4096},"cost":{"input":0.2,"output":0.4},"canonical_model_id":"ai21/jamba-mini"}}},"commandcode":{"id":"commandcode","env":["CMD_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.commandcode.ai/provider/v1","name":"CommandCode","doc":"https://commandcode.ai/docs/provider","models":{"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"cache_write":0},"canonical_model_id":"openai/gpt-5.4"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":2,"output":8,"cache_read":0.5,"cache_write":0},"canonical_model_id":"openai/gpt-5.3-codex"},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"claude-fable-5-1":{"id":"claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075,"cache_write":0},"canonical_model_id":"openai/gpt-5.4-mini"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":0},"canonical_model_id":"openai/gpt-5.5"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"claude-haiku-4-5-20251001":{"id":"claude-haiku-4-5-20251001","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":45,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1,"cache_write":12.5}},"canonical_model_id":"openai/gpt-5.6-sol"},"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-flash-vision-exp":{"id":"deepseek/deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"deepseek/deepseek-v4.1-flash-fast":{"id":"deepseek/deepseek-v4.1-flash-fast","name":"DeepSeek V4.1 Flash Fast","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.16,"output":0.58,"cache_read":0.016},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.66,"output":1.98,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v4-flash-fast":{"id":"deepseek/deepseek-v4-flash-fast","name":"DeepSeek V4 Flash Fast","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.28,"output":0.56,"cache_read":0.07},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4-flash"},"tencent/hy3-paid":{"id":"tencent/hy3-paid","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":192000,"output":128000},"cost":{"input":0.14,"output":0.58,"cache_read":0.035},"canonical_model_id":"tencent/hy3"},"tencent/hy4-preview":{"id":"tencent/hy4-preview","name":"Hy4 preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":64000},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-5.3-flashx":{"id":"z-ai/glm-5.3-flashx","name":"GLM-5.3-FlashX","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.37,"output":1.25,"cache_read":0.075},"canonical_model_id":"zhipuai/glm-5.3-flash"},"thinkingmachines/inkling-small":{"id":"thinkingmachines/inkling-small","name":"Inkling Small","description":"Multimodal MoE reasoning model (276B total, 12B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":1000000},"cost":{"input":0.5,"output":1.2,"cache_read":0.1},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/inkling":{"id":"thinkingmachines/inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":4.05,"cache_read":0.17},"canonical_model_id":"thinkingmachines/inkling"},"meta/muse-spark-1.3":{"id":"meta/muse-spark-1.3","name":"Muse Spark 1.3","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.3"},"meta/muse-spark-1.1":{"id":"meta/muse-spark-1.1","name":"Muse Spark 1.1","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.1"},"meta/muse-spark-1.2":{"id":"meta/muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"meta/muse-spark-1.2-contributor":{"id":"meta/muse-spark-1.2-contributor","name":"Muse Spark 1.2 (Contributor)","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.1,"output":0.2,"cache_read":0.002},"canonical_model_id":"meta/muse-spark-1.2"},"meta/muse-wonder-1.0":{"id":"meta/muse-wonder-1.0","name":"Muse Wonder","description":"Muse Wonder is a frontier multimodal reasoning model from Meta for personal and professional agents, long-horizon coding, and computer use. It combines Active Memory, which carries relevant context across conversations, with Active Focus, which keeps it working through blockers toward a goal.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":4,"output":20,"cache_read":0.2},"canonical_model_id":"meta/muse-wonder-1.0"},"meta/muse-spark-1.3-contributor":{"id":"meta/muse-spark-1.3-contributor","name":"Muse Spark 1.3 (Contributor)","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.1,"output":0.2,"cache_read":0.002},"canonical_model_id":"meta/muse-spark-1.3"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"google/gemini-3.6-flash"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"cache_read":0.15,"cache_write":0.08334},"canonical_model_id":"google/gemini-3.7-flash"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-4-argon":{"id":"google/gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":2,"output":10,"cache_read":0.1},"canonical_model_id":"google/gemini-4-argon"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.1-flash-lite"},"Qwen/Qwen3.8-27B":{"id":"Qwen/Qwen3.8-27B","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.4,"output":3,"cache_read":0.04},"canonical_model_id":"alibaba/qwen3.8-27b"},"Qwen/Qwen3.8-Max":{"id":"Qwen/Qwen3.8-Max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"Qwen/Qwen3.8-Max-0902":{"id":"Qwen/Qwen3.8-Max-0902","name":"Qwen3.8 Max 0902","description":"2026-09-02 upgraded snapshot of Qwen3.8 Max with stronger coding, collaborative agents, and multimodal document understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-max-0902"},"Qwen/Qwen3.8-Flash":{"id":"Qwen/Qwen3.8-Flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.16,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-flash"},"Qwen/Qwen3.8-Omni-Flash":{"id":"Qwen/Qwen3.8-Omni-Flash","name":"Qwen3.8 Omni Flash","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-omni-flash"},"xai/grok-4.7":{"id":"xai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"xai/grok-4.5":{"id":"xai/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.5"},"xai/grok-4.6":{"id":"xai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"MiniMaxAI/MiniMax-M3":{"id":"MiniMaxAI/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":512000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"MiniMaxAI/MiniMax-M2.5":{"id":"MiniMaxAI/MiniMax-M2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5"},"MiniMaxAI/MiniMax-M2.7":{"id":"MiniMaxAI/MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7"},"sakana/fugu-ultra":{"id":"sakana/fugu-ultra","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"sakana/fugu-ultra"},"inclusionai/ling-3.1-flash:free":{"id":"inclusionai/ling-3.1-flash:free","name":"Ling 3.1 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"inclusionai/ling-3.1-flash"},"moonshotai/Kimi-K2.7-Code-Highspeed":{"id":"moonshotai/Kimi-K2.7-Code-Highspeed","name":"Kimi K2.7 Code Highspeed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"moonshotai/Kimi-K3":{"id":"moonshotai/Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/Kimi-K2.7-Code":{"id":"moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-5.2-Fast":{"id":"zai-org/GLM-5.2-Fast","name":"GLM-5.2-Fast","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":3,"output":10.25,"cache_read":0.5},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-5.3":{"id":"zai-org/GLM-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"nvidia/nemotron-3-ultra-550b-a55b":{"id":"nvidia/nemotron-3-ultra-550b-a55b","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.6,"output":2.4,"cache_read":0.12},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"stepfun/Step-3.7-Flash":{"id":"stepfun/Step-3.7-Flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"stepfun/Step-5-Preview":{"id":"stepfun/Step-5-Preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":1000000},"cost":{"input":1,"output":2.7,"cache_read":0.05},"canonical_model_id":"stepfun/step-5-preview"},"stepfun/Step-3.5-Flash":{"id":"stepfun/Step-3.5-Flash","name":"Step 3.5 Flash","description":"StepFun flash lane for quick multimodal reasoning and coding assistance","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.09,"output":0.3,"cache_read":0.02},"canonical_model_id":"stepfun/step-3.5-flash"},"mistral/mistral-large-4":{"id":"mistral/mistral-large-4","name":"Mistral Large 4","description":"Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":262144},"cost":{"input":1.36,"output":4.18,"cache_read":0.14},"canonical_model_id":"mistral/mistral-large-4"}}},"lowrouter":{"id":"lowrouter","env":["LOWROUTER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.lowrouter.ai/v1","name":"LowRouter","doc":"https://lowrouter.ai/docs/models/available","models":{"auto/mistralai/ministral-8b-2512":{"id":"auto/mistralai/ministral-8b-2512","name":"Ministral 3 8B","description":"Compact open vision-language model for edge deployment, instruction following, and tool use","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.1569,"output":0.1569,"cache_read":0.0157},"canonical_model_id":"mistral/ministral-3-8b-instruct-2512"},"auto/mistralai/mistral-large-4":{"id":"auto/mistralai/mistral-large-4","name":"Mistral Large 4","description":"Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":262144},"status":"beta","cost":{"input":0.7112,"output":2.1859,"cache_read":0.0732},"canonical_model_id":"mistral/mistral-large-4"},"auto/mistralai/mistral-medium-3.5":{"id":"auto/mistralai/mistral-medium-3.5","name":"Mistral Medium 3.5","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.5688,"output":7.8442,"cache_read":0.1569},"canonical_model_id":"mistral/mistral-medium-2604"},"auto/mistralai/mistral-small-2603":{"id":"auto/mistralai/mistral-small-2603","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.1569,"output":0.6275,"cache_read":0.0157},"canonical_model_id":"mistral/mistral-small-2603"},"auto/mistralai/mistral-large-2512":{"id":"auto/mistralai/mistral-large-2512","name":"Mistral Large 3","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5229,"output":1.5688,"cache_read":0.0523},"canonical_model_id":"mistral/mistral-large-2512"},"auto/mistralai/ministral-14b-2512":{"id":"auto/mistralai/ministral-14b-2512","name":"Ministral 3 14B","description":"Open vision-language model for efficient local deployment, instruction following, and tool use","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.2092,"output":0.2092,"cache_read":0.0209},"canonical_model_id":"mistral/ministral-3-14b-instruct-2512"},"auto/mistralai/ministral-3b-2512":{"id":"auto/mistralai/ministral-3b-2512","name":"Ministral 3 3B","description":"Compact open vision-language model for edge deployment, instruction following, and tool use","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.1046,"output":0.1046,"cache_read":0.0105},"canonical_model_id":"mistral/ministral-3-3b-instruct-2512"},"auto/mistralai/codestral-2508":{"id":"auto/mistralai/codestral-2508","name":"Codestral 25.08","description":"Mistral code model for low-latency completion, fill-in-the-middle, and code generation","family":"codestral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.3138,"output":0.9413,"cache_read":0.0314},"canonical_model_id":"mistral/codestral-2508"},"auto/openai/gpt-5.4":{"id":"auto/openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"auto/openai/gpt-oss-safeguard-120b":{"id":"auto/openai/gpt-oss-safeguard-120b","name":"GPT OSS Safeguard 120B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.18,"output":0.73},"canonical_model_id":"openai/gpt-oss-safeguard-120b"},"auto/openai/gpt-4o":{"id":"auto/openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"auto/openai/gpt-5-mini":{"id":"auto/openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"auto/openai/gpt-5-nano":{"id":"auto/openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"auto/openai/gpt-6.1-sol":{"id":"auto/openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"auto/openai/gpt-6-astra":{"id":"auto/openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"auto/openai/gpt-4o-mini":{"id":"auto/openai/gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"auto/openai/gpt-oss-20b":{"id":"auto/openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.113,"output":0.4745},"canonical_model_id":"openai/gpt-oss-20b"},"auto/openai/gpt-oss-safeguard-20b":{"id":"auto/openai/gpt-oss-safeguard-20b","name":"GPT OSS Safeguard 20B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.08,"output":0.24},"canonical_model_id":"openai/gpt-oss-safeguard-20b"},"auto/openai/gpt-5.4-mini":{"id":"auto/openai/gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"auto/openai/gpt-5.6-luna":{"id":"auto/openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"auto/openai/gpt-5.2":{"id":"auto/openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"auto/openai/gpt-5.5":{"id":"auto/openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"auto/openai/gpt-4.1":{"id":"auto/openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"auto/openai/gpt-4.1-mini":{"id":"auto/openai/gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"auto/openai/gpt-6-luna":{"id":"auto/openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"auto/openai/gpt-5.6-terra":{"id":"auto/openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"auto/openai/gpt-oss-120b":{"id":"auto/openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.1695,"output":0.6779},"canonical_model_id":"openai/gpt-oss-120b"},"auto/openai/o3":{"id":"auto/openai/o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"auto/openai/gpt-5":{"id":"auto/openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"auto/openai/gpt-5.6-sol":{"id":"auto/openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"auto/openai/gpt-6-sol":{"id":"auto/openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"}}},"reflection":{"id":"reflection","env":["REFLECTION_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.reflection.ai/openai/v1","name":"Reflection","doc":"https://developers.reflection.ai/models","models":{"Beam-1.0-501B-A23B":{"id":"Beam-1.0-501B-A23B","name":"Beam 1.0 501B A23B","description":"Sparse mixture-of-experts reasoning model with 23B active parameters for coding and agentic workflows","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-06-30","release_date":"2026-10-05","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"reflection/beam-1.0-501b-a23b"}}},"inference":{"id":"inference","env":["INFERENCE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://inference.net/v1","name":"Inference","doc":"https://inference.net/models","models":{"meta/llama-3.1-8b-instruct":{"id":"meta/llama-3.1-8b-instruct","name":"Llama 3.1 8B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16000,"output":4096},"cost":{"input":0.025,"output":0.025}},"meta/llama-3.2-11b-vision-instruct":{"id":"meta/llama-3.2-11b-vision-instruct","name":"Llama 3.2 11B Vision Instruct","description":"Open Llama multimodal model for image understanding and text reasoning","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":16000,"output":4096},"cost":{"input":0.055,"output":0.055}},"meta/llama-3.2-1b-instruct":{"id":"meta/llama-3.2-1b-instruct","name":"Llama 3.2 1B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16000,"output":4096},"cost":{"input":0.01,"output":0.01}},"meta/llama-3.2-3b-instruct":{"id":"meta/llama-3.2-3b-instruct","name":"Llama 3.2 3B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16000,"output":4096},"cost":{"input":0.02,"output":0.02}},"google/gemma-3":{"id":"google/gemma-3","name":"Google Gemma 3","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":125000,"output":4096},"cost":{"input":0.15,"output":0.3}},"osmosis/osmosis-structure-0.6b":{"id":"osmosis/osmosis-structure-0.6b","name":"Osmosis Structure 0.6B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","family":"osmosis","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4000,"output":2048},"cost":{"input":0.1,"output":0.5}},"mistral/mistral-nemo-12b-instruct":{"id":"mistral/mistral-nemo-12b-instruct","name":"Mistral Nemo 12B Instruct","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16000,"output":4096},"cost":{"input":0.038,"output":0.1}},"qwen/qwen3-embedding-4b":{"id":"qwen/qwen3-embedding-4b","name":"Qwen 3 Embedding 4B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2024-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":2048},"cost":{"input":0.01,"output":0}},"qwen/qwen-2.5-7b-vision-instruct":{"id":"qwen/qwen-2.5-7b-vision-instruct","name":"Qwen 2.5 7B Vision Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":125000,"output":4096},"cost":{"input":0.2,"output":0.2}}}},"iflowcn":{"id":"iflowcn","env":["IFLOW_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://apis.iflow.cn/v1","name":"iFlow","doc":"https://platform.iflow.cn/en/docs","models":{"qwen3-vl-plus":{"id":"qwen3-vl-plus","name":"Qwen3-VL-Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0,"output":0}},"glm-4.6":{"id":"glm-4.6","name":"GLM-4.6","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-01","last_updated":"2025-11-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":0,"output":0}},"qwen3-32b":{"id":"qwen3-32b","name":"Qwen3-32B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-01","last_updated":"2024-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"cost":{"input":0,"output":0}},"qwen3-max":{"id":"qwen3-max","name":"Qwen3-Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0,"output":0}},"deepseek-v3":{"id":"deepseek-v3","name":"DeepSeek-V3","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-26","last_updated":"2024-12-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"cost":{"input":0,"output":0}},"qwen3-235b-a22b-thinking-2507":{"id":"qwen3-235b-a22b-thinking-2507","name":"Qwen3-235B-A22B-Thinking","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-01","last_updated":"2025-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0,"output":0}},"qwen3-max-preview":{"id":"qwen3-max-preview","name":"Qwen3-Max-Preview","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0,"output":0}},"qwen3-coder-plus":{"id":"qwen3-coder-plus","name":"Qwen3-Coder-Plus","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-01","last_updated":"2025-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0,"output":0}},"qwen3-235b-a22b-instruct":{"id":"qwen3-235b-a22b-instruct","name":"Qwen3-235B-A22B-Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-01","last_updated":"2025-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0,"output":0}},"kimi-k2-0905":{"id":"kimi-k2-0905","name":"Kimi-K2-0905","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":0,"output":0}},"kimi-k2":{"id":"kimi-k2","name":"Kimi-K2","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-01","last_updated":"2024-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"cost":{"input":0,"output":0}},"qwen3-235b":{"id":"qwen3-235b","name":"Qwen3-235B-A22B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-01","last_updated":"2024-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"cost":{"input":0,"output":0}},"deepseek-r1":{"id":"deepseek-r1","name":"DeepSeek-R1","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-01-20","last_updated":"2025-01-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"cost":{"input":0,"output":0}},"deepseek-v3.2":{"id":"deepseek-v3.2","name":"DeepSeek-V3.2-Exp","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":64000},"cost":{"input":0,"output":0}}}},"minimax-cn-coding-plan":{"id":"minimax-cn-coding-plan","env":["MINIMAX_API_KEY"],"npm":"@ai-sdk/anthropic","api":"https://api.minimax.cn/anthropic/v1","name":"MiniMax Token Plan (minimax.cn)","doc":"https://platform.minimaxi.com/docs/token-plan/intro","models":{"MiniMax-M3":{"id":"MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-25","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"MiniMax-M2.1":{"id":"MiniMax-M2.1","name":"MiniMax-M2.1","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"MiniMax-M3.1-Flash-Preview":{"id":"MiniMax-M3.1-Flash-Preview","name":"MiniMax-M3.1-Flash-Preview","description":"Frontier multimodal coding model with 1M context window and tunable thinking depth","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-27","last_updated":"2026-09-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":512000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"minimax/MiniMax-M3.1-Flash-Preview"},"MiniMax-M2.5":{"id":"MiniMax-M2.5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"MiniMax-M2.7":{"id":"MiniMax-M2.7","name":"MiniMax-M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"MiniMax-M2.7-highspeed":{"id":"MiniMax-M2.7-highspeed","name":"MiniMax-M2.7-highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"MiniMax-M2":{"id":"MiniMax-M2","name":"MiniMax-M2","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0}},"MiniMax-M2.5-highspeed":{"id":"MiniMax-M2.5-highspeed","name":"MiniMax-M2.5-highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-13","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}}}},"thinkingmachines":{"id":"thinkingmachines","env":["TINKER_API_KEY"],"npm":"@ai-sdk/anthropic","api":"https://tinker.thinkingmachines.dev/services/tinker-prod/anthropic/api/v1","name":"Thinking Machines","doc":"https://tinker-docs.thinkingmachines.ai/tinker/compatible-apis/anthropic/","models":{"thinkingmachines/Inkling:peft:262144":{"id":"thinkingmachines/Inkling:peft:262144","name":"Inkling (256K)","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":3.74,"output":9.36,"cache_read":0.748},"canonical_model_id":"thinkingmachines/inkling"},"thinkingmachines/Inkling":{"id":"thinkingmachines/Inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":1.87,"output":4.68,"cache_read":0.374},"canonical_model_id":"thinkingmachines/inkling"}}},"stepfun-step-plan":{"id":"stepfun-step-plan","env":["STEPFUN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.stepfun.com/step_plan/v1","name":"StepFun Step Plan (China)","doc":"https://platform.stepfun.com/docs/zh/step-plan/integrations/reasoning-api","models":{"step-5-preview":{"id":"step-5-preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":65536},"canonical_model_id":"stepfun/step-5-preview"},"step-router-v1":{"id":"step-router-v1","name":"Step Router v1","description":"StepFun routing model that dispatches requests to the appropriate Step model.","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":256000}},"step-3.5-flash-2603":{"id":"step-3.5-flash-2603","name":"Step 3.5 Flash 2603","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"canonical_model_id":"stepfun/step-3.5-flash-2603"},"step-3.5-flash":{"id":"step-3.5-flash","name":"Step 3.5 Flash","description":"StepFun flash lane for quick multimodal reasoning and coding assistance","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"canonical_model_id":"stepfun/step-3.5-flash"},"step-3.7-flash":{"id":"step-3.7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"canonical_model_id":"stepfun/step-3.7-flash"}}},"melious":{"id":"melious","env":["MELIOUS_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.melious.ai/v1","name":"Melious","doc":"https://melious.ai/docs/reference/models","models":{"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.11592,"output":0.46368,"cache_read":0.023184},"canonical_model_id":"zhipuai/glm-5.3-flash"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.11592,"output":0.2898,"cache_read":0.023184},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":3.1878,"output":15.939,"cache_read":0.788256},"canonical_model_id":"moonshotai/kimi-k3"},"glm-5":{"id":"glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":203000,"output":131072},"cost":{"input":1.10124,"output":3.36168,"cache_read":0.266616},"canonical_model_id":"zhipuai/glm-5"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.23184,"output":1.1592,"cache_read":0.011592},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.81144,"output":4.0572,"cache_read":0.266616},"canonical_model_id":"moonshotai/kimi-k2.6"},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.5796,"output":2.95596,"cache_read":0.139104},"canonical_model_id":"moonshotai/kimi-k2.5"},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":203000,"output":131072},"cost":{"input":1.50696,"output":4.6368,"cache_read":0.370944},"canonical_model_id":"zhipuai/glm-5.1"},"deepseek-r1-0528":{"id":"deepseek-r1-0528","name":"DeepSeek-R1","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":32768},"cost":{"input":0.69552,"output":2.78208,"cache_read":0.185472},"canonical_model_id":"deepseek/deepseek-r1"},"deepseek-v3.2":{"id":"deepseek-v3.2","name":"DeepSeek V3.2","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":64000},"cost":{"input":0.34776,"output":0.5796,"cache_read":0.092736},"canonical_model_id":"deepseek/deepseek-v3.2"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.1592,"output":3.4776,"cache_read":0.23184},"canonical_model_id":"zhipuai/glm-5.3"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.81144,"output":3.4776,"cache_read":0.220248},"canonical_model_id":"moonshotai/kimi-k2.7-code"}}},"berget":{"id":"berget","env":["BERGET_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.berget.ai/v1","name":"Berget.AI","doc":"https://api.berget.ai","models":{"google/gemma-4-31B-it":{"id":"google/gemma-4-31B-it","name":"Gemma 4 31B Instruct","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["audio","image","text","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.275,"output":0.55}},"Qwen/Qwen3.8-27B-FP8":{"id":"Qwen/Qwen3.8-27B-FP8","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.46,"output":3.48},"canonical_model_id":"alibaba/qwen3.8-27b"},"mistralai/Mistral-Small-3.2-24B-Instruct-2506":{"id":"mistralai/Mistral-Small-3.2-24B-Instruct-2506","name":"Mistral Small 3.2 24B Instruct 2506","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-10-01","last_updated":"2025-10-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":8192},"cost":{"input":0.33,"output":0.33}},"moonshotai/Kimi-K3":{"id":"moonshotai/Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-27","last_updated":"2026-07-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":327680,"output":32768},"cost":{"input":3,"output":15},"canonical_model_id":"moonshotai/kimi-k3"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":32768},"cost":{"input":1.54,"output":4.84},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-5.3-Flash":{"id":"zai-org/GLM-5.3-Flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-09-30","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":16384},"cost":{"input":0.29,"output":0.58},"canonical_model_id":"zhipuai/glm-5.3-flash"}}},"snowflake-cortex":{"id":"snowflake-cortex","env":["SNOWFLAKE_ACCOUNT","SNOWFLAKE_CORTEX_PAT"],"npm":"@ai-sdk/openai-compatible","api":"https://${SNOWFLAKE_ACCOUNT}.snowflakecomputing.com/api/v2/cortex/v1","name":"Snowflake Cortex","doc":"https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-rest-api","models":{"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":16384},"canonical_model_id":"anthropic/claude-haiku-4-5"},"openai-gpt-5.5":{"id":"openai-gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"status":"beta","canonical_model_id":"openai/gpt-5.5"},"claude-opus-4-5":{"id":"claude-opus-4-5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"canonical_model_id":"anthropic/claude-opus-4-5"},"claude-sonnet-4-5":{"id":"claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":16384},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"openai-gpt-5-nano":{"id":"openai-gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":272000,"input":272000,"output":8192},"status":"beta","canonical_model_id":"openai/gpt-5-nano"},"openai-gpt-5":{"id":"openai-gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":272000,"input":272000,"output":8192},"status":"beta","canonical_model_id":"openai/gpt-5"},"openai-gpt-4.1":{"id":"openai-gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000},"canonical_model_id":"openai/gpt-4.1"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"canonical_model_id":"anthropic/claude-opus-5"},"mistral-large2":{"id":"mistral-large2","name":"Mistral Large (latest)","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2024-11-01","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"canonical_model_id":"mistral/mistral-large-latest"},"openai-gpt-5.2":{"id":"openai-gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"canonical_model_id":"openai/gpt-5.2"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"canonical_model_id":"anthropic/claude-fable-5"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"canonical_model_id":"anthropic/claude-opus-4-8"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"canonical_model_id":"anthropic/claude-sonnet-5"},"openai-gpt-5.6-luna":{"id":"openai-gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"status":"beta","canonical_model_id":"openai/gpt-5.6-luna"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"canonical_model_id":"anthropic/claude-opus-4-6"},"openai-gpt-5.6-sol":{"id":"openai-gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"status":"beta","canonical_model_id":"openai/gpt-5.6-sol"},"openai-gpt-5-mini":{"id":"openai-gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":272000,"input":272000,"output":8192},"status":"beta","canonical_model_id":"openai/gpt-5-mini"},"deepseek-r1":{"id":"deepseek-r1","name":"DeepSeek-R1","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"canonical_model_id":"deepseek/deepseek-r1"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":16384},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"openai-gpt-5.1":{"id":"openai-gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":272000,"input":272000,"output":8192},"canonical_model_id":"openai/gpt-5.1"},"snowflake-llama3.3-70b":{"id":"snowflake-llama3.3-70b","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"openai-gpt-5.6-terra":{"id":"openai-gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"status":"beta","canonical_model_id":"openai/gpt-5.6-terra"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"status":"beta","experimental":{"modes":{"fast":{"cost":{"input":30,"output":150,"cache_read":3,"cache_write":37.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"canonical_model_id":"anthropic/claude-opus-4-7"},"gemini-3.1-pro":{"id":"gemini-3.1-pro","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"canonical_model_id":"google/gemini-3.1-pro-preview"},"openai-gpt-5.4":{"id":"openai-gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"status":"beta","experimental":{"modes":{"fast":{"cost":{"input":5,"output":30,"cache_read":0.5},"provider":{"body":{"service_tier":"priority"}}}}},"canonical_model_id":"openai/gpt-5.4"}}},"sarvam":{"id":"sarvam","env":["SARVAM_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.sarvam.ai/v1","name":"Sarvam AI","doc":"https://docs.sarvam.ai/api-reference-docs/getting-started/models","models":{"sarvam-30b":{"id":"sarvam-30b","name":"Sarvam-30B","description":"Efficient Indian-language reasoning model for chat, coding, and multilingual work","family":"sarvam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":[null,"low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-18","last_updated":"2026-03-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536}},"sarvam-105b":{"id":"sarvam-105b","name":"Sarvam-105B","description":"Flagship Indian-language reasoning model for enterprise multilingual applications","family":"sarvam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":[null,"low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-18","last_updated":"2026-03-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072}}}},"nova":{"id":"nova","env":["NOVA_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.nova.amazon.com/v1","name":"Nova","doc":"https://nova.amazon.com/dev/documentation","models":{"nova-2-pro-v1":{"id":"nova-2-pro-v1","name":"Nova 2 Pro","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-12-03","last_updated":"2026-01-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0,"output":0,"reasoning":0}},"nova-2-lite-v1":{"id":"nova-2-lite-v1","name":"Nova 2 Lite","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0,"output":0,"reasoning":0}}}},"abacus":{"id":"abacus","env":["ABACUS_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://routellm.abacus.ai/v1","name":"Abacus","doc":"https://abacus.ai/help/api","models":{"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.4"},"grok-4-1-fast-non-reasoning":{"id":"grok-4-1-fast-non-reasoning","name":"Grok 4.1 Fast (Non-Reasoning)","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-11-17","last_updated":"2025-11-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":16384},"cost":{"input":0.2,"output":0.5}},"qwen3.7-max":{"id":"qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":2.5,"output":7.5},"canonical_model_id":"alibaba/qwen3.7-max"},"gemini-3.1-flash-image-preview":{"id":"gemini-3.1-flash-image-preview","name":"Nano Banana 2 Preview","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-26","last_updated":"2026-02-26","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":1048576,"output":32768},"cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3.1-flash-image-preview"},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"gpt-5.2-codex":{"id":"gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Code-specialist GPT for repository edits, reviews, and long-running software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-codex"},"gpt-5.1-codex":{"id":"gpt-5.1-codex","name":"GPT-5.1 Codex","description":"Codex GPT for repository edits, code review, and practical software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex"},"gemini-2.5-flash-image":{"id":"gemini-2.5-flash-image","name":"Nano Banana","description":"Nano Banana image model for fast generation, edits, and character-consistent assets","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.3,"output":30},"canonical_model_id":"google/gemini-2.5-flash-image"},"gpt-4o":{"id":"gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6},"canonical_model_id":"alibaba/qwen3.8-max"},"gpt-5-codex":{"id":"gpt-5-codex","name":"GPT-5-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5-codex"},"gpt-5-mini":{"id":"gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"claude-3-7-sonnet-20250219":{"id":"claude-3-7-sonnet-20250219","name":"Claude Sonnet 3.7","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-10-31","release_date":"2025-02-19","last_updated":"2025-02-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15}},"qwen-2.5-coder-32b":{"id":"qwen-2.5-coder-32b","name":"Qwen 2.5 Coder 32B","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-11-11","last_updated":"2024-11-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.79,"output":0.79}},"o4-mini":{"id":"o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4},"canonical_model_id":"openai/o4-mini"},"o3-mini":{"id":"o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.18},"canonical_model_id":"openai/gpt-5.3-codex"},"gpt-4.1-nano":{"id":"gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"muse-spark-1.1":{"id":"muse-spark-1.1","name":"Muse Spark 1.1","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32000},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.1"},"gpt-5-nano":{"id":"gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"gpt-5.2-chat-latest":{"id":"gpt-5.2-chat-latest","name":"GPT-5.2 Chat Latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2026-01-01","last_updated":"2026-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.75,"output":14}},"gpt-5.1-chat-latest":{"id":"gpt-5.1-chat-latest","name":"GPT-5.1 Chat Latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.25,"output":10}},"qwen3-max":{"id":"qwen3-max","name":"Qwen3 Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"cost":{"input":1.2,"output":6}},"claude-opus-4-20250514":{"id":"claude-opus-4-20250514","name":"Claude Opus 4","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-05-14","last_updated":"2025-05-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75}},"gemini-3.6-flash":{"id":"gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"google/gemini-3.6-flash"},"kimi-k2-turbo-preview":{"id":"kimi-k2-turbo-preview","name":"Kimi K2 Turbo Preview","description":"Fast Kimi model for responsive chat, coding help, and agent loops","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-08","last_updated":"2025-07-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":8192},"cost":{"input":0.15,"output":8}},"grok-4.3":{"id":"grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":1.25,"output":2.5,"cache_read":0.2},"canonical_model_id":"xai/grok-4.3"},"grok-4-fast-non-reasoning":{"id":"grok-4-fast-non-reasoning","name":"Grok 4 Fast (Non-Reasoning)","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-09","last_updated":"2025-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":16384},"cost":{"input":0.2,"output":0.5}},"claude-opus-4-1-20250805":{"id":"claude-opus-4-1-20250805","name":"Claude Opus 4.1","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75}},"claude-opus-4-5-20251101":{"id":"claude-opus-4-5-20251101","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-01","last_updated":"2025-11-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"gemini-3-pro-image-preview":{"id":"gemini-3-pro-image-preview","name":"Nano Banana Pro Preview","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-20","last_updated":"2025-11-20","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":2,"output":12,"cache_read":0.2},"canonical_model_id":"google/gemini-3-pro-image-preview"},"gemini-3.5-flash-lite":{"id":"gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"gemini-3.1-flash-image":{"id":"gemini-3.1-flash-image","name":"Nano Banana 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":1048576,"output":32768},"cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3.1-flash-image"},"gemini-3.1-pro-preview":{"id":"gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2},"canonical_model_id":"google/gemini-3.1-pro-preview"},"grok-4.5":{"id":"grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":32768},"cost":{"input":2,"output":6},"canonical_model_id":"xai/grok-4.5"},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.6,"output":3}},"gpt-5.1":{"id":"gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"llama-3.3-70b-versatile":{"id":"llama-3.3-70b-versatile","name":"Llama 3.3 70B Versatile","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.59,"output":0.79}},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-5"},"mimo-v2-pro":{"id":"mimo-v2-pro","name":"MiMo-V2-Pro","description":"Earlier MiMo Pro model for multimodal agents, reasoning, and code tasks","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1,"output":3,"cache_read":0.2},"canonical_model_id":"xiaomi/mimo-v2-pro"},"gpt-4o-mini":{"id":"gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-4o-mini"},"o3-pro":{"id":"o3-pro","name":"o3-pro","description":"High-effort o3 tier for difficult technical reasoning and careful answers","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-06-10","last_updated":"2025-06-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":20,"output":40},"canonical_model_id":"openai/o3-pro"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15},"canonical_model_id":"google/gemini-3.5-flash"},"gemini-2.5-pro":{"id":"gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"google/gemini-2.5-pro"},"gemini-3-pro-image":{"id":"gemini-3-pro-image","name":"Nano Banana Pro","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":2,"output":12,"cache_read":0.2},"canonical_model_id":"google/gemini-3-pro-image"},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-2.5-flash"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50},"canonical_model_id":"anthropic/claude-fable-5"},"muse-spark-1.2":{"id":"muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":1,"output":6,"cache_read":0.1},"canonical_model_id":"openai/gpt-5.6-luna"},"gpt-5.1-codex-max":{"id":"gpt-5.1-codex-max","name":"GPT-5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10}},"gpt-5.2":{"id":"gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-4-8"},"grok-code-fast-1":{"id":"grok-code-fast-1","name":"Grok Code Fast 1","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-09-01","last_updated":"2025-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":16384},"cost":{"input":0.2,"output":1.5}},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5"},"claude-sonnet-4-5-20250929":{"id":"claude-sonnet-4-5-20250929","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"gpt-4.1":{"id":"gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15},"canonical_model_id":"anthropic/claude-sonnet-5"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-4-6"},"gemini-3.7-flash":{"id":"gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.7-flash"},"gpt-5.3-codex-xhigh":{"id":"gpt-5.3-codex-xhigh","name":"GPT-5.3 Codex XHigh","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14}},"gemini-3-flash-preview":{"id":"gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05},"canonical_model_id":"google/gemini-3-flash-preview"},"gpt-4o-2024-11-20":{"id":"gpt-4o-2024-11-20","name":"GPT-4o (2024-11-20)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-11-20","last_updated":"2024-11-20","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10}},"claude-haiku-4-5-20251001":{"id":"claude-haiku-4-5-20251001","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"gpt-4.1-mini":{"id":"gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"gpt-5.3-chat-latest":{"id":"gpt-5.3-chat-latest","name":"GPT-5.3 Chat Latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-01","last_updated":"2026-03-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.75,"output":14}},"claude-sonnet-4-20250514":{"id":"claude-sonnet-4-20250514","name":"Claude Sonnet 4","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-05-14","last_updated":"2025-05-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15}},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.6-terra"},"o3":{"id":"o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-4-7"},"gpt-5":{"id":"gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"grok-4.6":{"id":"grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":32768},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"gemini-3.1-flash-lite-preview":{"id":"gemini-3.1-flash-lite-preview","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-01","last_updated":"2026-03-01","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"cache_write":1}},"route-llm":{"id":"route-llm","name":"RouteLLM","description":"RouteLLM routes prompts to an appropriate Abacus-backed text-generation model","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-01-01","last_updated":"2026-07-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"cost":{"input":3,"output":15}},"grok-4-0709":{"id":"grok-4-0709","name":"Grok 4","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-07-09","last_updated":"2025-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":16384},"cost":{"input":3,"output":15}},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.6-sol"},"gemini-3.1-flash-lite":{"id":"gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025},"canonical_model_id":"google/gemini-3.1-flash-lite"},"deepseek/deepseek-v3.1":{"id":"deepseek/deepseek-v3.1","name":"DeepSeek V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-01-20","last_updated":"2025-01-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.55,"output":1.66}},"meta-llama/Meta-Llama-3.3-70B-Instruct":{"id":"meta-llama/Meta-Llama-3.3-70B-Instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.59,"output":0.79},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"meta-llama/Meta-Llama-3.1-8B-Instruct":{"id":"meta-llama/Meta-Llama-3.1-8B-Instruct","name":"Llama 3.1 8B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.02,"output":0.05}},"meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo":{"id":"meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo","name":"Llama 3.1 405B Instruct Turbo","description":"Compact Llama instruction model for fast chat and local deployment","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":3.5,"output":3.5}},"meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8":{"id":"meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8","name":"Llama 4 Maverick 17B Instruct","description":"Open multimodal Llama for strong reasoning with efficient everyday serving","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":8192},"cost":{"input":0.14,"output":0.59},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"thinkingmachines/Inkling":{"id":"thinkingmachines/Inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":3.74,"output":9.36,"cache_read":0.748},"canonical_model_id":"thinkingmachines/inkling"},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.14,"output":0.4},"canonical_model_id":"google/gemma-4-31b-it"},"Qwen/QwQ-32B":{"id":"Qwen/QwQ-32B","name":"QwQ 32B","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2024-11-28","last_updated":"2024-11-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.4,"output":0.4}},"Qwen/Qwen3-235B-A22B-Instruct-2507":{"id":"Qwen/Qwen3-235B-A22B-Instruct-2507","name":"Qwen3 235B A22B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-07-01","last_updated":"2025-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.13,"output":0.6}},"Qwen/Qwen2.5-72B-Instruct":{"id":"Qwen/Qwen2.5-72B-Instruct","name":"Qwen 2.5 72B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-09-19","last_updated":"2024-09-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.11,"output":0.38}},"Qwen/Qwen3-32B":{"id":"Qwen/Qwen3-32B","name":"Qwen3 32B","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.09,"output":0.29},"canonical_model_id":"alibaba/qwen3-32b"},"Qwen/Qwen3-Coder-480B-A35B-Instruct":{"id":"Qwen/Qwen3-Coder-480B-A35B-Instruct","name":"Qwen3-Coder 480B-A35B Instruct","description":"Open Qwen coding heavyweight for repository reasoning and agentic engineering","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.29,"output":1.2},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"Qwen/Qwen3.6-27B":{"id":"Qwen/Qwen3.6-27B","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.32,"output":3.2},"canonical_model_id":"alibaba/qwen3.6-27b"},"deepseek-ai/DeepSeek-R1":{"id":"deepseek-ai/DeepSeek-R1","name":"DeepSeek R1","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-01-20","last_updated":"2025-01-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":3,"output":7}},"deepseek-ai/DeepSeek-V4-Flash":{"id":"deepseek-ai/DeepSeek-V4-Flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32768},"cost":{"input":0.14,"output":0.28,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek-ai/DeepSeek-V4-Pro":{"id":"deepseek-ai/DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32768},"cost":{"input":1.74,"output":3.48,"cache_read":0.15},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek-ai/DeepSeek-V3.2":{"id":"deepseek-ai/DeepSeek-V3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-06-15","last_updated":"2025-06-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.27,"output":0.4}},"deepseek-ai/DeepSeek-V3.1-Terminus":{"id":"deepseek-ai/DeepSeek-V3.1-Terminus","name":"DeepSeek V3.1 Terminus","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-06-01","last_updated":"2025-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.27,"output":1}},"MiniMaxAI/MiniMax-M3":{"id":"MiniMaxAI/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M3"},"MiniMaxAI/MiniMax-M2.7":{"id":"MiniMaxAI/MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2.7"},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/Kimi-K3":{"id":"moonshotai/Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/Kimi-K2.7-Code":{"id":"moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"zai-org/GLM-5.1":{"id":"zai-org/GLM-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-4.7":{"id":"zai-org/GLM-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2},"canonical_model_id":"zhipuai/glm-4.7"},"zai-org/GLM-5":{"id":"zai-org/GLM-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1,"output":3.2},"canonical_model_id":"zhipuai/glm-5"},"zai-org/GLM-4.6":{"id":"zai-org/GLM-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.6,"output":2.2},"canonical_model_id":"zhipuai/glm-4.6"},"zai-org/GLM-4.5":{"id":"zai-org/GLM-4.5","name":"GLM-4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":96000},"cost":{"input":0.6,"output":2.2},"canonical_model_id":"zhipuai/glm-4.5"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.08,"output":0.44},"canonical_model_id":"openai/gpt-oss-120b"}}},"novita-ai":{"id":"novita-ai","env":["NOVITA_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.novita.ai/openai","name":"Novita AI","doc":"https://novita.ai/docs/guides/introduction","models":{"baai/bge-m3":{"id":"baai/bge-m3","type":"embedding","name":"BGE M3","description":"Multilingual embedding model combining dense, sparse, and multi-vector retrieval","family":"bge","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-01-30","last_updated":"2024-01-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":0},"cost":{"input":0.01,"output":0},"canonical_model_id":"baai/bge-m3"},"baai/bge-reranker-v2-m3":{"id":"baai/bge-reranker-v2-m3","type":"reranking","name":"BGE Reranker V2 M3","description":"Lightweight multilingual cross-encoder that scores query-document relevance","family":"bge","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-03-15","last_updated":"2024-03-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8000,"output":0},"cost":{"input":0.01,"output":0},"canonical_model_id":"baai/bge-reranker-v2-m3"},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.44,"output":1.32,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-r1-0528-qwen3-8b":{"id":"deepseek/deepseek-r1-0528-qwen3-8b","name":"DeepSeek R1 0528 Qwen3 8B","description":"DeepSeek R1 0528 distilled into Qwen3 8B for mathematics, coding, and reasoning","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"release_date":"2025-05-29","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"cost":{"input":0.06,"output":0.09},"canonical_model_id":"deepseek/deepseek-r1-0528-qwen3-8b"},"deepseek/deepseek-ocr-2":{"id":"deepseek/deepseek-ocr-2","name":"DeepSeek OCR 2","description":"High-accuracy OCR model for extracting text from documents, screenshots, receipts, and natural scenes","attachment":true,"reasoning":false,"tool_call":false,"release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0.03,"output":0.03},"canonical_model_id":"deepseek/deepseek-ocr-2"},"deepseek/deepseek-r1-turbo":{"id":"deepseek/deepseek-r1-turbo","name":"DeepSeek R1 (Turbo)","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":16000},"cost":{"input":0.7,"output":2.5},"canonical_model_id":"deepseek/deepseek-r1"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek/deepseek_v3":{"id":"deepseek/deepseek_v3","name":"DeepSeek-V3","description":"Open DeepSeek MoE chat model for coding, math, and general reasoning","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-12-26","last_updated":"2024-12-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":16000},"cost":{"input":0.89,"output":0.89},"canonical_model_id":"deepseek/deepseek-v3"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":1.6,"output":3.2,"cache_read":0.135},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-r1-0528":{"id":"deepseek/deepseek-r1-0528","name":"DeepSeek R1 0528","description":"May 2025 DeepSeek R1 update with improved mathematics, coding, and reasoning","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":32768},"cost":{"input":0.7,"output":2.5,"cache_read":0.35},"canonical_model_id":"deepseek/deepseek-r1-0528"},"tencent/hy3":{"id":"tencent/hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":192000,"output":262144},"cost":{"input":0.14,"output":0.58,"cache_read":0.035},"canonical_model_id":"tencent/hy3"},"tencent/hy4-preview":{"id":"tencent/hy4-preview","name":"Hy4 preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":64000},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"},"meta-llama/llama-4-maverick-17b-128e-instruct-fp8":{"id":"meta-llama/llama-4-maverick-17b-128e-instruct-fp8","name":"Llama 4 Maverick 17B Instruct","description":"Open multimodal Llama for strong reasoning with efficient everyday serving","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":8192},"cost":{"input":0.27,"output":0.85},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"meta-llama/llama-3.3-70b-instruct":{"id":"meta-llama/llama-3.3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":12288,"output":12288},"cost":{"input":0.135,"output":0.4},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"meta-llama/llama-3.1-8b-instruct":{"id":"meta-llama/llama-3.1-8b-instruct","name":"Llama-3.1-8B-Instruct","description":"Compact open Llama model for lightweight chat, drafting, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":16384},"cost":{"input":0.02,"output":0.05},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"meta-llama/llama-3.2-1b-instruct":{"id":"meta-llama/llama-3.2-1b-instruct","name":"Llama 3.2 1B Instruct","description":"Compact instruction-tuned Llama model for multilingual dialogue and on-device assistants","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":32000},"cost":{"input":0.02,"output":0.02},"canonical_model_id":"meta/llama-3.2-1b-instruct"},"meta-llama/llama-4-scout-17b-16e-instruct":{"id":"meta-llama/llama-4-scout-17b-16e-instruct","name":"Llama 4 Scout 17B Instruct","description":"Open Llama with long-context vision for efficient multimodal agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.18,"output":0.59},"canonical_model_id":"meta/llama-4-scout-17b-instruct"},"nousresearch/hermes-2-pro-llama-3-8b":{"id":"nousresearch/hermes-2-pro-llama-3-8b","name":"Hermes 2 Pro Llama 3 8B","description":"Llama 3 fine-tune optimized for function calling, structured JSON responses, and dialogue","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-04-30","last_updated":"2024-04-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0.14,"output":0.14},"canonical_model_id":"nousresearch/hermes-2-pro-llama-3-8b"},"xiaomimimo/mimo-v2.6-pro":{"id":"xiaomimimo/mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"xiaomimimo/mimo-v2.5":{"id":"xiaomimimo/mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.168,"output":0.336,"cache_read":0.0034},"canonical_model_id":"xiaomi/mimo-v2.5"},"xiaomimimo/mimo-v2.5-pro":{"id":"xiaomimimo/mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.522,"output":1.044,"cache_read":0.0043},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"xiaomimimo/mimo-v2.6-flash":{"id":"xiaomimimo/mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"baidu/ernie-4.5-21B-a3b":{"id":"baidu/ernie-4.5-21B-a3b","name":"ERNIE 4.5 21B A3B","description":"Open ERNIE text MoE with 21B total and 3B active parameters","family":"ernie","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-06-30","last_updated":"2025-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":120000,"output":8000},"cost":{"input":0.07,"output":0.28},"canonical_model_id":"baidu/ernie-4.5-21b-a3b"},"baidu/cobuddy":{"id":"baidu/cobuddy","name":"CoBuddy","description":"Baidu Qianfan model optimized for code generation and tool-using coding agents","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-05-06","last_updated":"2026-05-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":65536},"cost":{"input":0.28,"output":1.13,"cache_read":0.07},"canonical_model_id":"baidu/cobuddy"},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.14,"output":0.4},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemma-3-27b-it":{"id":"google/gemma-3-27b-it","name":"Gemma 3 27B IT","description":"Largest open Gemma 3 instruction model for multilingual text generation and visual understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":98304,"output":16384},"cost":{"input":0.119,"output":0.2},"canonical_model_id":"google/gemma-3-27b-it"},"google/gemma-4-26b-a4b-it":{"id":"google/gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.13,"output":0.4},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemma-3-12b-it":{"id":"google/gemma-3-12b-it","name":"Gemma 3 12B IT","description":"Open multimodal Gemma instruction model for multilingual text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.05,"output":0.1},"canonical_model_id":"google/gemma-3-12b-it"},"minimaxai/minimax-m1-80k":{"id":"minimaxai/minimax-m1-80k","name":"MiniMax M1 80K","description":"Open hybrid-attention MoE reasoning model with a million-token context and an 80K thinking budget","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":40000},"cost":{"input":0.55,"output":2.2},"canonical_model_id":"minimax/minimax-m1-80k"},"inclusionai/ling-3.0-flash":{"id":"inclusionai/ling-3.0-flash","name":"Ling 3.0 Flash","description":"Hybrid-linear MoE reasoning model with 124B total and 5.1B active parameters for efficient agents","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-07-23","last_updated":"2026-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.06,"output":0.18,"cache_read":0.012},"canonical_model_id":"inclusionai/ling-3.0-flash"},"inclusionai/ling-3.1-flash":{"id":"inclusionai/ling-3.1-flash","name":"Ling 3.1 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.3,"output":0.9,"cache_read":0.06},"canonical_model_id":"inclusionai/ling-3.1-flash"},"inclusionai/ling-3.0-flash-sante":{"id":"inclusionai/ling-3.0-flash-sante","name":"Ling 3.0 Flash Sante","description":"Health and medicine specialization of Ling 3.0 Flash for medical reasoning and evidence-based retrieval","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.075,"output":0.22,"cache_read":0.015},"canonical_model_id":"inclusionai/ling-3.0-flash-sante"},"inclusionai/ling-3.0-flash-vl":{"id":"inclusionai/ling-3.0-flash-vl","name":"Ling 3.0 Flash VL","description":"Native multimodal hybrid MoE model for image and video understanding, reasoning, and visual agents","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.075,"output":0.22,"cache_read":0.015},"canonical_model_id":"inclusionai/ling-3.0-flash-vl"},"inclusionai/ling-3.0-flash-fin":{"id":"inclusionai/ling-3.0-flash-fin","name":"Ling 3.0 Flash Fin","description":"Finance-enhanced model for financial research, multi-step investment workflows, and long-horizon planning and execution","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"release_date":"2026-08-27","last_updated":"2026-09-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.075,"output":0.22,"cache_read":0.015},"canonical_model_id":"inclusionai/ling-3.0-flash-fin"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.8,"output":3.4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2-thinking":{"id":"moonshotai/kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Thinking Kimi model for slower research passes, planning, and hard technical questions","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":0.6,"output":2.5,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"moonshotai/kimi-k2.5":{"id":"moonshotai/kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":3,"cache_read":0.1},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/kimi-k2-instruct":{"id":"moonshotai/kimi-k2-instruct","name":"Kimi K2 Instruct","description":"Non-thinking Kimi K2 MoE instruction model for coding and tool-using agents","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.57,"output":2.3},"canonical_model_id":"moonshotai/kimi-k2-instruct"},"moonshotai/kimi-k2-0905":{"id":"moonshotai/kimi-k2-0905","name":"Kimi K2 Instruct 0905","description":"September 2025 Kimi K2 instruction update with a 256K context and improved agentic coding","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":0.6,"output":2.5},"canonical_model_id":"moonshotai/kimi-k2-0905"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"zai-org/glm-4.6v":{"id":"zai-org/glm-4.6v","name":"GLM-4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.3,"output":0.9,"cache_read":0.055},"canonical_model_id":"zhipuai/glm-4.6v"},"zai-org/glm-5.3-flash":{"id":"zai-org/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/glm-4.6":{"id":"zai-org/glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.55,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.6"},"zai-org/glm-5":{"id":"zai-org/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202800,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"zai-org/glm-4.5v":{"id":"zai-org/glm-4.5v","name":"GLM-4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":16384},"cost":{"input":0.6,"output":1.8,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5v"},"zai-org/glm-4.7-flash":{"id":"zai-org/glm-4.7-flash","name":"GLM-4.7-Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.07,"output":0.4,"cache_read":0.01},"canonical_model_id":"zhipuai/glm-4.7-flash"},"zai-org/glm-4.7":{"id":"zai-org/glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.7"},"zai-org/glm-5.2":{"id":"zai-org/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/glm-5.1":{"id":"zai-org/glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1.38,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"zai-org/autoglm-phone-9b-multilingual":{"id":"zai-org/autoglm-phone-9b-multilingual","name":"AutoGLM Phone 9B Multilingual","description":"Multilingual visual model for operating smartphone interfaces and mobile agents","family":"glm","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-12-10","last_updated":"2025-12-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.035,"output":0.138},"canonical_model_id":"zhipuai/autoglm-phone-9b-multilingual"},"zai-org/glm-4.5-air":{"id":"zai-org/glm-4.5-air","name":"GLM-4.5-Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.13,"output":0.85,"cache_read":0.025},"canonical_model_id":"zhipuai/glm-4.5-air"},"zai-org/glm-5.3":{"id":"zai-org/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"apodex/apodex-1.1-mini":{"id":"apodex/apodex-1.1-mini","name":"Apodex 1.1 Mini","description":"Open-weight 35B MoE model for long-horizon research, forecasting, and tool-assisted work","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-24","last_updated":"2026-08-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"apodex/apodex-1.1-mini"},"nvidia/nemotron-3-nano-30b-a3b":{"id":"nvidia/nemotron-3-nano-30b-a3b","name":"Nemotron 3 Nano 30B A3B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.05,"output":0.2},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"gryphe/mythomax-l2-13b":{"id":"gryphe/mythomax-l2-13b","name":"MythoMax L2 13B","description":"Llama 2 merge combining MythoLogic and Huginn for creative writing and roleplay","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2023-08-10","last_updated":"2023-08-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":3200},"cost":{"input":0.09,"output":0.09},"canonical_model_id":"gryphe/mythomax-l2-13b"},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131100},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5"},"minimax/minimax-m2.7":{"id":"minimax/minimax-m2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"tiers":[{"input":0.6,"output":2.4,"cache_read":0.12,"tier":{"type":"context","size":524288}}],"context_over_200k":{"input":0.6,"output":2.4,"cache_read":0.12}},"canonical_model_id":"minimax/MiniMax-M3"},"minimax/minimax-m2.7-highspeed":{"id":"minimax/minimax-m2.7-highspeed","name":"MiniMax-M2.7-highspeed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"paddlepaddle/paddleocr-vl":{"id":"paddlepaddle/paddleocr-vl","name":"PaddleOCR VL","description":"Compact vision-language model for multilingual document parsing, OCR, tables, formulas, and charts","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-10-16","last_updated":"2025-10-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":16384},"cost":{"input":0.02,"output":0.02},"canonical_model_id":"paddlepaddle/paddleocr-vl"},"stepfun/step-5-preview":{"id":"stepfun/step-5-preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":64000},"cost":{"input":1,"output":2.7,"cache_read":0.1},"canonical_model_id":"stepfun/step-5-preview"},"stepfun/step-3.7-flash":{"id":"stepfun/step-3.7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":256000,"output":256000},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"mindai/macaron-v1-tall":{"id":"mindai/macaron-v1-tall","name":"Macaron V1 Tall","description":"Qwen3.6-based Mixture-of-LoRA model with specialists for chat, personal agents, coding, and generative UI","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.2475,"output":1.43,"cache_read":0.044},"canonical_model_id":"mindlab/macaron-v1-tall"},"mindai/macaron-v1-venti":{"id":"mindai/macaron-v1-venti","name":"Macaron V1 Venti","description":"GLM-5.2-based Mixture-of-LoRA model with specialists for chat, personal agents, coding, and generative UI","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.825,"output":2.475,"cache_read":0.165},"canonical_model_id":"mindlab/macaron-v1-venti"},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":1.25,"output":3.75,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.42,"output":3,"cache_read":0.085},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3.8-2.4t-a95b":{"id":"qwen/qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"qwen/qwen3.5-27b":{"id":"qwen/qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.3,"output":2.4},"canonical_model_id":"alibaba/qwen3.5-27b"},"qwen/qwen3.8-max":{"id":"qwen/qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-max"},"qwen/qwen3-omni-30b-a3b-thinking":{"id":"qwen/qwen3-omni-30b-a3b-thinking","name":"Qwen3 Omni 30B A3B Thinking","description":"Multimodal reasoning model accepting text, images, video, and audio with text output","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-22","last_updated":"2025-09-22","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":16384},"cost":{"input":0.25,"output":0.97,"input_audio":2.2},"canonical_model_id":"alibaba/qwen3-omni-30b-a3b-thinking"},"qwen/qwen3-reranker-8b":{"id":"qwen/qwen3-reranker-8b","type":"reranking","name":"Qwen3 Reranker 8B","description":"Multilingual query-document reranking model supporting more than 100 languages","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":0},"cost":{"input":0.05,"output":0},"canonical_model_id":"alibaba/qwen3-reranker-8b"},"qwen/qwen3-vl-30b-a3b-instruct":{"id":"qwen/qwen3-vl-30b-a3b-instruct","name":"Qwen3 VL 30B A3B Instruct","description":"Open vision-language MoE model for image and video understanding, documents, and visual agents","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-04","last_updated":"2025-10-04","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.2,"output":0.7},"canonical_model_id":"alibaba/qwen3-vl-30b-a3b-instruct"},"qwen/qwen3.5-122b-a10b":{"id":"qwen/qwen3.5-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.4,"output":3.2},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"qwen/qwen3.6-35b-a3b":{"id":"qwen/qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.248,"output":1.485},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"qwen/qwen-mt-plus":{"id":"qwen/qwen-mt-plus","name":"Qwen MT Plus","description":"Flagship Qwen translation model with terminology control and support for 92 languages","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-07-24","last_updated":"2025-07-24","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":8192},"cost":{"input":0.25,"output":0.75},"canonical_model_id":"alibaba/qwen-mt-plus"},"qwen/qwen3.8-flash":{"id":"qwen/qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen/qwen3-embedding-8b":{"id":"qwen/qwen3-embedding-8b","type":"embedding","name":"Qwen3 Embedding 8B","description":"Multilingual text embedding model for retrieval, code search, classification, and clustering","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":0},"cost":{"input":0.07,"output":0},"canonical_model_id":"alibaba/qwen3-embedding-8b"},"qwen/qwen3.5-35b-a3b":{"id":"qwen/qwen3.5-35b-a3b","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.25,"output":2},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"qwen/qwen3.5-397b-a17b":{"id":"qwen/qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.6,"output":3.6},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"qwen/qwen3.6-27b":{"id":"qwen/qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.6,"output":3.6},"canonical_model_id":"alibaba/qwen3.6-27b"},"baichuan/baichuan-m2-32b":{"id":"baichuan/baichuan-m2-32b","name":"Baichuan M2 32B","description":"Open medical model trained for clinical reasoning and patient interaction with on, off, and auto thinking modes","family":"baichuan","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"temperature":true,"release_date":"2025-08-13","last_updated":"2025-08-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.07,"output":0.07},"canonical_model_id":"baichuan/baichuan-m2-32b"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.05,"output":0.25},"canonical_model_id":"openai/gpt-oss-120b"},"microsoft/wizardlm-2-8x22b":{"id":"microsoft/wizardlm-2-8x22b","name":"WizardLM 2 8x22B","description":"Microsoft WizardLM instruction-tuned Mixtral MoE for multilingual dialogue and complex tasks","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2024-04-15","last_updated":"2024-04-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65535,"output":8000},"cost":{"input":0.62,"output":0.62},"canonical_model_id":"microsoft/wizardlm-2-8x22b"}}},"302ai":{"id":"302ai","env":["302AI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.302.ai/v1","name":"302.AI","doc":"https://doc.302.ai","models":{"grok-4-1-fast-reasoning":{"id":"grok-4-1-fast-reasoning","name":"grok-4-1-fast-reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2025-11-20","last_updated":"2025-11-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":0.2,"output":0.5}},"glm-4.6v":{"id":"glm-4.6v","name":"GLM-4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.145,"output":0.43}},"gpt-5.4":{"id":"gpt-5.4","name":"gpt-5.4","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"cache_write":0,"tiers":[{"input":5,"output":22.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5}}},"glm-4.5":{"id":"glm-4.5","name":"GLM-4.5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-29","last_updated":"2025-07-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.286,"output":1.142}},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"claude-haiku-4-5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-16","last_updated":"2025-10-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5}},"qwen3.7-max":{"id":"qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":1.8,"output":5.3},"canonical_model_id":"alibaba/qwen3.7-max"},"gemini-3.1-flash-image-preview":{"id":"gemini-3.1-flash-image-preview","name":"gemini-3.1-flash-image-preview","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-27","last_updated":"2026-02-27","modalities":{"input":["text","image","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":60}},"grok-4.7":{"id":"grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"cache_write":0.5},"canonical_model_id":"xai/grok-4.7"},"MiniMax-M3":{"id":"MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.72,"output":2.88},"canonical_model_id":"minimax/MiniMax-M3"},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"gpt-5.4-nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-19","last_updated":"2026-03-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25}},"gemini-3.5-flash-thinking":{"id":"gemini-3.5-flash-thinking","name":"gemini-3.5-flash-thinking","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9},"canonical_model_id":"google/gemini-3.5-flash"},"gemini-3-pro-preview":{"id":"gemini-3-pro-preview","name":"gemini-3-pro-preview","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":2,"output":12}},"glm-5v-turbo":{"id":"glm-5v-turbo","name":"GLM-5V-Turbo","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":0.72,"output":3.2}},"gemini-2.5-flash-image":{"id":"gemini-2.5-flash-image","name":"gemini-2.5-flash-image","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-10-08","last_updated":"2025-10-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.3,"output":30}},"gpt-4o":{"id":"gpt-4o","name":"gpt-4o","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-05-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10}},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.075,"output":0.25},"canonical_model_id":"zhipuai/glm-5.3-flash"},"glm-4.6":{"id":"glm-4.6","name":"glm-4.6","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.286,"output":1.142}},"qwen3-235b-a22b-instruct-2507":{"id":"qwen3-235b-a22b-instruct-2507","name":"qwen3-235b-a22b-instruct-2507","description":"Tool-capable chat model for instruction following and agentic application workflows","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":65536},"cost":{"input":0.29,"output":1.143}},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2.16,"output":6.36},"canonical_model_id":"alibaba/qwen3.8-max"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15},"canonical_model_id":"moonshotai/kimi-k3"},"gpt-5.6-sol-pro":{"id":"gpt-5.6-sol-pro","name":"gpt-5.6-sol-pro","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30},"canonical_model_id":"openai/gpt-5.6-sol"},"gpt-5-mini":{"id":"gpt-5-mini","name":"gpt-5-mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-08","last_updated":"2025-08-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2}},"qwen3.5-plus":{"id":"qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.12,"output":0.69},"canonical_model_id":"alibaba/qwen3.5-plus"},"claude-sonnet-4-6-thinking":{"id":"claude-sonnet-4-6-thinking","name":"claude-sonnet-4-6-thinking","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-08","release_date":"2026-02-18","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15}},"glm-5":{"id":"glm-5","name":"glm-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.6}},"gpt-4.1-nano":{"id":"gpt-4.1-nano","name":"gpt-4.1-nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.1,"output":0.4}},"grok-4-fast-reasoning":{"id":"grok-4-fast-reasoning","name":"grok-4-fast-reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":0.2,"output":0.5}},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4},"canonical_model_id":"moonshotai/kimi-k2.6"},"gpt-5.2-chat-latest":{"id":"gpt-5.2-chat-latest","name":"gpt-5.2-chat-latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-12","last_updated":"2025-12-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1.75,"output":14}},"gpt-5.1-chat-latest":{"id":"gpt-5.1-chat-latest","name":"gpt-5.1-chat-latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-14","last_updated":"2025-11-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1.25,"output":10}},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"MiniMax-M2.1":{"id":"MiniMax-M2.1","name":"MiniMax-M2.1","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2.1"},"gemini-2.5-flash-preview-09-2025":{"id":"gemini-2.5-flash-preview-09-2025","name":"gemini-2.5-flash-preview-09-2025","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-09-26","last_updated":"2025-09-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.3,"output":2.5}},"glm-4.5v":{"id":"glm-4.5v","name":"GLM-4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-12","last_updated":"2025-08-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":16384},"cost":{"input":0.29,"output":0.86}},"claude-fable-5-1":{"id":"claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50},"canonical_model_id":"anthropic/claude-fable-5-1"},"gemini-3.6-flash":{"id":"gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5},"canonical_model_id":"google/gemini-3.6-flash"},"claude-opus-5-thinking":{"id":"claude-opus-5-thinking","name":"claude-opus-5-thinking","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-5"},"qwen3-coder-480b-a35b-instruct":{"id":"qwen3-coder-480b-a35b-instruct","name":"qwen3-coder-480b-a35b-instruct","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.86,"output":3.43}},"doubao-seed-1-6-vision-250815":{"id":"doubao-seed-1-6-vision-250815","name":"doubao-seed-1-6-vision-250815","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.114,"output":1.143}},"claude-sonnet-4-5-20250929-thinking":{"id":"claude-sonnet-4-5-20250929-thinking","name":"claude-sonnet-4-5-20250929-thinking","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15}},"grok-4.3":{"id":"grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5},"canonical_model_id":"xai/grok-4.3"},"kimi-k2-thinking":{"id":"kimi-k2-thinking","name":"kimi-k2-thinking","description":"Kimi reasoning model for long-horizon research, planning, and tool use","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.575,"output":2.3}},"grok-4-fast-non-reasoning":{"id":"grok-4-fast-non-reasoning","name":"grok-4-fast-non-reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":0.2,"output":0.5}},"grok-4.20-beta-0309-reasoning":{"id":"grok-4.20-beta-0309-reasoning","name":"grok-4.20-beta-0309-reasoning","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":2,"output":6}},"claude-opus-4-1-20250805":{"id":"claude-opus-4-1-20250805","name":"claude-opus-4-1-20250805","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":31999}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75}},"gpt-5-pro":{"id":"gpt-5-pro","name":"gpt-5-pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-08","last_updated":"2025-10-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":272000},"cost":{"input":15,"output":120}},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"openai/gpt-6.1-sol"},"claude-opus-4-5-20251101":{"id":"claude-opus-4-5-20251101","name":"claude-opus-4-5-20251101","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-11-25","last_updated":"2025-11-25","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25}},"gemini-3-pro-image-preview":{"id":"gemini-3-pro-image-preview","name":"gemini-3-pro-image-preview","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-06","release_date":"2025-11-20","last_updated":"2025-11-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":64000},"cost":{"input":2,"output":120}},"gemini-3.5-flash-lite":{"id":"gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5},"canonical_model_id":"google/gemini-3.5-flash-lite"},"gemini-2.0-flash-lite":{"id":"gemini-2.0-flash-lite","name":"gemini-2.0-flash-lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-11","release_date":"2025-06-16","last_updated":"2025-06-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":8192},"cost":{"input":0.075,"output":0.3}},"qwen3-235b-a22b":{"id":"qwen3-235b-a22b","name":"Qwen3-235B-A22B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-29","last_updated":"2025-04-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.29,"output":2.86}},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50},"canonical_model_id":"openai/gpt-6-astra"},"gemini-3.1-pro-preview":{"id":"gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12},"canonical_model_id":"google/gemini-3.1-pro-preview"},"grok-4.5":{"id":"grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6},"canonical_model_id":"xai/grok-4.5"},"gpt-5.6-luna-pro":{"id":"gpt-5.6-luna-pro","name":"gpt-5.6-luna-pro","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2},"canonical_model_id":"openai/gpt-5.6-luna"},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.66,"output":3.3},"canonical_model_id":"moonshotai/kimi-k2.5"},"gpt-5.1":{"id":"gpt-5.1","name":"gpt-5.1","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-14","last_updated":"2025-11-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10}},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-5"},"qwen3.7-max-2026-06-08":{"id":"qwen3.7-max-2026-06-08","name":"qwen3.7-max-2026-06-08","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":1.8,"output":5.3},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen3.6-35b-a3b":{"id":"qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.283,"output":1.705},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"kimi-k2-0905-preview":{"id":"kimi-k2-0905-preview","name":"kimi-k2-0905-preview","description":"Kimi model for long-context chat, coding, and agentic reasoning","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.632,"output":2.53}},"deepseek-flash":{"id":"deepseek-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9},"canonical_model_id":"google/gemini-3.5-flash"},"gemini-2.5-pro":{"id":"gemini-2.5-pro","name":"gemini-2.5-pro","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":1.25,"output":10}},"qwen3.6-flash":{"id":"qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.188,"output":1.133},"canonical_model_id":"alibaba/qwen3.6-flash"},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"gemini-2.5-flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.3,"output":2.5}},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50},"canonical_model_id":"anthropic/claude-fable-5"},"doubao-seed-1-6-thinking-250715":{"id":"doubao-seed-1-6-thinking-250715","name":"doubao-seed-1-6-thinking-250715","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":16000},"cost":{"input":0.121,"output":1.21}},"gpt-5-thinking":{"id":"gpt-5-thinking","name":"gpt-5-thinking","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-08-08","last_updated":"2025-08-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.25,"output":10}},"MiniMax-M1":{"id":"MiniMax-M1","name":"MiniMax-M1","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-06-16","last_updated":"2025-06-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.132,"output":1.254}},"MiniMax-M2.5":{"id":"MiniMax-M2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2.5"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"gpt-5.4-mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-19","last_updated":"2026-03-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5}},"glm-4.7":{"id":"glm-4.7","name":"glm-4.7","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.286,"output":1.142}},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2},"canonical_model_id":"openai/gpt-5.6-luna"},"MiniMax-M2.7":{"id":"MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2.7"},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.18,"output":0.564},"canonical_model_id":"alibaba/qwen3.8-flash"},"gpt-5.2":{"id":"gpt-5.2","name":"gpt-5.2","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-12","last_updated":"2025-12-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14}},"deepseek-v3.2-thinking":{"id":"deepseek-v3.2-thinking","name":"DeepSeek-V3.2-Thinking","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000},"cost":{"input":0.29,"output":0.43}},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-4-8"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30},"canonical_model_id":"openai/gpt-5.5"},"claude-sonnet-4-5-20250929":{"id":"claude-sonnet-4-5-20250929","name":"claude-sonnet-4-5-20250929","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15}},"gpt-4.1":{"id":"gpt-4.1","name":"gpt-4.1","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8}},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10},"canonical_model_id":"anthropic/claude-sonnet-5"},"qwen3.5-35b-a3b":{"id":"qwen3.5-35b-a3b","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.06,"output":0.46},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"qwen3-30b-a3b":{"id":"qwen3-30b-a3b","name":"Qwen3-30B-A3B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-29","last_updated":"2025-04-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.11,"output":1.08}},"gemini-3.7-flash":{"id":"gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75},"canonical_model_id":"google/gemini-3.7-flash"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4},"canonical_model_id":"zhipuai/glm-5.2"},"gemini-2.5-flash-nothink":{"id":"gemini-2.5-flash-nothink","name":"gemini-2.5-flash-nothink","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-24","last_updated":"2025-06-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.3,"output":2.5}},"doubao-seed-1-8-251215":{"id":"doubao-seed-1-8-251215","name":"doubao-seed-1-8-251215","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-12-18","last_updated":"2025-12-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":224000,"output":64000},"cost":{"input":0.114,"output":0.286}},"claude-opus-4-1-20250805-thinking":{"id":"claude-opus-4-1-20250805-thinking","name":"claude-opus-4-1-20250805-thinking","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2025-05-27","last_updated":"2025-05-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75}},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":1.4,"output":4.4},"canonical_model_id":"zhipuai/glm-5.1"},"gemini-3-flash-preview":{"id":"gemini-3-flash-preview","name":"gemini-3-flash-preview","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2025-12-18","last_updated":"2025-12-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.5,"output":3}},"claude-haiku-4-5-20251001":{"id":"claude-haiku-4-5-20251001","name":"claude-haiku-4-5-20251001","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-16","last_updated":"2025-10-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5}},"mistral-large-2512":{"id":"mistral-large-2512","name":"mistral-large-2512","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":262144},"cost":{"input":1.1,"output":3.3}},"MiniMax-M2":{"id":"MiniMax-M2","name":"MiniMax-M2","description":"MiniMax model for chat, coding, office work, and agentic tasks","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-10-26","last_updated":"2025-10-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.33,"output":1.32}},"gemini-2.5-flash-lite-preview-09-2025":{"id":"gemini-2.5-flash-lite-preview-09-2025","name":"gemini-2.5-flash-lite-preview-09-2025","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-09-26","last_updated":"2025-09-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.1,"output":0.4}},"gpt-4.1-mini":{"id":"gpt-4.1-mini","name":"gpt-4.1-mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6}},"gpt-5.6-terra-pro":{"id":"gpt-5.6-terra-pro","name":"gpt-5.6-terra-pro","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12},"canonical_model_id":"openai/gpt-5.6-terra"},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"anthropic/claude-haiku-5-5"},"gemini-3.8-flash":{"id":"gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75},"canonical_model_id":"google/gemini-3.8-flash"},"ministral-14b-2512":{"id":"ministral-14b-2512","name":"ministral-14b-2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000},"cost":{"input":0.33,"output":0.33}},"glm-5-turbo":{"id":"glm-5-turbo","name":"glm-5-turbo","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":0.72,"output":3.2}},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"openai/gpt-6-luna"},"grok-4.1":{"id":"grok-4.1","name":"grok-4.1","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":2,"output":10}},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"claude-sonnet-4-6","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-18","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15}},"gpt-5.3-chat-latest":{"id":"gpt-5.3-chat-latest","name":"GPT-5.3 Chat (latest)","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1.75,"output":14},"canonical_model_id":"openai/gpt-5.3-chat-latest"},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"qwen3.6-plus":{"id":"qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.3,"output":1.8},"canonical_model_id":"alibaba/qwen3.6-plus"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12},"canonical_model_id":"openai/gpt-5.6-terra"},"deepseek-v3.2":{"id":"deepseek-v3.2","name":"deepseek-v3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.29,"output":0.43}},"claude-opus-4-7-thinking":{"id":"claude-opus-4-7-thinking","name":"claude-opus-4-7-thinking","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-4-7"},"o3":{"id":"o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8},"canonical_model_id":"openai/o3"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4},"canonical_model_id":"zhipuai/glm-5.3"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"claude-opus-4-7","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5}}},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"gpt-5":{"id":"gpt-5","name":"gpt-5","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-08","last_updated":"2025-08-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10}},"grok-4.6":{"id":"grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6},"canonical_model_id":"xai/grok-4.6"},"gemini-3.1-flash-lite-preview":{"id":"gemini-3.1-flash-lite-preview","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5},"canonical_model_id":"google/gemini-3.1-flash-lite-preview"},"qwen3-max-2025-09-23":{"id":"qwen3-max-2025-09-23","name":"qwen3-max-2025-09-23","description":"Flagship model for demanding analysis, coding, and production agent workflows","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-24","last_updated":"2025-09-24","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":258048,"output":65536},"cost":{"input":0.86,"output":3.43}},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.285,"output":1.15},"canonical_model_id":"alibaba/qwen3.7-plus"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30},"canonical_model_id":"openai/gpt-5.6-sol"},"gemini-4-argon":{"id":"gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":4,"output":10,"cache_read":0.2,"cache_write":0.375},"canonical_model_id":"google/gemini-4-argon"},"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-6-sol"},"gemini-3.1-flash-lite":{"id":"gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5},"canonical_model_id":"google/gemini-3.1-flash-lite"}}},"openrouter":{"id":"openrouter","env":["OPENROUTER_API_KEY"],"npm":"@openrouter/ai-sdk-provider","api":"https://openrouter.ai/api/v1","name":"OpenRouter","doc":"https://openrouter.ai/models","models":{"sao10k/l3-lunaris-8b":{"id":"sao10k/l3-lunaris-8b","name":"Llama 3 8B Lunaris","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-13","last_updated":"2024-08-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":7372},"cost":{"input":0.04,"output":0.05}},"sao10k/l3.3-euryale-70b":{"id":"sao10k/l3.3-euryale-70b","name":"Llama 3.3 Euryale 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-12-18","last_updated":"2024-12-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.65,"output":0.75}},"sao10k/l3.1-euryale-70b":{"id":"sao10k/l3.1-euryale-70b","name":"Llama 3.1 Euryale 70B v2.2","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-28","last_updated":"2024-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.85,"output":0.85}},"bytedance-seed/seed-1.6-flash":{"id":"bytedance-seed/seed-1.6-flash","name":"Seed 1.6 Flash","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.075,"output":0.3,"tiers":[{"input":0.1,"output":0.8,"tier":{"type":"context","size":128000}}]}},"bytedance-seed/seed-2.0-lite":{"id":"bytedance-seed/seed-2.0-lite","name":"Seed 2.0 Lite","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.25,"output":2,"tiers":[{"input":0.5,"output":4,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"bytedance-seed/seed-2-1-turbo":{"id":"bytedance-seed/seed-2-1-turbo","name":"Seed 2.1 Turbo","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":235929},"cost":{"input":0.5,"output":2.5}},"bytedance-seed/seed-2.0-mini":{"id":"bytedance-seed/seed-2.0-mini","name":"Seed 2.0 Mini","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.1,"output":0.4,"tiers":[{"input":0.2,"output":0.8,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"bytedance-seed/seed-2.0-code":{"id":"bytedance-seed/seed-2.0-code","name":"Seed 2.0 Code","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.5,"output":3,"tiers":[{"input":1,"output":6,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"bytedance-seed/seed-1.6":{"id":"bytedance-seed/seed-1.6","name":"Seed 1.6","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.25,"output":2,"tiers":[{"input":0.5,"output":4,"tier":{"type":"context","size":128000}}]}},"~moonshotai/kimi-latest":{"id":"~moonshotai/kimi-latest","name":"Kimi Latest","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.294,"output":28,"cache_read":0.284}},"poolside/laguna-s-2.1:free":{"id":"poolside/laguna-s-2.1:free","name":"Laguna S 2.1 (free)","description":"Free provider route for experiments, demos, and cost-sensitive chat workloads","family":"laguna-s","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0}},"poolside/laguna-s-2.1":{"id":"poolside/laguna-s-2.1","name":"Laguna S 2.1","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"laguna-s","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.09,"output":0.18,"cache_read":0.009}},"poolside/laguna-xs-2.1:free":{"id":"poolside/laguna-xs-2.1:free","name":"Laguna XS 2.1 (free)","description":"Free provider route for experiments, demos, and cost-sensitive chat workloads","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-02","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"poolside/laguna-xs-2.1"},"poolside/laguna-xs-2.1":{"id":"poolside/laguna-xs-2.1","name":"Laguna XS 2.1","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-02","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.06,"output":0.12,"cache_read":0.03},"canonical_model_id":"poolside/laguna-xs-2.1"},"prism-ml/ternary-bonsai-2-27b":{"id":"prism-ml/ternary-bonsai-2-27b","name":"Ternary Bonsai 2 27B","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-18","last_updated":"2026-09-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.075,"output":0.5,"cache_read":0.0375}},"anthropic/claude-opus-4.1":{"id":"anthropic/claude-opus-4.1","name":"Claude Opus 4.1 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1"},"anthropic/claude-opus-4.5":{"id":"anthropic/claude-opus-4.5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-opus-4.6":{"id":"anthropic/claude-opus-4.6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5}},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5}},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic/claude-haiku-5.5":{"id":"anthropic/claude-haiku-5.5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-haiku-4.5":{"id":"anthropic/claude-haiku-4.5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-sonnet-5.5":{"id":"anthropic/claude-sonnet-5.5","name":"Claude Sonnet 5.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-fable-5.1":{"id":"anthropic/claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-sonnet-4.5":{"id":"anthropic/claude-sonnet-4.5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-5.5":{"id":"anthropic/claude-opus-5.5","name":"Claude Opus 5.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"nex-agi/nex-n2.5-mini":{"id":"nex-agi/nex-n2.5-mini","name":"Nex-N2.5-Mini","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"agi","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.025,"output":0.1,"cache_read":0.0025}},"nex-agi/nex-n2.5-pro":{"id":"nex-agi/nex-n2.5-pro","name":"Nex-N2.5-Pro","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"agi","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.075,"output":0.25,"cache_read":0.015}},"cohere/command-r-08-2024":{"id":"cohere/command-r-08-2024","name":"Command R","description":"Cohere retrieval model for long-context chat and enterprise RAG workflows","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"cohere/command-r-08-2024"},"cohere/command-a-plus":{"id":"cohere/command-a-plus","name":"Command A+","description":"Cohere command model for multilingual enterprise agents, tools, and chat","family":"command-a","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":192000,"output":64000},"cost":{"input":0.3,"output":1.5,"cache_read":0.15}},"cohere/command-a":{"id":"cohere/command-a","name":"Command A","description":"Cohere command model for multilingual enterprise agents, tools, and chat","family":"command-a","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-03-13","last_updated":"2025-03-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-a"},"cohere/north-mini-code:free":{"id":"cohere/north-mini-code:free","name":"North Mini Code (free)","description":"Cohere coding model for practical software engineering and agentic edits","family":"north","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-17","last_updated":"2026-06-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0,"output":0}},"cohere/command-r7b-12-2024":{"id":"cohere/command-r7b-12-2024","name":"Command R7B","description":"Cohere retrieval model for long-context chat and enterprise RAG workflows","family":"command-r","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-12-02","last_updated":"2024-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.0375,"output":0.15},"canonical_model_id":"cohere/command-r7b-12-2024"},"cohere/command-r-plus-08-2024":{"id":"cohere/command-r-plus-08-2024","name":"Command R+","description":"Cohere's RAG workhorse for long-context enterprise search and tool use","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-r-plus-08-2024"},"deepseek/deepseek-chat-v3.1":{"id":"deepseek/deepseek-chat-v3.1","name":"DeepSeek V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":32768},"cost":{"input":0.25,"output":0.95,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-chat-v3.1"},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":0.018,"output":1.28,"cache_read":0.018},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":0.036,"output":0.6633,"cache_read":0.0054},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-flash-vision-exp":{"id":"deepseek/deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":0.2156,"output":0.6468,"cache_read":0.00686},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"deepseek/deepseek-v3.1-terminus":{"id":"deepseek/deepseek-v3.1-terminus","name":"DeepSeek V3.1 Terminus","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-22","last_updated":"2025-09-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":147456},"cost":{"input":0.27,"output":1}},"deepseek/deepseek-chat":{"id":"deepseek/deepseek-chat","name":"DeepSeek Chat","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-12-01","last_updated":"2026-02-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":16384},"cost":{"input":0.32,"output":0.89},"canonical_model_id":"deepseek/deepseek-chat"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.66,"output":1.98,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek/deepseek-v3.2-exp":{"id":"deepseek/deepseek-v3.2-exp","name":"DeepSeek V3.2 Exp","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":147456},"cost":{"input":0.27,"output":0.41}},"deepseek/deepseek-chat-v3-0324":{"id":"deepseek/deepseek-chat-v3-0324","name":"DeepSeek V3 0324","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07-31","release_date":"2025-03-24","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":115200},"cost":{"input":0.29,"output":1.14,"cache_read":0.11},"canonical_model_id":"deepseek/deepseek-chat-v3-0324"},"deepseek/deepseek-r1":{"id":"deepseek/deepseek-r1","name":"DeepSeek-R1","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":16000},"cost":{"input":0.7,"output":2.5},"canonical_model_id":"deepseek/deepseek-r1"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.31755,"output":0.6351,"cache_read":0.026463},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-r1-0528":{"id":"deepseek/deepseek-r1-0528","name":"DeepSeek R1 0528","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":32768},"cost":{"input":0.5,"output":2.15,"cache_read":0.35},"canonical_model_id":"deepseek/deepseek-r1-0528"},"deepseek/deepseek-v3.2":{"id":"deepseek/deepseek-v3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":147456},"cost":{"input":0.259,"output":0.8,"cache_read":0.14},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943717},"cost":{"input":0.091,"output":0.182,"cache_read":0.0182},"canonical_model_id":"deepseek/deepseek-v4-flash"},"unbiased/pareto-26.9":{"id":"unbiased/pareto-26.9","name":"Pareto 26.9","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":2.5,"output":7.5,"cache_read":0.25}},"tencent/hy3-preview":{"id":"tencent/hy3-preview","name":"Hy3 preview","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.18,"output":0.6,"cache_read":0.06},"canonical_model_id":"tencent/hy3-preview"},"tencent/hunyuan-a13b-instruct":{"id":"tencent/hunyuan-a13b-instruct","name":"Hunyuan A13B Instruct","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"hunyuan","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-07-08","last_updated":"2025-07-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.14,"output":0.57}},"tencent/hy-mt2-30b-a3b":{"id":"tencent/hy-mt2-30b-a3b","name":"Hy-MT2-30B-A3B","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-08-20","last_updated":"2026-08-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":4096},"cost":{"input":0.074,"output":0.295},"canonical_model_id":"tencent/hy-mt2-30b-a3b"},"tencent/hy-mt2-1.8b":{"id":"tencent/hy-mt2-1.8b","name":"Hy-MT2-1.8B","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-08-20","last_updated":"2026-08-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":4096},"cost":{"input":0.044,"output":0.177},"canonical_model_id":"tencent/hy-mt2-1.8b"},"tencent/hy3":{"id":"tencent/hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":192000,"output":128000},"cost":{"input":0.0825,"output":0.33,"cache_read":0.020625},"canonical_model_id":"tencent/hy3"},"tencent/hy-mt2-7b":{"id":"tencent/hy-mt2-7b","name":"Hy-MT2-7B","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-08-19","last_updated":"2026-08-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":4096},"cost":{"input":0.074,"output":0.295},"canonical_model_id":"tencent/hy-mt2-7b"},"tencent/hy4-preview":{"id":"tencent/hy4-preview","name":"Hy4 preview","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":64000},"cost":{"input":0.7506,"output":2.2509,"cache_read":0.0378},"canonical_model_id":"tencent/hy4-preview"},"anthracite-org/magnum-v4-72b":{"id":"anthracite-org/magnum-v4-72b","name":"Magnum v4 72B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":4096},"cost":{"input":2.5,"output":5}},"meta-llama/llama-4-scout":{"id":"meta-llama/llama-4-scout","name":"Llama 4 Scout","description":"Open multimodal Llama model for long-context analysis and efficient agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1310720,"output":16384},"cost":{"input":0.1,"output":0.3}},"meta-llama/llama-guard-4-12b":{"id":"meta-llama/llama-guard-4-12b","name":"Llama Guard 4 12B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-04-30","last_updated":"2025-04-30","modalities":{"input":["image","text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":16384},"cost":{"input":0.18,"output":0.18}},"meta-llama/llama-4-maverick":{"id":"meta-llama/llama-4-maverick","name":"Llama 4 Maverick","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":16384},"cost":{"input":0.1875,"output":0.6525,"cache_read":0.05}},"meta-llama/llama-3.3-70b-instruct":{"id":"meta-llama/llama-3.3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.1,"output":0.32},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"meta-llama/llama-3.1-8b-instruct":{"id":"meta-llama/llama-3.1-8b-instruct","name":"Llama-3.1-8B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.05,"output":0.08,"cache_read":0.025},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"meta-llama/llama-3.2-1b-instruct":{"id":"meta-llama/llama-3.2-1b-instruct","name":"Llama 3.2 1B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":60000,"output":54000},"cost":{"input":0.027,"output":0.201},"canonical_model_id":"meta/llama-3.2-1b-instruct"},"meta-llama/llama-3.2-3b-instruct":{"id":"meta-llama/llama-3.2-3b-instruct","name":"Llama 3.2 3B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.05,"output":0.33}},"meta-llama/llama-3.1-70b-instruct":{"id":"meta-llama/llama-3.1-70b-instruct","name":"Llama-3.1-70B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.4,"output":0.4},"canonical_model_id":"meta/llama-3.1-70b-instruct"},"~google/gemini-flash-latest":{"id":"~google/gemini-flash-latest","name":"Gemini Flash Latest","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"reasoning":3.75,"cache_read":0.075,"cache_write":0.041667}},"~google/gemini-pro-latest":{"id":"~google/gemini-pro-latest","name":"Gemini Pro Latest","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["audio","pdf","image","text","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":10,"reasoning":10,"cache_read":0.1,"cache_write":0.1875,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}}},"~unbiased/pareto-latest":{"id":"~unbiased/pareto-latest","name":"Pareto Latest","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":2.5,"output":7.5,"cache_read":0.25}},"perceptron/perceptron-mk1":{"id":"perceptron/perceptron-mk1","name":"Perceptron Mk1","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-05-12","last_updated":"2026-05-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":8192},"cost":{"input":0.15,"output":1.5}},"perceptron/perceptron-mk1.5":{"id":"perceptron/perceptron-mk1.5","name":"Perceptron Mk1.5","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-25","last_updated":"2026-09-25","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":36864,"output":8192},"cost":{"input":0.15,"output":1.5}},"z-ai/glm-4.6v":{"id":"z-ai/glm-4.6v","name":"GLM-4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.3,"output":0.9,"cache_read":0.055},"canonical_model_id":"zhipuai/glm-4.6v"},"z-ai/glm-4.5":{"id":"z-ai/glm-4.5","name":"GLM-4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5"},"z-ai/glm-5.3-prime":{"id":"z-ai/glm-5.3-prime","name":"GLM 5.3 Prime","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2.8,"output":8.8,"cache_read":0.56}},"z-ai/glm-5v-turbo":{"id":"z-ai/glm-5v-turbo","name":"GLM-5V-Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5v-turbo"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.0244,"output":0.6872,"cache_read":0.0125},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-4.6":{"id":"z-ai/glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.5,"output":2,"cache_read":0.1},"canonical_model_id":"zhipuai/glm-4.6"},"z-ai/glm-5":{"id":"z-ai/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"z-ai/glm-4.5v":{"id":"z-ai/glm-4.5v","name":"GLM-4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":16384},"cost":{"input":0.6,"output":1.8,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5v"},"z-ai/glm-5.3-flashx":{"id":"z-ai/glm-5.3-flashx","name":"GLM 5.3 FlashX","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-18","last_updated":"2026-09-18","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.37,"output":1.25,"cache_read":0.09}},"z-ai/glm-4.7-flash":{"id":"z-ai/glm-4.7-flash","name":"GLM-4.7-Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":117964},"cost":{"input":0.0605,"output":0.4},"canonical_model_id":"zhipuai/glm-4.7-flash"},"z-ai/glm-4.7":{"id":"z-ai/glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.7"},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":0.62,"output":2.42,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/glm-5.1":{"id":"z-ai/glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":128000},"cost":{"input":0.966,"output":3.036,"cache_read":0.1794},"canonical_model_id":"zhipuai/glm-5.1"},"z-ai/glm-5-turbo":{"id":"z-ai/glm-5-turbo","name":"GLM-5-Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5-turbo"},"z-ai/glm-4.5-air":{"id":"z-ai/glm-4.5-air","name":"GLM-4.5-Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.13,"output":0.85,"cache_read":0.025},"canonical_model_id":"zhipuai/glm-4.5-air"},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":0.079,"output":4.8,"cache_read":0.078},"canonical_model_id":"zhipuai/glm-5.3"},"reflection/beam-1.0-501b-a23b":{"id":"reflection/beam-1.0-501b-a23b","name":"Beam 1.0 501B A23B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-06-30","release_date":"2026-10-16","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.25,"output":1}},"inference-net/schematron-v2-small":{"id":"inference-net/schematron-v2-small","name":"Schematron V2 Small","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-09-12","last_updated":"2026-09-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.05,"output":0.23,"cache_read":0.05}},"inference-net/schematron-v2-turbo":{"id":"inference-net/schematron-v2-turbo","name":"Schematron V2 Turbo","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-09-12","last_updated":"2026-09-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.03,"output":0.15,"cache_read":0.03}},"thinkingmachines/inkling-small:free":{"id":"thinkingmachines/inkling-small:free","name":"Inkling Small (free)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/inkling-small":{"id":"thinkingmachines/inkling-small","name":"Inkling Small","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":262144},"cost":{"input":0.45,"output":1.2,"cache_read":0.1},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/inkling:free":{"id":"thinkingmachines/inkling:free","name":"Inkling (free)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"thinkingmachines/inkling"},"thinkingmachines/inkling":{"id":"thinkingmachines/inkling","name":"Inkling","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":471859},"cost":{"input":1,"output":4.05,"cache_read":0.17},"canonical_model_id":"thinkingmachines/inkling"},"meituan/longcat-2.0":{"id":"meituan/longcat-2.0","name":"LongCat 2.0","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"longcat","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-20","last_updated":"2026-07-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048756,"output":262144},"cost":{"input":0.3,"output":1.2,"cache_read":0.006}},"openrouter/bodybuilder":{"id":"openrouter/bodybuilder","name":"Body Builder (beta)","description":"Preview model for early access evaluation, prototyping, and compatibility testing","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2025-12-05","last_updated":"2025-12-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000}},"openrouter/free":{"id":"openrouter/free","name":"Free Models Router","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-01","last_updated":"2026-02-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":8000},"cost":{"input":0,"output":0}},"openrouter/pareto-code":{"id":"openrouter/pareto-code","name":"Pareto Code Router","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":200000}},"openrouter/fusion":{"id":"openrouter/fusion","name":"Fusion","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000}},"openrouter/auto":{"id":"openrouter/auto","name":"Auto Router","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"auto","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2023-11-08","last_updated":"2023-11-08","modalities":{"input":["text","image","audio","pdf","video"],"output":["text","image"]},"open_weights":false,"limit":{"context":2000000,"output":2000000}},"perplexity/sonar-pro":{"id":"perplexity/sonar-pro","name":"Sonar Pro","description":"Advanced Sonar search model for deeper research and cited synthesis","family":"sonar-pro","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-03-07","last_updated":"2025-03-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8000},"cost":{"input":3,"output":15}},"perplexity/sonar-deep-research":{"id":"perplexity/sonar-deep-research","name":"Sonar Deep Research","description":"Sonar search model for current answers, retrieval, and citation-backed chat","family":"sonar-deep-research","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-03-07","last_updated":"2025-03-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":115200},"cost":{"input":2,"output":8,"reasoning":3}},"perplexity/sonar":{"id":"perplexity/sonar","name":"Sonar","description":"Sonar search model for current answers, retrieval, and citation-backed chat","family":"sonar","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-01-27","last_updated":"2025-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":127072,"output":114364},"cost":{"input":1,"output":1}},"perplexity/sonar-reasoning-pro":{"id":"perplexity/sonar-reasoning-pro","name":"Sonar Reasoning Pro","description":"Web-grounded reasoning model for multi-step research and cited answers","family":"sonar-reasoning","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-03-07","last_updated":"2025-03-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":115200},"cost":{"input":2,"output":8}},"perplexity/sonar-pro-search":{"id":"perplexity/sonar-pro-search","name":"Sonar Pro Search","description":"Advanced Sonar search model for deeper research and cited synthesis","family":"sonar-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-10-30","last_updated":"2025-10-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8000},"cost":{"input":3,"output":15}},"meta/muse-spark-1.3":{"id":"meta/muse-spark-1.3","name":"Muse Spark 1.3","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.3"},"meta/muse-glimmer-30b":{"id":"meta/muse-glimmer-30b","name":"Muse Glimmer 30B","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.3,"output":1.2,"cache_read":0.04},"canonical_model_id":"meta/muse-glimmer-30b"},"meta/muse-wonder":{"id":"meta/muse-wonder","name":"Muse Wonder","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":4,"output":20,"cache_read":0.2}},"meta/muse-spark-1.1":{"id":"meta/muse-spark-1.1","name":"Muse Spark 1.1","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.1"},"meta/muse-spark-1.2":{"id":"meta/muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"meta/muse-spark-1.2-contributor":{"id":"meta/muse-spark-1.2-contributor","name":"Muse Spark 1.2 Contributor","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-08-21","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"meta/muse-spark-1.3-contributor":{"id":"meta/muse-spark-1.3-contributor","name":"Muse Spark 1.3 Contributor","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"meta/muse-spark-open":{"id":"meta/muse-spark-open","name":"Muse Spark Open","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-open"},"nousresearch/hermes-3-llama-3.1-70b":{"id":"nousresearch/hermes-3-llama-3.1-70b","name":"Hermes 3 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"nousresearch","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-18","last_updated":"2024-08-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.7,"output":0.7}},"nousresearch/hermes-3-llama-3.1-405b":{"id":"nousresearch/hermes-3-llama-3.1-405b","name":"Hermes 3 405B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"nousresearch","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-16","last_updated":"2024-08-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":1,"output":1}},"nousresearch/hermes-4-405b":{"id":"nousresearch/hermes-4-405b","name":"Hermes 4 405B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"hermes","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":1,"output":3}},"scaledown/summarize":{"id":"scaledown/summarize","name":"Summarize","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":4000},"cost":{"input":0.04,"output":0}},"scaledown/extract":{"id":"scaledown/extract","name":"Extract","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":900000},"cost":{"input":0.04,"output":0}},"~z-ai/glm-flash-latest":{"id":"~z-ai/glm-flash-latest","name":"GLM Flash Latest","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.0244,"output":0.6872,"cache_read":0.0125}},"~z-ai/glm-latest":{"id":"~z-ai/glm-latest","name":"GLM Latest","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-19","last_updated":"2026-08-19","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.0608,"output":4.4,"cache_read":0.0565}},"arcee-ai/trinity-large-thinking":{"id":"arcee-ai/trinity-large-thinking","name":"Trinity Large Thinking","description":"Reasoning-optimized 398B MoE agent model with extended thinking for long-horizon and multi-turn tool use","family":"trinity","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":80000},"cost":{"input":0.25,"output":0.8,"cache_read":0.06},"canonical_model_id":"arcee-ai/trinity-large-thinking"},"~openai/gpt-terra-latest":{"id":"~openai/gpt-terra-latest","name":"GPT Terra Latest","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}}},"~openai/gpt-luna-latest":{"id":"~openai/gpt-luna-latest","name":"GPT Luna Latest","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}}},"~openai/gpt-sol-latest":{"id":"~openai/gpt-sol-latest","name":"GPT Sol Latest","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}}},"~openai/gpt-astra-latest":{"id":"~openai/gpt-astra-latest","name":"GPT Astra Latest","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}}},"~openai/gpt-mini-latest":{"id":"~openai/gpt-mini-latest","name":"GPT Mini Latest","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075}},"cognitivecomputations/dolphin-mistral-24b-venice-edition":{"id":"cognitivecomputations/dolphin-mistral-24b-venice-edition","name":"Uncensored","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-04-30","release_date":"2025-07-09","last_updated":"2025-07-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.2,"output":0.9}},"thedrummer/skyfall-36b-v2":{"id":"thedrummer/skyfall-36b-v2","name":"Skyfall 36B V2","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2025-03-10","last_updated":"2025-03-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":29491},"cost":{"input":0.55,"output":0.8,"cache_read":0.25}},"thedrummer/unslopnemo-12b":{"id":"thedrummer/unslopnemo-12b","name":"UnslopNemo 12B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-04-30","release_date":"2024-11-08","last_updated":"2024-11-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":819200},"cost":{"input":0.4,"output":0.4}},"thedrummer/cydonia-24b-v4.1":{"id":"thedrummer/cydonia-24b-v4.1","name":"Cydonia 24B V4.1","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-04-30","release_date":"2025-09-27","last_updated":"2025-09-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.3,"output":0.5,"cache_read":0.15}},"x-ai/grok-4.20-multi-agent":{"id":"x-ai/grok-4.20-multi-agent","name":"Grok 4.20 Multi-Agent","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-09-01","release_date":"2026-03-31","last_updated":"2026-03-31","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":1800000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"x-ai/grok-4.7":{"id":"x-ai/grok-4.7","name":"Grok 4.7","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"x-ai/grok-4.3":{"id":"x-ai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":900000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.3"},"x-ai/grok-4.5":{"id":"x-ai/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.3,"tiers":[{"input":4,"output":12,"cache_read":0.6,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":0.6}},"canonical_model_id":"xai/grok-4.5"},"x-ai/grok-build-0.1":{"id":"x-ai/grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":230400},"cost":{"input":1,"output":2,"cache_read":0.2,"tiers":[{"input":2,"output":4,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2,"output":4,"cache_read":0.4}},"canonical_model_id":"xai/grok-build-0.1"},"x-ai/grok-4.20":{"id":"x-ai/grok-4.20","name":"Grok 4.20","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09-01","release_date":"2026-03-31","last_updated":"2026-03-31","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":1800000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"x-ai/grok-4.6":{"id":"x-ai/grok-4.6","name":"Grok 4.6","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"~anthropic/claude-opus-latest":{"id":"~anthropic/claude-opus-latest","name":"Claude Opus Latest","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5}},"~anthropic/claude-haiku-latest":{"id":"~anthropic/claude-haiku-latest","name":"Claude Haiku Latest","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]}},"~anthropic/claude-sonnet-latest":{"id":"~anthropic/claude-sonnet-latest","name":"Claude Sonnet Latest","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5}},"~anthropic/claude-fable-latest":{"id":"~anthropic/claude-fable-latest","name":"Claude Fable Latest","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5}},"upstage/solar-pro-3":{"id":"upstage/solar-pro-3","name":"Solar Pro 3","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":117964},"cost":{"input":0.15,"output":0.6,"cache_read":0.015}},"upstage/solar-pro4":{"id":"upstage/solar-pro4","name":"Solar Pro 4","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"solar","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":131072},"cost":{"input":0.09,"output":0.36,"cache_read":0.018}},"upstage/solar-mini4":{"id":"upstage/solar-mini4","name":"Solar Mini 4","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"solar","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":131072},"cost":{"input":0.05,"output":0.2,"cache_read":0.005}},"~deepseek/deepseek-flash-latest":{"id":"~deepseek/deepseek-flash-latest","name":"DeepSeek Flash Latest","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-14","last_updated":"2026-09-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.036,"output":0.6633,"cache_read":0.0054}},"~deepseek/deepseek-pro-latest":{"id":"~deepseek/deepseek-pro-latest","name":"DeepSeek Pro Latest","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-14","last_updated":"2026-09-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":393216},"cost":{"input":0.24948,"output":0.74844,"cache_read":0.007938}},"~deepseek/deepseek-v4-flash-latest":{"id":"~deepseek/deepseek-v4-flash-latest","name":"DeepSeek V4 Flash Latest","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-01","last_updated":"2026-08-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.00441,"output":1.152,"cache_read":0.00441}},"~x-ai/grok-latest":{"id":"~x-ai/grok-latest","name":"Grok Latest","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}}},"bytedance/ui-tars-1.5-7b":{"id":"bytedance/ui-tars-1.5-7b","name":"UI-TARS 7B ","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01-31","release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["image","text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":2048},"cost":{"input":0.1,"output":0.2,"cache_read":0.1}},"liquid/lfm-2.5-2.6b:free":{"id":"liquid/lfm-2.5-2.6b:free","name":"LFM2.5-2.6B (free)","description":"Free provider route for experiments, demos, and cost-sensitive chat workloads","family":"liquid","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":8192},"cost":{"input":0,"output":0}},"liquid/lfm-2.5-24b-a2b":{"id":"liquid/lfm-2.5-24b-a2b","name":"LFM2.5-24B-A2B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"liquid","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.05,"output":0.7,"cache_read":0.025}},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.2,"output":0.4},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemini-3.1-flash-image-preview":{"id":"google/gemini-3.1-flash-image-preview","name":"Nano Banana 2 Preview","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-26","last_updated":"2026-02-26","modalities":{"input":["image","text"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":58982},"cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3.1-flash-image-preview"},"google/lyria-3-pro-preview":{"id":"google/lyria-3-pro-preview","name":"Lyria 3 Pro Preview","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"lyria","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-03-25","last_updated":"2026-03-25","modalities":{"input":["text","image"],"output":["text","audio"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"google/lyria-3-pro-preview"},"google/gemma-3-27b-it":{"id":"google/gemma-3-27b-it","name":"Gemma 3 27B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.08,"output":0.45,"cache_read":0.04},"canonical_model_id":"google/gemma-3-27b-it"},"google/gemma-4-31b-it:free":{"id":"google/gemma-4-31b-it:free","name":"Gemma 4 31B (free)","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemini-2.5-flash-image":{"id":"google/gemini-2.5-flash-image","name":"Nano Banana","description":"Nano Banana image model for fast generation, edits, and character-consistent assets","family":"gemini-flash","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":32768,"output":8192},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":0.083333},"canonical_model_id":"google/gemini-2.5-flash-image"},"google/gemma-4-26b-a4b-it:free":{"id":"google/gemma-4-26b-a4b-it:free","name":"Gemma 4 26B A4B (free)","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemma-2-27b-it":{"id":"google/gemma-2-27b-it","name":"Gemma 2 27B","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2024-07-13","last_updated":"2024-07-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":2048},"cost":{"input":0.65,"output":0.65},"canonical_model_id":"google/gemma-2-27b-it"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"reasoning":3.75,"cache_read":0.075,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.6-flash"},"google/gemma-4-26b-a4b-it":{"id":"google/gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.09,"output":0.3,"cache_read":0.05},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemini-3-pro-image-preview":{"id":"google/gemini-3-pro-image-preview","name":"Nano Banana Pro Preview","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-20","last_updated":"2025-11-20","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":2,"output":12,"reasoning":12,"cache_read":0.2,"cache_write":0.375},"canonical_model_id":"google/gemini-3-pro-image-preview"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"reasoning":2.5,"cache_read":0.03,"cache_write":0.083333},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemini-3.1-flash-image":{"id":"google/gemini-3.1-flash-image","name":"Nano Banana 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["image","text"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3.1-flash-image"},"google/lyria-3-clip-preview":{"id":"google/lyria-3-clip-preview","name":"Lyria 3 Clip Preview","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"lyria","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-03-25","last_updated":"2026-03-25","modalities":{"input":["text","image"],"output":["text","audio"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"google/lyria-3-clip-preview"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"reasoning":12,"cache_read":0.2,"cache_write":0.375,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemma-3-12b-it":{"id":"google/gemma-3-12b-it","name":"Gemma 3 12B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.05,"output":0.15},"canonical_model_id":"google/gemma-3-12b-it"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"reasoning":9,"cache_read":0.15,"cache_write":0.083333},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"reasoning":10,"cache_read":0.125,"cache_write":0.375,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro"},"google/gemini-3-pro-image":{"id":"google/gemini-3-pro-image","name":"Nano Banana Pro","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":2,"output":12,"reasoning":12,"cache_read":0.2,"cache_write":0.375},"canonical_model_id":"google/gemini-3-pro-image"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.3,"output":2.5,"reasoning":2.5,"cache_read":0.03,"cache_write":0.083333},"canonical_model_id":"google/gemini-2.5-flash"},"google/gemini-3.1-flash-lite-image":{"id":"google/gemini-3.1-flash-lite-image","name":"Nano Banana 2 Lite","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":58982},"cost":{"input":0.25,"output":1.5},"canonical_model_id":"google/gemini-3.1-flash-lite-image"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"reasoning":3.75,"cache_read":0.075,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.7-flash"},"google/gemini-3.1-pro-preview-customtools":{"id":"google/gemini-3.1-pro-preview-customtools","name":"Gemini 3.1 Pro Preview Custom Tools","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"reasoning":12,"cache_read":0.2,"cache_write":0.375,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview-customtools"},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"reasoning":3,"cache_read":0.05,"cache_write":0.083333},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.825,"output":4.125,"reasoning":4.125,"cache_read":0.0825,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemma-3-4b-it":{"id":"google/gemma-3-4b-it","name":"Gemma 3 4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.05,"output":0.1},"canonical_model_id":"google/gemma-3-4b-it"},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.1,"output":0.4,"reasoning":0.4,"cache_read":0.01,"cache_write":0.083333},"canonical_model_id":"google/gemini-2.5-flash-lite"},"google/gemini-2.5-pro-preview":{"id":"google/gemini-2.5-pro-preview","name":"Gemini 2.5 Pro Preview 06-05","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01-31","release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["pdf","image","text","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"reasoning":10,"cache_read":0.125,"cache_write":0.375,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro-preview"},"google/gemini-3.1-flash-lite-preview":{"id":"google/gemini-3.1-flash-lite-preview","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"reasoning":1.5,"cache_read":0.025,"cache_write":0.083333},"canonical_model_id":"google/gemini-3.1-flash-lite-preview"},"google/gemini-nano-banana-2.1":{"id":"google/gemini-nano-banana-2.1","name":"Nano Banana 2.1","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["image","text"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":58982},"cost":{"input":1.5,"output":7.5},"canonical_model_id":"google/gemini-nano-banana-2.1"},"google/gemini-4-argon":{"id":"google/gemini-4-argon","name":"Gemini 4 Argon","description":"Gemini multimodal model for text, image, audio, video, and document tasks","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":10,"reasoning":10,"cache_read":0.1,"cache_write":0.1875},"canonical_model_id":"google/gemini-4-argon"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"reasoning":1.5,"cache_read":0.025,"cache_write":0.083333},"canonical_model_id":"google/gemini-3.1-flash-lite"},"writer/palmyra-x5":{"id":"writer/palmyra-x5","name":"Palmyra X5","description":"General-purpose chat model for instruction following, writing, and analysis","family":"palmyra","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-01-21","last_updated":"2026-01-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1040000,"output":8192},"cost":{"input":0.6,"output":6}},"moondream/moondream3-preview":{"id":"moondream/moondream3-preview","name":"Moondream 3 Preview","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":4096},"cost":{"input":0.3,"output":2.5}},"moondream/moondream3.1-9b-a2b":{"id":"moondream/moondream3.1-9b-a2b","name":"Moondream 3.1","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":4096},"cost":{"input":0.3,"output":2.5}},"ibm-granite/granite-4.0-h-micro":{"id":"ibm-granite/granite-4.0-h-micro","name":"Granite 4.0 Micro","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"granite","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-10-20","last_updated":"2025-10-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":117900},"cost":{"input":0.017,"output":0.112}},"ibm-granite/granite-4.2-8b":{"id":"ibm-granite/granite-4.2-8b","name":"Granite 4.2 8B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"granite","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-31","last_updated":"2026-08-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.06,"output":0.25,"cache_read":0.015}},"fireworks/ember-1":{"id":"fireworks/ember-1","name":"Ember-1","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-24","last_updated":"2026-09-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":3,"output":15,"cache_read":0.3}},"mistralai/mistral-nemo":{"id":"mistralai/mistral-nemo","name":"Mistral Nemo","description":"Efficient Mistral-NVIDIA open model for multilingual chat and local deployment","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.029,"output":0.03},"canonical_model_id":"mistral/mistral-nemo"},"mistralai/ministral-8b-2512":{"id":"mistralai/ministral-8b-2512","name":"Ministral 3 8B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.15,"output":0.15,"cache_read":0.015},"canonical_model_id":"mistral/ministral-8b-2512"},"mistralai/mistral-small-24b-instruct-2501":{"id":"mistralai/mistral-small-24b-instruct-2501","name":"Mistral Small 3","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-01-30","last_updated":"2025-01-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"cost":{"input":0.05,"output":0.08},"canonical_model_id":"mistral/mistral-small-24b-instruct-2501"},"mistralai/devstral-2512":{"id":"mistralai/devstral-2512","name":"Devstral 2","description":"Mistral coding agent model for repository tasks and software engineering workflows","family":"devstral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.4,"output":2,"cache_read":0.04},"canonical_model_id":"mistral/devstral-2512"},"mistralai/mistral-saba":{"id":"mistralai/mistral-saba","name":"Saba","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-02-17","last_updated":"2025-02-17","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":26214},"cost":{"input":0.2,"output":0.6,"cache_read":0.02},"canonical_model_id":"mistral/mistral-saba"},"mistralai/mistral-medium-3-5":{"id":"mistralai/mistral-medium-3-5","name":"Mistral Medium 3.5","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":209715},"cost":{"input":1.5,"output":7.5},"canonical_model_id":"mistral/mistral-medium-3-5"},"mistralai/mistral-medium-3.1":{"id":"mistralai/mistral-medium-3.1","name":"Mistral Medium 3.1","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06-30","release_date":"2025-08-13","last_updated":"2025-08-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":104857},"cost":{"input":0.4,"output":2,"cache_read":0.04},"canonical_model_id":"mistral/mistral-medium-3.1"},"mistralai/mistral-small-3.2-24b-instruct":{"id":"mistralai/mistral-small-3.2-24b-instruct","name":"Mistral Small 3.2 24B","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["image","text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":0.09375,"output":0.25},"canonical_model_id":"mistral/mistral-small-3.2-24b-instruct"},"mistralai/mistral-large":{"id":"mistralai/mistral-large","name":"Mistral Large","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11-30","release_date":"2024-02-26","last_updated":"2024-02-26","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":102400},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"mistral/mistral-large"},"mistralai/mistral-small-2603":{"id":"mistralai/mistral-small-2603","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"mistral/mistral-small-2603"},"mistralai/mistral-medium-3":{"id":"mistralai/mistral-medium-3","name":"Mistral Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":104857},"cost":{"input":0.4,"output":2,"cache_read":0.04},"canonical_model_id":"mistral/mistral-medium-3"},"mistralai/voxtral-small-24b-2507":{"id":"mistralai/voxtral-small-24b-2507","name":"Voxtral Small 24B 2507","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"voxtral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":26214},"cost":{"input":0.1,"output":0.3,"cache_read":0.01},"canonical_model_id":"mistral/voxtral-small-24b-2507"},"mistralai/mistral-large-2512":{"id":"mistralai/mistral-large-2512","name":"Mistral Large 3","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.5,"output":1.5,"cache_read":0.05},"canonical_model_id":"mistral/mistral-large-2512"},"mistralai/mistral-large-2407":{"id":"mistralai/mistral-large-2407","name":"Mistral Large 2407","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-03-31","release_date":"2024-11-19","last_updated":"2024-11-19","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":104857},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"mistral/mistral-large-2407"},"mistralai/ministral-14b-2512":{"id":"mistralai/ministral-14b-2512","name":"Ministral 3 14B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.2,"output":0.2,"cache_read":0.02},"canonical_model_id":"mistral/ministral-14b-2512"},"mistralai/mistral-large-4-0":{"id":"mistralai/mistral-large-4-0","name":"Mistral Large 4","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":262144},"cost":{"input":0.68,"output":2.09,"cache_read":0.07}},"mistralai/mistral-small-3.1-24b-instruct":{"id":"mistralai/mistral-small-3.1-24b-instruct","name":"Mistral Small 3.1 24B","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-03-17","last_updated":"2025-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":102400},"cost":{"input":0.351,"output":0.555},"canonical_model_id":"mistral/mistral-small-3.1-24b-instruct"},"mistralai/ministral-3b-2512":{"id":"mistralai/ministral-3b-2512","name":"Ministral 3 3B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":104857},"cost":{"input":0.1,"output":0.1,"cache_read":0.01},"canonical_model_id":"mistral/ministral-3b-2512"},"mistralai/mixtral-8x22b-instruct":{"id":"mistralai/mixtral-8x22b-instruct","name":"Mixtral 8x22B Instruct","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-01-31","release_date":"2024-04-17","last_updated":"2024-04-17","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":52428},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"mistral/mixtral-8x22b-instruct"},"mistralai/codestral-2508":{"id":"mistralai/codestral-2508","name":"Codestral 25.08","description":"Mistral coding model for code completion, generation, and developer workflows","family":"codestral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":204800},"cost":{"input":0.3,"output":0.9,"cache_read":0.03},"canonical_model_id":"mistral/codestral-2508"},"sakana/fugu-max":{"id":"sakana/fugu-max","name":"Fugu Max","description":"Multi-agent model for routing expert agents across complex analytical tasks","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"sakana/fugu-max"},"sakana/fugu-ultra-v2":{"id":"sakana/fugu-ultra-v2","name":"Fugu Ultra v2","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-08-28","release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"sakana/fugu-ultra-v2"},"sakana/fugu-ultra":{"id":"sakana/fugu-ultra","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"sakana/fugu-ultra"},"sakana/sakana-namazu":{"id":"sakana/sakana-namazu","name":"Sakana Namazu","description":"Multi-agent model for routing expert agents across complex analytical tasks","family":"sakana-namazu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.95,"output":4,"cache_read":0.15},"canonical_model_id":"sakana/sakana-namazu"},"inclusionai/ling-3.0-flash":{"id":"inclusionai/ling-3.0-flash","name":"Ling 3.0 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-23","last_updated":"2026-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.021,"output":0.063,"cache_read":0.0042}},"inclusionai/ling-3.1-flash":{"id":"inclusionai/ling-3.1-flash","name":"Ling 3.1 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-02","last_updated":"2026-10-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":235929},"cost":{"input":0.075,"output":0.225,"cache_read":0.015}},"inclusionai/ling-3.0-flash-vl":{"id":"inclusionai/ling-3.0-flash-vl","name":"Ling 3.0 Flash VL","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.06,"output":0.18,"cache_read":0.012}},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":0.304,"output":12.533,"cache_read":0.21},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.65,"output":3.41,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2-thinking":{"id":"moonshotai/kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Thinking Kimi model for slower research passes, planning, and hard technical questions","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":0.6,"output":2.5,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"moonshotai/kimi-k2.5":{"id":"moonshotai/kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.5,"output":2.5,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/kimi-k2-0905":{"id":"moonshotai/kimi-k2-0905","name":"Kimi K2 Instruct 0905","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":0.6,"output":2.5},"canonical_model_id":"moonshotai/kimi-k2-0905"},"moonshotai/kimi-k2":{"id":"moonshotai/kimi-k2","name":"Kimi K2 0711","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-12-31","release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.57,"output":2.3},"canonical_model_id":"moonshotai/kimi-k2"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.6712,"output":3.35,"cache_read":0.18},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"rekaai/reka-flash-3":{"id":"rekaai/reka-flash-3","name":"Reka Flash 3","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"reka","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01-31","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":58982},"cost":{"input":0.1,"output":0.2}},"rekaai/reka-edge":{"id":"rekaai/reka-edge","name":"Reka Edge","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"reka","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-20","last_updated":"2026-03-20","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":14745},"cost":{"input":0.1,"output":0.1}},"nvidia/nemotron-3.5-super-vl:free":{"id":"nvidia/nemotron-3.5-super-vl:free","name":"Nemotron 3.5 Super VL (free)","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0}},"nvidia/nemotron-3-nano-30b-a3b":{"id":"nvidia/nemotron-3-nano-30b-a3b","name":"Nemotron 3 Nano 30B A3B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.06,"output":0.24},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"nvidia/nemotron-3.5-content-safety:free":{"id":"nvidia/nemotron-3.5-content-safety:free","name":"Nemotron 3.5 Content Safety (free)","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-content-safety"},"nvidia/nemotron-3.5-lightning":{"id":"nvidia/nemotron-3.5-lightning","name":"Nemotron 3.5 Lightning 30B A3B","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.07,"output":0.2,"cache_read":0.04},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning:free":{"id":"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning:free","name":"Nemotron 3 Nano Omni (free)","description":"Open Nemotron omni model combining reasoning with text, vision, and audio","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning"},"nvidia/nemotron-3-super-120b-a12b":{"id":"nvidia/nemotron-3-super-120b-a12b","name":"Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.08,"output":0.45},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"nvidia/nemotron-3.5-super-vl":{"id":"nvidia/nemotron-3.5-super-vl","name":"Nemotron 3.5 Super VL","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":235929},"cost":{"input":0.15,"output":0.5,"cache_read":0.02}},"nvidia/nemotron-3-ultra-550b-a55b:free":{"id":"nvidia/nemotron-3-ultra-550b-a55b:free","name":"Nemotron 3 Ultra (free)","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/nemotron-3-ultra-550b-a55b":{"id":"nvidia/nemotron-3-ultra-550b-a55b","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":182520},"cost":{"input":0.6,"output":2.4,"cache_read":0.12},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/nemotron-3-super-120b-a12b:free":{"id":"nvidia/nemotron-3-super-120b-a12b:free","name":"Nemotron 3 Super (free)","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"nvidia/nemotron-3.5-content-safety":{"id":"nvidia/nemotron-3.5-content-safety","name":"Nemotron 3.5 Content Safety","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.2,"output":0.2},"canonical_model_id":"nvidia/nemotron-3.5-content-safety"},"nvidia/nemotron-3.5-lightning:free":{"id":"nvidia/nemotron-3.5-lightning:free","name":"Nemotron 3.5 Lightning (free)","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"xiaomi/mimo-v2.6-pro":{"id":"xiaomi/mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"MiMo pro model for strong multimodal reasoning and agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"xiaomi/mimo-v2.5":{"id":"xiaomi/mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.5"},"xiaomi/mimo-v2.6-pro-ultraspeed":{"id":"xiaomi/mimo-v2.6-pro-ultraspeed","name":"MiMo-V2.6-Pro-UltraSpeed","description":"MiMo pro model for strong multimodal reasoning and agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":4.35,"output":8.7,"cache_read":0.036},"canonical_model_id":"xiaomi/mimo-v2.6-pro-ultraspeed"},"xiaomi/mimo-v2.5-pro":{"id":"xiaomi/mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"xiaomi/mimo-v2.6-flash":{"id":"xiaomi/mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo flash model for fast multimodal assistance and agent workflows","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"undi95/remm-slerp-l2-13b":{"id":"undi95/remm-slerp-l2-13b","name":"ReMM SLERP 13B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-06-30","release_date":"2023-07-22","last_updated":"2023-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":6144,"output":5529},"cost":{"input":0.35,"output":0.65}},"gryphe/mythomax-l2-13b":{"id":"gryphe/mythomax-l2-13b","name":"MythoMax 13B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-06-30","release_date":"2023-07-02","last_updated":"2023-07-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":3686},"cost":{"input":0.08,"output":0.11}},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":32768},"cost":{"input":0.27,"output":0.95,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5"},"minimax/minimax-01":{"id":"minimax/minimax-01","name":"MiniMax-01","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-03-31","release_date":"2025-01-15","last_updated":"2025-01-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000192,"output":40000},"cost":{"input":0.2,"output":1.1}},"minimax/minimax-m2-her":{"id":"minimax/minimax-m2-her","name":"MiniMax-M2 Her","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-01-23","last_updated":"2026-01-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"output":2048},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2-Her"},"minimax/minimax-m2.7":{"id":"minimax/minimax-m2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/minimax-m1":{"id":"minimax/minimax-m1","name":"MiniMax M1","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-06-30","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":40000},"cost":{"input":0.55,"output":2.2}},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"minimax/minimax-m2.1":{"id":"minimax/minimax-m2.1","name":"MiniMax-M2.1","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":false,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.1"},"minimax/minimax-m2":{"id":"minimax/minimax-m2","name":"MiniMax-M2","description":"Efficient open MiniMax model built for coding agents and tool-heavy workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.255,"output":1.02},"canonical_model_id":"minimax/MiniMax-M2"},"mancer/weaver":{"id":"mancer/weaver","name":"Weaver (alpha)","description":"General-purpose chat model for instruction following, writing, and analysis","family":"alpha","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-06-30","release_date":"2023-08-02","last_updated":"2023-08-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8000,"output":6000},"cost":{"input":0.4,"output":0.75}},"stepfun/step-5-preview":{"id":"stepfun/step-5-preview","name":"Step 5 Preview","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1000000,"output":64000},"cost":{"input":1,"output":2.7,"cache_read":0.1},"canonical_model_id":"stepfun/step-5-preview"},"stepfun/step-3.5-flash":{"id":"stepfun/step-3.5-flash","name":"Step 3.5 Flash","description":"StepFun flash lane for quick multimodal reasoning and coding assistance","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"stepfun/step-3.5-flash"},"stepfun/step-3.7-flash":{"id":"stepfun/step-3.7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":256000,"output":230400},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"dots-studio/dots-3-note-preview:free":{"id":"dots-studio/dots-3-note-preview:free","name":"Dots3-Note Preview (free)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":512000,"output":460800},"cost":{"input":0,"output":0}},"inception/mercury-2.5":{"id":"inception/mercury-2.5","name":"Mercury 2.5","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":260000,"output":65536},"cost":{"input":0.04,"output":0.15,"cache_read":0.004}},"inception/mercury-2":{"id":"inception/mercury-2","name":"Mercury 2","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-04","last_updated":"2026-03-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":50000},"cost":{"input":0.25,"output":0.75,"cache_read":0.025}},"amazon/nova-lite-v1":{"id":"amazon/nova-lite-v1","name":"Nova Lite 1.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":5120},"cost":{"input":0.06,"output":0.24}},"amazon/nova-2-lite-v1":{"id":"amazon/nova-2-lite-v1","name":"Nova 2 Lite","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.3,"output":2.5}},"amazon/nova-pro-v1":{"id":"amazon/nova-pro-v1","name":"Nova Pro 1.0","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":5120},"cost":{"input":0.8,"output":3.2}},"amazon/nova-premier-v1":{"id":"amazon/nova-premier-v1","name":"Nova Premier 1.0","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-10-31","last_updated":"2025-10-31","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32000},"cost":{"input":2.5,"output":12.5,"cache_read":0.625}},"amazon/nova-micro-v1":{"id":"amazon/nova-micro-v1","name":"Nova Micro 1.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-micro","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":5120},"cost":{"input":0.035,"output":0.14}},"relace/relace-search":{"id":"relace/relace-search","name":"Relace Search","description":"Tool-capable chat model for instruction following and agentic application workflows","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":1,"output":3}},"relace/relace-apply-3":{"id":"relace/relace-apply-3","name":"Relace Apply 3","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2025-09-26","last_updated":"2025-09-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.85,"output":1.25}},"aion-labs/aion-2.0":{"id":"aion-labs/aion-2.0","name":"Aion-2.0","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.8,"output":1.6,"cache_read":0.2}},"aion-labs/aion-rp-llama-3.1-8b":{"id":"aion-labs/aion-rp-llama-3.1-8b","name":"Aion-RP 1.0 (8B)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12-31","release_date":"2025-02-04","last_updated":"2025-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":29491},"cost":{"input":0.8,"output":1.6}},"aion-labs/aion-3.0":{"id":"aion-labs/aion-3.0","name":"Aion-3.0","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-07","last_updated":"2026-07-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":3,"output":6,"cache_read":0.75}},"aion-labs/aion-3.5":{"id":"aion-labs/aion-3.5","name":"Aion 3.5","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":3,"output":6,"cache_read":0.75}},"aion-labs/aion-3.5-mini":{"id":"aion-labs/aion-3.5-mini","name":"Aion 3.5 Mini","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.7,"output":1.4,"cache_read":0.18}},"aion-labs/aion-3.0-mini":{"id":"aion-labs/aion-3.0-mini","name":"Aion-3.0-Mini","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-07","last_updated":"2026-07-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.7,"output":1.4,"cache_read":0.18}},"qwen/qwen3-235b-a22b-2507":{"id":"qwen/qwen3-235b-a22b-2507","name":"Qwen3 235B A22B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06-30","release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.09,"output":0.55}},"qwen/qwen3-vl-235b-a22b-instruct":{"id":"qwen/qwen3-vl-235b-a22b-instruct","name":"Qwen3 VL 235B A22B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.21,"output":1.9,"cache_read":0.1},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":1.475,"output":4.425,"cache_read":0.295,"cache_write":1.84375},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":235929},"cost":{"input":0.24,"output":2.2,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3.8-2.4t-a95b":{"id":"qwen/qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"qwen/qwen3.5-27b":{"id":"qwen/qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":81920},"cost":{"input":0.26,"output":2.6},"canonical_model_id":"alibaba/qwen3.5-27b"},"qwen/qwen3-next-80b-a3b-thinking":{"id":"qwen/qwen3-next-80b-a3b-thinking","name":"Qwen3-Next 80B-A3B (Thinking)","description":"Efficient Qwen thinking model for local reasoning, math, and coding agents","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.15,"output":1.2},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-thinking"},"qwen/qwen3-coder-next":{"id":"qwen/qwen3-coder-next","name":"Qwen3 Coder Next","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.12,"output":0.8,"cache_read":0.07},"canonical_model_id":"alibaba/qwen3-coder-next"},"qwen/qwen3-coder":{"id":"qwen/qwen3-coder","name":"Qwen3 Coder 480B A35B","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06-30","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.3,"output":1,"cache_read":0.1}},"qwen/qwen3-32b":{"id":"qwen/qwen3-32b","name":"Qwen3 32B","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.08,"output":0.28},"canonical_model_id":"alibaba/qwen3-32b"},"qwen/qwen-plus":{"id":"qwen/qwen-plus","name":"Qwen Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.26,"output":0.78,"cache_read":0.052,"cache_write":0.325,"tiers":[{"input":0.78,"output":2.34,"cache_read":0.156,"cache_write":0.975,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.78,"output":2.34,"cache_read":0.156,"cache_write":0.975}},"canonical_model_id":"alibaba/qwen-plus"},"qwen/qwen3.7-flash":{"id":"qwen/qwen3.7-flash","name":"Qwen3.7 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":991808,"output":65536},"cost":{"input":0.03,"output":0.13,"cache_read":0.006,"cache_write":0.038,"tiers":[{"input":0.1,"output":0.4,"cache_read":0.02,"cache_write":0.125,"tier":{"type":"context","size":32000}},{"input":0.2,"output":0.8,"cache_read":0.04,"cache_write":0.25,"tier":{"type":"context","size":256000}}]},"canonical_model_id":"alibaba/qwen3.7-flash"},"qwen/qwen3-coder-30b-a3b-instruct":{"id":"qwen/qwen3-coder-30b-a3b-instruct","name":"Qwen3-Coder 30B-A3B Instruct","description":"Smaller Qwen coder for efficient local agents and repo-level fixes","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.07,"output":0.28},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"qwen/qwen3.8-omni-flash":{"id":"qwen/qwen3.8-omni-flash","name":"Qwen3.8 Omni Flash","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-omni-flash"},"qwen/qwen3-vl-30b-a3b-instruct":{"id":"qwen/qwen3-vl-30b-a3b-instruct","name":"Qwen3 VL 30B A3B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-04","last_updated":"2025-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"alibaba/qwen3-vl-30b-a3b-instruct"},"qwen/qwen3-235b-a22b-thinking-2507":{"id":"qwen/qwen3-235b-a22b-thinking-2507","name":"Qwen3 235B A22B Thinking 2507","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-06-30","release_date":"2025-07-25","last_updated":"2025-07-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.45,"output":3.5}},"qwen/qwen3.5-122b-a10b":{"id":"qwen/qwen3.5-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.26,"output":2.08},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"qwen/qwen3.6-35b-a3b":{"id":"qwen/qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.15,"output":1,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"qwen/qwen3-next-80b-a3b-instruct":{"id":"qwen/qwen3-next-80b-a3b-instruct","name":"Qwen3-Next 80B-A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.09,"output":1.1},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"qwen/qwen3-vl-30b-a3b-thinking":{"id":"qwen/qwen3-vl-30b-a3b-thinking","name":"Qwen3 VL 30B A3B Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.29,"output":1}},"qwen/qwen3.6-flash":{"id":"qwen/qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.1875,"output":1.125,"cache_write":0.234375,"tiers":[{"input":0.75,"output":3,"cache_write":0.9375,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.75,"output":3,"cache_write":0.9375}},"canonical_model_id":"alibaba/qwen3.6-flash"},"qwen/qwen3-coder-flash":{"id":"qwen/qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.195,"output":0.975,"cache_read":0.039,"cache_write":0.24375,"tiers":[{"input":0.325,"output":1.625,"cache_read":0.065,"cache_write":0.40625,"tier":{"type":"context","size":32000}},{"input":0.52,"output":2.6,"cache_read":0.104,"cache_write":0.65,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3-coder-flash"},"qwen/qwen-2.5-coder-32b-instruct":{"id":"qwen/qwen-2.5-coder-32b-instruct","name":"Qwen2.5 Coder 32B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-06-30","release_date":"2024-11-11","last_updated":"2024-11-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":29491},"cost":{"input":0.66,"output":1}},"qwen/qwen3.5-flash-02-23":{"id":"qwen/qwen3.5-flash-02-23","name":"Qwen3.5-Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-25","last_updated":"2026-02-25","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.065,"output":0.26}},"qwen/qwen3.5-9b":{"id":"qwen/qwen3.5-9b","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.1,"output":0.15},"canonical_model_id":"alibaba/qwen3.5-9b"},"qwen/qwen3.8-max-prime":{"id":"qwen/qwen3.8-max-prime","name":"Qwen 3.8 Max Prime","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.8-max","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":4,"output":12,"cache_read":0.5},"canonical_model_id":"alibaba/qwen3.8-max-prime"},"qwen/qwen3.5-plus-20260420":{"id":"qwen/qwen3.5-plus-20260420","name":"Qwen3.5 Plus 2026-04-20","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.5","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.3,"output":1.8,"cache_write":0.375,"tiers":[{"input":0.375,"output":2.25,"cache_write":0.46875,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.375,"output":2.25,"cache_write":0.46875}}},"qwen/qwen3.8-flash":{"id":"qwen/qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen/qwen3.5-35b-a3b":{"id":"qwen/qwen3.5-35b-a3b","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.15,"output":1,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"qwen/qwen3-30b-a3b":{"id":"qwen/qwen3-30b-a3b","name":"Qwen3 30B A3B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":16384},"cost":{"input":0.12,"output":0.5},"canonical_model_id":"alibaba/qwen3-30b-a3b"},"qwen/qwen3.5-397b-a17b":{"id":"qwen/qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.5,"output":3.6,"cache_read":0.3},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"qwen/qwen3-vl-8b-instruct":{"id":"qwen/qwen3-vl-8b-instruct","name":"Qwen3 VL 8B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-14","last_updated":"2025-10-14","modalities":{"input":["image","text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.25,"output":0.75,"cache_read":0.12}},"qwen/qwen3-30b-a3b-instruct-2507":{"id":"qwen/qwen3-30b-a3b-instruct-2507","name":"Qwen3 30B A3B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06-30","release_date":"2025-07-29","last_updated":"2025-07-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.1,"output":0.3}},"qwen/qwen2.5-vl-72b-instruct":{"id":"qwen/qwen2.5-vl-72b-instruct","name":"Qwen2.5 VL 72B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2025-02-01","last_updated":"2025-02-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":115200},"cost":{"input":0.8,"output":1,"cache_read":0.4}},"qwen/qwen-2.5-7b-instruct":{"id":"qwen/qwen-2.5-7b-instruct","name":"Qwen2.5 7B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2024-10-16","last_updated":"2024-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":29491},"cost":{"input":0.1,"output":0.2}},"qwen/qwen3.5-plus-02-15":{"id":"qwen/qwen3.5-plus-02-15","name":"Qwen3.5 Plus 2026-02-15","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.26,"output":1.56,"tiers":[{"input":0.325,"output":1.95,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.325,"output":1.95}}},"qwen/qwen-2.5-72b-instruct":{"id":"qwen/qwen-2.5-72b-instruct","name":"Qwen2.5 72B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2024-09-19","last_updated":"2024-09-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"cost":{"input":0.36,"output":0.4}},"qwen/qwen3.6-27b":{"id":"qwen/qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"alibaba/qwen3.6-27b"},"qwen/qwen3.6-plus":{"id":"qwen/qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.325,"output":1.95,"cache_write":0.40625,"tiers":[{"input":1.3,"output":3.9,"cache_write":1.625,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1.3,"output":3.9,"cache_write":1.625}},"canonical_model_id":"alibaba/qwen3.6-plus"},"qwen/qwen3-14b":{"id":"qwen/qwen3-14b","name":"Qwen3 14B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":16384},"cost":{"input":0.12,"output":0.24}},"qwen/qwen3.7-plus":{"id":"qwen/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.32,"output":1.28,"cache_read":0.064,"cache_write":0.4,"tiers":[{"input":0.96,"output":3.84,"cache_read":0.192,"cache_write":1.2,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.96,"output":3.84,"cache_read":0.192,"cache_write":1.2}},"canonical_model_id":"alibaba/qwen3.7-plus"},"qwen/qwen3.8-max-0902":{"id":"qwen/qwen3.8-max-0902","name":"Qwen3.8 Max 0902","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-max-0902"},"morph/morph-v3-large":{"id":"morph/morph-v3-large","name":"Morph V3 Large","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"morph","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-07-07","last_updated":"2025-07-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.9,"output":1.9}},"morph/morph-v3-fast":{"id":"morph/morph-v3-fast","name":"Morph V3 Fast","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"morph","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-07-07","last_updated":"2025-07-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":81920,"output":38000},"cost":{"input":0.8,"output":1.2}},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.4-image-2":{"id":"openai/gpt-5.4-image-2","name":"GPT-5.4 Image 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":false,"structured_output":true,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["image","text","pdf"],"output":["image","text"]},"open_weights":false,"limit":{"context":272000,"output":128000},"cost":{"input":8,"output":15,"cache_read":2},"canonical_model_id":"openai/gpt-5.4-image-2"},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.4-pro"},"openai/gpt-audio":{"id":"openai/gpt-audio","name":"GPT Audio","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10}},"openai/gpt-3.5-turbo":{"id":"openai/gpt-3.5-turbo","name":"GPT-3.5-turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"output":4096},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"openai/gpt-3.5-turbo"},"openai/gpt-6-astra-pro":{"id":"openai/gpt-6-astra-pro","name":"GPT-6 Astra Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}}},"openai/gpt-5.5-pro":{"id":"openai/gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.5-pro"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-4o-2024-05-13":{"id":"openai/gpt-4o-2024-05-13","name":"GPT-4o (2024-05-13)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-05-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":5,"output":15},"canonical_model_id":"openai/gpt-4o-2024-05-13"},"openai/gpt-4o-mini-2024-07-18":{"id":"openai/gpt-4o-mini-2024-07-18","name":"GPT-4o-mini (2024-07-18)","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"o-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075}},"openai/gpt-5.2-codex":{"id":"openai/gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Code-specialist GPT for repository edits, reviews, and long-running software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-codex"},"openai/gpt-5.1-codex":{"id":"openai/gpt-5.1-codex","name":"GPT-5.1 Codex","description":"Codex GPT for repository edits, code review, and practical software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.13},"canonical_model_id":"openai/gpt-5.1-codex"},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-chat-latest":{"id":"openai/gpt-chat-latest","name":"GPT Chat Latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-05-05","last_updated":"2026-05-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5}},"openai/gpt-audio-mini":{"id":"openai/gpt-audio-mini","name":"GPT Audio Mini","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"o-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.6,"output":2.4}},"openai/gpt-5.6-sol-pro":{"id":"openai/gpt-5.6-sol-pro","name":"GPT-5.6 Sol Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"openai/gpt-5.2-pro":{"id":"openai/gpt-5.2-pro","name":"GPT-5.2 Pro","description":"Higher-accuracy GPT-5.2 variant for tougher reasoning and review workflows","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":21,"output":168},"canonical_model_id":"openai/gpt-5.2-pro"},"openai/o4-mini":{"id":"openai/o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.275},"canonical_model_id":"openai/o4-mini"},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"openai/gpt-4":{"id":"openai/gpt-4","name":"GPT-4","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-11","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8191,"output":4096},"cost":{"input":30,"output":60},"canonical_model_id":"openai/gpt-4"},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"openai/o1":{"id":"openai/o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":15,"output":60,"cache_read":7.5},"canonical_model_id":"openai/o1"},"openai/gpt-5-pro":{"id":"openai/gpt-5-pro","name":"GPT-5 Pro","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":15,"output":120},"canonical_model_id":"openai/gpt-5-pro"},"openai/gpt-3.5-turbo-instruct":{"id":"openai/gpt-3.5-turbo-instruct","name":"GPT-3.5 Turbo Instruct","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2021-09-30","release_date":"2023-09-28","last_updated":"2023-09-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":4095,"output":3685},"cost":{"input":1.5,"output":2}},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-4o-2024-08-06":{"id":"openai/gpt-4o-2024-08-06","name":"GPT-4o (2024-08-06)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-08-06","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-08-06"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"openai/gpt-5.6-luna-pro":{"id":"openai/gpt-5.6-luna-pro","name":"GPT-5.6 Luna Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-5-image-mini":{"id":"openai/gpt-5-image-mini","name":"GPT-5 Image Mini","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-10-16","last_updated":"2025-10-16","modalities":{"input":["pdf","image","text"],"output":["image","text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":2.5,"output":2,"cache_read":0.25},"canonical_model_id":"openai/gpt-5-image-mini"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"openai/o3-pro":{"id":"openai/o3-pro","name":"o3-pro","description":"High-effort o3 tier for difficult technical reasoning and careful answers","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-06-10","last_updated":"2025-06-10","modalities":{"input":["text","pdf","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":20,"output":80},"canonical_model_id":"openai/o3-pro"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.018,"output":0.09,"cache_read":0.009},"canonical_model_id":"openai/gpt-oss-20b"},"openai/gpt-oss-safeguard-20b":{"id":"openai/gpt-oss-safeguard-20b","name":"GPT OSS Safeguard 20B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.075,"output":0.3,"cache_read":0.0375},"canonical_model_id":"openai/gpt-oss-safeguard-20b"},"openai/o3-mini-high":{"id":"openai/o3-mini-high","name":"o3 Mini High","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-10-31","release_date":"2025-02-12","last_updated":"2025-02-12","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55}},"openai/gpt-3.5-turbo-16k":{"id":"openai/gpt-3.5-turbo-16k","name":"GPT-3.5 Turbo 16k","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2021-09-30","release_date":"2023-08-28","last_updated":"2023-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"output":4096},"cost":{"input":3,"output":4}},"openai/gpt-5.2-chat":{"id":"openai/gpt-5.2-chat","name":"GPT-5.2 Chat","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt-codex","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-10","last_updated":"2025-12-10","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"openai/gpt-6-sol-pro":{"id":"openai/gpt-6-sol-pro","name":"GPT-6 Sol Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}}},"openai/gpt-5-image":{"id":"openai/gpt-5-image","name":"GPT-5 Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-10-01","release_date":"2025-10-14","last_updated":"2025-10-14","modalities":{"input":["image","text","pdf"],"output":["image","text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":10,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-5-image"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.1-codex-max":{"id":"openai/gpt-5.1-codex-max","name":"GPT-5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex-max"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-4o-2024-11-20":{"id":"openai/gpt-4o-2024-11-20","name":"GPT-4o (2024-11-20)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-11-20","last_updated":"2024-11-20","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-11-20"},"openai/gpt-3.5-turbo-0613":{"id":"openai/gpt-3.5-turbo-0613","name":"GPT-3.5 Turbo (older v0613)","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2021-09-30","release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":4095,"output":3685},"cost":{"input":1,"output":2}},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-5.6-terra-pro":{"id":"openai/gpt-5.6-terra-pro","name":"GPT-5.6 Terra Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-6.1-sol-pro":{"id":"openai/gpt-6.1-sol-pro","name":"GPT-6.1 Sol Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}}},"openai/o4-mini-high":{"id":"openai/o4-mini-high","name":"o4 Mini High","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-06-30","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.275}},"openai/gpt-6-luna-pro":{"id":"openai/gpt-6-luna-pro","name":"GPT-6 Luna Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}}},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-4-turbo":{"id":"openai/gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":10,"output":30},"canonical_model_id":"openai/gpt-4-turbo"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-5.1-codex-mini":{"id":"openai/gpt-5.1-codex-mini","name":"GPT-5.1 Codex mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.03},"canonical_model_id":"openai/gpt-5.1-codex-mini"},"openai/o3":{"id":"openai/o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"openai/o1-pro":{"id":"openai/o1-pro","name":"o1-pro","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2025-03-19","last_updated":"2025-03-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":150,"output":600},"canonical_model_id":"openai/o1-pro"},"microsoft/phi-4":{"id":"microsoft/phi-4","name":"Phi 4","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","family":"phi","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2025-01-10","last_updated":"2025-01-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":14745},"cost":{"input":0.07,"output":0.14}},"microsoft/wizardlm-2-8x22b":{"id":"microsoft/wizardlm-2-8x22b","name":"WizardLM-2 8x22B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-04-30","release_date":"2024-04-16","last_updated":"2024-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65535,"output":8000},"cost":{"input":0.62,"output":0.62}}}},"perplexity":{"id":"perplexity","env":["PERPLEXITY_API_KEY"],"npm":"@ai-sdk/perplexity","name":"Perplexity","doc":"https://docs.perplexity.ai","models":{"sonar-pro":{"id":"sonar-pro","name":"Sonar Pro","description":"Deeper Sonar search model with broader retrieval and stronger synthesis","family":"sonar-pro","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":3,"output":15}},"sonar-deep-research":{"id":"sonar-deep-research","name":"Perplexity Sonar Deep Research","description":"Sonar search model for current answers, retrieval, and citation-backed chat","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":false,"temperature":false,"knowledge":"2025-01","release_date":"2025-02-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32768},"cost":{"input":2,"output":8,"reasoning":3}},"sonar":{"id":"sonar","name":"Sonar","description":"Fast web-grounded Sonar for current answers, citations, and lightweight retrieval","family":"sonar","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":1,"output":1}},"sonar-reasoning-pro":{"id":"sonar-reasoning-pro","name":"Sonar Reasoning Pro","description":"Web-grounded Sonar for multi-step research questions that need cited reasoning","family":"sonar-reasoning","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":2,"output":8}}}},"iteracompute":{"id":"iteracompute","env":["ITERACOMPUTE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.iteracompute.com/v1","name":"IteraCompute","doc":"https://iteracompute.com/docs.html","models":{"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731 (legacy alias)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.29,"output":1.16,"cache_read":0.0058},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.29,"output":1.16,"cache_read":0.0058},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.89,"output":2.69,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.099,"output":0.35,"cache_read":0.025},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.99,"output":3.45,"cache_read":0.245},"canonical_model_id":"zhipuai/glm-5.3"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":999999},"cost":{"input":2.39,"output":11.99,"cache_read":0.24},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.69,"output":3.29,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":524288},"cost":{"input":0.299,"output":1.19,"cache_read":0.045},"canonical_model_id":"minimax/MiniMax-M3"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3.8-2.4t-a95b":{"id":"qwen/qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.95,"output":5.7,"cache_read":0.245},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"}}},"the-grid-ai":{"id":"the-grid-ai","env":["THEGRID_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.thegrid.ai/v1","name":"The Grid AI","doc":"https://thegrid.ai/docs","models":{"bytedance-pro-latest":{"id":"bytedance-pro-latest","name":"ByteDance Pro Latest","description":"Lab latest market for ByteDance Pro supply. You contract for the latest qualifying route, not a specific model.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"input":256000,"output":131072}},"minimax-latest":{"id":"minimax-latest","name":"MiniMax Latest","description":"Lab latest market for MiniMax supply. You contract for the latest qualifying route, not a specific model.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":512000}},"agent-prime":{"id":"agent-prime","name":"Agent Prime","description":"Reliable models for dependable agentic applications, multi-step tool use, and reasoning workflows. Any model that meets the contract spec can serve your request.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-05-04","last_updated":"2026-07-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":196608,"input":120000,"output":131072},"status":"beta"},"claude-opus-latest":{"id":"claude-opus-latest","name":"Claude Opus Latest","description":"Lab latest market for Claude Opus frontier supply. You contract for the latest qualifying route, not a specific model.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-06","last_updated":"2026-07-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000}},"code-max":{"id":"code-max","name":"Code Max","description":"Frontier models for complex research, architectural decisions, debugging, and multi-file development. Any model that meets the contract spec can serve your request.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-05-04","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000},"status":"beta"},"agent-max":{"id":"agent-max","name":"Agent Max","description":"Frontier models for autonomous research, deep multi-step tool chains, and complex long-horizon tasks. Any model that meets the contract spec can serve your request.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-05-04","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000},"status":"beta"},"text-max":{"id":"text-max","name":"Text Max","description":"Frontier models for deep reasoning, long context, and complex workflows. Any model that meets the contract spec can serve your request.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-02-26","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000}},"gpt-sol-latest":{"id":"gpt-sol-latest","name":"GPT Sol Latest","description":"Lab latest market for GPT frontier supply. You contract for the latest qualifying route, not a specific model.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000}},"code-prime":{"id":"code-prime","name":"Code Prime","description":"Reliable models for everyday software tasks, code completion, review, and standard debugging. Any model that meets the contract spec can serve your request.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-05-04","last_updated":"2026-07-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":196608,"input":120000,"output":131072},"status":"beta"},"text-prime":{"id":"text-prime","name":"Text Prime","description":"Reliable models for everyday text generation, editing, and analysis across diverse workflows. Any model that meets the contract spec can serve your request.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-26","last_updated":"2026-07-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":196608,"input":120000,"output":131072}},"gemini-pro-latest":{"id":"gemini-pro-latest","name":"Gemini Pro Latest","description":"Lab latest market for Gemini Pro frontier supply. You contract for the latest qualifying route, not a specific model.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":65536}},"deepseek-pro-latest":{"id":"deepseek-pro-latest","name":"DeepSeek Pro Latest","description":"Lab latest market for DeepSeek Pro supply. You contract for the latest qualifying route, not a specific model.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":384000}},"code-standard":{"id":"code-standard","name":"Code Standard","description":"Price-optimized models for rapid autocomplete, linting, high-frequency suggestions, and batch edits. Any model that meets the contract spec can serve your request.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-05-04","last_updated":"2026-07-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":120000,"output":65536},"status":"beta"},"text-standard":{"id":"text-standard","name":"Text Standard","description":"Price-optimized models with low-latency, high-throughput and shorter maximum outputs. Any model that meets the contract spec can serve your request.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-26","last_updated":"2026-07-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":120000,"output":65536}},"agent-standard":{"id":"agent-standard","name":"Agent Standard","description":"Price-optimized models for fast tool calls, simple agent loops, high-throughput automation, and orchestration. Any model that meets the contract spec can serve your request.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-05-04","last_updated":"2026-07-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":120000,"output":65536},"status":"beta"},"glm-latest":{"id":"glm-latest","name":"GLM Latest","description":"Lab latest market for GLM supply. You contract for the latest qualifying route, not a specific model.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000}}}},"meta":{"id":"meta","env":["META_MODEL_API_KEY"],"npm":"@ai-sdk/openai","api":"https://api.meta.ai/v1","name":"Meta","doc":"https://dev.meta.ai/docs","models":{"muse-spark-1.3":{"id":"muse-spark-1.3","name":"Muse Spark 1.3","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.3"},"muse-spark-1.1":{"id":"muse-spark-1.1","name":"Muse Spark 1.1","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.1"},"muse-spark-1.2":{"id":"muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"muse-spark-1.2-contributor":{"id":"muse-spark-1.2-contributor","name":"Muse Spark 1.2 Contributor","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.1,"output":0.2,"cache_read":0.002},"canonical_model_id":"meta/muse-spark-1.2"},"muse-wonder-1.0":{"id":"muse-wonder-1.0","name":"Muse Wonder","description":"Muse Wonder is a frontier multimodal reasoning model from Meta for personal and professional agents, long-horizon coding, and computer use. It combines Active Memory, which carries relevant context across conversations, with Active Focus, which keeps it working through blockers toward a goal.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":4,"output":20,"cache_read":0.2},"canonical_model_id":"meta/muse-wonder-1.0"},"muse-spark-1.3-contributor":{"id":"muse-spark-1.3-contributor","name":"Muse Spark 1.3 Contributor","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.1,"output":0.2,"cache_read":0.002},"canonical_model_id":"meta/muse-spark-1.3"}}},"cline-pass":{"id":"cline-pass","env":["CLINE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.cline.bot/api/v1","name":"ClinePass","doc":"https://docs.cline.bot/getting-started/clinepass","models":{"cline-pass/mimo-v2.6-pro":{"id":"cline-pass/mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"cline-pass/qwen3.7-max":{"id":"cline-pass/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":2.5,"output":7.5,"cache_read":0.5,"cache_write":3.125},"canonical_model_id":"alibaba/qwen3.7-max"},"cline-pass/mimo-v2.5":{"id":"cline-pass/mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.5"},"cline-pass/glm-5.3-flash":{"id":"cline-pass/glm-5.3-flash","name":"cline-pass/glm-5.3-flash","description":"Latest natively multimodal model in the GLM-5 series","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03}},"cline-pass/qwen3.8-max":{"id":"cline-pass/qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"cline-pass/kimi-k3":{"id":"cline-pass/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"cline-pass/deepseek-v4.1-flash":{"id":"cline-pass/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"cline-pass/kimi-k2.6":{"id":"cline-pass/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"cline-pass/mimo-v2.5-pro":{"id":"cline-pass/mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.74,"output":3.48,"cache_read":0.0145},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"cline-pass/mimo-v2.6-flash":{"id":"cline-pass/mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"cline-pass/minimax-m3":{"id":"cline-pass/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"cline-pass/glm-5.2":{"id":"cline-pass/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"cline-pass/deepseek-v4-pro":{"id":"cline-pass/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.74,"output":3.48,"cache_read":0.0145},"canonical_model_id":"deepseek/deepseek-v4-pro"},"cline-pass/muse-spark-1.3-contributor":{"id":"cline-pass/muse-spark-1.3-contributor","name":"Muse Spark 1.3 Contributor","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"canonical_model_id":"meta/muse-spark-1.3"},"cline-pass/glm-5.3":{"id":"cline-pass/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"cline-pass/kimi-k2.7-code":{"id":"cline-pass/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"cline-pass/qwen3.7-plus":{"id":"cline-pass/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.4,"output":1.6,"cache_read":0.04,"cache_write":0.5,"tiers":[{"input":1.2,"output":4.8,"cache_read":0.12,"cache_write":1.5,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1.2,"output":4.8,"cache_read":0.12,"cache_write":1.5}},"canonical_model_id":"alibaba/qwen3.7-plus"},"cline-pass/deepseek-v4-flash":{"id":"cline-pass/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"deepseek/deepseek-v4-flash"}}},"modal":{"id":"modal","env":["MODAL_PROXY_TOKEN"],"npm":"@ai-sdk/openai-compatible","api":"https://inference.us-west.modal.direct/v1","name":"Modal","doc":"https://modal.com/docs/guide/endpoints","models":{"thinkingmachines/Inkling-NVFP4":{"id":"thinkingmachines/Inkling-NVFP4","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":1.2,"output":5,"cache_read":0.27},"canonical_model_id":"thinkingmachines/inkling"},"Qwen/Qwen3.8-2.4T-A95B":{"id":"Qwen/Qwen3.8-2.4T-A95B","name":"Qwen3.8-Max","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1010000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"moonshotai/Kimi-K3":{"id":"moonshotai/Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"reasoning":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"zai-org/GLM-5.3-Flash":{"id":"zai-org/GLM-5.3-Flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.45,"output":1.5,"cache_read":0.09},"canonical_model_id":"zhipuai/glm-5.3-flash"}}},"coralbricks":{"id":"coralbricks","env":["CORAL_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://inference.coralbricks.ai/v1","name":"CoralBricks","doc":"https://www.coralbricks.ai/docs","models":{"glm-5.3-fp4":{"id":"glm-5.3-fp4","name":"GLM 5.3 FP4","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.12,"output":4.4,"cache_read":0,"cache_write":1.68},"canonical_model_id":"zhipuai/glm-5.3"},"deepseek-v4.1-flash-fast":{"id":"deepseek-v4.1-flash-fast","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.01,"output":1.2,"cache_read":0,"cache_write":0.09},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"glm-5.3-fast":{"id":"glm-5.3-fast","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.12,"output":4.4,"cache_read":0,"cache_write":1.68},"canonical_model_id":"zhipuai/glm-5.3"},"deepseek-v4.1-flash-fast-fp4":{"id":"deepseek-v4.1-flash-fast-fp4","name":"DeepSeek V4.1 Flash FP4","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.01,"output":1.2,"cache_read":0,"cache_write":0.09},"canonical_model_id":"deepseek/deepseek-v4.1-flash"}}},"routing-run":{"id":"routing-run","env":["ROUTING_RUN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.routing.run/v1","name":"routing.run","doc":"https://docs.routing.run/api-reference/models","models":{"nemotron-3-ultra":{"id":"nemotron-3-ultra","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32000},"cost":{"input":0.1,"output":0.1},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"cost":{"input":0.275,"output":1.1},"canonical_model_id":"moonshotai/kimi-k2.6"},"qwen3.5-9b":{"id":"qwen3.5-9b","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32000},"cost":{"input":0.16,"output":0.48},"canonical_model_id":"alibaba/qwen3.5-9b"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000},"cost":{"input":0.7,"output":4.2},"canonical_model_id":"openai/gpt-5.6-luna"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-4-8"},"glm-5.2-nitro":{"id":"glm-5.2-nitro","name":"GLM 5.2 Nitro","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"cost":{"input":0.8,"output":2.4},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"cost":{"input":0.8,"output":2.4},"canonical_model_id":"zhipuai/glm-5.2"},"kimi-k2.6-nitro":{"id":"kimi-k2.6-nitro","name":"Kimi K2.6 Nitro","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"cost":{"input":0.275,"output":1.1},"canonical_model_id":"moonshotai/kimi-k2.6"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":64000},"cost":{"input":0.348,"output":0.696},"canonical_model_id":"deepseek/deepseek-v4-pro"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"kimi-k2.7-code-nitro":{"id":"kimi-k2.7-code-nitro","name":"Kimi K2.7 Code Nitro","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"cost":{"input":0.275,"output":1.1},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000},"cost":{"input":1.5,"output":9},"canonical_model_id":"openai/gpt-5.6-terra"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"cost":{"input":0.275,"output":1.1},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15},"canonical_model_id":"openai/gpt-5.6-sol"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":64000},"cost":{"input":0.112,"output":0.224},"canonical_model_id":"deepseek/deepseek-v4-flash"}}},"echo":{"id":"echo","env":["ECHO_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://echo.tracerml.ai/v1","name":"Echo","doc":"https://echo.tracerml.ai/docs/api","models":{"echo":{"id":"echo","name":"Echo","description":"Adaptive model for coding, reasoning, and tool-driven agent workflows through one OpenAI-compatible endpoint","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-19","last_updated":"2026-08-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"status":"beta","cost":{"input":10,"output":50}}}},"neuralwatt":{"id":"neuralwatt","env":["NEURALWATT_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.neuralwatt.com/v1","name":"Neuralwatt","doc":"https://portal.neuralwatt.com/docs","models":{"mimo-v2.6-pro":{"id":"mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":393216},"cost":{"input":0.87,"output":1.74,"cache_read":0.036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"glm-5.2-short-fast":{"id":"glm-5.2-short-fast","name":"GLM 5.2 Short Fast","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-06-17","last_updated":"2026-06-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":199984,"output":32000},"status":"deprecated","cost":{"input":1.45,"output":4.5,"cache_read":0.145},"canonical_model_id":"zhipuai/glm-5.2"},"kimi-k3-flex":{"id":"kimi-k3-flex","name":"Kimi K3 Flex","description":"Kimi K3 on the flex tier: discounted, best-effort latency, requests may be held under load","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":1048560},"cost":{"input":1.95,"output":9.75,"cache_read":0.195},"canonical_model_id":"moonshotai/kimi-k3"},"deepseek-v4-flash-flex":{"id":"deepseek-v4-flash-flex","name":"DeepSeek V4 Flash Flex","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":393216},"cost":{"input":0.091,"output":0.182,"cache_read":0.0182},"canonical_model_id":"deepseek/deepseek-v4-flash"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":1048560},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"glm-5.2-short-flex":{"id":"glm-5.2-short-flex","name":"GLM 5.2 Short Flex","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-06-17","last_updated":"2026-06-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":199984,"output":32000},"status":"deprecated","cost":{"input":0.9425,"output":2.925,"cache_read":0.09425},"canonical_model_id":"zhipuai/glm-5.2"},"qwen3.6-35b":{"id":"qwen3.6-35b","name":"Qwen3.6 35B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131056,"output":131056},"cost":{"input":0.29,"output":1.15,"cache_read":0.029},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"glm-5.2-fast":{"id":"glm-5.2-fast","name":"GLM 5.2 Fast","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-06-17","last_updated":"2026-06-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":1048560},"status":"deprecated","cost":{"input":1.45,"output":4.5,"cache_read":0.145},"canonical_model_id":"zhipuai/glm-5.2"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":1048560},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","xhigh","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":393216},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"kimi-k3-fast":{"id":"kimi-k3-fast","name":"Kimi K3 Fast","description":"Kimi K3 with thinking disabled for low-latency tool calling, vision, and JSON work","family":"kimi-k3","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":1048560},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"qwen3.6-35b-flex":{"id":"qwen3.6-35b-flex","name":"Qwen3.6 35B Flex","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131056,"output":131056},"cost":{"input":0.1885,"output":0.7475,"cache_read":0.01885},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"qwen-3.8-27b":{"id":"qwen-3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262128,"output":131072},"cost":{"input":0.45,"output":3.2,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-27b"},"glm-5.2-short":{"id":"glm-5.2-short","name":"GLM 5.2 Short","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-06-17","last_updated":"2026-06-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":199984,"output":32000},"status":"deprecated","cost":{"input":1.45,"output":4.5,"cache_read":0.145},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.3-flash-flex":{"id":"glm-5.3-flash-flex","name":"GLM-5.3 Flash Flex","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":1048560},"cost":{"input":0.0975,"output":0.325,"cache_read":0.0195},"canonical_model_id":"zhipuai/glm-5.3-flash"},"qwen3.6-35b-fast":{"id":"qwen3.6-35b-fast","name":"Qwen3.6 35B Fast","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"qwen3.6","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131056,"output":131056},"cost":{"input":0.29,"output":1.15,"cache_read":0.029},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"glm-5.2-flex":{"id":"glm-5.2-flex","name":"GLM 5.2 Flex","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-06-17","last_updated":"2026-06-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":1048560},"status":"deprecated","cost":{"input":0.9425,"output":2.925,"cache_read":0.09425},"canonical_model_id":"zhipuai/glm-5.2"},"deepseek-v4-flash-speed":{"id":"deepseek-v4-flash-speed","name":"DeepSeek V4 Flash (Speed)","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":393216},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"mimo-v2.6-pro-flex":{"id":"mimo-v2.6-pro-flex","name":"MiMo-V2.6-Pro Flex","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":393216},"cost":{"input":0.5655,"output":1.131,"cache_read":0.0234},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"glm-5.2":{"id":"glm-5.2","name":"GLM 5.2","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-06-17","last_updated":"2026-06-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":1048560},"status":"deprecated","cost":{"input":1.45,"output":4.5,"cache_read":0.145},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.2-short-fast-flex":{"id":"glm-5.2-short-fast-flex","name":"GLM 5.2 Short Fast Flex","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-06-17","last_updated":"2026-06-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":199984,"output":32000},"status":"deprecated","cost":{"input":0.9425,"output":2.925,"cache_read":0.09425},"canonical_model_id":"zhipuai/glm-5.2"},"kimi-k2.7-code-fast":{"id":"kimi-k2.7-code-fast","name":"Kimi K2.7 Code Fast","description":"Kimi K2.7 Code with reasoning capped to a short budget for lower latency; reasoning cannot be disabled on this model","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262128,"output":262128},"cost":{"input":0.95,"output":4,"cache_read":0.095},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"gemma-4-31b":{"id":"gemma-4-31b","name":"Gemma 4 31B","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262128,"output":16384},"cost":{"input":0.144,"output":0.42,"cache_read":0.0144},"canonical_model_id":"google/gemma-4-31b-it"},"glm-5.3-flex":{"id":"glm-5.3-flex","name":"GLM 5.3 Flex","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":1048560},"cost":{"input":0.9425,"output":2.925,"cache_read":0.09425},"canonical_model_id":"zhipuai/glm-5.3"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":393216},"status":"deprecated","cost":{"input":1,"output":3,"cache_read":0.1},"canonical_model_id":"deepseek/deepseek-v4-pro"},"qwen-3.8-27b-flex":{"id":"qwen-3.8-27b-flex","name":"Qwen3.8 27B Flex","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262128,"output":131072},"cost":{"input":0.2925,"output":2.08,"cache_read":0.1625},"canonical_model_id":"alibaba/qwen3.8-27b"},"kimi-k2.7-code-flex":{"id":"kimi-k2.7-code-flex","name":"Kimi K2.7 Code Flex","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262128,"output":262128},"cost":{"input":0.6175,"output":2.6,"cache_read":0.06175},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"glm-5.3":{"id":"glm-5.3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":1048560},"cost":{"input":1.45,"output":4.5,"cache_read":0.145},"canonical_model_id":"zhipuai/glm-5.3"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262128,"output":262128},"cost":{"input":0.95,"output":4,"cache_read":0.095},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"deepseek-v4.1-flash-flex":{"id":"deepseek-v4.1-flash-flex","name":"DeepSeek V4.1 Flash Flex","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","xhigh","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":393216},"cost":{"input":0.0975,"output":0.39,"cache_read":0.00975},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":393216},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash"}}},"gitlab":{"id":"gitlab","env":["GITLAB_TOKEN"],"npm":"gitlab-ai-provider","name":"GitLab Duo","doc":"https://docs.gitlab.com/user/duo_agent_platform/","models":{"duo-chat-gpt-5-4-nano":{"id":"duo-chat-gpt-5-4-nano","name":"Agentic Chat (GPT-5.4 Nano)","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0,"output":0}},"duo-chat-opus-5-5":{"id":"duo-chat-opus-5-5","name":"Agentic Chat (Claude Opus 5.5)","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"anthropic/claude-opus-5-5"},"duo-chat-gpt-6-1-sol":{"id":"duo-chat-gpt-6-1-sol","name":"Agentic Chat (GPT-6.1 Sol)","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"openai/gpt-6.1-sol"},"duo-chat-sonnet-5-5":{"id":"duo-chat-sonnet-5-5","name":"Agentic Chat (Claude Sonnet 5.5)","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"duo-chat-gpt-6-astra":{"id":"duo-chat-gpt-6-astra","name":"Agentic Chat (GPT-6 Astra)","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"openai/gpt-6-astra"},"duo-chat-opus-4-5":{"id":"duo-chat-opus-4-5","name":"Agentic Chat (Claude Opus 4.5)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2026-01-08","last_updated":"2026-01-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"duo-chat-gpt-5-mini":{"id":"duo-chat-gpt-5-mini","name":"Agentic Chat (GPT-5 Mini)","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2026-01-22","last_updated":"2026-01-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0,"output":0}},"duo-chat-gpt-6-luna":{"id":"duo-chat-gpt-6-luna","name":"Agentic Chat (GPT-6 Luna)","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"openai/gpt-6-luna"},"duo-chat-sonnet-4-5":{"id":"duo-chat-sonnet-4-5","name":"Agentic Chat (Claude Sonnet 4.5)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2026-01-08","last_updated":"2026-01-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"duo-chat-gpt-5-6-sol":{"id":"duo-chat-gpt-5-6-sol","name":"Agentic Chat (GPT-5.6 Sol)","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"openai/gpt-5.6-sol"},"duo-chat-sonnet-4-6":{"id":"duo-chat-sonnet-4-6","name":"Agentic Chat (Claude Sonnet 4.6)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-02-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"duo-chat-gpt-5-4-mini":{"id":"duo-chat-gpt-5-4-mini","name":"Agentic Chat (GPT-5.4 Mini)","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0,"output":0}},"duo-chat-haiku-4-5":{"id":"duo-chat-haiku-4-5","name":"Agentic Chat (Claude Haiku 4.5)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2026-01-08","last_updated":"2026-01-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"duo-chat-fable-5-1":{"id":"duo-chat-fable-5-1","name":"Agentic Chat (Claude Fable 5.1)","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"anthropic/claude-fable-5-1"},"duo-chat-gpt-5-5":{"id":"duo-chat-gpt-5-5","name":"Agentic Chat (GPT-5.5)","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0,"output":0}},"duo-chat-fable-5":{"id":"duo-chat-fable-5","name":"Agentic Chat (Claude Fable 5)","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"anthropic/claude-fable-5"},"duo-chat-gpt-5-3-codex":{"id":"duo-chat-gpt-5-3-codex","name":"Agentic Chat (GPT-5.3 Codex)","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0,"output":0}},"duo-chat-gpt-5-1":{"id":"duo-chat-gpt-5-1","name":"Agentic Chat (GPT-5.1)","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2026-01-22","last_updated":"2026-01-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0,"output":0}},"duo-chat-gpt-6-sol":{"id":"duo-chat-gpt-6-sol","name":"Agentic Chat (GPT-6 Sol)","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"openai/gpt-6-sol"},"duo-chat-opus-4-7":{"id":"duo-chat-opus-4-7","name":"Agentic Chat (Claude Opus 4.7)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"duo-chat-gpt-5-2":{"id":"duo-chat-gpt-5-2","name":"Agentic Chat (GPT-5.2)","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-01-23","last_updated":"2026-01-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0,"output":0}},"duo-chat-opus-5":{"id":"duo-chat-opus-5","name":"Agentic Chat (Claude Opus 5)","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"anthropic/claude-opus-5"},"duo-chat-opus-4-6":{"id":"duo-chat-opus-4-6","name":"Agentic Chat (Claude Opus 4.6)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"duo-chat-gpt-5-6-luna":{"id":"duo-chat-gpt-5-6-luna","name":"Agentic Chat (GPT-5.6 Luna)","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"openai/gpt-5.6-luna"},"duo-chat-gpt-5-codex":{"id":"duo-chat-gpt-5-codex","name":"Agentic Chat (GPT-5 Codex)","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2026-01-22","last_updated":"2026-01-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0,"output":0}},"duo-chat-sonnet-5":{"id":"duo-chat-sonnet-5","name":"Agentic Chat (Claude Sonnet 5)","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"anthropic/claude-sonnet-5"},"duo-chat-opus-4-8":{"id":"duo-chat-opus-4-8","name":"Agentic Chat (Claude Opus 4.8)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"duo-chat-gpt-5-2-codex":{"id":"duo-chat-gpt-5-2-codex","name":"Agentic Chat (GPT-5.2 Codex)","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-01-22","last_updated":"2026-01-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0,"output":0}},"duo-chat-gpt-5-4":{"id":"duo-chat-gpt-5-4","name":"Agentic Chat (GPT-5.4)","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0,"output":0}},"duo-chat-gpt-5-6-terra":{"id":"duo-chat-gpt-5-6-terra","name":"Agentic Chat (GPT-5.6 Terra)","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"openai/gpt-5.6-terra"}}},"infer":{"id":"infer","env":["INFER_API_KEY"],"npm":"@ai-sdk/openai","api":"https://infer.flow7.org/v1","name":"Infer by Flow7","doc":"https://infer.flow7.org/opencode","models":{"infer/gpt-6-astra:official":{"id":"infer/gpt-6-astra:official","name":"GPT-6 Astra (Official API)","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":271999,"output":128000},"provider":{"shape":"responses"},"cost":{"input":12.5,"output":62.5,"cache_read":1.25,"cache_write":15.625},"canonical_model_id":"openai/gpt-6-astra"},"infer/gpt-5.6-sol:official":{"id":"infer/gpt-5.6-sol:official","name":"GPT-5.6 Sol (Official API)","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":271999,"output":128000},"provider":{"shape":"responses"},"cost":{"input":2.5,"output":12.5,"cache_read":0.25,"cache_write":3.125},"canonical_model_id":"openai/gpt-5.6-sol"}}},"azure":{"id":"azure","env":["AZURE_RESOURCE_NAME","AZURE_API_KEY"],"npm":"@ai-sdk/azure","name":"Azure","doc":"https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models","models":{"grok-4-1-fast-reasoning":{"id":"grok-4-1-fast-reasoning","name":"Grok 4.1 Fast (Reasoning)","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-06-27","last_updated":"2025-06-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.2,"output":0.5,"cache_read":0.05}},"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":5,"output":30,"cache_read":0.5},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"deepseek-v3.2-speciale":{"id":"deepseek-v3.2-speciale","name":"DeepSeek-V3.2-Speciale","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0.58,"output":1.68}},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25}},"gpt-5.4-pro":{"id":"gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.4-pro"},"grok-4-1-fast-non-reasoning":{"id":"grok-4-1-fast-non-reasoning","name":"Grok 4.1 Fast (Non-Reasoning)","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-06-27","last_updated":"2025-06-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.2,"output":0.5,"cache_read":0.05}},"phi-4-reasoning":{"id":"phi-4-reasoning","name":"Phi-4-reasoning","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"phi","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2023-10","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":4096},"cost":{"input":0.125,"output":0.5}},"grok-4.7":{"id":"grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"status":"beta","canonical_model_id":"xai/grok-4.7"},"text-embedding-3-small":{"id":"text-embedding-3-small","name":"text-embedding-3-small","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536},"cost":{"input":0.02,"output":0}},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 Nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"gpt-5.2-codex":{"id":"gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-01-14","last_updated":"2026-01-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"gpt-5.1-codex":{"id":"gpt-5.1-codex","name":"GPT-5.1 Codex","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gpt-codex","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-14","last_updated":"2025-11-14","modalities":{"input":["text","image","audio"],"output":["text","image","audio"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125}},"gpt-4o":{"id":"gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"status":"deprecated","cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"ministral-3b":{"id":"ministral-3b","name":"Ministral 3B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-03","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.04,"output":0.04}},"gpt-chat-latest":{"id":"gpt-chat-latest","name":"GPT Chat Latest","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-05-05","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"beta","cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5-instant"},"gpt-5-codex":{"id":"gpt-5-codex","name":"GPT-5-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.13}},"gpt-5-mini":{"id":"gpt-5-mini","name":"GPT-5 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.03}},"gpt-image-2":{"id":"gpt-image-2","name":"GPT-Image-2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":30,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-2"},"o4-mini":{"id":"o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":1.1,"output":4.4,"cache_read":0.275},"canonical_model_id":"openai/o4-mini"},"llama-4-maverick-17b-128e-instruct-fp8":{"id":"llama-4-maverick-17b-128e-instruct-fp8","name":"Llama 4 Maverick 17B 128E Instruct FP8","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":16384},"cost":{"input":0.25,"output":1}},"o3-mini":{"id":"o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"claude-opus-4-5":{"id":"claude-opus-4-5","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-11-24","last_updated":"2025-08-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"text-embedding-ada-002":{"id":"text-embedding-ada-002","name":"text-embedding-ada-002","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2022-12-15","last_updated":"2022-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536},"cost":{"input":0.1,"output":0}},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek-V4.1-Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"status":"beta","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/models","shape":"completions"},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-24","last_updated":"2026-02-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"gpt-4.1-nano":{"id":"gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"status":"deprecated","cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"gpt-5-nano":{"id":"gpt-5-nano","name":"GPT-5 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.01}},"phi-4-multimodal":{"id":"phi-4-multimodal","name":"Phi-4-multimodal","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"phi","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2023-10","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.08,"output":0.32,"input_audio":4}},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/models","shape":"completions"},"cost":{"input":0.95,"output":4}},"claude-sonnet-4-5":{"id":"claude-sonnet-4-5","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75}},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"gpt-image-2.5-flare":{"id":"gpt-image-2.5-flare","name":"GPT Image 2.5 Flare","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":30,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-2.5-flare"},"claude-fable-5-1":{"id":"claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"mistral-medium-2505":{"id":"mistral-medium-2505","name":"Mistral Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000},"cost":{"input":0.4,"output":2}},"cohere-embed-v3-multilingual":{"id":"cohere-embed-v3-multilingual","name":"Embed v3 Multilingual","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"cohere-embed","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2023-11-07","last_updated":"2023-11-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512,"output":1024},"cost":{"input":0.1,"output":0}},"o1":{"id":"o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":15,"output":60,"cache_read":7.5}},"codex-mini":{"id":"codex-mini","name":"Codex Mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-04","release_date":"2025-05-16","last_updated":"2025-05-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":1.5,"output":6,"cache_read":0.375}},"phi-4-reasoning-plus":{"id":"phi-4-reasoning-plus","name":"Phi-4-reasoning-plus","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"phi","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2023-10","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":4096},"cost":{"input":0.125,"output":0.5}},"claude-mythos-5":{"id":"claude-mythos-5","name":"Claude Mythos 5","description":"Restricted Claude model for advanced cybersecurity and biology research workflows","family":"claude-mythos","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"status":"beta","provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-mythos-5"},"gpt-5-pro":{"id":"gpt-5-pro","name":"GPT-5 Pro","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":15,"output":120},"canonical_model_id":"openai/gpt-5-pro"},"gpt-3.5-turbo-instruct":{"id":"gpt-3.5-turbo-instruct","name":"GPT-3.5 Turbo Instruct","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2021-08","release_date":"2023-09-21","last_updated":"2023-09-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":4096,"output":4096},"status":"deprecated","cost":{"input":1.5,"output":2}},"gpt-3.5-turbo-0125":{"id":"gpt-3.5-turbo-0125","name":"GPT-3.5 Turbo 0125","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2021-08","release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":4096},"status":"deprecated","cost":{"input":0.5,"output":1.5}},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"text-embedding-3-large":{"id":"text-embedding-3-large","name":"text-embedding-3-large","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":3072},"cost":{"input":0.13,"output":0}},"claude-opus-4-1":{"id":"claude-opus-4-1","name":"Claude Opus 4.1","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75}},"cohere-embed-v-4-0":{"id":"cohere-embed-v-4-0","name":"Embed v4","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"cohere-embed","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-04-15","last_updated":"2025-04-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":1536},"cost":{"input":0.12,"output":0}},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"codestral-2501":{"id":"codestral-2501","name":"Codestral 25.01","description":"Mistral coding model for code completion, generation, and developer workflows","family":"codestral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-03","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.3,"output":0.9}},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-06","last_updated":"2026-02-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/models","shape":"completions"},"cost":{"input":0.6,"output":3}},"gpt-5.1":{"id":"gpt-5.1","name":"GPT-5.1","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-14","last_updated":"2025-11-14","modalities":{"input":["text","image","audio"],"output":["text","image","audio"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":2.5,"output":20,"cache_read":0.25},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":1.25,"output":10,"cache_read":0.125}},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"llama-3.3-70b-instruct":{"id":"llama-3.3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.71,"output":0.71}},"gpt-4o-mini":{"id":"gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"status":"deprecated","cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"cohere-command-a":{"id":"cohere-command-a","name":"Command A","description":"Cohere command model for multilingual enterprise agents, tools, and chat","family":"command-a","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2025-03-13","last_updated":"2025-03-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":2.5,"output":10}},"cohere-embed-v3-english":{"id":"cohere-embed-v3-english","name":"Embed v3 English","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"cohere-embed","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2023-11-07","last_updated":"2023-11-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512,"output":1024},"cost":{"input":0.1,"output":0}},"model-router":{"id":"model-router","name":"Model Router","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"model-router","attachment":true,"reasoning":false,"tool_call":true,"release_date":"2025-05-19","last_updated":"2025-11-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":16384},"provider":{"shape":"completions"},"cost":{"input":0.14,"output":0}},"gpt-image-2.5-sunburst":{"id":"gpt-image-2.5-sunburst","name":"GPT Image 2.5 Sunburst","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":30,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-2.5-sunburst"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"status":"beta","provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"gpt-image-1":{"id":"gpt-image-1","name":"GPT-Image-1","description":"OpenAI image model for production generation, edits, and brand-safe visual workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-04-24","last_updated":"2025-04-24","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":40,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-1"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 Mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":1.5,"output":9,"cache_read":0.15},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"gpt-5.1-codex-max":{"id":"gpt-5.1-codex-max","name":"GPT-5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex-max"},"gpt-5.2":{"id":"gpt-5.2","name":"GPT-5.2","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":3.5,"output":28,"cache_read":0.35},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":1.75,"output":14,"cache_read":0.125}},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2025-12-31","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5}},"canonical_model_id":"anthropic/claude-opus-4-8"},"phi-4":{"id":"phi-4","name":"Phi-4","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","family":"phi","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2023-10","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.125,"output":0.5}},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":12.5,"output":75,"cache_read":1.25},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"mistral-small-2503":{"id":"mistral-small-2503","name":"Mistral Small 3.1","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2025-03-01","last_updated":"2025-03-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32768},"cost":{"input":0.1,"output":0.3}},"phi-4-mini-reasoning":{"id":"phi-4-mini-reasoning","name":"Phi-4-mini-reasoning","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"phi","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2023-10","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.075,"output":0.3}},"gpt-4.1":{"id":"gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"status":"deprecated","cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-07-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5}}},"gpt-4-turbo-vision":{"id":"gpt-4-turbo-vision","name":"GPT-4 Turbo Vision","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-11","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":10,"output":30}},"grok-4-20-non-reasoning":{"id":"grok-4-20-non-reasoning","name":"Grok 4.20 (Non-Reasoning)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-04-08","last_updated":"2026-04-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":8192},"status":"beta","cost":{"input":2,"output":6}},"gpt-3.5-turbo-1106":{"id":"gpt-3.5-turbo-1106","name":"GPT-3.5 Turbo 1106","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2021-08","release_date":"2023-11-06","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":4096},"status":"deprecated","cost":{"input":1,"output":2}},"gpt-4.1-mini":{"id":"gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"status":"deprecated","cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"deepseek-r1":{"id":"deepseek-r1","name":"DeepSeek-R1","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-01-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":163840},"status":"deprecated","cost":{"input":1.35,"output":5.4}},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek-V4-Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/models","shape":"completions"},"cost":{"input":1.74,"output":3.48},"canonical_model_id":"deepseek/deepseek-v4-pro"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"llama-4-scout-17b-16e-instruct":{"id":"llama-4-scout-17b-16e-instruct","name":"Llama 4 Scout 17B 16E Instruct","description":"Open multimodal Llama model for long-context analysis and efficient agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.2,"output":0.78}},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"gpt-image-1.5":{"id":"gpt-image-1.5","name":"GPT-Image-1.5","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-11-25","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":32,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-1.5"},"grok-4-20-reasoning":{"id":"grok-4-20-reasoning","name":"Grok 4.20 (Reasoning)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-04-08","last_updated":"2026-04-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":8192},"status":"beta","cost":{"input":2,"output":6}},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":4,"output":24,"cache_read":0.4,"cache_write":5},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"deepseek-v3.2":{"id":"deepseek-v3.2","name":"DeepSeek-V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0.58,"output":1.68}},"gpt-4-turbo":{"id":"gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":10,"output":30},"canonical_model_id":"openai/gpt-4-turbo"},"gpt-5.1-codex-mini":{"id":"gpt-5.1-codex-mini","name":"GPT-5.1 Codex Mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-14","last_updated":"2025-11-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025}},"o3":{"id":"o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/models","shape":"completions"},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"gpt-5":{"id":"gpt-5","name":"GPT-5","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.13}},"grok-4.6":{"id":"grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"status":"beta","cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":8,"output":40,"cache_read":0.8,"cache_write":10},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":4,"output":20,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":45,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1,"cache_write":12.5}},"canonical_model_id":"openai/gpt-5.6-sol"},"phi-4-mini":{"id":"phi-4-mini","name":"Phi-4-mini","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"phi","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-10","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.075,"output":0.3}},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek-V4-Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/models","shape":"completions"},"cost":{"input":0.19,"output":0.51},"canonical_model_id":"deepseek/deepseek-v4-flash"},"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"}}},"freemodel":{"id":"freemodel","env":["FREEMODEL_API_KEY"],"npm":"@ai-sdk/anthropic","api":"https://cc.freemodel.dev/v1","name":"FreeModel","doc":"https://freemodel.dev","models":{"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://api.freemodel.dev/v1"},"cost":{"input":2.5,"output":15,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.4"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://api.freemodel.dev/v1"},"cost":{"input":1.75,"output":14,"cache_read":0.175,"cache_write":1.75},"canonical_model_id":"openai/gpt-5.3-codex"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://api.freemodel.dev/v1"},"cost":{"input":0.75,"output":4.5,"cache_read":0.075,"cache_write":0.75},"canonical_model_id":"openai/gpt-5.4-mini"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://api.freemodel.dev/v1"},"cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":5},"canonical_model_id":"openai/gpt-5.5"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"claude-haiku-4-5-20251001":{"id":"claude-haiku-4-5-20251001","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"}}},"azure-cognitive-services":{"id":"azure-cognitive-services","env":["AZURE_COGNITIVE_SERVICES_RESOURCE_NAME","AZURE_COGNITIVE_SERVICES_API_KEY"],"npm":"@ai-sdk/azure","name":"Azure Cognitive Services","doc":"https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models","models":{"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":5,"output":30,"cache_read":0.5},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_COGNITIVE_SERVICES_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25}},"gpt-5.4-pro":{"id":"gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.4-pro"},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 Nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"gpt-chat-latest":{"id":"gpt-chat-latest","name":"GPT Chat Latest","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-05-05","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"beta","cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5-instant"},"claude-opus-4-5":{"id":"claude-opus-4-5","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-11-24","last_updated":"2025-08-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_COGNITIVE_SERVICES_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${AZURE_COGNITIVE_SERVICES_RESOURCE_NAME}.services.ai.azure.com/models","shape":"completions"},"cost":{"input":0.95,"output":4},"canonical_model_id":"moonshotai/kimi-k2.6"},"claude-sonnet-4-5":{"id":"claude-sonnet-4-5","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_COGNITIVE_SERVICES_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75}},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_COGNITIVE_SERVICES_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"claude-fable-5-1":{"id":"claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_COGNITIVE_SERVICES_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"claude-mythos-5":{"id":"claude-mythos-5","name":"Claude Mythos 5","description":"Restricted Claude model for advanced cybersecurity and biology research workflows","family":"claude-mythos","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"status":"beta","provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_COGNITIVE_SERVICES_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-mythos-5"},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"claude-opus-4-1":{"id":"claude-opus-4-1","name":"Claude Opus 4.1","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_COGNITIVE_SERVICES_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75}},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${AZURE_COGNITIVE_SERVICES_RESOURCE_NAME}.services.ai.azure.com/models","shape":"completions"},"cost":{"input":0.6,"output":3},"canonical_model_id":"moonshotai/kimi-k2.5"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_COGNITIVE_SERVICES_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"status":"beta","provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_COGNITIVE_SERVICES_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 Mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":1.5,"output":9,"cache_read":0.15},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":1,"output":6,"cache_read":0.1,"cache_write":1.25,"tiers":[{"input":2,"output":9,"cache_read":0.2,"cache_write":2.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":2,"output":9,"cache_read":0.2,"cache_write":2.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2025-12-31","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_COGNITIVE_SERVICES_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5}},"canonical_model_id":"anthropic/claude-opus-4-8"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_COGNITIVE_SERVICES_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-07-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_COGNITIVE_SERVICES_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5}}},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_COGNITIVE_SERVICES_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_COGNITIVE_SERVICES_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_COGNITIVE_SERVICES_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":4,"output":24,"cache_read":0.4,"cache_write":5},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2.5,"output":15,"cache_read":0.25,"cache_write":3.125,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"cache_write":6.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5,"cache_write":6.25}},"canonical_model_id":"openai/gpt-5.6-terra"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_COGNITIVE_SERVICES_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":8,"output":40,"cache_read":0.8,"cache_write":10},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.6-sol"},"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"phi-4-mini":{"id":"phi-4-mini","name":"Phi-4-mini","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"phi","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-10","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.075,"output":0.3}},"gpt-5":{"id":"gpt-5","name":"GPT-5","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.13}},"o3":{"id":"o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"gpt-5.1-codex-mini":{"id":"gpt-5.1-codex-mini","name":"GPT-5.1 Codex Mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-14","last_updated":"2025-11-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025}},"gpt-4-turbo":{"id":"gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":10,"output":30},"canonical_model_id":"openai/gpt-4-turbo"},"deepseek-v3.2":{"id":"deepseek-v3.2","name":"DeepSeek-V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0.58,"output":1.68}},"gpt-image-1.5":{"id":"gpt-image-1.5","name":"GPT-Image-1.5","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-11-25","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":32,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-1.5"},"llama-4-scout-17b-16e-instruct":{"id":"llama-4-scout-17b-16e-instruct","name":"Llama 4 Scout 17B 16E Instruct","description":"Open multimodal Llama model for long-context analysis and efficient agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.2,"output":0.78}},"deepseek-r1":{"id":"deepseek-r1","name":"DeepSeek-R1","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-01-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":163840},"status":"deprecated","cost":{"input":1.35,"output":5.4}},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"gpt-4.1-mini":{"id":"gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"status":"deprecated","cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"gpt-3.5-turbo-1106":{"id":"gpt-3.5-turbo-1106","name":"GPT-3.5 Turbo 1106","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2021-08","release_date":"2023-11-06","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":4096},"status":"deprecated","cost":{"input":1,"output":2}},"gpt-4-turbo-vision":{"id":"gpt-4-turbo-vision","name":"GPT-4 Turbo Vision","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-11","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":10,"output":30}},"gpt-4.1":{"id":"gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"status":"deprecated","cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"phi-4-mini-reasoning":{"id":"phi-4-mini-reasoning","name":"Phi-4-mini-reasoning","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"phi","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2023-10","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.075,"output":0.3}},"mistral-small-2503":{"id":"mistral-small-2503","name":"Mistral Small 3.1","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2025-03-01","last_updated":"2025-03-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32768},"cost":{"input":0.1,"output":0.3}},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":12.5,"output":75,"cache_read":1.25},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"phi-4":{"id":"phi-4","name":"Phi-4","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","family":"phi","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2023-10","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.125,"output":0.5}},"gpt-5.2":{"id":"gpt-5.2","name":"GPT-5.2","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":3.5,"output":28,"cache_read":0.35},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":1.75,"output":14,"cache_read":0.125}},"gpt-5.1-codex-max":{"id":"gpt-5.1-codex-max","name":"GPT-5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex-max"},"gpt-image-1":{"id":"gpt-image-1","name":"GPT-Image-1","description":"OpenAI image model for production generation, edits, and brand-safe visual workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-04-24","last_updated":"2025-04-24","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":40,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-1"},"gpt-image-2.5-sunburst":{"id":"gpt-image-2.5-sunburst","name":"GPT Image 2.5 Sunburst","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":30,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-2.5-sunburst"},"model-router":{"id":"model-router","name":"Model Router","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"model-router","attachment":true,"reasoning":false,"tool_call":true,"release_date":"2025-05-19","last_updated":"2025-11-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":16384},"provider":{"shape":"completions"},"cost":{"input":0.14,"output":0}},"cohere-embed-v3-english":{"id":"cohere-embed-v3-english","name":"Embed v3 English","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"cohere-embed","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2023-11-07","last_updated":"2023-11-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512,"output":1024},"cost":{"input":0.1,"output":0}},"cohere-command-a":{"id":"cohere-command-a","name":"Command A","description":"Cohere command model for multilingual enterprise agents, tools, and chat","family":"command-a","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2025-03-13","last_updated":"2025-03-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":2.5,"output":10}},"gpt-4o-mini":{"id":"gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"status":"deprecated","cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"llama-3.3-70b-instruct":{"id":"llama-3.3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.71,"output":0.71}},"gpt-5.1":{"id":"gpt-5.1","name":"GPT-5.1","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-14","last_updated":"2025-11-14","modalities":{"input":["text","image","audio"],"output":["text","image","audio"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":2.5,"output":20,"cache_read":0.25},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":1.25,"output":10,"cache_read":0.125}},"codestral-2501":{"id":"codestral-2501","name":"Codestral 25.01","description":"Mistral coding model for code completion, generation, and developer workflows","family":"codestral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-03","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.3,"output":0.9}},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"cohere-embed-v-4-0":{"id":"cohere-embed-v-4-0","name":"Embed v4","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"cohere-embed","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-04-15","last_updated":"2025-04-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":1536},"cost":{"input":0.12,"output":0}},"text-embedding-3-large":{"id":"text-embedding-3-large","name":"text-embedding-3-large","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":3072},"cost":{"input":0.13,"output":0}},"gpt-3.5-turbo-0125":{"id":"gpt-3.5-turbo-0125","name":"GPT-3.5 Turbo 0125","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2021-08","release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":4096},"status":"deprecated","cost":{"input":0.5,"output":1.5}},"gpt-3.5-turbo-instruct":{"id":"gpt-3.5-turbo-instruct","name":"GPT-3.5 Turbo Instruct","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2021-08","release_date":"2023-09-21","last_updated":"2023-09-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":4096,"output":4096},"status":"deprecated","cost":{"input":1.5,"output":2}},"gpt-5-pro":{"id":"gpt-5-pro","name":"GPT-5 Pro","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":15,"output":120},"canonical_model_id":"openai/gpt-5-pro"},"phi-4-reasoning-plus":{"id":"phi-4-reasoning-plus","name":"Phi-4-reasoning-plus","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"phi","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2023-10","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":4096},"cost":{"input":0.125,"output":0.5}},"codex-mini":{"id":"codex-mini","name":"Codex Mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-04","release_date":"2025-05-16","last_updated":"2025-05-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":1.5,"output":6,"cache_read":0.375}},"o1":{"id":"o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":15,"output":60,"cache_read":7.5}},"cohere-embed-v3-multilingual":{"id":"cohere-embed-v3-multilingual","name":"Embed v3 Multilingual","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"cohere-embed","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2023-11-07","last_updated":"2023-11-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512,"output":1024},"cost":{"input":0.1,"output":0}},"mistral-medium-2505":{"id":"mistral-medium-2505","name":"Mistral Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000},"cost":{"input":0.4,"output":2}},"gpt-image-2.5-flare":{"id":"gpt-image-2.5-flare","name":"GPT Image 2.5 Flare","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":30,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-2.5-flare"},"phi-4-multimodal":{"id":"phi-4-multimodal","name":"Phi-4-multimodal","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"phi","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2023-10","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.08,"output":0.32,"input_audio":4}},"gpt-5-nano":{"id":"gpt-5-nano","name":"GPT-5 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.01}},"gpt-4.1-nano":{"id":"gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"status":"deprecated","cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-24","last_updated":"2026-02-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"text-embedding-ada-002":{"id":"text-embedding-ada-002","name":"text-embedding-ada-002","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2022-12-15","last_updated":"2022-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536},"cost":{"input":0.1,"output":0}},"o3-mini":{"id":"o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"llama-4-maverick-17b-128e-instruct-fp8":{"id":"llama-4-maverick-17b-128e-instruct-fp8","name":"Llama 4 Maverick 17B 128E Instruct FP8","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":16384},"cost":{"input":0.25,"output":1}},"o4-mini":{"id":"o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":1.1,"output":4.4,"cache_read":0.275},"canonical_model_id":"openai/o4-mini"},"gpt-image-2":{"id":"gpt-image-2","name":"GPT-Image-2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":30,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-2"},"gpt-5-mini":{"id":"gpt-5-mini","name":"GPT-5 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.03}},"gpt-5-codex":{"id":"gpt-5-codex","name":"GPT-5-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.13}},"ministral-3b":{"id":"ministral-3b","name":"Ministral 3B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-03","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.04,"output":0.04}},"gpt-4o":{"id":"gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"status":"deprecated","cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"gpt-5.1-codex":{"id":"gpt-5.1-codex","name":"GPT-5.1 Codex","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gpt-codex","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-14","last_updated":"2025-11-14","modalities":{"input":["text","image","audio"],"output":["text","image","audio"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125}},"gpt-5.2-codex":{"id":"gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-01-14","last_updated":"2026-01-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"text-embedding-3-small":{"id":"text-embedding-3-small","name":"text-embedding-3-small","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536},"cost":{"input":0.02,"output":0}},"phi-4-reasoning":{"id":"phi-4-reasoning","name":"Phi-4-reasoning","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"phi","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2023-10","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":4096},"cost":{"input":0.125,"output":0.5}},"deepseek-v3.2-speciale":{"id":"deepseek-v3.2-speciale","name":"DeepSeek-V3.2-Speciale","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0.58,"output":1.68}}}},"pendra":{"id":"pendra","env":["PENDRA_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.pendra.ai/api/v1","name":"Pendra","doc":"https://pendra.ai/docs/integrations/opencode","models":{"llama3.3:70b":{"id":"llama3.3:70b","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0,"output":0},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"qwen3-coder:30b":{"id":"qwen3-coder:30b","name":"Qwen3-Coder 30B-A3B Instruct","description":"Smaller Qwen coder for efficient local agents and repo-level fixes","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"gpt-oss:120b":{"id":"gpt-oss:120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"openai/gpt-oss-120b"},"qwen3.6:27b":{"id":"qwen3.6:27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3.6-27b"},"glm-4.7-flash":{"id":"glm-4.7-flash","name":"GLM-4.7-Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-4.7-flash"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-v4-flash"}}},"moark":{"id":"moark","env":["MOARK_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://moark.com/v1","name":"Moark","doc":"https://moark.com/docs/openapi/v1#tag/%E6%96%87%E6%9C%AC%E7%94%9F%E6%88%90","models":{"Kimi-K2.6":{"id":"Kimi-K2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.98,"output":4},"canonical_model_id":"moonshotai/kimi-k2.6"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.3},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15},"canonical_model_id":"moonshotai/kimi-k3"},"GLM-4.7":{"id":"GLM-4.7","name":"GLM-4.7","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.42,"output":2.2}},"MiniMax-M2.1":{"id":"MiniMax-M2.1","name":"MiniMax-M2.1","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.29,"output":1.2}},"DeepSeek-V4-Flash":{"id":"DeepSeek-V4-Flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.5,"output":0.5},"canonical_model_id":"deepseek/deepseek-v4-flash"},"DeepSeek-V4-Pro":{"id":"DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.8,"output":3.6},"canonical_model_id":"deepseek/deepseek-v4-pro"},"MiniMax-M2.7":{"id":"MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.29,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2.7"},"Qwen3.6-Flash":{"id":"Qwen3.6-Flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.18,"output":1.03},"canonical_model_id":"alibaba/qwen3.6-flash"},"GLM-5.3":{"id":"GLM-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.2,"output":4.18},"canonical_model_id":"zhipuai/glm-5.3"}}},"atomic-chat":{"id":"atomic-chat","env":["ATOMIC_CHAT_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"http://127.0.0.1:1337/v1","name":"Atomic Chat","doc":"https://atomic.chat","models":{"gemma-4-E4B-it-MLX-4bit":{"id":"gemma-4-E4B-it-MLX-4bit","name":"Gemma 4 E4B Instruct (MLX 4-bit)","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0,"output":0}},"Meta-Llama-3_1-8B-Instruct-GGUF":{"id":"Meta-Llama-3_1-8B-Instruct-GGUF","name":"Meta Llama 3.1 8B Instruct (GGUF)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":4096},"cost":{"input":0,"output":0}},"Qwen3_5-9B-Q4_K_M":{"id":"Qwen3_5-9B-Q4_K_M","name":"Qwen 3.5 9B (Q4_K_M)","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-03-05","last_updated":"2026-04-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0,"output":0}},"gemma-4-E4B-it-IQ4_XS":{"id":"gemma-4-E4B-it-IQ4_XS","name":"Gemma 4 E4B Instruct (IQ4_XS)","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0,"output":0}},"Qwen3_5-9B-MLX-4bit":{"id":"Qwen3_5-9B-MLX-4bit","name":"Qwen 3.5 9B (MLX 4-bit)","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-03-05","last_updated":"2026-04-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0,"output":0}}}},"qihang-ai":{"id":"qihang-ai","env":["QIHANG_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.qhaigc.net/v1","name":"QiHang","doc":"https://www.qhaigc.net/docs","models":{"gpt-5.2-codex":{"id":"gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.14,"output":1.14}},"gemini-3-pro-preview":{"id":"gemini-3-pro-preview","name":"Gemini 3 Pro Preview","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-11","release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65000},"cost":{"input":0.57,"output":3.43}},"gpt-5-mini":{"id":"gpt-5-mini","name":"GPT-5-Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":0.04,"output":0.29}},"claude-opus-4-5-20251101":{"id":"claude-opus-4-5-20251101","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2025-11-01","last_updated":"2025-11-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":0.71,"output":3.57}},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.09,"output":0.71,"tiers":[{"input":0.09,"output":0.71,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":0.09,"output":0.71}}},"gpt-5.2":{"id":"gpt-5.2","name":"GPT-5.2","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2}},"claude-sonnet-4-5-20250929":{"id":"claude-sonnet-4-5-20250929","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":0.43,"output":2.14}},"gemini-3-flash-preview":{"id":"gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.07,"output":0.43,"tiers":[{"input":0.07,"output":0.43,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":0.07,"output":0.43}}},"claude-haiku-4-5-20251001":{"id":"claude-haiku-4-5-20251001","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-10-01","last_updated":"2025-10-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":0.14,"output":0.71}}}},"ai-router":{"id":"ai-router","env":["AI_ROUTER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.ai-router.dev/v1","name":"AI-ROUTER","doc":"https://ai-router.dev/openai-compatible-api-gateway/","models":{"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.4"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":1,"output":6,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"openai/gpt-5.6-luna"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"cache_write":3.125},"canonical_model_id":"openai/gpt-5.6-terra"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"openai/gpt-5.6-sol"}}},"llmtr":{"id":"llmtr","env":["LLMTR_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://llmtr.com/v1","name":"LLMTR","doc":"https://llmtr.com/docs","models":{"muse-glimmer-30b-tr":{"id":"muse-glimmer-30b-tr","name":"Muse Glimmer 30B (TR)","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":2,"output":5,"cache_read":0.5},"canonical_model_id":"meta/muse-glimmer-30b"},"magibu-11b-v8":{"id":"magibu-11b-v8","name":"Magibu 11B v8","description":"Turkish-language chat model for instruction following and assistant flows","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-06-05","last_updated":"2026-08-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8192},"cost":{"input":0.1,"output":0.5}},"gemma-4":{"id":"gemma-4","name":"Gemma 4","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":2,"output":5,"cache_read":0.5},"canonical_model_id":"google/gemma-4-31b-it"},"trendyol-asure-12b":{"id":"trendyol-asure-12b","name":"Trendyol Asure 12B","description":"Turkish-language multimodal instruct model built on Gemma 3 12B for e-commerce text, chat, and image-text tasks","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-02-19","last_updated":"2026-02-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":40960},"cost":{"input":0.1,"output":0.5,"cache_read":0.025},"canonical_model_id":"trendyol/asure-12b"},"medgemma-4b":{"id":"medgemma-4b","name":"MedGemma 4B","description":"Multimodal medical-domain Gemma variant for text and image analysis","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-04-26","last_updated":"2026-08-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8192},"status":"deprecated","cost":{"input":3,"output":5}},"qwen3-6-35b":{"id":"qwen3-6-35b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":16384},"cost":{"input":5,"output":10},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"poolside/laguna-xs-2.1":{"id":"poolside/laguna-xs-2.1","name":"Laguna XS 2.1","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-02","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"poolside/laguna-xs-2.1"},"publicai/apertus-70b-instruct":{"id":"publicai/apertus-70b-instruct","name":"Apertus 70B Instruct","description":"Fully open 70B multilingual LLM supporting 1800+ languages with 65K context. Trained on 15T tokens of compliant open data. Apache 2.0, EU AI Act compliant.","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-09-02","last_updated":"2025-09-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":8192},"cost":{"input":0.82,"output":2.92},"canonical_model_id":"swiss-ai/apertus-70b"},"publicai/apertus-8b-instruct":{"id":"publicai/apertus-8b-instruct","name":"Apertus 8B Instruct","description":"Fully open 8B multilingual LLM supporting 1800+ languages with 65K context. Trained on compliant open data. Apache 2.0, EU AI Act compliant.","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-09-02","last_updated":"2025-09-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":8192},"cost":{"input":0.1,"output":0.2},"canonical_model_id":"swiss-ai/apertus-8b"},"thinkingmachines/inkling-small":{"id":"thinkingmachines/inkling-small","name":"Inkling Small","description":"Multimodal MoE reasoning model (276B total, 12B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.58,"output":1.44},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/inkling":{"id":"thinkingmachines/inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.87,"output":4.68},"canonical_model_id":"thinkingmachines/inkling"},"perplexity/sonar-deep-research":{"id":"perplexity/sonar-deep-research","name":"Sonar Deep Research","description":"Sonar search model for autonomous research and citation-backed long-form reports","family":"sonar","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":false,"knowledge":"2025-01","release_date":"2025-02-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32768},"cost":{"input":2,"output":8,"reasoning":3},"canonical_model_id":"perplexity/sonar-deep-research"},"meta/muse-spark-1.2-contributor":{"id":"meta/muse-spark-1.2-contributor","name":"Muse Spark 1.2 Contributor","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.1,"output":0.2},"canonical_model_id":"meta/muse-spark-1.2"},"upstage/solar-pro4":{"id":"upstage/solar-pro4","name":"Solar Pro 4","description":"Upstage's flagship model, specialized for agentic use","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02","release_date":"2026-08-06","last_updated":"2026-08-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":131072},"cost":{"input":0.03,"output":0.12},"canonical_model_id":"upstage/solar-pro4"},"upstage/solar-pro3":{"id":"upstage/solar-pro3","name":"Solar Pro 3","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"upstage/solar-pro3"},"upstage/solar-pro2":{"id":"upstage/solar-pro2","name":"Solar Pro 2","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"output":8192},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"upstage/solar-pro2"},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.1,"output":0.1},"canonical_model_id":"google/gemini-2.5-flash-lite"},"mimo/mimo-v2.5":{"id":"mimo/mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.14,"output":0.28},"canonical_model_id":"xiaomi/mimo-v2.5"},"mimo/mimo-v2.5-pro":{"id":"mimo/mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.435,"output":0.87},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"sakana/fugu-ultra":{"id":"sakana/fugu-ultra","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":5,"output":30},"canonical_model_id":"sakana/fugu-ultra"},"mistral/voxtral-small-latest":{"id":"mistral/voxtral-small-latest","name":"Voxtral Small (latest)","description":"Instruct model with native audio input for speech understanding and tool use","family":"voxtral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":32000},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"mistral/voxtral-small-latest"},"qwen/qwen-flash":{"id":"qwen/qwen-flash","name":"Qwen Flash","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.05,"output":0.4},"canonical_model_id":"alibaba/qwen-flash"},"qwen/qwen3-vl-plus":{"id":"qwen/qwen3-vl-plus","name":"Qwen3-VL Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32768},"cost":{"input":0.2,"output":1.6},"canonical_model_id":"alibaba/qwen3-vl-plus"},"qwen/qwen3.5-plus":{"id":"qwen/qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.4,"output":2.4},"canonical_model_id":"alibaba/qwen3.5-plus"},"qwen/qwen-plus":{"id":"qwen/qwen-plus","name":"Qwen Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.4,"output":1.2},"canonical_model_id":"alibaba/qwen-plus"},"qwen/qwen3-max":{"id":"qwen/qwen3-max","name":"Qwen3 Max","description":"Flagship Qwen3 model for coding agents, complex reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":65536},"cost":{"input":1.2,"output":6},"canonical_model_id":"alibaba/qwen3-max"},"qwen/qwen3.6-flash":{"id":"qwen/qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.25,"output":1.5},"canonical_model_id":"alibaba/qwen3.6-flash"},"qwen/qwen3-coder-flash":{"id":"qwen/qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.3,"output":1.5},"canonical_model_id":"alibaba/qwen3-coder-flash"},"qwen/qwen3-coder-plus":{"id":"qwen/qwen3-coder-plus","name":"Qwen3 Coder Plus","description":"Hosted Qwen coder for software agents, repo edits, and long-context code","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":1,"output":5},"canonical_model_id":"alibaba/qwen3-coder-plus"},"qwen/qwen3.5-397b-a17b":{"id":"qwen/qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0.6,"output":3.6},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"qwen/qwen3.6-plus":{"id":"qwen/qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.5,"output":3},"canonical_model_id":"alibaba/qwen3.6-plus"},"qwen/qwen3.7-plus":{"id":"qwen/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.4,"output":1.6},"canonical_model_id":"alibaba/qwen3.7-plus"}}},"alibaba":{"id":"alibaba","env":["DASHSCOPE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://dashscope-intl.aliyuncs.com/compatible-mode/v1","name":"Alibaba","doc":"https://www.alibabacloud.com/help/en/model-studio/models","models":{"qwen-flash":{"id":"qwen-flash","name":"Qwen Flash","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.05,"output":0.4}},"qwen3.5-flash":{"id":"qwen3.5-flash","name":"Qwen3.5 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"alibaba/qwen3.5-flash"},"qwen3.7-max":{"id":"qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2.5,"output":7.5,"cache_read":0.5,"cache_write":3.125}},"qwen2-5-32b-instruct":{"id":"qwen2-5-32b-instruct","name":"Qwen2.5 32B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.7,"output":2.8}},"qwq-plus":{"id":"qwq-plus","name":"QwQ Plus","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-03-05","last_updated":"2025-03-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.8,"output":2.4}},"qwen2-5-vl-72b-instruct":{"id":"qwen2-5-vl-72b-instruct","name":"Qwen2.5-VL 72B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":2.8,"output":8.4}},"qwen3-vl-plus":{"id":"qwen3-vl-plus","name":"Qwen3-VL Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.2,"output":1.6,"reasoning":4.8}},"qwen3.5-27b":{"id":"qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.3,"output":2.4}},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.2,"output":0.4,"cache_read":0.04},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"qwen-max":{"id":"qwen-max","name":"Qwen Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-03","last_updated":"2025-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":8192},"cost":{"input":1.6,"output":6.4}},"qwen3-next-80b-a3b-thinking":{"id":"qwen3-next-80b-a3b-thinking","name":"Qwen3-Next 80B-A3B (Thinking)","description":"Efficient Qwen thinking model for local reasoning, math, and coding agents","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":6}},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"qwen-plus-character-ja":{"id":"qwen-plus-character-ja","name":"Qwen Plus Character (Japanese)","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01","last_updated":"2024-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":512},"cost":{"input":0.5,"output":1.4}},"qwen3.5-plus":{"id":"qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.4,"output":2.4,"reasoning":2.4}},"qwen3-livetranslate-flash-realtime":{"id":"qwen3-livetranslate-flash-realtime","name":"Qwen3-LiveTranslate Flash Realtime","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-04","release_date":"2025-09-22","last_updated":"2025-09-22","modalities":{"input":["text","image","audio","video"],"output":["text","audio"]},"open_weights":false,"limit":{"context":53248,"output":4096},"cost":{"input":10,"output":10,"input_audio":10,"output_audio":38}},"qwen2-5-72b-instruct":{"id":"qwen2-5-72b-instruct","name":"Qwen2.5 72B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":1.4,"output":5.6}},"qwen3-32b":{"id":"qwen3-32b","name":"Qwen3 32B","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.7,"output":2.8,"reasoning":8.4}},"qwen-plus":{"id":"qwen-plus","name":"Qwen Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.4,"output":1.2,"reasoning":4}},"qwen3.7-flash":{"id":"qwen3.7-flash","name":"Qwen3.7 Flash","description":"Lightweight multimodal Qwen model for high-throughput text, image, and video tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":991808,"output":131072},"cost":{"input":0.03,"output":0.13,"cache_read":0.003,"cache_write":0.0375,"tiers":[{"input":0.1,"output":0.4,"cache_read":0.01,"cache_write":0.125,"tier":{"type":"context","size":32000}},{"input":0.2,"output":0.8,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":256000}}]},"canonical_model_id":"alibaba/qwen3.7-flash"},"qwen3-max":{"id":"qwen3-max","name":"Qwen3 Max","description":"Flagship Qwen3 model for coding agents, complex reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":1.2,"output":6}},"qwen-omni-turbo-realtime":{"id":"qwen-omni-turbo-realtime","name":"Qwen-Omni Turbo Realtime","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-05-08","last_updated":"2025-05-08","modalities":{"input":["text","image","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":32768,"output":2048},"cost":{"input":0.27,"output":1.07,"input_audio":4.44,"output_audio":8.89}},"qwen3-coder-480b-a35b-instruct":{"id":"qwen3-coder-480b-a35b-instruct","name":"Qwen3-Coder 480B-A35B Instruct","description":"Open Qwen coding heavyweight for repository reasoning and agentic engineering","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":1.5,"output":7.5,"tiers":[{"input":2.7,"output":13.5,"tier":{"type":"context","size":32000}},{"input":4.5,"output":22.5,"tier":{"type":"context","size":128000}}]}},"qwen-turbo":{"id":"qwen-turbo","name":"Qwen Turbo","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-11-01","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":16384},"cost":{"input":0.05,"output":0.2,"reasoning":0.5}},"qwen3-coder-30b-a3b-instruct":{"id":"qwen3-coder-30b-a3b-instruct","name":"Qwen3-Coder 30B-A3B Instruct","description":"Smaller Qwen coder for efficient local agents and repo-level fixes","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.45,"output":2.25,"tiers":[{"input":0.75,"output":3.75,"tier":{"type":"context","size":32000}},{"input":1.2,"output":6,"tier":{"type":"context","size":128000}}]}},"qwen3.8-omni-flash":{"id":"qwen3.8-omni-flash","name":"Qwen3.8 Omni Flash","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-omni-flash"},"qvq-max":{"id":"qvq-max","name":"QVQ Max","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qvq","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-03-25","last_updated":"2025-03-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":1.2,"output":4.8}},"qwen2-5-7b-instruct":{"id":"qwen2-5-7b-instruct","name":"Qwen2.5 7B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.175,"output":0.7}},"qwen3-omni-flash":{"id":"qwen3-omni-flash","name":"Qwen3-Omni Flash","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image","audio","video"],"output":["text","audio"]},"open_weights":false,"limit":{"context":65536,"output":16384},"cost":{"input":0.43,"output":1.66,"input_audio":3.81,"output_audio":15.11}},"qwen-vl-max":{"id":"qwen-vl-max","name":"Qwen-VL Max","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-08","last_updated":"2025-08-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.8,"output":3.2}},"qwen3-235b-a22b":{"id":"qwen3-235b-a22b","name":"Qwen3 235B-A22B","description":"Large open Qwen MoE for multilingual reasoning, coding, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.7,"output":2.8,"reasoning":8.4}},"qwen3-vl-30b-a3b":{"id":"qwen3-vl-30b-a3b","name":"Qwen3-VL 30B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.2,"output":0.8,"reasoning":2.4}},"qwen3.5-122b-a10b":{"id":"qwen3.5-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.4,"output":3.2}},"qwen3.6-35b-a3b":{"id":"qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.248,"output":1.485}},"qwen3-next-80b-a3b-instruct":{"id":"qwen3-next-80b-a3b-instruct","name":"Qwen3-Next 80B-A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":2}},"qwen-vl-plus":{"id":"qwen-vl-plus","name":"Qwen-VL Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-08-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.21,"output":0.63}},"qwen3.6-flash":{"id":"qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.1875,"output":1.125,"cache_write":0.234375}},"qwen3-coder-flash":{"id":"qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.3,"output":1.5}},"qwen2-5-omni-7b":{"id":"qwen2-5-omni-7b","name":"Qwen2.5-Omni 7B","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-12","last_updated":"2024-12","modalities":{"input":["text","image","audio","video"],"output":["text","audio"]},"open_weights":true,"limit":{"context":32768,"output":2048},"cost":{"input":0.1,"output":0.4,"input_audio":6.76}},"qwen-mt-plus":{"id":"qwen-mt-plus","name":"Qwen-MT Plus","description":"Translation model for multilingual conversion, localization, and cross-language workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-04","release_date":"2025-01","last_updated":"2025-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":8192},"cost":{"input":2.46,"output":7.37}},"qwen3-vl-235b-a22b":{"id":"qwen3-vl-235b-a22b","name":"Qwen3-VL 235B-A22B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.7,"output":2.8,"reasoning":8.4}},"qwen3-coder-plus":{"id":"qwen3-coder-plus","name":"Qwen3 Coder Plus","description":"Hosted Qwen coder for software agents, repo edits, and long-context code","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":1,"output":5}},"qwen2-5-14b-instruct":{"id":"qwen2-5-14b-instruct","name":"Qwen2.5 14B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.35,"output":1.4}},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen2-5-vl-7b-instruct":{"id":"qwen2-5-vl-7b-instruct","name":"Qwen2.5-VL 7B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.35,"output":1.05}},"qwen3.5-35b-a3b":{"id":"qwen3.5-35b-a3b","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.25,"output":2}},"qwen3.6-max-preview":{"id":"qwen3.6-max-preview","name":"Qwen3.6 Max Preview","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":1.3,"output":7.8,"cache_read":0.13,"cache_write":1.625}},"qwen-mt-turbo":{"id":"qwen-mt-turbo","name":"Qwen-MT Turbo","description":"Translation model for multilingual conversion, localization, and cross-language workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-04","release_date":"2025-01","last_updated":"2025-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":8192},"cost":{"input":0.16,"output":0.49}},"qwen3.5-397b-a17b":{"id":"qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.6,"output":3.6}},"qwen3-8b":{"id":"qwen3-8b","name":"Qwen3 8B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.18,"output":0.7,"reasoning":2.1}},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.28,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"qwen-omni-turbo":{"id":"qwen-omni-turbo","name":"Qwen-Omni Turbo","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-01-19","last_updated":"2025-03-26","modalities":{"input":["text","image","audio","video"],"output":["text","audio"]},"open_weights":false,"limit":{"context":32768,"output":2048},"cost":{"input":0.07,"output":0.27,"input_audio":4.44,"output_audio":8.89}},"qwen3-omni-flash-realtime":{"id":"qwen3-omni-flash-realtime","name":"Qwen3-Omni Flash Realtime","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image","audio","video"],"output":["text","audio"]},"open_weights":false,"limit":{"context":65536,"output":16384},"cost":{"input":0.52,"output":1.99,"input_audio":4.57,"output_audio":18.13}},"qwen3-asr-flash":{"id":"qwen3-asr-flash","name":"Qwen3-ASR Flash","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2024-04","release_date":"2025-09-08","last_updated":"2025-09-08","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":53248,"output":4096},"cost":{"input":0.035,"output":0.035}},"qwen3.6-27b":{"id":"qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.6,"output":3.6}},"qwen3.6-plus":{"id":"qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625,"tiers":[{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5}}},"qwen3-14b":{"id":"qwen3-14b","name":"Qwen3 14B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.35,"output":1.4,"reasoning":4.2}},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-04","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.4,"output":1.6,"cache_read":0.04,"cache_write":0.5,"tiers":[{"input":1.2,"output":4.8,"cache_read":0.12,"cache_write":1.5,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1.2,"output":4.8,"cache_read":0.12,"cache_write":1.5}}},"qwen-vl-ocr":{"id":"qwen-vl-ocr","name":"Qwen-VL OCR","description":"OCR model for extracting structured text from documents and screenshots","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-04","release_date":"2024-10-28","last_updated":"2025-04-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":34096,"output":4096},"cost":{"input":0.07,"output":0.16}}}},"auriko":{"id":"auriko","env":["AURIKO_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.auriko.ai/v1","name":"Auriko","doc":"https://docs.auriko.ai","models":{"qwen-3.6-plus":{"id":"qwen-3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.1,"tiers":[{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5}},"canonical_model_id":"alibaba/qwen3.6-plus"},"minimax-m2-7-highspeed":{"id":"minimax-m2-7-highspeed","name":"MiniMax-M2.7-highspeed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"grok-4.3":{"id":"grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.3"},"gemini-3.1-pro-preview":{"id":"gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":2.8},"canonical_model_id":"moonshotai/kimi-k2.5"},"gemini-2.5-pro":{"id":"gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro"},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-2.5-flash"},"minimax-m2-7":{"id":"minimax-m2-7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.435,"output":0.87,"cache_read":0.003625},"canonical_model_id":"deepseek/deepseek-v4-pro"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":30,"output":150,"cache_read":3,"cache_write":37.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"deepseek/deepseek-v4-flash"}}},"zenmux":{"id":"zenmux","env":["ZENMUX_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://zenmux.ai/api/v1","name":"ZenMux","doc":"https://docs.zenmux.ai","models":{"anthropic/claude-opus-4.1":{"id":"anthropic/claude-opus-4.1","name":"Claude Opus 4.1","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75}},"anthropic/claude-opus-4.5":{"id":"anthropic/claude-opus-4.5","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"anthropic/claude-opus-4.6":{"id":"anthropic/claude-opus-4.6","name":"Claude Opus 4.6","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-06","last_updated":"2026-02-06","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"anthropic/claude-3.5-haiku":{"id":"anthropic/claude-3.5-haiku","name":"Claude 3.5 Haiku","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2024-11-04","last_updated":"2024-11-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":0.8,"output":4,"cache_read":0.08,"cache_write":1}},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude Opus 4.7","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-sonnet-5-free":{"id":"anthropic/claude-sonnet-5-free","name":"Claude Sonnet 5 (Free)","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-haiku-4.5":{"id":"anthropic/claude-haiku-4.5","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25}},"anthropic/claude-fable-5.1":{"id":"anthropic/claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-sonnet-4.5":{"id":"anthropic/claude-sonnet-4.5","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75}},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-3.7-sonnet":{"id":"anthropic/claude-3.7-sonnet","name":"Claude 3.7 Sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-02-24","last_updated":"2025-02-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75}},"anthropic/claude-sonnet-4":{"id":"anthropic/claude-sonnet-4","name":"Claude Sonnet 4","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75}},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":4},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude Sonnet 4.6","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-18","last_updated":"2026-02-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75}},"anthropic/claude-opus-5.5":{"id":"anthropic/claude-opus-5.5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-opus-4":{"id":"anthropic/claude-opus-4","name":"Claude Opus 4","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75}},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-chat":{"id":"deepseek/deepseek-chat","name":"DeepSeek-V3.2 (Non-thinking Mode)","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"status":"deprecated","cost":{"input":0.28,"output":0.42,"cache_read":0.03}},"deepseek/deepseek-v3.2-exp":{"id":"deepseek/deepseek-v3.2-exp","name":"DeepSeek-V3.2-Exp","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":163000,"output":64000},"cost":{"input":0.22,"output":0.33}},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.435,"output":0.87,"cache_read":0.003625},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v3.2":{"id":"deepseek/deepseek-v3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-12-05","last_updated":"2025-12-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"cost":{"input":0.28,"output":0.43}},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"tencent/hy3-preview":{"id":"tencent/hy3-preview","name":"Hy3 preview","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.172,"output":0.572,"cache_read":0.058,"cache_write":0},"canonical_model_id":"tencent/hy3-preview"},"z-ai/glm-4.6v":{"id":"z-ai/glm-4.6v","name":"GLM 4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.1456,"output":0.4367,"cache_read":0.0291,"tiers":[{"input":0.2911,"output":0.8734,"cache_read":0.0582,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.6v"},"z-ai/glm-4.5":{"id":"z-ai/glm-4.5","name":"GLM 4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":96000},"cost":{"input":0.2911,"output":1.1645,"cache_read":0.0582,"tiers":[{"input":0.5823,"output":2.3291,"cache_read":0.1165,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.5"},"z-ai/glm-5v-turbo":{"id":"z-ai/glm-5v-turbo","name":"GLM 5V Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":0.726,"output":3.1946,"cache_read":0.1743,"tiers":[{"input":1.0165,"output":3.7754,"cache_read":0.2614,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-5v-turbo"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-4.6":{"id":"z-ai/glm-4.6","name":"GLM 4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.2911,"output":1.1645,"cache_read":0.0582,"tiers":[{"input":0.5823,"output":2.3291,"cache_read":0.1165,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.6"},"z-ai/glm-5":{"id":"z-ai/glm-5","name":"GLM 5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.58,"output":2.6,"cache_read":0.14,"tiers":[{"input":0.87,"output":3.18,"cache_read":0.22,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-5"},"z-ai/glm-4.6v-flash":{"id":"z-ai/glm-4.6v-flash","name":"GLM 4.6V FlashX","description":"Lightweight GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.0218,"output":0.2184,"cache_read":0.0044,"tiers":[{"input":0.0437,"output":0.4367,"cache_read":0.0044,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.6v-flash"},"z-ai/glm-5.3-flashx":{"id":"z-ai/glm-5.3-flashx","name":"GLM 5.3 FlashX","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.375,"output":1.25,"cache_read":0.075},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-4.7":{"id":"z-ai/glm-4.7","name":"GLM 4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.2911,"output":1.1645,"cache_read":0.0582,"tiers":[{"input":0.5823,"output":2.3291,"cache_read":0.1165,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.7"},"z-ai/glm-4.7-flash-free":{"id":"z-ai/glm-4.7-flash-free","name":"GLM 4.7 Flash (Free)","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-4.7-flash"},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.98,"output":3.08,"cache_read":0.182},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/glm-5.1":{"id":"z-ai/glm-5.1","name":"GLM 5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.8781,"output":3.5126,"cache_read":0.1903,"tiers":[{"input":1.1709,"output":4.098,"cache_read":0.2927,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-5.1"},"z-ai/glm-4.7-flashx":{"id":"z-ai/glm-4.7-flashx","name":"GLM 4.7 FlashX","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.0728,"output":0.4367,"cache_read":0.0146},"canonical_model_id":"zhipuai/glm-4.7-flashx"},"z-ai/glm-5-turbo":{"id":"z-ai/glm-5-turbo","name":"GLM 5 Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":0.73,"output":3.19,"cache_read":0.174,"tiers":[{"input":1.02,"output":3.77,"cache_read":0.261,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-5-turbo"},"z-ai/glm-4.6v-flash-free":{"id":"z-ai/glm-4.6v-flash-free","name":"GLM 4.6V Flash (Free)","description":"Lightweight GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"tiers":[{"input":0,"output":0,"cache_read":0,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.6v-flash"},"z-ai/glm-image":{"id":"z-ai/glm-image","name":"GLM-Image","description":"GLM-Image is an image generation model adopts a hybrid autoregressive + diffusion decoder architecture. In general image generation quality, GLM‑Image aligns with mainstream latent diffusion approaches, but it shows significant advantages in text-rendering and knowledge‑intensive generation scenarios. It performs especially well in tasks requiring precise semantic understanding and complex information expression, while maintaining strong capabilities in high‑fidelity and fine‑grained detail generation. In addition to text‑to‑image generation, GLM‑Image also supports a rich set of image‑to‑image tasks including image editing, style transfer, identity‑preserving generation, and multi‑subject consistency.","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["image"]},"open_weights":true,"limit":{"context":10240,"output":0},"canonical_model_id":"zhipuai/glm-image"},"z-ai/glm-4.5-air":{"id":"z-ai/glm-4.5-air","name":"GLM 4.5 Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":96000},"cost":{"input":0.1165,"output":0.2911,"cache_read":0.0233,"tiers":[{"input":0.1747,"output":1.1645,"cache_read":0.0349,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.5-air"},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"kuaishou/kat-coder-pro-v2":{"id":"kuaishou/kat-coder-pro-v2","name":"KAT-Coder-Pro-V2","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-03-30","last_updated":"2026-03-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":80000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06}},"baidu/ernie-5.0-thinking-preview":{"id":"baidu/ernie-5.0-thinking-preview","name":"ERNIE 5.0","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-01-22","last_updated":"2026-01-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"cost":{"input":0.84,"output":3.37}},"x-ai/grok-4.3":{"id":"x-ai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.3"},"x-ai/grok-4.5":{"id":"x-ai/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.5"},"x-ai/grok-voice-tts-1.0":{"id":"x-ai/grok-voice-tts-1.0","name":"Grok Voice TTS 1.0","description":"Convert text into spoken audio with a single API call. The API supports a rich set of expressive voices, inline speech tags for fine-grained delivery control, and output formats from high-fidelity MP3 to telephony-optimized μ-law.","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":15000,"output":15000},"canonical_model_id":"xai/grok-voice-tts-1.0"},"x-ai/grok-imagine-image-2.0":{"id":"x-ai/grok-imagine-image-2.0","name":"Grok Imagine Image 2.0","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"grok","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-08-07","last_updated":"2026-08-07","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":66000,"output":0},"canonical_model_id":"xai/grok-imagine-image-2.0"},"x-ai/grok-voice-stt-1.0":{"id":"x-ai/grok-voice-stt-1.0","name":"Grok Voice STT 1.0","description":"Grok Voice STT 1.0 is xAI's speech-to-text model. It supports transcription with word-level timestamps, optional speaker diarization, and multichannel audio.","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-08-04","last_updated":"2026-08-04","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":15000,"output":15000},"canonical_model_id":"xai/grok-voice-stt-1.0"},"x-ai/grok-build-0.1":{"id":"x-ai/grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.2},"canonical_model_id":"xai/grok-build-0.1"},"x-ai/grok-4.2-fast":{"id":"x-ai/grok-4.2-fast","name":"Grok 4.2 Fast","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":2,"output":6,"cache_read":0.2,"tiers":[{"input":4,"output":12,"cache_read":0.2,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"xai/grok-4.20-0309-reasoning"},"x-ai/grok-4.2-fast-non-reasoning":{"id":"x-ai/grok-4.2-fast-non-reasoning","name":"Grok 4.2 Fast Non Reasoning","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":2,"output":6,"cache_read":0.2,"tiers":[{"input":4,"output":12,"cache_read":0.2,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"xai/grok-4.20-0309-non-reasoning"},"x-ai/grok-4.6":{"id":"x-ai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"volcengine/doubao-seed-2.0-mini":{"id":"volcengine/doubao-seed-2.0-mini","name":"Doubao-Seed-2.0-mini","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-02-14","release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":0.03,"output":0.28,"cache_read":0.01,"cache_write":0.0024}},"volcengine/doubao-seed-2.0-lite":{"id":"volcengine/doubao-seed-2.0-lite","name":"Doubao-Seed-2.0-lite","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-02-14","release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":0.09,"output":0.51,"cache_read":0.02,"cache_write":0.0024}},"volcengine/doubao-seed-code":{"id":"volcengine/doubao-seed-code","name":"Doubao-Seed-Code","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-11-11","last_updated":"2025-11-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"status":"deprecated","cost":{"input":0.17,"output":1.12,"cache_read":0.03}},"volcengine/doubao-seed-2.0-pro":{"id":"volcengine/doubao-seed-2.0-pro","name":"Doubao-Seed-2.0-pro","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-02-14","release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":0.45,"output":2.24,"cache_read":0.09,"cache_write":0.0024}},"volcengine/doubao-seed-1.8":{"id":"volcengine/doubao-seed-1.8","name":"Doubao-Seed-1.8","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-12-18","last_updated":"2025-12-18","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":0.11,"output":0.28,"cache_read":0.02,"cache_write":0.0024}},"volcengine/doubao-seed-2.0-code":{"id":"volcengine/doubao-seed-2.0-code","name":"Doubao Seed 2.0 Code","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-03-20","last_updated":"2026-03-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.9,"output":4.48}},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-02-19","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","pdf","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048000,"output":64000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":4.5}},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["pdf","image","text","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048000,"output":64000},"cost":{"input":1.25,"output":10,"cache_read":0.31,"cache_write":4.5}},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["pdf","image","text","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048000,"output":64000},"cost":{"input":0.3,"output":2.5,"cache_read":0.07,"cache_write":1}},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048000,"output":64000},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":1}},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["pdf","image","text","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048000,"output":64000},"cost":{"input":0.1,"output":0.4,"cache_read":0.03,"cache_write":1}},"google/gemini-3.1-flash-lite-preview":{"id":"google/gemini-3.1-flash-lite-preview","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-03-20","last_updated":"2025-03-20","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":65530},"cost":{"input":0.25,"output":1.5}},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025},"canonical_model_id":"google/gemini-3.1-flash-lite"},"sapiens-ai/agnes-1.5-lite":{"id":"sapiens-ai/agnes-1.5-lite","name":"Agnes 1.5 Lite","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-03-26","last_updated":"2026-03-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.12,"output":0.6}},"sapiens-ai/agnes-1.5-pro":{"id":"sapiens-ai/agnes-1.5-pro","name":"Agnes 1.5 Pro","description":"Flagship model for demanding analysis, coding, and production agent workflows","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-21","last_updated":"2026-03-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.16,"output":0.8}},"inclusionai/ring-2.6-1t":{"id":"inclusionai/ring-2.6-1t","name":"inclusionAI: Ring-2.6-1T","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-12-31","release_date":"2026-05-07","last_updated":"2026-05-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":65000},"cost":{"input":0.3,"output":2.5,"cache_read":0.06}},"inclusionai/ring-1t":{"id":"inclusionai/ring-1t","name":"Ring-1T","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-10-12","last_updated":"2025-10-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"status":"deprecated","cost":{"input":0.56,"output":2.24,"cache_read":0.11}},"inclusionai/ling-1t":{"id":"inclusionai/ling-1t","name":"Ling-1T","description":"Tool-capable chat model for instruction following and agentic application workflows","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-10-09","last_updated":"2025-10-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"status":"deprecated","cost":{"input":0.56,"output":2.24,"cache_read":0.11}},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.7-code-highspeed":{"id":"moonshotai/kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code HighSpeed","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2025-01-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262140,"output":262140},"cost":{"input":0.95,"output":4,"cache_read":0.16}},"moonshotai/kimi-k2-thinking":{"id":"moonshotai/kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Kimi reasoning model for long-horizon research, planning, and tool use","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":64000},"status":"deprecated","cost":{"input":0.6,"output":2.5,"cache_read":0.15}},"moonshotai/kimi-k2.5":{"id":"moonshotai/kimi-k2.5","name":"Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2025-01-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":64000},"cost":{"input":0.58,"output":3.02,"cache_read":0.1}},"moonshotai/kimi-k3-free":{"id":"moonshotai/kimi-k3-free","name":"Kimi K3 (Free)","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2-0905":{"id":"moonshotai/kimi-k2-0905","name":"Kimi K2 0905","description":"Kimi model for long-context chat, coding, and agentic reasoning","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-09-04","last_updated":"2025-09-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":64000},"status":"deprecated","cost":{"input":0.6,"output":2.5,"cache_read":0.15}},"moonshotai/kimi-k2.7-code-free":{"id":"moonshotai/kimi-k2.7-code-free","name":"Kimi K2.7 Code (Free)","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"moonshotai/kimi-k2-thinking-turbo":{"id":"moonshotai/kimi-k2-thinking-turbo","name":"Kimi K2 Thinking Turbo","description":"Kimi reasoning model for long-horizon research, planning, and tool use","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":64000},"status":"deprecated","cost":{"input":1.15,"output":8,"cache_read":0.15}},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"xiaomi/mimo-v2.6-pro":{"id":"xiaomi/mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"xiaomi/mimo-v2-flash":{"id":"xiaomi/mimo-v2-flash","name":"MiMo-V2-Flash","description":"MiMo flash model for fast multimodal assistance and agent workflows","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-12-01","release_date":"2025-12-16","last_updated":"2026-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.1,"output":0.3,"cache_read":0.01},"canonical_model_id":"xiaomi/mimo-v2-flash"},"xiaomi/mimo-v2.5":{"id":"xiaomi/mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.4,"output":2,"cache_read":0.08,"tiers":[{"input":0.8,"output":4,"cache_read":0.16,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.8,"output":4,"cache_read":0.16}},"canonical_model_id":"xiaomi/mimo-v2.5"},"xiaomi/mimo-v2-omni":{"id":"xiaomi/mimo-v2-omni","name":"MiMo V2 Omni","description":"MiMo omni model for text, image, video, audio, and agents","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":265000,"output":265000},"cost":{"input":0.4,"output":2,"cache_read":0.08},"canonical_model_id":"xiaomi/mimo-v2-omni"},"xiaomi/mimo-v2-pro":{"id":"xiaomi/mimo-v2-pro","name":"MiMo V2 Pro","description":"Earlier MiMo Pro model for multimodal agents, reasoning, and code tasks","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":256000},"cost":{"input":1,"output":3,"cache_read":0.2,"tiers":[{"input":2,"output":6,"cache_read":0.4,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.4}},"canonical_model_id":"xiaomi/mimo-v2-pro"},"xiaomi/mimo-v2.5-pro":{"id":"xiaomi/mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1,"output":3,"cache_read":0.2,"tiers":[{"input":2,"output":6,"cache_read":0.4,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.4}},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"minimax/minimax-m2.5-lightning":{"id":"minimax/minimax-m2.5-lightning","name":"MiniMax M2.5 highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-02-13","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":204800,"output":131072},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":0.6,"output":4.8,"cache_read":0.06,"cache_write":0.75}},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-02-13","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":204800,"output":131072},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375}},"minimax/minimax-m2.7":{"id":"minimax/minimax-m2.7","name":"MiniMax M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-03-20","last_updated":"2026-03-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":204800,"output":131070},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":0.3055,"output":1.2219}},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":0.6,"output":2.4},"canonical_model_id":"minimax/MiniMax-M3"},"minimax/minimax-m2.7-highspeed":{"id":"minimax/minimax-m2.7-highspeed","name":"MiniMax M2.7 highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-03-20","last_updated":"2026-03-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":204800,"output":131070},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":0.611,"output":2.4439}},"minimax/minimax-m2.1":{"id":"minimax/minimax-m2.1","name":"MiniMax M2.1","description":"MiniMax model for chat, coding, office work, and agentic tasks","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":204000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.38}},"minimax/minimax-m2":{"id":"minimax/minimax-m2","name":"MiniMax M2","description":"MiniMax model for chat, coding, office work, and agentic tasks","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":204000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.38}},"stepfun/step-3":{"id":"stepfun/step-3","name":"Step-3","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-07-31","last_updated":"2025-07-31","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"output":64000},"status":"deprecated","cost":{"input":0.21,"output":0.57}},"stepfun/step-3.5-flash":{"id":"stepfun/step-3.5-flash","name":"Step 3.5 Flash","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-02-02","last_updated":"2026-02-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":0.1,"output":0.3}},"stepfun/step-3.7-flash":{"id":"stepfun/step-3.7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.2,"output":1.15},"canonical_model_id":"stepfun/step-3.7-flash"},"stepfun/step-3.7-flash-free":{"id":"stepfun/step-3.7-flash-free","name":"Step 3.7 Flash (Free)","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0,"output":0},"canonical_model_id":"stepfun/step-3.7-flash"},"qwen/qwen3.5-flash":{"id":"qwen/qwen3.5-flash","name":"Qwen3.5 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-03-20","last_updated":"2026-03-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1020000,"output":1020000},"cost":{"input":0.1,"output":0.4}},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":2.5,"output":7.5,"cache_read":0.5,"cache_write":3.125},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen3.5-plus":{"id":"qwen/qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-03-20","last_updated":"2026-03-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.8,"output":4.8}},"qwen/qwen3-max":{"id":"qwen/qwen3-max","name":"Qwen3-Max-Thinking","description":"Qwen reasoning model for deliberate problem solving, math, and coding","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-01-23","last_updated":"2026-01-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":1.2,"output":6}},"qwen/qwen3-coder-plus":{"id":"qwen/qwen3-coder-plus","name":"Qwen3-Coder-Plus","description":"Qwen coding model for software agents, repository edits, and code reasoning","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25}},"qwen/qwen3.6-plus":{"id":"qwen/qwen3.6-plus","name":"Qwen3.6-Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-03-30","last_updated":"2026-03-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625,"tiers":[{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5}}},"qwen/qwen3.7-plus":{"id":"qwen/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.4,"output":1.6,"cache_read":0.08,"cache_write":0.5,"tiers":[{"input":1.2,"output":4.8,"cache_read":0.24,"cache_write":1.5,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1.2,"output":4.8,"cache_read":0.24,"cache_write":1.5}},"canonical_model_id":"alibaba/qwen3.7-plus"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-20","last_updated":"2026-03-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":3.75,"output":18.75}},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT-5.4 Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-20","last_updated":"2026-03-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":45,"output":225}},"openai/gpt-5.3-chat":{"id":"openai/gpt-5.3-chat","name":"GPT-5.3 Chat","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-20","last_updated":"2026-03-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16380},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":1.75,"output":14}},"openai/gpt-5.5-pro":{"id":"openai/gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.5-pro"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-20","last_updated":"2026-03-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":0.2,"output":1.25}},"openai/gpt-5.2-codex":{"id":"openai/gpt-5.2-codex","name":"GPT-5.2-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2025-01-01","release_date":"2026-01-15","last_updated":"2026-01-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":64000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":1.75,"output":14,"cache_read":0.17}},"openai/gpt-5.1-codex":{"id":"openai/gpt-5.1-codex","name":"GPT-5.1-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":64000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":1.25,"output":10,"cache_read":0.12}},"openai/gpt-5-codex":{"id":"openai/gpt-5-codex","name":"GPT-5 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":64000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":1.25,"output":10,"cache_read":0.12}},"openai/gpt-5.2-pro":{"id":"openai/gpt-5.2-pro","name":"GPT-5.2-Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":21,"output":168}},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-20","last_updated":"2026-03-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":1.75,"output":14}},"openai/gpt-5.5-instant":{"id":"openai/gpt-5.5-instant","name":"GPT-5.5 Instant","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12-01","release_date":"2026-05-05","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5-instant"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":64000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":1.25,"output":10,"cache_read":0.12}},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-20","last_updated":"2026-03-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":0.75,"output":4.5}},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":1,"output":6,"cache_read":0.1,"cache_write":1.25,"tiers":[{"input":2,"output":9,"cache_read":0.2,"cache_write":2.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":2,"output":9,"cache_read":0.2,"cache_write":2.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2025-01-01","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":64000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":1.75,"output":14,"cache_read":0.17}},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":12.5,"output":75,"cache_read":1.25},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-5.1-chat":{"id":"openai/gpt-5.1-chat","name":"GPT-5.1 Chat","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"status":"deprecated","provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":1.25,"output":10,"cache_read":0.12}},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"cache_write":3.125,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"cache_write":6.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5,"cache_write":6.25}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-5.1-codex-mini":{"id":"openai/gpt-5.1-codex-mini","name":"GPT-5.1-Codex-Mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":64000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":0.25,"output":2,"cache_read":0.03}},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":64000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":1.25,"output":10,"cache_read":0.12}},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":45,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1,"cache_write":12.5}},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"}}},"unorouter":{"id":"unorouter","env":["UNOROUTER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.unorouter.com/v1","name":"UnoRouter","doc":"https://unorouter.com/models","models":{"gpt-5.5:free":{"id":"gpt-5.5:free","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"openai/gpt-5.5"},"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":1.8,"output":10.8},"canonical_model_id":"openai/gpt-5.4"},"glm-4.5-flash:free":{"id":"glm-4.5-flash:free","name":"GLM-4.5-Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":98304},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-4.5-flash"},"gemma-4-31b-it:free":{"id":"gemma-4-31b-it:free","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemma-4-31b-it"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.2675,"output":5.3368},"canonical_model_id":"moonshotai/kimi-k2.6"},"nemotron-3-ultra-550b-a55b:free":{"id":"nemotron-3-ultra-550b-a55b:free","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"gpt-5.4:free":{"id":"gpt-5.4:free","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"openai/gpt-5.4"},"minimax-m2.7":{"id":"minimax-m2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.819,"output":3.276},"canonical_model_id":"minimax/MiniMax-M2.7"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.1857,"output":1.1142},"canonical_model_id":"google/gemini-3.5-flash"},"gpt-5.2":{"id":"gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.05,"output":8.4},"canonical_model_id":"openai/gpt-5.2"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.425,"output":2.125},"canonical_model_id":"anthropic/claude-opus-4-8"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1875,"output":1.125},"canonical_model_id":"openai/gpt-5.5"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":1.44,"output":7.2},"canonical_model_id":"anthropic/claude-sonnet-5"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.6001,"output":5.0288},"canonical_model_id":"zhipuai/glm-5.2"},"step-3.7-flash:free":{"id":"step-3.7-flash:free","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0,"output":0},"canonical_model_id":"stepfun/step-3.7-flash"},"deepseek-v4-flash:free":{"id":"deepseek-v4-flash:free","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-v4-flash"},"claude-haiku-4-5-20251001":{"id":"claude-haiku-4-5-20251001","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1.2,"output":6},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"deepseek-v4-pro:free":{"id":"deepseek-v4-pro:free","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-v4-pro"},"glm-5.2:free":{"id":"glm-5.2:free","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-5.2"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.8999,"output":1.7999},"canonical_model_id":"deepseek/deepseek-v4-pro"},"qwen3.5-397b-a17b:free":{"id":"qwen3.5-397b-a17b:free","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"minimax-m2.7:free":{"id":"minimax-m2.7:free","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"minimax/MiniMax-M2.7"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.0625,"output":0.125},"canonical_model_id":"deepseek/deepseek-v4-flash"}}},"salad-cloud":{"id":"salad-cloud","env":["SALAD_CLOUD_API_KEY"],"npm":"@saladtechnologies-oss/ai-sdk-provider","name":"SaladCloud AI Gateway","doc":"https://docs.salad.com/ai-gateway/explanation/overview","models":{"qwen3.6-35b-a3b":{"id":"qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Qwen MoE for agentic tasks, complex reasoning, code generation, and instruction following","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":262144},"cost":{"input":0.09,"output":0.6},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"}}},"vispark":{"id":"vispark","env":["VISPARK_LAB_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.lab.vispark.in/v1","name":"Vispark","doc":"https://lab.vispark.in/#vision","models":{"vispark/vision-large":{"id":"vispark/vision-large","name":"Vision Large","description":"Most capable Vision model for complex reasoning, detailed media analysis, and structured output over a 1M-token context window.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-05-15","last_updated":"2026-09","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":7.37,"output":22.11}},"vispark/vision-small":{"id":"vispark/vision-small","name":"Vision Small","description":"Fast, low-cost multimodal model for understanding text, images, audio, video, and PDFs, with tool calling and a 1M-token context window.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-05-15","last_updated":"2026-09","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":1.05,"output":3.16}},"vispark/vision-medium":{"id":"vispark/vision-medium","name":"Vision Medium","description":"Balanced multimodal model pairing a 1M-token context window with deeper reasoning for analysis, content creation, and tool use across text, image, audio, video, and PDF inputs.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-05-15","last_updated":"2026-09","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":4.21,"output":12.63}}}},"siliconflow-cn":{"id":"siliconflow-cn","env":["SILICONFLOW_CN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.siliconflow.cn/v1","name":"SiliconFlow (China)","doc":"https://cloud.siliconflow.com/models","models":{"ByteDance-Seed/Seed-OSS-36B-Instruct":{"id":"ByteDance-Seed/Seed-OSS-36B-Instruct","name":"ByteDance-Seed/Seed-OSS-36B-Instruct","description":"Tool-capable chat model for instruction following and agentic application workflows","family":"seed","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-04","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.21,"output":0.57}},"tencent/Hunyuan-A13B-Instruct":{"id":"tencent/Hunyuan-A13B-Instruct","name":"tencent/Hunyuan-A13B-Instruct","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"hunyuan","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-06-30","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":131000},"cost":{"input":0.14,"output":0.57}},"Qwen/Qwen3.5-4B":{"id":"Qwen/Qwen3.5-4B","name":"Qwen/Qwen3.5-4B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0,"output":0}},"Qwen/Qwen3.5-27B":{"id":"Qwen/Qwen3.5-27B","name":"Qwen/Qwen3.5-27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-25","last_updated":"2026-02-25","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.26,"output":2.09}},"Qwen/Qwen3.6-35B-A3B":{"id":"Qwen/Qwen3.6-35B-A3B","name":"Qwen/Qwen3.6-35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.23,"output":1.86}},"Qwen/Qwen3-235B-A22B-Thinking-2507":{"id":"Qwen/Qwen3-235B-A22B-Thinking-2507","name":"Qwen/Qwen3-235B-A22B-Thinking-2507","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-28","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.13,"output":0.6}},"Qwen/Qwen3-14B":{"id":"Qwen/Qwen3-14B","name":"Qwen/Qwen3-14B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-30","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":131000},"cost":{"input":0.07,"output":0.28}},"Qwen/Qwen3-8B":{"id":"Qwen/Qwen3-8B","name":"Qwen/Qwen3-8B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-30","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":131000},"cost":{"input":0.06,"output":0.06}},"Qwen/Qwen3-32B":{"id":"Qwen/Qwen3-32B","name":"Qwen/Qwen3-32B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-30","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":131000},"cost":{"input":0.14,"output":0.57}},"Qwen/Qwen3.5-35B-A3B":{"id":"Qwen/Qwen3.5-35B-A3B","name":"Qwen/Qwen3.5-35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-25","last_updated":"2026-02-25","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.23,"output":1.86}},"Qwen/Qwen3.5-122B-A10B":{"id":"Qwen/Qwen3.5-122B-A10B","name":"Qwen/Qwen3.5-122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-26","last_updated":"2026-02-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.29,"output":2.32}},"Qwen/Qwen3.5-9B":{"id":"Qwen/Qwen3.5-9B","name":"Qwen/Qwen3.5-9B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.22,"output":1.74}},"Qwen/Qwen3.5-397B-A17B":{"id":"Qwen/Qwen3.5-397B-A17B","name":"Qwen/Qwen3.5-397B-A17B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.29,"output":1.74}},"Qwen/Qwen3-Coder-480B-A35B-Instruct":{"id":"Qwen/Qwen3-Coder-480B-A35B-Instruct","name":"Qwen/Qwen3-Coder-480B-A35B-Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-31","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.25,"output":1}},"Qwen/Qwen3-VL-32B-Instruct":{"id":"Qwen/Qwen3-VL-32B-Instruct","name":"Qwen/Qwen3-VL-32B-Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-21","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.2,"output":0.6}},"Qwen/Qwen2.5-7B-Instruct":{"id":"Qwen/Qwen2.5-7B-Instruct","name":"Qwen/Qwen2.5-7B-Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-09-18","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":33000,"output":4000},"cost":{"input":0.05,"output":0.05}},"Qwen/Qwen3-Coder-30B-A3B-Instruct":{"id":"Qwen/Qwen3-Coder-30B-A3B-Instruct","name":"Qwen/Qwen3-Coder-30B-A3B-Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-01","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.07,"output":0.28}},"Qwen/Qwen2.5-72B-Instruct":{"id":"Qwen/Qwen2.5-72B-Instruct","name":"Qwen/Qwen2.5-72B-Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-09-18","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":33000,"output":4000},"cost":{"input":0.59,"output":0.59}},"Qwen/Qwen3-VL-30B-A3B-Thinking":{"id":"Qwen/Qwen3-VL-30B-A3B-Thinking","name":"Qwen/Qwen3-VL-30B-A3B-Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-11","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.29,"output":1}},"Qwen/Qwen3-30B-A3B-Instruct-2507":{"id":"Qwen/Qwen3-30B-A3B-Instruct-2507","name":"Qwen/Qwen3-30B-A3B-Instruct-2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-30","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.09,"output":0.3}},"Qwen/Qwen3-VL-32B-Thinking":{"id":"Qwen/Qwen3-VL-32B-Thinking","name":"Qwen/Qwen3-VL-32B-Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-21","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.2,"output":1.5}},"Qwen/Qwen3-VL-8B-Instruct":{"id":"Qwen/Qwen3-VL-8B-Instruct","name":"Qwen/Qwen3-VL-8B-Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-15","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.18,"output":0.68}},"Qwen/Qwen3-VL-30B-A3B-Instruct":{"id":"Qwen/Qwen3-VL-30B-A3B-Instruct","name":"Qwen/Qwen3-VL-30B-A3B-Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-05","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.29,"output":1}},"deepseek-ai/DeepSeek-R1":{"id":"deepseek-ai/DeepSeek-R1","name":"deepseek-ai/DeepSeek-R1","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":164000,"output":164000},"cost":{"input":0.5,"output":2.18}},"deepseek-ai/DeepSeek-V4-Flash":{"id":"deepseek-ai/DeepSeek-V4-Flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek-ai/DeepSeek-OCR":{"id":"deepseek-ai/DeepSeek-OCR","name":"deepseek-ai/DeepSeek-OCR","description":"OCR model for extracting structured text from documents and screenshots","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-10-20","last_updated":"2025-10-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0,"output":0}},"deepseek-ai/DeepSeek-V4-Pro":{"id":"deepseek-ai/DeepSeek-V4-Pro","name":"deepseek-ai/DeepSeek-V4-Pro","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1049000,"output":393000},"cost":{"input":1.74,"output":3.48,"cache_read":0.145}},"deepseek-ai/DeepSeek-V3.2":{"id":"deepseek-ai/DeepSeek-V3.2","name":"deepseek-ai/DeepSeek-V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-03","last_updated":"2025-12-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":164000,"output":164000},"cost":{"input":0.27,"output":0.42}},"deepseek-ai/DeepSeek-V3.1-Terminus":{"id":"deepseek-ai/DeepSeek-V3.1-Terminus","name":"deepseek-ai/DeepSeek-V3.1-Terminus","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-29","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":164000,"output":164000},"cost":{"input":0.27,"output":1}},"deepseek-ai/DeepSeek-V3":{"id":"deepseek-ai/DeepSeek-V3","name":"deepseek-ai/DeepSeek-V3","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-12-26","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":164000,"output":164000},"cost":{"input":0.25,"output":1}},"stepfun-ai/Step-3.5-Flash":{"id":"stepfun-ai/Step-3.5-Flash","name":"stepfun-ai/Step-3.5-Flash","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","family":"step","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-11","last_updated":"2026-02-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.1,"output":0.3}},"inclusionAI/Ling-flash-2.0":{"id":"inclusionAI/Ling-flash-2.0","name":"inclusionAI/Ling-flash-2.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-18","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":131000},"cost":{"input":0.14,"output":0.57}},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1049000,"output":262000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-4.5-Air":{"id":"zai-org/GLM-4.5-Air","name":"zai-org/GLM-4.5-Air","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-air","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-28","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":131000},"cost":{"input":0.14,"output":0.86}},"Pro/deepseek-ai/DeepSeek-R1":{"id":"Pro/deepseek-ai/DeepSeek-R1","name":"Pro/deepseek-ai/DeepSeek-R1","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":164000,"output":164000},"cost":{"input":0.5,"output":2.18}},"Pro/deepseek-ai/DeepSeek-V3.2":{"id":"Pro/deepseek-ai/DeepSeek-V3.2","name":"Pro/deepseek-ai/DeepSeek-V3.2","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-03","last_updated":"2025-12-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":164000,"output":164000},"cost":{"input":0.27,"output":0.42}},"Pro/deepseek-ai/DeepSeek-V3":{"id":"Pro/deepseek-ai/DeepSeek-V3","name":"Pro/deepseek-ai/DeepSeek-V3","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-12-26","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":164000,"output":164000},"cost":{"input":0.25,"output":1}},"Pro/deepseek-ai/DeepSeek-V3.1-Terminus":{"id":"Pro/deepseek-ai/DeepSeek-V3.1-Terminus","name":"Pro/deepseek-ai/DeepSeek-V3.1-Terminus","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-29","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":164000,"output":164000},"cost":{"input":0.27,"output":1}},"Pro/MiniMaxAI/MiniMax-M2.5":{"id":"Pro/MiniMaxAI/MiniMax-M2.5","name":"Pro/MiniMaxAI/MiniMax-M2.5","description":"Frontier MiniMax model for engineering, office tasks, and agentic reasoning","family":"minimax","attachment":false,"reasoning":false,"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-13","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":192000,"output":131000},"cost":{"input":0.3,"output":1.22}},"Pro/moonshotai/Kimi-K2.6":{"id":"Pro/moonshotai/Kimi-K2.6","name":"Pro/moonshotai/Kimi-K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.95,"output":4,"cache_read":0.16}},"Pro/moonshotai/Kimi-K2.5":{"id":"Pro/moonshotai/Kimi-K2.5","name":"Pro/moonshotai/Kimi-K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.45,"output":2.25,"cache_read":0.07}},"Pro/zai-org/GLM-5.1":{"id":"Pro/zai-org/GLM-5.1","name":"Pro/zai-org/GLM-5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-04-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":205000,"output":205000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0}},"Pro/zai-org/GLM-5":{"id":"Pro/zai-org/GLM-5","name":"Pro/zai-org/GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":205000,"output":205000},"cost":{"input":1,"output":3.2}},"PaddlePaddle/PaddleOCR-VL-1.5":{"id":"PaddlePaddle/PaddleOCR-VL-1.5","name":"PaddlePaddle/PaddleOCR-VL-1.5","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-01-29","last_updated":"2026-01-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":16384},"cost":{"input":0,"output":0}}}},"regolo-ai":{"id":"regolo-ai","env":["REGOLO_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.regolo.ai/v1","name":"Regolo AI","doc":"https://docs.regolo.ai/","models":{"qwen3.8-27b":{"id":"qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":120000,"output":120000},"cost":{"input":0.58,"output":2.42},"canonical_model_id":"alibaba/qwen3.8-27b"},"brick-v1-beta":{"id":"brick-v1-beta","name":"Brick v1 Beta","description":"Semantic router by Regolo.ai that directs each request to the most suitable model, optimizing costs and performance","family":"model-router","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-02-06","last_updated":"2026-02-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":100000,"output":15000},"status":"beta","cost":{"input":0,"output":0}},"qwen3.5-122b":{"id":"qwen3.5-122b","name":"Qwen3.5-122B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-01","last_updated":"2026-02-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.9,"output":3.6}},"qwen3-coder-next":{"id":"qwen3-coder-next","name":"Qwen3-Coder-Next","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-01","last_updated":"2026-03-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.3,"output":1.2}},"apertus-70b":{"id":"apertus-70b","name":"Apertus 70B","description":"Fully open 70B multilingual LLM supporting 1800+ languages with 65K context. Trained on 15T tokens of compliant open data. Apache 2.0, EU AI Act compliant.","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-09-02","last_updated":"2025-09-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":30000,"output":30000},"cost":{"input":0.46,"output":2.42},"canonical_model_id":"swiss-ai/apertus-70b"},"glm5.2":{"id":"glm5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":96000,"output":96000},"cost":{"input":2.31,"output":6},"canonical_model_id":"zhipuai/glm-5.2"},"qwen3-reranker-4b":{"id":"qwen3-reranker-4b","name":"Qwen3-Reranker-4B","description":"Reranking model for improving retrieval quality in search and recommendation systems","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-02-01","last_updated":"2026-02-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0.12,"output":0.12}},"deepseek-ocr-2":{"id":"deepseek-ocr-2","name":"DeepSeek OCR 2","description":"High-accuracy OCR model for extracting text from documents, screenshots, receipts, and natural scenes","attachment":true,"reasoning":false,"tool_call":false,"release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":4000,"output":4000},"cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-ocr-2"},"llama-3.3-70b-instruct":{"id":"llama-3.3-70b-instruct","name":"Llama 3.3 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.6,"output":2.7}},"gemma4-31b":{"id":"gemma4-31b","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":100000,"output":100000},"cost":{"input":0.46,"output":2.42},"canonical_model_id":"google/gemma-4-31b-it"},"brick-complexity-pro":{"id":"brick-complexity-pro","name":"Brick Complexity Pro","description":"Complexity classifier that powers the Brick semantic router by extracting query difficulty","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-02-06","last_updated":"2026-02-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":100000,"output":15000},"cost":{"input":0.12,"output":0.46}},"gpt-oss-20b":{"id":"gpt-oss-20b","name":"GPT-OSS-20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-03-01","last_updated":"2026-03-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.4,"output":1.8}},"qwen3.5-9b":{"id":"qwen3.5-9b","name":"Qwen3.5-9B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-01","last_updated":"2026-02-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.15,"output":0.6}},"qwen3-embedding-8b":{"id":"qwen3-embedding-8b","name":"Qwen3-Embedding-8B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-02-01","last_updated":"2026-02-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0.1,"output":0.1}},"mistral-small-4-119b":{"id":"mistral-small-4-119b","name":"Mistral Small 4 119B","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-15","last_updated":"2026-03-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":16384},"cost":{"input":0.75,"output":3}},"qwen-image":{"id":"qwen-image","name":"Qwen-Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-03-01","last_updated":"2026-03-01","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":8192,"output":4096},"cost":{"input":0.5,"output":2}},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT-OSS-120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1,"output":4.2}},"faster-whisper-large-v3":{"id":"faster-whisper-large-v3","name":"Faster Whisper Large v3","description":"Open Whisper checkpoint for robust multilingual transcription and captioning","family":"whisper","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2024-10-01","last_updated":"2024-10-01","modalities":{"input":["audio"],"output":["text"]},"open_weights":true,"limit":{"context":448,"output":4096},"cost":{"input":0,"output":0},"canonical_model_id":"openai/whisper-large-v3"}}},"xiaomi-token-plan-ams":{"id":"xiaomi-token-plan-ams","env":["XIAOMI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://token-plan-ams.xiaomimimo.com/v1","name":"Xiaomi Token Plan (Europe)","doc":"https://platform.xiaomimimo.com/#/docs","models":{"mimo-v2.6-pro":{"id":"mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"mimo-v2.6-flash":{"id":"mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"mimo-v2.5-tts-voiceclone":{"id":"mimo-v2.5-tts-voiceclone","name":"MiMo-V2.5-TTS-VoiceClone","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mimo","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["audio"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0,"output":0}},"mimo-v2.5-pro":{"id":"mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"mimo-v2-tts":{"id":"mimo-v2-tts","name":"MiMo-V2-TTS","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mimo","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["audio"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0,"output":0}},"mimo-v2-pro":{"id":"mimo-v2-pro","name":"MiMo-V2-Pro","description":"Earlier MiMo Pro model for multimodal agents, reasoning, and code tasks","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2-pro"},"mimo-v2.5-tts":{"id":"mimo-v2.5-tts","name":"MiMo-V2.5-TTS","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mimo","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["audio"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0,"output":0}},"mimo-v2.5-tts-voicedesign":{"id":"mimo-v2.5-tts-voicedesign","name":"MiMo-V2.5-TTS-VoiceDesign","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mimo","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["audio"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0,"output":0}},"mimo-v2.5":{"id":"mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.5"}}},"inceptron":{"id":"inceptron","env":["INCEPTRON_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.inceptron.io/v1","name":"Inceptron","doc":"https://docs.inceptron.io","models":{"deepseek-ai/DeepSeek-V4-Flash-0731":{"id":"deepseek-ai/DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.13,"output":0.28,"cache_read":0.03,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.53,"output":3.39,"cache_read":0.17,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/Kimi-K2.7-Code":{"id":"moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.66,"output":3.4,"cache_read":0.18,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.71,"output":2.35,"cache_read":0.12,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"}}},"aimlapi":{"id":"aimlapi","env":["AIMLAPI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.aimlapi.com/v1","name":"AI/ML API","doc":"https://docs.aimlapi.com","models":{"sao10k/l3-lunaris-8b":{"id":"sao10k/l3-lunaris-8b","name":"Llama 3 8B Lunaris","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-13","last_updated":"2024-08-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":7372},"cost":{"input":0.06877,"output":0.06877},"canonical_model_id":"sao10k/l3-lunaris-8b"},"sao10k/l3.3-euryale-70b":{"id":"sao10k/l3.3-euryale-70b","name":"Llama 3.3 Euryale 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-12-18","last_updated":"2024-12-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.89401,"output":1.03155},"canonical_model_id":"sao10k/l3.3-euryale-70b"},"sao10k/l3.1-euryale-70b":{"id":"sao10k/l3.1-euryale-70b","name":"Llama 3.1 Euryale 70B v2.2","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-28","last_updated":"2024-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":1.99488,"output":1.99488},"canonical_model_id":"sao10k/l3.1-euryale-70b"},"bytedance-seed/seed-1.6-flash":{"id":"bytedance-seed/seed-1.6-flash","name":"Seed 1.6 Flash","description":"Low-latency ByteDance Seed model for high-throughput chat, extraction, and lightweight tool use","family":"seed","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-28","last_updated":"2025-08-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.103155,"output":0.41262},"canonical_model_id":"bytedance-seed/seed-1-6-flash"},"bytedance-seed/seed-2.0-lite":{"id":"bytedance-seed/seed-2.0-lite","name":"Seed-2.0-Lite","description":"Cost-efficient ByteDance Seed 2.0 model for production chat, analysis, and structured generation","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.34385,"output":2.7508},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"bytedance-seed/seed-2.0-mini":{"id":"bytedance-seed/seed-2.0-mini","name":"Seed-2.0-Mini","description":"Lightweight ByteDance Seed 2.0 model for low-latency multimodal reasoning and high-volume tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.13754,"output":0.55016},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"bytedance-seed/seed-2.0-code":{"id":"bytedance-seed/seed-2.0-code","name":"Seed-2.0-Code","description":"ByteDance Seed coding model for multimodal software engineering and long-running agents","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.6877,"output":4.1262},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"anthropic/claude-opus-4.5":{"id":"anthropic/claude-opus-4.5","name":"Claude 4.5 Opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":6.877,"output":34.385,"cache_read":0.6877},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude 4.7 Opus","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":6.877,"output":34.385,"cache_read":0.6877},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic/claude-haiku-5.5":{"id":"anthropic/claude-haiku-5.5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.13,"output":0.65,"cache_read":0.013},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude 4.8 Opus","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":6.877,"output":34.385,"cache_read":0.6877},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-haiku-4.5":{"id":"anthropic/claude-haiku-4.5","name":"Claude 4.5 Haiku","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1.3754,"output":6.877,"cache_read":0.13754},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":6.5,"output":32.5,"cache_read":0.65},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-sonnet-5.5":{"id":"anthropic/claude-sonnet-5.5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.6,"output":13,"cache_read":0.26},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-fable-5.1":{"id":"anthropic/claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":13,"output":65,"cache_read":0.325},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-sonnet-4.5":{"id":"anthropic/claude-sonnet-4.5","name":"Claude 4.5 Sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":4.1262,"output":20.631,"cache_read":0.41262},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":13,"output":65,"cache_read":1.3},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.6,"output":13,"cache_read":0.26},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude 4.6 Sonnet","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":4.1262,"output":20.631,"cache_read":0.41262},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-5.5":{"id":"anthropic/claude-opus-5.5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.2,"output":26,"cache_read":0.26},"canonical_model_id":"anthropic/claude-opus-5-5"},"cohere/command-r-08-2024":{"id":"cohere/command-r-08-2024","name":"Command R (08-2024)","description":"Cohere retrieval model for long-context chat and enterprise RAG workflows","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.20631,"output":0.82524},"canonical_model_id":"cohere/command-r-08-2024"},"cohere/command-a":{"id":"cohere/command-a","name":"Command A","description":"Cohere command model for multilingual enterprise agents, tools, and chat","family":"command-a","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-03-13","last_updated":"2025-03-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":3.4385,"output":13.754},"canonical_model_id":"cohere/command-a"},"cohere/command-r7b-12-2024":{"id":"cohere/command-r7b-12-2024","name":"Command R7B (12-2024)","description":"Cohere retrieval model for long-context chat and enterprise RAG workflows","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-12-02","last_updated":"2024-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.051578,"output":0.20631},"canonical_model_id":"cohere/command-r7b-12-2024"},"cohere/command-r-plus-08-2024":{"id":"cohere/command-r-plus-08-2024","name":"Command R+ (08-2024)","description":"Cohere's RAG workhorse for long-context enterprise search and tool use","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":3.4385,"output":13.754},"canonical_model_id":"cohere/command-r-plus-08-2024"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.39,"output":1.56,"cache_read":0.0078},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-flash-vision-exp":{"id":"deepseek/deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.572,"output":1.716,"cache_read":0.0182},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"deepseek/deepseek-chat":{"id":"deepseek/deepseek-chat","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.39,"output":1.56,"cache_read":0.0078},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":2.393196,"output":4.786392,"cache_read":0.199433},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek/deepseek-chat-v3-0324":{"id":"deepseek/deepseek-chat-v3-0324","name":"DeepSeek V3","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07-31","release_date":"2025-03-24","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":124000},"cost":{"input":0.398866,"output":1.567956,"cache_read":0.192556},"canonical_model_id":"deepseek/deepseek-chat-v3-0324"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.17,"output":3.51,"cache_read":0.039},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.39,"output":1.56,"cache_read":0.0078},"canonical_model_id":"deepseek/deepseek-v4-flash"},"unbiased/pareto":{"id":"unbiased/pareto","name":"Pareto","description":"Blended multimodal model that runs multiple language models in parallel and returns a synthesized answer","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":3.4385,"output":10.3155,"cache_read":0.34385},"canonical_model_id":"unbiased/pareto"},"tencent/hy-mt2-30b-a3b":{"id":"tencent/hy-mt2-30b-a3b","name":"Hy-MT2-30B-A3B","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-08-20","last_updated":"2026-08-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":4096},"cost":{"input":0.10178,"output":0.405743},"canonical_model_id":"tencent/hy-mt2-30b-a3b"},"tencent/hy-mt2-1.8b":{"id":"tencent/hy-mt2-1.8b","name":"Hy-MT2-1.8B","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-08-20","last_updated":"2026-08-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":4096},"cost":{"input":0.060518,"output":0.243446},"canonical_model_id":"tencent/hy-mt2-1.8b"},"tencent/hy3":{"id":"tencent/hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.27508,"output":1.10032,"cache_read":0.06877},"canonical_model_id":"tencent/hy3"},"tencent/hy-mt2-7b":{"id":"tencent/hy-mt2-7b","name":"Hy-MT2-7B","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-08-19","last_updated":"2026-08-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":4096},"cost":{"input":0.10178,"output":0.405743},"canonical_model_id":"tencent/hy-mt2-7b"},"tencent/hy4-preview":{"id":"tencent/hy4-preview","name":"Hy4 preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":64000},"cost":{"input":1.147084,"output":3.439875,"cache_read":0.057767},"canonical_model_id":"tencent/hy4-preview"},"anthracite-org/magnum-v4-72b":{"id":"anthracite-org/magnum-v4-72b","name":"Magnum v4 72B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":16384},"cost":{"input":4.1262,"output":6.877},"canonical_model_id":"anthracite-org/magnum-v4-72b"},"meta-llama/Llama-3.3-70B-Instruct-Turbo":{"id":"meta-llama/Llama-3.3-70B-Instruct-Turbo","name":"Llama 3.3 70B Instruct Turbo","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":127000},"cost":{"input":1.352,"output":1.352},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"z-ai/glm-4.6v":{"id":"z-ai/glm-4.6v","name":"GLM 4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.41262,"output":1.23786,"cache_read":0.075647},"canonical_model_id":"zhipuai/glm-4.6v"},"z-ai/glm-5v-turbo":{"id":"z-ai/glm-5v-turbo","name":"GLM 5V Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":131072},"cost":{"input":1.56,"output":5.2,"cache_read":0.312},"canonical_model_id":"zhipuai/glm-5v-turbo"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.195,"output":0.65,"cache_read":0.039},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-4.5v":{"id":"z-ai/glm-4.5v","name":"GLM 4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":16384},"cost":{"input":0.82524,"output":2.47572,"cache_read":0.151294},"canonical_model_id":"zhipuai/glm-4.5v"},"z-ai/glm-4.7-flash":{"id":"z-ai/glm-4.7-flash","name":"GLM 4.7 Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":16384},"cost":{"input":0.171925,"output":0.6877,"cache_read":0.013754},"canonical_model_id":"zhipuai/glm-4.7-flash"},"z-ai/glm-5-turbo":{"id":"z-ai/glm-5-turbo","name":"GLM 5 Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":1.56,"output":5.2,"cache_read":0.312},"canonical_model_id":"zhipuai/glm-5-turbo"},"inference-net/schematron-v2-small":{"id":"inference-net/schematron-v2-small","name":"Schematron V2 Small","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-09-12","last_updated":"2026-09-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.06877,"output":0.316342},"canonical_model_id":"inference-net/schematron-v2-small"},"inference-net/schematron-v2-turbo":{"id":"inference-net/schematron-v2-turbo","name":"Schematron V2 Turbo","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-09-12","last_updated":"2026-09-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.041262,"output":0.20631},"canonical_model_id":"inference-net/schematron-v2-turbo"},"thinkingmachines/inkling-small":{"id":"thinkingmachines/inkling-small","name":"Inkling Small","description":"Multimodal MoE reasoning model (276B total, 12B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":262144},"cost":{"input":0.797732,"output":1.980576,"cache_read":0.159546},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/inkling":{"id":"thinkingmachines/inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.3754,"output":5.57037,"cache_read":0.233818},"canonical_model_id":"thinkingmachines/inkling"},"perplexity/sonar-pro":{"id":"perplexity/sonar-pro","name":"Sonar Pro","description":"Deeper Sonar search model with broader retrieval and stronger synthesis","family":"sonar-pro","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":3.9,"output":19.5},"canonical_model_id":"perplexity/sonar-pro"},"perplexity/sonar":{"id":"perplexity/sonar","name":"Sonar","description":"Fast web-grounded Sonar for current answers, citations, and lightweight retrieval","family":"sonar","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":100000},"cost":{"input":1.3,"output":1.3},"canonical_model_id":"perplexity/sonar"},"meta/muse-spark-1.3":{"id":"meta/muse-spark-1.3","name":"Muse Spark 1.3","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.71925,"output":5.84545,"cache_read":0.20631},"canonical_model_id":"meta/muse-spark-1.3"},"meta/muse-glimmer-30b":{"id":"meta/muse-glimmer-30b","name":"Muse Glimmer 30B","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.48139,"output":2.0631,"cache_read":0.055016},"canonical_model_id":"meta/muse-glimmer-30b"},"meta/muse-spark-1.1":{"id":"meta/muse-spark-1.1","name":"Muse Spark 1.1","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.71925,"output":5.84545,"cache_read":0.20631},"canonical_model_id":"meta/muse-spark-1.1"},"meta/muse-spark-1.2":{"id":"meta/muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.71925,"output":5.84545,"cache_read":0.20631},"canonical_model_id":"meta/muse-spark-1.2"},"nousresearch/hermes-3-llama-3.1-70b":{"id":"nousresearch/hermes-3-llama-3.1-70b","name":"Hermes 3 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"nousresearch","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-18","last_updated":"2024-08-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.96278,"output":0.96278},"canonical_model_id":"nousresearch/hermes-3-llama-3.1-70b"},"nousresearch/hermes-3-llama-3.1-405b":{"id":"nousresearch/hermes-3-llama-3.1-405b","name":"Hermes 3 405B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"nousresearch","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-16","last_updated":"2024-08-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":1.3754,"output":1.3754},"canonical_model_id":"nousresearch/hermes-3-llama-3.1-405b"},"alibaba/qwen3.8-27b":{"id":"alibaba/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.61893,"output":4.40128},"canonical_model_id":"alibaba/qwen3.8-27b"},"alibaba/qwen3.8-2.4t-a95b":{"id":"alibaba/qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":52429},"cost":{"input":3.4385,"output":8.59625,"cache_read":0.6877},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"alibaba/qwen-max":{"id":"alibaba/qwen-max","name":"Qwen Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-03","last_updated":"2025-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":8192},"cost":{"input":2.08,"output":8.32,"cache_read":0.416},"canonical_model_id":"alibaba/qwen-max"},"alibaba/qwen3.8-max":{"id":"alibaba/qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2.6,"output":7.8,"cache_read":0.325},"canonical_model_id":"alibaba/qwen3.8-max"},"alibaba/qwen-plus":{"id":"alibaba/qwen-plus","name":"Qwen Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":16384},"cost":{"input":0.52,"output":1.56,"cache_read":0.104},"canonical_model_id":"alibaba/qwen-plus"},"alibaba/qwen3-coder-480b-a35b-instruct":{"id":"alibaba/qwen3-coder-480b-a35b-instruct","name":"Qwen3 Coder","description":"Open Qwen coding heavyweight for repository reasoning and agentic engineering","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":65536},"cost":{"input":1.3754,"output":6.705075,"cache_read":1.3754},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"alibaba/qwen3-next-80b-a3b-instruct":{"id":"alibaba/qwen3-next-80b-a3b-instruct","name":"Qwen3 Next 80B A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":129024,"output":16384},"cost":{"input":0.20631,"output":1.65048},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"alibaba/qwen3.8-max-prime":{"id":"alibaba/qwen3.8-max-prime","name":"Qwen3.8 Max Prime","description":"High-throughput edition of Qwen3.8 Max for coding, professional work, multimodal understanding, and long-running agent workflows","family":"qwen3.8-max","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":5.5016,"output":16.5048,"cache_read":0.6877},"canonical_model_id":"alibaba/qwen3.8-max-prime"},"alibaba/qwen3.8-flash":{"id":"alibaba/qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.208,"output":0.611,"cache_read":0.0208},"canonical_model_id":"alibaba/qwen3.8-flash"},"cognitivecomputations/dolphin-mistral-24b-venice-edition":{"id":"cognitivecomputations/dolphin-mistral-24b-venice-edition","name":"Venice Uncensored","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-04-30","release_date":"2025-07-09","last_updated":"2025-07-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.27508,"output":1.23786},"canonical_model_id":"cognitivecomputations/dolphin-mistral-24b-venice-edition"},"thedrummer/skyfall-36b-v2":{"id":"thedrummer/skyfall-36b-v2","name":"Skyfall 36B V2","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2025-03-10","last_updated":"2025-03-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.75647,"output":1.10032,"cache_read":0.34385},"canonical_model_id":"thedrummer/skyfall-36b-v2"},"thedrummer/unslopnemo-12b":{"id":"thedrummer/unslopnemo-12b","name":"UnslopNemo 12B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-04-30","release_date":"2024-11-08","last_updated":"2024-11-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.55016,"output":0.55016},"canonical_model_id":"thedrummer/unslopnemo-12b"},"thedrummer/cydonia-24b-v4.1":{"id":"thedrummer/cydonia-24b-v4.1","name":"Cydonia 24B V4.1","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-04-30","release_date":"2025-09-27","last_updated":"2025-09-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.41262,"output":0.6877,"cache_read":0.20631},"canonical_model_id":"thedrummer/cydonia-24b-v4.1"},"x-ai/grok-4-fast-non-reasoning":{"id":"x-ai/grok-4-fast-non-reasoning","name":"Grok 4 Fast Non-Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-18","last_updated":"2025-12-18","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":1999000},"cost":{"input":1.625,"output":3.25,"cache_read":0.26},"canonical_model_id":"xai/grok-4-fast-non-reasoning"},"x-ai/grok-4-20-0309-non-reasoning":{"id":"x-ai/grok-4-20-0309-non-reasoning","name":"Grok 4.20 Non-Reasoning","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":1999000},"cost":{"input":1.625,"output":3.25,"cache_read":0.26},"canonical_model_id":"xai/grok-4.20-0309-non-reasoning"},"upstage/solar-pro-3":{"id":"upstage/solar-pro-3","name":"Solar Pro 3","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.20631,"output":0.82524,"cache_read":0.020631},"canonical_model_id":"upstage/solar-pro3"},"upstage/solar-pro4":{"id":"upstage/solar-pro4","name":"Solar Pro 4","description":"Upstage's flagship model, specialized for agentic use","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02","release_date":"2026-08-06","last_updated":"2026-08-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":131072},"cost":{"input":0.041262,"output":0.165048,"cache_read":0.008252},"canonical_model_id":"upstage/solar-pro4"},"google/gemini-flash-latest":{"id":"google/gemini-flash-latest","name":"Gemini Flash Latest","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2.0631,"output":12.3786,"cache_read":0.20631},"canonical_model_id":"google/gemini-flash-latest"},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B Instruct","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":1.361646,"output":2.049346,"cache_read":1.361646},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemma-3-27b-it":{"id":"google/gemma-3-27b-it","name":"Gemma 3 27B","description":"Largest open Gemma 3 instruction model for multilingual text generation and visual understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":117964},"cost":{"input":0.20631,"output":0.632684,"cache_read":0.103155},"canonical_model_id":"google/gemma-3-27b-it"},"google/gemma-2-27b-it":{"id":"google/gemma-2-27b-it","name":"Gemma 2 27B","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2024-07-13","last_updated":"2024-07-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":2048},"cost":{"input":0.89401,"output":0.89401},"canonical_model_id":"google/gemma-2-27b-it"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.95,"output":9.75,"cache_read":0.195},"canonical_model_id":"google/gemini-3.6-flash"},"google/gemma-4-26b-a4b-it":{"id":"google/gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":128000},"cost":{"input":0.20631,"output":0.82524,"cache_read":0.20631},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":2.6,"output":15.6,"cache_read":0.65},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemma-3-12b-it":{"id":"google/gemma-3-12b-it","name":"Gemma 3 12B","description":"Open multimodal Gemma instruction model for multilingual text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":96000},"cost":{"input":0.06877,"output":0.20631,"cache_read":0.055016},"canonical_model_id":"google/gemma-3-12b-it"},"google/gemini-3-8-flash":{"id":"google/gemini-3-8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.975,"output":4.875,"cache_read":0.0975},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.975,"output":4.875,"cache_read":0.0975},"canonical_model_id":"google/gemini-3.7-flash"},"google/gemini-3.1-pro-preview-customtools":{"id":"google/gemini-3.1-pro-preview-customtools","name":"Gemini 3.1 Pro Preview Custom Tools","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048756,"output":65536},"cost":{"input":2.7508,"output":16.5048,"cache_read":0.27508},"canonical_model_id":"google/gemini-3.1-pro-preview-customtools"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.975,"output":4.875,"cache_read":0.0975},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemma-3-4b-it":{"id":"google/gemma-3-4b-it","name":"Gemma 3 4B","description":"Open multimodal Gemma instruction model for efficient text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":32768},"cost":{"input":0.06877,"output":0.13754,"cache_read":0.055016},"canonical_model_id":"google/gemma-3-4b-it"},"google/gemini-3.1-flash-lite-preview":{"id":"google/gemini-3.1-flash-lite-preview","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.34385,"output":2.0631,"cache_read":0.034385},"canonical_model_id":"google/gemini-3.1-flash-lite-preview"},"ibm-granite/granite-4.0-h-micro":{"id":"ibm-granite/granite-4.0-h-micro","name":"Granite 4.0 Micro","description":"Compact open-weight hybrid Granite model for lightweight enterprise chat and tool calling","family":"granite","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-02","last_updated":"2025-10-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":131000},"cost":{"input":0.023382,"output":0.154045},"canonical_model_id":"ibm/granite-4-h-micro"},"mistralai/mistral-nemo":{"id":"mistralai/mistral-nemo","name":"Mistral NeMo","description":"Efficient Mistral-NVIDIA open model for multilingual chat and local deployment","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.20631,"output":0.233818,"cache_read":0.20631},"canonical_model_id":"mistral/mistral-nemo"},"mistralai/ministral-8b-2512":{"id":"mistralai/ministral-8b-2512","name":"Ministral 3 8B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.41262,"output":0.41262,"cache_read":0.020631},"canonical_model_id":"mistral/ministral-8b-2512"},"mistralai/mistral-small-24b-instruct-2501":{"id":"mistralai/mistral-small-24b-instruct-2501","name":"Small 3","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-01-30","last_updated":"2025-01-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"cost":{"input":0.06877,"output":0.110032},"canonical_model_id":"mistral/mistral-small-24b-instruct-2501"},"mistralai/devstral-2512":{"id":"mistralai/devstral-2512","name":"Devstral 2 2512","description":"Mistral's coding-agent model for repository work, terminal tasks, and software fixes","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.605176,"output":3.02588,"cache_read":0.060518},"canonical_model_id":"mistral/devstral-2512"},"mistralai/mistral-saba":{"id":"mistralai/mistral-saba","name":"Saba","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-02-17","last_updated":"2025-02-17","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":26214},"cost":{"input":0.27508,"output":0.82524,"cache_read":0.027508},"canonical_model_id":"mistral/mistral-saba"},"mistralai/mistral-medium-3-5":{"id":"mistralai/mistral-medium-3-5","name":"Medium 3.5","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":209715},"cost":{"input":2.0631,"output":10.3155},"canonical_model_id":"mistral/mistral-medium-3-5"},"mistralai/mistral-medium-3.1":{"id":"mistralai/mistral-medium-3.1","name":"Medium 3.1","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06-30","release_date":"2025-08-13","last_updated":"2025-08-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":104857},"cost":{"input":0.55016,"output":2.7508,"cache_read":0.055016},"canonical_model_id":"mistral/mistral-medium-3.1"},"mistralai/mistral-small-3.2-24b-instruct":{"id":"mistralai/mistral-small-3.2-24b-instruct","name":"Small 3.2 24B","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["image","text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.103155,"output":0.27508},"canonical_model_id":"mistral/mistral-small-3.2-24b-instruct"},"mistralai/mistral-large":{"id":"mistralai/mistral-large","name":"Large","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11-30","release_date":"2024-02-26","last_updated":"2024-02-26","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":102400},"cost":{"input":2.7508,"output":8.2524,"cache_read":0.27508},"canonical_model_id":"mistral/mistral-large"},"mistralai/mistral-small-2603":{"id":"mistralai/mistral-small-2603","name":"Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.257888,"output":1.03155,"cache_read":0.020631},"canonical_model_id":"mistral/mistral-small-2603"},"mistralai/mistral-medium-3":{"id":"mistralai/mistral-medium-3","name":"Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":104857},"cost":{"input":0.55016,"output":2.7508,"cache_read":0.055016},"canonical_model_id":"mistral/mistral-medium-3"},"mistralai/voxtral-small-24b-2507":{"id":"mistralai/voxtral-small-24b-2507","name":"Voxtral Small 24B 2507","description":"Open audio-language model for speech transcription, audio understanding, and voice-driven tool use","family":"voxtral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":32768},"cost":{"input":0.13754,"output":0.41262,"cache_read":0.013754},"canonical_model_id":"mistral/voxtral-small-24b-2507"},"mistralai/mistral-large-2407":{"id":"mistralai/mistral-large-2407","name":"Large 2407","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-03-31","release_date":"2024-11-19","last_updated":"2024-11-19","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":104857},"cost":{"input":2.7508,"output":8.2524,"cache_read":0.27508},"canonical_model_id":"mistral/mistral-large-2407"},"mistralai/ministral-14b-2512":{"id":"mistralai/ministral-14b-2512","name":"Ministral 3 14B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.48139,"output":0.48139,"cache_read":0.027508},"canonical_model_id":"mistral/ministral-14b-2512"},"mistralai/mistral-small-3.1-24b-instruct":{"id":"mistralai/mistral-small-3.1-24b-instruct","name":"Small 3.1 24B","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-03-17","last_updated":"2025-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0.482765,"output":0.763347},"canonical_model_id":"mistral/mistral-small-3.1-24b-instruct"},"mistralai/ministral-3b-2512":{"id":"mistralai/ministral-3b-2512","name":"Ministral 3 3B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":104857},"cost":{"input":0.20631,"output":0.20631,"cache_read":0.013754},"canonical_model_id":"mistral/ministral-3b-2512"},"mistralai/mixtral-8x22b-instruct":{"id":"mistralai/mixtral-8x22b-instruct","name":"Mixtral 8x22B Instruct","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-01-31","release_date":"2024-04-17","last_updated":"2024-04-17","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":52428},"cost":{"input":2.7508,"output":8.2524,"cache_read":0.27508},"canonical_model_id":"mistral/mixtral-8x22b-instruct"},"mistralai/codestral-2508":{"id":"mistralai/codestral-2508","name":"Codestral 2508","description":"Mistral code model for low-latency completion, fill-in-the-middle, and code generation","family":"codestral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":8192},"cost":{"input":0.41262,"output":1.23786,"cache_read":0.041262},"canonical_model_id":"mistral/codestral-2508"},"sakana/fugu-max":{"id":"sakana/fugu-max","name":"Fugu Max","description":"Multi-agent model for routing expert agents across complex analytical tasks","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.7508,"output":8.2524,"cache_read":0.34385},"canonical_model_id":"sakana/fugu-max"},"sakana/fugu-ultra-v2":{"id":"sakana/fugu-ultra-v2","name":"Fugu Ultra v2","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-08-28","release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":6.877,"output":41.262,"cache_read":0.6877},"canonical_model_id":"sakana/fugu-ultra-v2"},"sakana/fugu-ultra":{"id":"sakana/fugu-ultra","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":6.877,"output":41.262,"cache_read":0.6877},"canonical_model_id":"sakana/fugu-ultra"},"moonshotai/kimi-k2-thinking":{"id":"moonshotai/kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Thinking Kimi model for slower research passes, planning, and hard technical questions","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":0.82524,"output":3.4385,"cache_read":0.20631},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"moonshotai/kimi-k2-0905":{"id":"moonshotai/kimi-k2-0905","name":"Kimi K2 0905","description":"September 2025 Kimi K2 instruction update with a 256K context and improved agentic coding","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":1.3754,"output":4.1262},"canonical_model_id":"moonshotai/kimi-k2-0905"},"moonshotai/kimi-k2":{"id":"moonshotai/kimi-k2","name":"Kimi K2 0711","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-12-31","release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.783978,"output":3.16342},"canonical_model_id":"moonshotai/kimi-k2"},"rekaai/reka-edge":{"id":"rekaai/reka-edge","name":"Reka Edge","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"reka","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-20","last_updated":"2026-03-20","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":16384},"cost":{"input":0.13754,"output":0.13754},"canonical_model_id":"rekaai/reka-edge"},"xiaomi/mimo-v2.5":{"id":"xiaomi/mimo-v2.5","name":"MiMo V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.192556,"output":0.385112,"cache_read":0.003851},"canonical_model_id":"xiaomi/mimo-v2.5"},"xiaomi/mimo-v2.5-pro":{"id":"xiaomi/mimo-v2.5-pro","name":"MiMo V2.5 Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.598299,"output":1.196598,"cache_read":0.004951},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"undi95/remm-slerp-l2-13b":{"id":"undi95/remm-slerp-l2-13b","name":"ReMM SLERP 13B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-06-30","release_date":"2023-07-22","last_updated":"2023-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":6144,"output":4096},"cost":{"input":0.6877,"output":1.03155},"canonical_model_id":"undi95/remm-slerp-l2-13b"},"gryphe/mythomax-l2-13b":{"id":"gryphe/mythomax-l2-13b","name":"MythoMax 13B","description":"Llama 2 merge combining MythoLogic and Huginn for creative writing and roleplay","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2023-08-10","last_updated":"2023-08-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":4096},"cost":{"input":2.578875,"output":2.578875,"cache_read":2.578875},"canonical_model_id":"gryphe/mythomax-l2-13b"},"mancer/weaver":{"id":"mancer/weaver","name":"Weaver (alpha)","description":"General-purpose chat model for instruction following, writing, and analysis","family":"alpha","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-06-30","release_date":"2023-08-02","last_updated":"2023-08-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8000,"output":2000},"cost":{"input":1.03155,"output":1.3754},"canonical_model_id":"mancer/weaver"},"stepfun/step-5-preview":{"id":"stepfun/step-5-preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":64000},"cost":{"input":1.3754,"output":3.71358,"cache_read":0.06877},"canonical_model_id":"stepfun/step-5-preview"},"inception/mercury-2.5":{"id":"inception/mercury-2.5","name":"Mercury 2.5","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":260000,"output":65536},"cost":{"input":0.27508,"output":1.03155,"cache_read":0.027508},"canonical_model_id":"inception/mercury-2.5"},"inception/mercury-2":{"id":"inception/mercury-2","name":"Mercury 2","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-04","last_updated":"2026-03-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":50000},"cost":{"input":0.34385,"output":1.03155,"cache_read":0.034385},"canonical_model_id":"inception/mercury-2"},"amazon/nova-lite-v1":{"id":"amazon/nova-lite-v1","name":"Nova Lite 1.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":5120},"cost":{"input":0.082524,"output":0.330096},"canonical_model_id":"amazon/nova-lite-v1"},"amazon/nova-pro-v1":{"id":"amazon/nova-pro-v1","name":"Nova Pro 1.0","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":5120},"cost":{"input":1.10032,"output":4.40128},"canonical_model_id":"amazon/nova-pro-v1"},"amazon/nova-micro-v1":{"id":"amazon/nova-micro-v1","name":"Nova Micro 1.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-micro","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":5120},"cost":{"input":0.048139,"output":0.192556},"canonical_model_id":"amazon/nova-micro-v1"},"relace/relace-search":{"id":"relace/relace-search","name":"Search","description":"Tool-capable chat model for instruction following and agentic application workflows","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":1.3754,"output":4.1262},"canonical_model_id":"relace/relace-search"},"relace/relace-apply-3":{"id":"relace/relace-apply-3","name":"Apply 3","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2025-09-26","last_updated":"2025-09-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":1.16909,"output":1.71925},"canonical_model_id":"relace/relace-apply-3"},"aion-labs/aion-rp-llama-3.1-8b":{"id":"aion-labs/aion-rp-llama-3.1-8b","name":"Aion-RP 1.0 (8B)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12-31","release_date":"2025-02-04","last_updated":"2025-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":1.10032,"output":2.20064},"canonical_model_id":"aion-labs/aion-rp-llama-3.1-8b"},"morph/morph-v3-large":{"id":"morph/morph-v3-large","name":"V3 Large","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"morph","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-07-07","last_updated":"2025-07-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":1.23786,"output":2.61326},"canonical_model_id":"morph/morph-v3-large"},"morph/morph-v3-fast":{"id":"morph/morph-v3-fast","name":"V3 Fast","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"morph","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-07-07","last_updated":"2025-07-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":81920,"output":38000},"cost":{"input":1.10032,"output":1.65048},"canonical_model_id":"morph/morph-v3-fast"},"openai/gpt-5.4-image-2":{"id":"openai/gpt-5.4-image-2","name":"GPT-5.4 Image 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":true,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["image","text","pdf"],"output":["image","text"]},"open_weights":false,"limit":{"context":272000,"output":128000},"cost":{"input":11.0032,"output":20.631,"cache_read":2.7508},"canonical_model_id":"openai/gpt-5.4-image-2"},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":41.262,"output":247.572},"canonical_model_id":"openai/gpt-5.4-pro"},"openai/gpt-3.5-turbo":{"id":"openai/gpt-3.5-turbo","name":"GPT-3.5 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16000,"output":4096},"cost":{"input":0.65,"output":1.95},"canonical_model_id":"openai/gpt-3.5-turbo"},"openai/gpt-5.5-pro":{"id":"openai/gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":41.262,"output":247.572},"canonical_model_id":"openai/gpt-5.5-pro"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 Nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.27508,"output":1.71925,"cache_read":0.027508},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-4o-2024-05-13":{"id":"openai/gpt-4o-2024-05-13","name":"GPT-4o","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-05-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":6.5,"output":19.5},"canonical_model_id":"openai/gpt-4o-2024-05-13"},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":3.25,"output":13,"cache_read":1.625},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-5.6-sol-pro":{"id":"openai/gpt-5.6-sol-pro","name":"GPT-5.6 Sol Pro","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5.5016,"output":27.508,"cache_read":0.55016},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.325,"output":2.6,"cache_read":0.0325},"canonical_model_id":"openai/gpt-5-mini"},"openai/gpt-5.2-pro":{"id":"openai/gpt-5.2-pro","name":"GPT-5.2 Pro","description":"Higher-accuracy GPT-5.2 variant for tougher reasoning and review workflows","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":28.8834,"output":231.0672},"canonical_model_id":"openai/gpt-5.2-pro"},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3 Mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.43,"output":5.72,"cache_read":0.715},"canonical_model_id":"openai/o3-mini"},"openai/gpt-4":{"id":"openai/gpt-4","name":"GPT-4","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-11","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8000,"output":8192},"cost":{"input":39,"output":78,"cache_read":39},"canonical_model_id":"openai/gpt-4"},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":4.8139,"output":38.5112,"cache_read":0.48139},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1 Nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.13,"output":0.52,"cache_read":0.0325},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.065,"output":0.52,"cache_read":0.0065},"canonical_model_id":"openai/gpt-5-nano"},"openai/o1":{"id":"openai/o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":100000},"cost":{"input":19.5,"output":78,"cache_read":9.75},"canonical_model_id":"openai/o1"},"openai/gpt-5-pro":{"id":"openai/gpt-5-pro","name":"GPT-5 Pro","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":272000},"cost":{"input":20.631,"output":165.048},"canonical_model_id":"openai/gpt-5-pro"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.6,"output":13,"cache_read":0.13},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-4o-2024-08-06":{"id":"openai/gpt-4o-2024-08-06","name":"GPT-4o","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-08-06","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":3.25,"output":13,"cache_read":1.625},"canonical_model_id":"openai/gpt-4o-2024-08-06"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":13,"output":65,"cache_read":1.3},"canonical_model_id":"openai/gpt-6-astra"},"openai/gpt-5.6-luna-pro":{"id":"openai/gpt-5.6-luna-pro","name":"GPT-5.6 Luna Pro","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.27508,"output":1.65048,"cache_read":0.027508},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o Mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.195,"output":0.78,"cache_read":0.0975},"canonical_model_id":"openai/gpt-4o-mini"},"openai/o3-pro":{"id":"openai/o3-pro","name":"o3 Pro","description":"High-effort o3 tier for difficult technical reasoning and careful answers","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-06-10","last_updated":"2025-06-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":27.508,"output":110.032},"canonical_model_id":"openai/o3-pro"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":117964},"cost":{"input":0.103155,"output":0.41262,"cache_read":0.051578},"canonical_model_id":"openai/gpt-oss-20b"},"openai/gpt-oss-safeguard-20b":{"id":"openai/gpt-oss-safeguard-20b","name":"gpt-oss-safeguard-20b","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.103155,"output":0.41262,"cache_read":0.051578},"canonical_model_id":"openai/gpt-oss-safeguard-20b"},"openai/gpt-5-4":{"id":"openai/gpt-5-4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":3.25,"output":19.5,"cache_read":0.325},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 Mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":2.0631,"output":12.3786,"cache_read":0.20631},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.26,"output":1.56,"cache_read":0.026},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.1-codex-max":{"id":"openai/gpt-5.1-codex-max","name":"GPT-5.1-Codex-Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":3.4385,"output":27.508,"cache_read":0.34385},"canonical_model_id":"openai/gpt-5.1-codex-max"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2.6,"output":10.4,"cache_read":0.65},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-5-5":{"id":"openai/gpt-5-5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":6.5,"output":39,"cache_read":0.65},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-4o-2024-11-20":{"id":"openai/gpt-4o-2024-11-20","name":"GPT-4o","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-11-20","last_updated":"2024-11-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":3.25,"output":13,"cache_read":1.625},"canonical_model_id":"openai/gpt-4o-2024-11-20"},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 Mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.52,"output":2.08,"cache_read":0.13},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-5.6-terra-pro":{"id":"openai/gpt-5.6-terra-pro","name":"GPT-5.6 Terra Pro","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.7508,"output":16.5048,"cache_read":0.27508},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.13,"output":0.65,"cache_read":0.013},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-5-2":{"id":"openai/gpt-5-2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":2.275,"output":18.2,"cache_read":0.2275},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.6,"output":15.6,"cache_read":0.26},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-4-turbo":{"id":"openai/gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":13,"output":39},"canonical_model_id":"openai/gpt-4-turbo"},"openai/gpt-5-1":{"id":"openai/gpt-5-1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.625,"output":13,"cache_read":0.1625},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":117964},"cost":{"input":0.48139,"output":1.30663,"cache_read":0.48139},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.625,"output":13,"cache_read":0.1625},"canonical_model_id":"openai/gpt-5"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5.2,"output":26,"cache_read":0.52},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.6,"output":13,"cache_read":0.26},"canonical_model_id":"openai/gpt-6-sol"},"openai/o1-pro":{"id":"openai/o1-pro","name":"o1-pro","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2025-03-19","last_updated":"2025-03-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":206.31,"output":825.24},"canonical_model_id":"openai/o1-pro"},"zhipu/glm-5.2":{"id":"zhipu/glm-5.2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.82,"output":5.72,"cache_read":0.338},"canonical_model_id":"zhipuai/glm-5.2"},"zhipu/glm-5.3":{"id":"zhipu/glm-5.3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":131072},"cost":{"input":1.82,"output":5.72,"cache_read":0.338},"canonical_model_id":"zhipuai/glm-5.3"},"moonshot/kimi-k3":{"id":"moonshot/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3.9,"output":19.5,"cache_read":0.39},"canonical_model_id":"moonshotai/kimi-k3"}}},"upstage":{"id":"upstage","env":["UPSTAGE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.upstage.ai/v1/solar","name":"Upstage","doc":"https://developers.upstage.ai/docs/apis/chat","models":{"solar-pro4":{"id":"solar-pro4","name":"Solar Pro 4","description":"Upstage's flagship model, specialized for agentic use","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02","release_date":"2026-08-06","last_updated":"2026-08-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06}},"solar-pro3":{"id":"solar-pro3","name":"solar-pro3","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.25,"output":0.25}},"solar-mini":{"id":"solar-mini","name":"solar-mini","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"solar-mini","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2024-06-12","last_updated":"2025-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":4096},"cost":{"input":0.15,"output":0.15}},"solar-pro2":{"id":"solar-pro2","name":"solar-pro2","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"output":8192},"cost":{"input":0.25,"output":0.25}}}},"vultr":{"id":"vultr","env":["VULTR_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.vultrinference.com/v1","name":"Vultr","doc":"https://api.vultrinference.com/","models":{"mimo-v2.6-pro-rl":{"id":"mimo-v2.6-pro-rl","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.4,"output":0.8},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"qwen3.8-27b":{"id":"qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.15,"output":1},"canonical_model_id":"alibaba/qwen3.8-27b"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.1,"output":0.35},"canonical_model_id":"zhipuai/glm-5.3-flash"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.1,"output":0.25},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"muse-glimmer-30b":{"id":"muse-glimmer-30b","name":"Muse Glimmer 30B","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.25,"output":1},"canonical_model_id":"meta/muse-glimmer-30b"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"laguna-s-2.1":{"id":"laguna-s-2.1","name":"Laguna S 2.1","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":32768},"cost":{"input":0.09,"output":0.18},"canonical_model_id":"poolside/laguna-s-2.1"},"glm-5.x-menthol":{"id":"glm-5.x-menthol","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.4,"output":1.75},"canonical_model_id":"zhipuai/glm-5"},"nemotron-3-nano-omni-30b-a3b-reasoning":{"id":"nemotron-3-nano-omni-30b-a3b-reasoning","name":"Nemotron 3 Nano Omni 30B A3B Reasoning","description":"Open Nemotron omni model combining reasoning with text, vision, and audio","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.1,"output":0.25},"canonical_model_id":"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning"},"mimo-v2.6-flash-rl":{"id":"mimo-v2.6-flash-rl","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.1,"output":0.25},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":512000},"cost":{"input":0.2,"output":0.9},"canonical_model_id":"minimax/MiniMax-M3"},"qwen3.8-flash-next":{"id":"qwen3.8-flash-next","name":"Qwen3.8 Flash Next","description":"Open-weight experimental preview of the Qwen4 architecture: hybrid-attention MoE (125B total, 6B active) with vision encoder for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.1,"output":0.2},"canonical_model_id":"alibaba/qwen3.8-flash-next"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.75,"output":3},"canonical_model_id":"zhipuai/glm-5.2"},"nemotron-3.5-content-safety":{"id":"nemotron-3.5-content-safety","name":"Nemotron 3.5 Content Safety","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.05,"output":0.15},"canonical_model_id":"nvidia/nemotron-3.5-content-safety"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.75,"output":3},"canonical_model_id":"zhipuai/glm-5.3"}}},"huggingface":{"id":"huggingface","env":["HF_TOKEN"],"npm":"@ai-sdk/openai-compatible","api":"https://router.huggingface.co/v1","name":"Hugging Face","doc":"https://huggingface.co/docs/inference-providers","models":{"tencent/Hy3":{"id":"tencent/Hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":192000,"output":128000},"cost":{"input":0.14,"output":0.58},"canonical_model_id":"tencent/hy3"},"tencent/Hy4-preview":{"id":"tencent/Hy4-preview","name":"Hy4 preview","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":64000},"cost":{"input":0.834,"output":2.501},"canonical_model_id":"tencent/hy4-preview"},"meta-llama/Llama-3.1-8B-Instruct":{"id":"meta-llama/Llama-3.1-8B-Instruct","name":"Llama-3.1-8B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":4096},"cost":{"input":0.06,"output":0.06},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"meta-llama/Llama-3.3-70B-Instruct":{"id":"meta-llama/Llama-3.3-70B-Instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":4096},"cost":{"input":0.59,"output":0.79},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"XiaomiMiMo/MiMo-V2-Flash":{"id":"XiaomiMiMo/MiMo-V2-Flash","name":"MiMo-V2-Flash","description":"MiMo flash model for fast multimodal assistance and agent workflows","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":4096},"cost":{"input":0.1,"output":0.3}},"XiaomiMiMo/MiMo-V2.5-Pro":{"id":"XiaomiMiMo/MiMo-V2.5-Pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1,"output":3},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"XiaomiMiMo/MiMo-V2.5":{"id":"XiaomiMiMo/MiMo-V2.5","name":"MiMo-V2.5","description":"MiMo model for long-context reasoning, perception, and agentic tasks","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.4,"output":2},"canonical_model_id":"xiaomi/mimo-v2.5"},"thinkingmachines/Inkling-Small":{"id":"thinkingmachines/Inkling-Small","name":"Inkling Small","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":1048576},"cost":{"input":0.5,"output":1.2},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/Inkling":{"id":"thinkingmachines/Inkling","name":"Inkling","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1,"output":4.05},"canonical_model_id":"thinkingmachines/inkling"},"google/gemma-3-27b-it":{"id":"google/gemma-3-27b-it","name":"Gemma 3 27B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.08,"output":0.16},"canonical_model_id":"google/gemma-3-27b-it"},"google/gemma-3-12b-it":{"id":"google/gemma-3-12b-it","name":"Gemma 3 12B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.05,"output":0.15},"canonical_model_id":"google/gemma-3-12b-it"},"google/gemma-3-4b-it":{"id":"google/gemma-3-4b-it","name":"Gemma 3 4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.05,"output":0.1},"canonical_model_id":"google/gemma-3-4b-it"},"google/gemma-4-31B-it":{"id":"google/gemma-4-31B-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.14,"output":0.4},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemma-4-26B-A4B-it":{"id":"google/gemma-4-26B-A4B-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.13,"output":0.4},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"Qwen/Qwen3-VL-235B-A22B-Instruct":{"id":"Qwen/Qwen3-VL-235B-A22B-Instruct","name":"Qwen3 VL 235B A22B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.3,"output":1.5},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"Qwen/Qwen3.8-27B":{"id":"Qwen/Qwen3.8-27B","name":"Qwen3.8 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.4,"output":3},"canonical_model_id":"alibaba/qwen3.8-27b"},"Qwen/Qwen3-Next-80B-A3B-Instruct":{"id":"Qwen/Qwen3-Next-80B-A3B-Instruct","name":"Qwen3-Next-80B-A3B-Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-11","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":66536},"cost":{"input":0.25,"output":1}},"Qwen/Qwen2.5-Coder-32B-Instruct":{"id":"Qwen/Qwen2.5-Coder-32B-Instruct","name":"Qwen2.5-Coder-32B-Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-11-12","last_updated":"2024-11-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.06,"output":0.2},"canonical_model_id":"alibaba/qwen2.5-coder-32b-instruct"},"Qwen/Qwen3-Coder-Next":{"id":"Qwen/Qwen3-Coder-Next","name":"Qwen3-Coder-Next","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.2,"output":1.5}},"Qwen/Qwen3-VL-30B-A3B-Instruct":{"id":"Qwen/Qwen3-VL-30B-A3B-Instruct","name":"Qwen3 VL 30B A3B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-04","last_updated":"2025-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.2,"output":0.7},"canonical_model_id":"alibaba/qwen3-vl-30b-a3b-instruct"},"Qwen/Qwen3-VL-235B-A22B-Thinking":{"id":"Qwen/Qwen3-VL-235B-A22B-Thinking","name":"Qwen3 VL 235B A22B Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.98,"output":3.95},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-thinking"},"Qwen/Qwen3.5-27B":{"id":"Qwen/Qwen3.5-27B","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.3,"output":2.4},"canonical_model_id":"alibaba/qwen3.5-27b"},"Qwen/Qwen3-Next-80B-A3B-Thinking":{"id":"Qwen/Qwen3-Next-80B-A3B-Thinking","name":"Qwen3-Next-80B-A3B-Thinking","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-11","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.3,"output":2}},"Qwen/Qwen3.6-35B-A3B":{"id":"Qwen/Qwen3.6-35B-A3B","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.15,"output":0.95},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"Qwen/Qwen3-235B-A22B-Thinking-2507":{"id":"Qwen/Qwen3-235B-A22B-Thinking-2507","name":"Qwen3-235B-A22B-Thinking-2507","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-25","last_updated":"2025-07-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.3,"output":3}},"Qwen/Qwen3-235B-A22B-Instruct-2507":{"id":"Qwen/Qwen3-235B-A22B-Instruct-2507","name":"Qwen3 235B-A22B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.855,"output":2.565},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"Qwen/Qwen3-235B-A22B":{"id":"Qwen/Qwen3-235B-A22B","name":"Qwen3 235B-A22B","description":"Large open Qwen MoE for multilingual reasoning, coding, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":16384},"cost":{"input":0.2,"output":0.8},"canonical_model_id":"alibaba/qwen3-235b-a22b"},"Qwen/Qwen3-32B":{"id":"Qwen/Qwen3-32B","name":"Qwen3 32B","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.29,"output":0.59},"canonical_model_id":"alibaba/qwen3-32b"},"Qwen/Qwen3-Coder-30B-A3B-Instruct":{"id":"Qwen/Qwen3-Coder-30B-A3B-Instruct","name":"Qwen3-Coder 30B-A3B Instruct","description":"Smaller Qwen coder for efficient local agents and repo-level fixes","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.07,"output":0.26},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"Qwen/Qwen3-Embedding-8B":{"id":"Qwen/Qwen3-Embedding-8B","name":"Qwen 3 Embedding 8B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2024-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":4096},"cost":{"input":0.01,"output":0}},"Qwen/Qwen3.5-35B-A3B":{"id":"Qwen/Qwen3.5-35B-A3B","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.25,"output":2},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"Qwen/Qwen3.5-122B-A10B":{"id":"Qwen/Qwen3.5-122B-A10B","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.4,"output":3.2},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"Qwen/Qwen3.5-9B":{"id":"Qwen/Qwen3.5-9B","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.17,"output":0.25},"canonical_model_id":"alibaba/qwen3.5-9b"},"Qwen/Qwen3.5-397B-A17B":{"id":"Qwen/Qwen3.5-397B-A17B","name":"Qwen3.5-397B-A17B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-02-01","last_updated":"2026-02-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.6,"output":3.6}},"Qwen/Qwen3-Embedding-4B":{"id":"Qwen/Qwen3-Embedding-4B","name":"Qwen 3 Embedding 4B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2024-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":2048},"cost":{"input":0.01,"output":0}},"Qwen/Qwen3.8-2.4T-A95B":{"id":"Qwen/Qwen3.8-2.4T-A95B","name":"Qwen3.8 2.4T A95B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":2.5,"output":6.25},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"Qwen/Qwen3-30B-A3B":{"id":"Qwen/Qwen3-30B-A3B","name":"Qwen3 30B A3B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":16384},"cost":{"input":0.12,"output":0.5},"canonical_model_id":"alibaba/qwen3-30b-a3b"},"Qwen/Qwen3-Coder-480B-A35B-Instruct":{"id":"Qwen/Qwen3-Coder-480B-A35B-Instruct","name":"Qwen3-Coder-480B-A35B-Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":66536},"cost":{"input":2,"output":2}},"Qwen/Qwen3.6-27B":{"id":"Qwen/Qwen3.6-27B","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.47,"output":3.19},"canonical_model_id":"alibaba/qwen3.6-27b"},"deepseek-ai/DeepSeek-V3.1":{"id":"deepseek-ai/DeepSeek-V3.1","name":"DeepSeek-V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.27,"output":1},"canonical_model_id":"deepseek/deepseek-v3.1"},"deepseek-ai/DeepSeek-V4-Flash-0731":{"id":"deepseek-ai/DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.14,"output":0.28},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek-ai/DeepSeek-R1":{"id":"deepseek-ai/DeepSeek-R1","name":"DeepSeek-R1","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":32768},"cost":{"input":0.7,"output":2.5},"canonical_model_id":"deepseek/deepseek-r1"},"deepseek-ai/DeepSeek-V4-Pro-0813":{"id":"deepseek-ai/DeepSeek-V4-Pro-0813","name":"DeepSeek V4 Pro 0813","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.32,"output":3.96},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek-ai/DeepSeek-V4.1-Flash":{"id":"deepseek-ai/DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek-ai/DeepSeek-V4-Flash":{"id":"deepseek-ai/DeepSeek-V4-Flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.14,"output":0.28},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek-ai/DeepSeek-V4-Pro":{"id":"deepseek-ai/DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.435,"output":0.87,"cache_read":0.003625},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek-ai/DeepSeek-V3.2":{"id":"deepseek-ai/DeepSeek-V3.2","name":"DeepSeek-V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":65536},"cost":{"input":0.28,"output":0.4}},"deepseek-ai/DeepSeek-R1-0528":{"id":"deepseek-ai/DeepSeek-R1-0528","name":"DeepSeek-R1-0528","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":163840},"cost":{"input":3,"output":5}},"deepseek-ai/DeepSeek-V3":{"id":"deepseek-ai/DeepSeek-V3","name":"DeepSeek-V3","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-12-26","last_updated":"2024-12-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":8192},"cost":{"input":0.4,"output":1.3},"canonical_model_id":"deepseek/deepseek-v3"},"deepseek-ai/DeepSeek-V3-0324":{"id":"deepseek-ai/DeepSeek-V3-0324","name":"DeepSeek V3 0324","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-03-24","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":163840},"cost":{"input":0.27,"output":1.12},"canonical_model_id":"deepseek/deepseek-v3-0324"},"deepseek-ai/DeepSeek-V4-Flash-Vision-Exp":{"id":"deepseek-ai/DeepSeek-V4-Flash-Vision-Exp","name":"DeepSeek V4 Flash Vision Exp","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.44,"output":1.32},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"stepfun-ai/Step-3.7-Flash":{"id":"stepfun-ai/Step-3.7-Flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.2,"output":1.15},"canonical_model_id":"stepfun/step-3.7-flash"},"stepfun-ai/Step-3.5-Flash":{"id":"stepfun-ai/Step-3.5-Flash","name":"Step 3.5 Flash","description":"StepFun flash lane for quick multimodal reasoning and coding assistance","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"stepfun/step-3.5-flash"},"MiniMaxAI/MiniMax-M3":{"id":"MiniMaxAI/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":512000},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M3"},"MiniMaxAI/MiniMax-M1-80k":{"id":"MiniMaxAI/MiniMax-M1-80k","name":"MiniMax M1 80K","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":80000},"cost":{"input":0.55,"output":2.2},"canonical_model_id":"minimax/minimax-m1-80k"},"MiniMaxAI/MiniMax-M2.1":{"id":"MiniMaxAI/MiniMax-M2.1","name":"MiniMax-M2.1","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-10","release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2}},"MiniMaxAI/MiniMax-M2.5":{"id":"MiniMaxAI/MiniMax-M2.5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03}},"MiniMaxAI/MiniMax-M2.7":{"id":"MiniMaxAI/MiniMax-M2.7","name":"MiniMax-M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06}},"MiniMaxAI/MiniMax-M2":{"id":"MiniMaxAI/MiniMax-M2","name":"MiniMax-M2","description":"Efficient open MiniMax model built for coding agents and tool-heavy workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2"},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi-K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16}},"moonshotai/Kimi-K3":{"id":"moonshotai/Kimi-K3","name":"Kimi K3","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":3,"output":15},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/Kimi-K2-Instruct":{"id":"moonshotai/Kimi-K2-Instruct","name":"Kimi-K2-Instruct","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-07-14","last_updated":"2025-07-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":1,"output":3}},"moonshotai/Kimi-K2.7-Code":{"id":"moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"moonshotai/Kimi-K2.5":{"id":"moonshotai/Kimi-K2.5","name":"Kimi-K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-01-01","last_updated":"2026-01-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":3,"cache_read":0.1}},"moonshotai/Kimi-K2-Thinking":{"id":"moonshotai/Kimi-K2-Thinking","name":"Kimi-K2-Thinking","description":"Kimi reasoning model for long-horizon research, planning, and tool use","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":2.5,"cache_read":0.15}},"moonshotai/Kimi-K2-Instruct-0905":{"id":"moonshotai/Kimi-K2-Instruct-0905","name":"Kimi-K2-Instruct-0905","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-09-04","last_updated":"2025-09-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":1,"output":3}},"zai-org/GLM-4.6V-Flash":{"id":"zai-org/GLM-4.6V-Flash","name":"GLM-4.6V-Flash","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.3,"output":0.9},"canonical_model_id":"zhipuai/glm-4.6v-flash"},"zai-org/GLM-5.1":{"id":"zai-org/GLM-5.1","name":"GLM-5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-04-03","last_updated":"2026-04-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2}},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":1.4,"output":4.4},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-4.5-Air":{"id":"zai-org/GLM-4.5-Air","name":"GLM-4.5-Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.13,"output":0.85},"canonical_model_id":"zhipuai/glm-4.5-air"},"zai-org/GLM-4.7":{"id":"zai-org/GLM-4.7","name":"GLM-4.7","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11}},"zai-org/GLM-5":{"id":"zai-org/GLM-5","name":"GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-11","last_updated":"2026-02-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2}},"zai-org/GLM-5.3-Flash":{"id":"zai-org/GLM-5.3-Flash","name":"GLM-5.3-Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/GLM-4.5V":{"id":"zai-org/GLM-4.5V","name":"GLM-4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":16384},"cost":{"input":0.6,"output":1.8},"canonical_model_id":"zhipuai/glm-4.5v"},"zai-org/GLM-4.6":{"id":"zai-org/GLM-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.55,"output":2.2},"canonical_model_id":"zhipuai/glm-4.6"},"zai-org/AutoGLM-Phone-9B-Multilingual":{"id":"zai-org/AutoGLM-Phone-9B-Multilingual","name":"AutoGLM Phone 9B Multilingual","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-12-10","last_updated":"2025-12-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.035,"output":0.138},"canonical_model_id":"zhipuai/autoglm-phone-9b-multilingual"},"zai-org/GLM-4.7-Flash":{"id":"zai-org/GLM-4.7-Flash","name":"GLM-4.7-Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-08-08","last_updated":"2025-08-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0,"output":0}},"zai-org/GLM-5.3":{"id":"zai-org/GLM-5.3","name":"GLM-5.3","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4},"canonical_model_id":"zhipuai/glm-5.3"},"zai-org/GLM-4.5":{"id":"zai-org/GLM-4.5","name":"GLM-4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.6,"output":2.2},"canonical_model_id":"zhipuai/glm-4.5"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.1,"output":0.5},"canonical_model_id":"openai/gpt-oss-20b"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.25,"output":0.69},"canonical_model_id":"openai/gpt-oss-120b"}}},"volcengine":{"id":"volcengine","env":["ARK_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://ark.cn-beijing.volces.com/api/v3","name":"Volcengine Ark","doc":"https://www.volcengine.com/docs/82379/1330310","models":{"glm-5-3-flash-260828":{"id":"glm-5-3-flash-260828","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.11875,"output":0.41563,"cache_read":0.03414},"canonical_model_id":"zhipuai/glm-5.3-flash"},"doubao-seed-1-6-251015":{"id":"doubao-seed-1-6-251015","name":"Seed 1.6","description":"ByteDance Seed model for long-context reasoning, instruction following, and tool-assisted tasks","family":"seed","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":0.11875,"output":1.18747,"cache_read":0.02375,"tiers":[{"input":0.17812,"output":2.37494,"cache_read":0.02375,"tier":{"type":"context","size":32000}},{"input":0.35624,"output":3.56241,"cache_read":0.02375,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-1-6"},"doubao-seed-2-0-pro-260215":{"id":"doubao-seed-2-0-pro-260215","name":"Seed 2.0 Pro","description":"Flagship ByteDance Seed 2.0 model for complex multimodal reasoning and long-horizon agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.47499,"output":2.37494,"cache_read":0.095,"tiers":[{"input":0.71248,"output":3.56241,"cache_read":0.1425,"tier":{"type":"context","size":32000}},{"input":1.42496,"output":7.12482,"cache_read":0.28499,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-pro"},"doubao-seed-2-0-lite-260428":{"id":"doubao-seed-2-0-lite-260428","name":"Seed 2.0 Lite","description":"Cost-efficient ByteDance Seed 2.0 model for production chat, analysis, and structured generation","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":131072},"cost":{"input":0.08906,"output":0.53436,"cache_read":0.01781,"tiers":[{"input":0.13359,"output":0.80154,"cache_read":0.02672,"tier":{"type":"context","size":32000}},{"input":0.26718,"output":1.60308,"cache_read":0.05344,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"doubao-seed-2-1-pro-260628":{"id":"doubao-seed-2-1-pro-260628","name":"Seed 2.1 Pro","description":"Flagship ByteDance Seed 2.1 model for complex multimodal reasoning, coding, and agents","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.8906,"output":4.45301,"cache_read":0.17812},"canonical_model_id":"bytedance-seed/seed-2.1-pro"},"doubao-seed-1-6-vision-250815":{"id":"doubao-seed-1-6-vision-250815","name":"Seed 1.6 Vision","description":"ByteDance Seed multimodal model for image understanding, visual reasoning, and tool-assisted tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-08-15","last_updated":"2025-08-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.11875,"output":1.18747,"cache_read":0.02375,"tiers":[{"input":0.17812,"output":2.37494,"cache_read":0.02375,"tier":{"type":"context","size":32000}},{"input":0.35624,"output":3.56241,"cache_read":0.02375,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-1-6-vision"},"doubao-seed-2-0-mini-260428":{"id":"doubao-seed-2-0-mini-260428","name":"Seed 2.0 Mini","description":"Lightweight ByteDance Seed 2.0 model for low-latency multimodal reasoning and high-volume tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":131072},"cost":{"input":0.02969,"output":0.29687,"cache_read":0.00594,"tiers":[{"input":0.05937,"output":0.59374,"cache_read":0.01187,"tier":{"type":"context","size":32000}},{"input":0.11875,"output":1.18747,"cache_read":0.02375,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"doubao-seed-2-0-code-preview-260215":{"id":"doubao-seed-2-0-code-preview-260215","name":"Seed 2.0 Code","description":"ByteDance Seed coding model for multimodal software engineering and long-running agents","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.47499,"output":2.37494,"cache_read":0.095,"tiers":[{"input":0.71248,"output":3.56241,"cache_read":0.1425,"tier":{"type":"context","size":32000}},{"input":1.42496,"output":7.12482,"cache_read":0.28499,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"doubao-seed-2-1-turbo-260628":{"id":"doubao-seed-2-1-turbo-260628","name":"Seed 2.1 Turbo","description":"Faster ByteDance Seed 2.1 model for multimodal reasoning and latency-sensitive agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.4453,"output":2.22651,"cache_read":0.08906},"canonical_model_id":"bytedance-seed/seed-2.1-turbo"},"glm-5-2-260617":{"id":"glm-5-2-260617","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.18747,"output":4.15615,"cache_read":0.29687},"canonical_model_id":"zhipuai/glm-5.2"},"doubao-seed-1-8-251228":{"id":"doubao-seed-1-8-251228","name":"Seed 1.8","description":"ByteDance Seed model for multimodal reasoning, long-context analysis, and agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-12-28","last_updated":"2025-12-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":0.11875,"output":1.18747,"cache_read":0.02375,"tiers":[{"input":0.17812,"output":2.37494,"cache_read":0.02375,"tier":{"type":"context","size":32000}},{"input":0.35624,"output":3.56241,"cache_read":0.02375,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-1-8"},"doubao-seed-evolving":{"id":"doubao-seed-evolving","name":"Seed Evolving","description":"Rolling ByteDance Seed model for rapidly updated reasoning, coding, and agent capabilities","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.8906,"output":4.45301,"cache_read":0.17812},"canonical_model_id":"bytedance-seed/seed-evolving"},"doubao-seed-1-6-flash-250828":{"id":"doubao-seed-1-6-flash-250828","name":"Seed 1.6 Flash","description":"Low-latency ByteDance Seed model for high-throughput chat, extraction, and lightweight tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-08-28","last_updated":"2025-08-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.02227,"output":0.22265,"cache_read":0.00445,"tiers":[{"input":0.04453,"output":0.4453,"cache_read":0.00445,"tier":{"type":"context","size":32000}},{"input":0.08906,"output":0.8906,"cache_read":0.00445,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-1-6-flash"},"doubao-seed-character-260628":{"id":"doubao-seed-character-260628","name":"Seed Character","description":"ByteDance Seed model optimized for character-driven dialogue and consistent conversational behavior","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.11875,"output":0.29687,"cache_read":0.02375,"tiers":[{"input":0.17812,"output":0.8906,"cache_read":0.02375,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"bytedance-seed/seed-character"},"deepseek-v4-pro-ga-260813":{"id":"deepseek-v4-pro-ga-260813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.3359,"output":4.00771,"cache_read":0.04453},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek-v4-flash-ga-260731":{"id":"deepseek-v4-flash-ga-260731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.4453,"output":1.3359,"cache_read":0.01484},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"}}},"impossibl":{"id":"impossibl","env":["IMPOSSIBL_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.impossibl.com/v1","name":"Impossibl","doc":"https://impossibl.com/docs/models","models":{"cerebras/gpt-oss-120b":{"id":"cerebras/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.35,"output":0.75},"canonical_model_id":"openai/gpt-oss-120b"},"groq/gpt-oss-20b":{"id":"groq/gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.075,"output":0.3,"cache_read":0.0375},"canonical_model_id":"openai/gpt-oss-20b"},"groq/gpt-oss-120b":{"id":"groq/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-oss-120b"},"zai/glm-4.5":{"id":"zai/glm-4.5","name":"GLM-4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5"},"zai/glm-4.6":{"id":"zai/glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.6"},"zai/glm-5":{"id":"zai/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"zai/glm-4.7":{"id":"zai/glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.7"},"zai/glm-5.2":{"id":"zai/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"zai/glm-5.1":{"id":"zai/glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"zai/glm-5-turbo":{"id":"zai/glm-5-turbo","name":"GLM-5-Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5-turbo"},"zai/glm-4.5-air":{"id":"zai/glm-4.5-air","name":"GLM-4.5-Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.2,"output":1.1,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-4.5-air"},"anthropic/claude-haiku-4-5":{"id":"anthropic/claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-opus-4-5":{"id":"anthropic/claude-opus-4-5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-sonnet-4-5":{"id":"anthropic/claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-opus-4-8":{"id":"anthropic/claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-opus-4-6":{"id":"anthropic/claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024},{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-sonnet-4-6":{"id":"anthropic/claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024},{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-4-7":{"id":"anthropic/claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.74,"output":3.48,"cache_read":0.145},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.19,"output":0.51,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"thinkingmachines/inkling":{"id":"thinkingmachines/inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":1.87,"output":4.68,"cache_read":0.374},"canonical_model_id":"thinkingmachines/inkling"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"google/gemini-3.6-flash"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-2.5-flash"},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":512,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.01},"canonical_model_id":"google/gemini-2.5-flash-lite"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025},"canonical_model_id":"google/gemini-3.1-flash-lite"},"xai/grok-4.3":{"id":"xai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2},"canonical_model_id":"xai/grok-4.3"},"xai/grok-4.20-0309-reasoning":{"id":"xai/grok-4.20-0309-reasoning","name":"Grok 4.20 (Reasoning)","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2},"canonical_model_id":"xai/grok-4.20-0309-reasoning"},"xai/grok-4.5":{"id":"xai/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.3},"canonical_model_id":"xai/grok-4.5"},"xai/grok-4.20-0309-non-reasoning":{"id":"xai/grok-4.20-0309-non-reasoning","name":"Grok 4.20 (Non-Reasoning)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2},"canonical_model_id":"xai/grok-4.20-0309-non-reasoning"},"xai/grok-build-0.1":{"id":"xai/grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.2},"canonical_model_id":"xai/grok-build-0.1"},"fireworks/gpt-oss-20b":{"id":"fireworks/gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.07,"output":0.3,"cache_read":0.035},"canonical_model_id":"openai/gpt-oss-20b"},"fireworks/glm-5.2":{"id":"fireworks/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.2"},"fireworks/gpt-oss-120b":{"id":"fireworks/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"openai/gpt-oss-120b"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"xiaomi/mimo-v2.5":{"id":"xiaomi/mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.003},"canonical_model_id":"xiaomi/mimo-v2.5"},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":2.5,"output":7.5,"cache_read":0.5},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen3.8-max-preview":{"id":"qwen/qwen3.8-max-preview","name":"Qwen3.8 Max Preview","description":"Preview Qwen flagship for million-token multimodal reasoning and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-19","last_updated":"2026-07-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2.5,"output":7.5},"canonical_model_id":"alibaba/qwen3.8-max-preview"},"qwen/qwen3.6-flash":{"id":"qwen/qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.05,"tiers":[{"input":1,"output":4,"cache_read":0.2,"tier":{"type":"context","size":262144}}],"context_over_200k":{"input":1,"output":4,"cache_read":0.2}},"canonical_model_id":"alibaba/qwen3.6-flash"},"qwen/qwen3.7-plus":{"id":"qwen/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.4,"output":1.6,"cache_read":0.08,"tiers":[{"input":1.2,"output":4.8,"cache_read":0.24,"tier":{"type":"context","size":262144}}],"context_over_200k":{"input":1.2,"output":4.8,"cache_read":0.24}},"canonical_model_id":"alibaba/qwen3.7-plus"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"cache_read":3,"tiers":[{"input":60,"output":270,"cache_read":3,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270,"cache_read":3}},"canonical_model_id":"openai/gpt-5.4-pro"},"openai/gpt-3.5-turbo":{"id":"openai/gpt-3.5-turbo","name":"GPT-3.5-turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"output":4096},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"openai/gpt-3.5-turbo"},"openai/gpt-5.5-pro":{"id":"openai/gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"cache_read":3,"tiers":[{"input":60,"output":270,"cache_read":3,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270,"cache_read":3}},"canonical_model_id":"openai/gpt-5.5-pro"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-5.2-codex":{"id":"openai/gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Code-specialist GPT for repository edits, reviews, and long-running software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-codex"},"openai/gpt-5.1-codex":{"id":"openai/gpt-5.1-codex","name":"GPT-5.1 Codex","description":"Codex GPT for repository edits, code review, and practical software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex"},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-5-codex":{"id":"openai/gpt-5-codex","name":"GPT-5-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5-codex"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"openai/o4-mini":{"id":"openai/o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.275},"canonical_model_id":"openai/o4-mini"},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"openai/o1":{"id":"openai/o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":15,"output":60,"cache_read":7.5},"canonical_model_id":"openai/o1"},"openai/gpt-5-pro":{"id":"openai/gpt-5-pro","name":"GPT-5 Pro","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":272000},"cost":{"input":15,"output":120},"canonical_model_id":"openai/gpt-5-pro"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-4-turbo":{"id":"openai/gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":10,"output":30},"canonical_model_id":"openai/gpt-4-turbo"},"openai/gpt-5.1-codex-mini":{"id":"openai/gpt-5.1-codex-mini","name":"GPT-5.1 Codex mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5.1-codex-mini"},"openai/o3":{"id":"openai/o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":45,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1,"cache_write":12.5}},"canonical_model_id":"openai/gpt-5.6-sol"}}},"xpersona":{"id":"xpersona","env":["XPERSONA_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://www.xpersona.co/v1","name":"Xpersona","doc":"https://www.xpersona.co/docs","models":{"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":0.75,"output":6,"reasoning":6,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4"},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":0.6,"output":3.7,"reasoning":3.7,"cache_read":0.06},"canonical_model_id":"anthropic/claude-haiku-4-5"},"xpersona-frieren-coder":{"id":"xpersona-frieren-coder","name":"Xpersona Frieren 1","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-30","release_date":"2026-05-01","last_updated":"2026-05-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":384000},"cost":{"input":1.5,"output":6,"reasoning":6,"cache_read":0.15}},"gpt-5.6":{"id":"gpt-5.6","name":"GPT-5.6","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":372000,"output":128000},"cost":{"input":1.5,"output":12,"reasoning":12,"cache_read":0.15},"canonical_model_id":"openai/gpt-5.6-sol"},"xpersona-gpt-5.5":{"id":"xpersona-gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-12-30","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3,"output":18,"reasoning":18,"cache_read":0.3},"canonical_model_id":"openai/gpt-5.5"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":1.55,"output":12.2,"reasoning":12.2,"cache_read":0.155},"canonical_model_id":"google/gemini-3.5-flash"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3,"output":18.5,"reasoning":18.5,"cache_read":0.3},"canonical_model_id":"anthropic/claude-fable-5"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":272000,"output":128000},"cost":{"input":0.375,"output":4,"reasoning":4,"cache_read":0.0375},"canonical_model_id":"openai/gpt-5.4-mini"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":1.5,"output":9.25,"reasoning":9.25,"cache_read":0.15},"canonical_model_id":"anthropic/claude-opus-4-8"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":1.5,"output":12,"reasoning":12,"cache_read":0.15},"canonical_model_id":"openai/gpt-5.5"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":0.9,"output":5.55,"reasoning":5.55,"cache_read":0.09},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":372000,"output":128000},"cost":{"input":1.5,"output":2,"reasoning":2,"cache_read":0.15},"canonical_model_id":"openai/gpt-5.6-terra"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":372000,"output":128000},"cost":{"input":1.5,"output":12,"reasoning":12,"cache_read":0.15},"canonical_model_id":"openai/gpt-5.6-sol"}}},"qiniu-ai":{"id":"qiniu-ai","env":["QINIU_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.qnaigc.com/v1","name":"Qiniu","doc":"https://developer.qiniu.com/aitokenapi","models":{"glm-4.5":{"id":"glm-4.5","name":"GLM 4.5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":98304}},"gemini-3.0-flash-preview":{"id":"gemini-3.0-flash-preview","name":"Gemini 3.0 Flash Preview","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-18","last_updated":"2025-12-18","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000}},"doubao-seed-2.0-mini":{"id":"doubao-seed-2.0-mini","name":"Doubao Seed 2.0 Mini","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000}},"mimo-v2-flash":{"id":"mimo-v2-flash","name":"Mimo-V2-Flash","description":"MiMo flash model for fast multimodal assistance and agent workflows","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12-01","release_date":"2025-12-16","last_updated":"2026-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.1,"output":0.3,"cache_read":0.01},"canonical_model_id":"xiaomi/mimo-v2-flash"},"doubao-seed-2.0-lite":{"id":"doubao-seed-2.0-lite","name":"Doubao Seed 2.0 Lite","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000}},"doubao-seed-1.6-thinking":{"id":"doubao-seed-1.6-thinking","name":"Doubao-Seed 1.6 Thinking","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-15","last_updated":"2025-08-15","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000}},"gemini-2.5-flash-image":{"id":"gemini-2.5-flash-image","name":"Gemini 2.5 Flash Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-10-22","last_updated":"2025-10-22","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":32768,"output":8192}},"gemini-3.0-pro-image-preview":{"id":"gemini-3.0-pro-image-preview","name":"Gemini 3.0 Pro Image Preview","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-11-20","last_updated":"2025-11-20","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":32768,"output":8192}},"claude-3.5-haiku":{"id":"claude-3.5-haiku","name":"Claude 3.5 Haiku","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192}},"qwen3-235b-a22b-instruct-2507":{"id":"qwen3-235b-a22b-instruct-2507","name":"Qwen3 235b A22B Instruct 2507","description":"Tool-capable chat model for instruction following and agentic application workflows","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-12","last_updated":"2025-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":64000}},"qwen3-next-80b-a3b-thinking":{"id":"qwen3-next-80b-a3b-thinking","name":"Qwen3 Next 80B A3B Thinking","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-12","last_updated":"2025-09-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768}},"qwen-max-2025-01-25":{"id":"qwen-max-2025-01-25","name":"Qwen2.5-Max-2025-01-25","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096}},"deepseek-v3-0324":{"id":"deepseek-v3-0324","name":"DeepSeek-V3-0324","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16000}},"qwen3-32b":{"id":"qwen3-32b","name":"Qwen3 32B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":40000,"output":4096}},"qwen3-max":{"id":"qwen3-max","name":"Qwen3 Max","description":"Flagship model for demanding analysis, coding, and production agent workflows","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-24","last_updated":"2025-09-24","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536}},"claude-4.5-sonnet":{"id":"claude-4.5-sonnet","name":"Claude 4.5 Sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000}},"deepseek-v3":{"id":"deepseek-v3","name":"DeepSeek-V3","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-08-13","last_updated":"2025-08-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16000}},"qwen3-coder-480b-a35b-instruct":{"id":"qwen3-coder-480b-a35b-instruct","name":"Qwen3 Coder 480B A35B Instruct","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-14","last_updated":"2025-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":4096}},"qwen-turbo":{"id":"qwen-turbo","name":"Qwen-Turbo","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":4096}},"gemini-2.0-flash":{"id":"gemini-2.0-flash","name":"Gemini 2.0 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":8192}},"gemini-2.0-flash-lite":{"id":"gemini-2.0-flash-lite","name":"Gemini 2.0 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":8192}},"claude-4.0-sonnet":{"id":"claude-4.0-sonnet","name":"Claude 4.0 Sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000}},"qwen2.5-vl-7b-instruct":{"id":"qwen2.5-vl-7b-instruct","name":"Qwen 2.5 VL 7B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192}},"qwen3-235b-a22b-thinking-2507":{"id":"qwen3-235b-a22b-thinking-2507","name":"Qwen3 235B A22B Thinking 2507","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-12","last_updated":"2025-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":4096}},"qwen3-235b-a22b":{"id":"qwen3-235b-a22b","name":"Qwen 3 235B A22B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000}},"doubao-seed-2.0-pro":{"id":"doubao-seed-2.0-pro","name":"Doubao Seed 2.0 Pro","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000}},"doubao-seed-1.6-flash":{"id":"doubao-seed-1.6-flash","name":"Doubao-Seed 1.6 Flash","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-15","last_updated":"2025-08-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000}},"qwen3-max-preview":{"id":"qwen3-max-preview","name":"Qwen3 Max Preview","description":"Flagship model for demanding analysis, coding, and production agent workflows","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-06","last_updated":"2025-09-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000}},"qwen3-next-80b-a3b-instruct":{"id":"qwen3-next-80b-a3b-instruct","name":"Qwen3 Next 80B A3B Instruct","description":"Tool-capable chat model for instruction following and agentic application workflows","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-12","last_updated":"2025-09-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768}},"qwen3-vl-30b-a3b-thinking":{"id":"qwen3-vl-30b-a3b-thinking","name":"Qwen3-Vl 30b A3b Thinking","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-09","last_updated":"2026-02-09","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000}},"doubao-1.5-pro-32k":{"id":"doubao-1.5-pro-32k","name":"Doubao 1.5 Pro 32k","description":"Flagship model for demanding analysis, coding, and production agent workflows","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":12000}},"claude-3.5-sonnet":{"id":"claude-3.5-sonnet","name":"Claude 3.5 Sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-09","last_updated":"2025-09-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8200}},"gpt-oss-20b":{"id":"gpt-oss-20b","name":"gpt-oss-20b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-06","last_updated":"2025-08-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096}},"gemini-2.5-pro":{"id":"gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536}},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":64000}},"qwen-vl-max-2025-01-25":{"id":"qwen-vl-max-2025-01-25","name":"Qwen VL-MAX-2025-01-25","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096}},"doubao-1.5-thinking-pro":{"id":"doubao-1.5-thinking-pro","name":"Doubao 1.5 Thinking Pro","description":"Flagship model for demanding analysis, coding, and production agent workflows","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16000}},"claude-4.5-haiku":{"id":"claude-4.5-haiku","name":"Claude 4.5 Haiku","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-10-16","last_updated":"2025-10-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000}},"kling-v2-6":{"id":"kling-v2-6","name":"Kling-V2 6","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-01-13","last_updated":"2026-01-13","modalities":{"input":["text","image","video"],"output":["video"]},"open_weights":false,"limit":{"context":99999999,"output":99999999}},"claude-4.1-opus":{"id":"claude-4.1-opus","name":"Claude 4.1 Opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-06","last_updated":"2025-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000}},"claude-3.7-sonnet":{"id":"claude-3.7-sonnet","name":"Claude 3.7 Sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000}},"MiniMax-M1":{"id":"MiniMax-M1","name":"MiniMax M1","description":"MiniMax model for chat, coding, office work, and agentic tasks","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":80000}},"doubao-seed-1.6":{"id":"doubao-seed-1.6","name":"Doubao-Seed 1.6","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-15","last_updated":"2025-08-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000}},"qwen3-30b-a3b":{"id":"qwen3-30b-a3b","name":"Qwen3 30B A3B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":40000,"output":4096}},"qwen3.5-397b-a17b":{"id":"qwen3.5-397b-a17b","name":"Qwen3.5 397B A17B","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-22","last_updated":"2026-02-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000}},"doubao-seed-2.0-code":{"id":"doubao-seed-2.0-code","name":"Doubao Seed 2.0 Code","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000}},"claude-4.0-opus":{"id":"claude-4.0-opus","name":"Claude 4.0 Opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000}},"kimi-k2":{"id":"kimi-k2","name":"Kimi K2","description":"Kimi model for long-context chat, coding, and agentic reasoning","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000}},"qwen3-30b-a3b-instruct-2507":{"id":"qwen3-30b-a3b-instruct-2507","name":"Qwen3 30b A3b Instruct 2507","description":"Tool-capable chat model for instruction following and agentic application workflows","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-04","last_updated":"2026-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000}},"qwen2.5-vl-72b-instruct":{"id":"qwen2.5-vl-72b-instruct","name":"Qwen 2.5 VL 72B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192}},"doubao-1.5-vision-pro":{"id":"doubao-1.5-vision-pro","name":"Doubao 1.5 Vision Pro","description":"Flagship model for demanding analysis, coding, and production agent workflows","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16000}},"claude-4.5-opus":{"id":"claude-4.5-opus","name":"Claude 4.5 Opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-11-25","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":200000}},"deepseek-v3.1":{"id":"deepseek-v3.1","name":"DeepSeek-V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-19","last_updated":"2025-08-19","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000}},"deepseek-r1":{"id":"deepseek-r1","name":"DeepSeek-R1","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000}},"qwen3-30b-a3b-thinking-2507":{"id":"qwen3-30b-a3b-thinking-2507","name":"Qwen3 30b A3b Thinking 2507","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-04","last_updated":"2026-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":126000,"output":32000}},"gemini-2.5-flash-lite":{"id":"gemini-2.5-flash-lite","name":"Gemini 2.5 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":64000}},"deepseek-r1-0528":{"id":"deepseek-r1-0528","name":"DeepSeek-R1-0528","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000}},"glm-4.5-air":{"id":"glm-4.5-air","name":"GLM 4.5 Air","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":4096}},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"gpt-oss-120b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-06","last_updated":"2025-08-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096}},"gemini-3.0-pro-preview":{"id":"gemini-3.0-pro-preview","name":"Gemini 3.0 Pro Preview","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000}},"deepseek/deepseek-v3.2-exp-thinking":{"id":"deepseek/deepseek-v3.2-exp-thinking","name":"DeepSeek/DeepSeek-V3.2-Exp-Thinking","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000}},"deepseek/deepseek-math-v2":{"id":"deepseek/deepseek-math-v2","name":"Deepseek/Deepseek-Math-V2","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-12-04","last_updated":"2025-12-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":160000,"output":160000}},"deepseek/deepseek-v3.1-terminus":{"id":"deepseek/deepseek-v3.1-terminus","name":"DeepSeek/DeepSeek-V3.1-Terminus","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-22","last_updated":"2025-09-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000}},"deepseek/deepseek-v3.2-251201":{"id":"deepseek/deepseek-v3.2-251201","name":"Deepseek/DeepSeek-V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000}},"deepseek/deepseek-v3.1-terminus-thinking":{"id":"deepseek/deepseek-v3.1-terminus-thinking","name":"DeepSeek/DeepSeek-V3.1-Terminus-Thinking","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-09-22","last_updated":"2025-09-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000}},"deepseek/deepseek-v3.2-exp":{"id":"deepseek/deepseek-v3.2-exp","name":"DeepSeek/DeepSeek-V3.2-Exp","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000}},"z-ai/glm-4.6":{"id":"z-ai/glm-4.6","name":"Z-AI/GLM 4.6","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-10-11","last_updated":"2025-10-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":200000}},"z-ai/glm-5":{"id":"z-ai/glm-5","name":"Z-Ai/GLM 5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000}},"z-ai/glm-4.7":{"id":"z-ai/glm-4.7","name":"Z-Ai/GLM 4.7","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":200000}},"z-ai/autoglm-phone-9b":{"id":"z-ai/autoglm-phone-9b","name":"Z-Ai/Autoglm Phone 9b","description":"GLM vision model for visual reasoning, documents, and multimodal agents","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":12800,"output":4096}},"meituan/longcat-flash-chat":{"id":"meituan/longcat-flash-chat","name":"Meituan/Longcat-Flash-Chat","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-11-05","last_updated":"2025-11-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":131072}},"meituan/longcat-flash-lite":{"id":"meituan/longcat-flash-lite","name":"Meituan/Longcat-Flash-Lite","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-06","last_updated":"2026-02-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":320000}},"x-ai/grok-4-fast-reasoning":{"id":"x-ai/grok-4-fast-reasoning","name":"X-Ai/Grok-4-Fast-Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-18","last_updated":"2025-12-18","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000}},"x-ai/grok-4.1-fast-reasoning":{"id":"x-ai/grok-4.1-fast-reasoning","name":"X-Ai/Grok 4.1 Fast Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-19","last_updated":"2025-12-19","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":20000000,"output":2000000}},"x-ai/grok-4-fast-non-reasoning":{"id":"x-ai/grok-4-fast-non-reasoning","name":"X-Ai/Grok-4-Fast-Non-Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-18","last_updated":"2025-12-18","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000}},"x-ai/grok-code-fast-1":{"id":"x-ai/grok-code-fast-1","name":"x-AI/Grok-Code-Fast 1","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-02","last_updated":"2025-09-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":10000}},"x-ai/grok-4.1-fast":{"id":"x-ai/grok-4.1-fast","name":"x-AI/Grok-4.1-Fast","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-11-20","last_updated":"2025-11-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000}},"x-ai/grok-4.1-fast-non-reasoning":{"id":"x-ai/grok-4.1-fast-non-reasoning","name":"X-Ai/Grok 4.1 Fast Non Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-19","last_updated":"2025-12-19","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000}},"x-ai/grok-4-fast":{"id":"x-ai/grok-4-fast","name":"x-AI/Grok-4-Fast","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-20","last_updated":"2025-09-20","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000}},"stepfun-ai/gelab-zero-4b-preview":{"id":"stepfun-ai/gelab-zero-4b-preview","name":"Stepfun-Ai/Gelab Zero 4b Preview","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":4096}},"moonshotai/kimi-k2-thinking":{"id":"moonshotai/kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Kimi reasoning model for long-horizon research, planning, and tool use","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-11-07","last_updated":"2025-11-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":100000}},"moonshotai/kimi-k2.5":{"id":"moonshotai/kimi-k2.5","name":"Moonshotai/Kimi-K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-01-28","last_updated":"2026-01-28","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000}},"moonshotai/kimi-k2-0905":{"id":"moonshotai/kimi-k2-0905","name":"Kimi K2 0905","description":"Kimi model for long-context chat, coding, and agentic reasoning","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-08","last_updated":"2025-09-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":100000}},"xiaomi/mimo-v2-flash":{"id":"xiaomi/mimo-v2-flash","name":"Xiaomi/Mimo-V2-Flash","description":"MiMo flash model for fast multimodal assistance and agent workflows","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12-01","release_date":"2025-12-16","last_updated":"2026-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.1,"output":0.3,"cache_read":0.01},"canonical_model_id":"xiaomi/mimo-v2-flash"},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"Minimax/Minimax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":204800,"output":128000}},"minimax/minimax-m2.5-highspeed":{"id":"minimax/minimax-m2.5-highspeed","name":"Minimax/Minimax-M2.5 Highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":204800,"output":128000}},"minimax/minimax-m2.1":{"id":"minimax/minimax-m2.1","name":"Minimax/Minimax-M2.1","description":"MiniMax model for chat, coding, office work, and agentic tasks","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":204800,"output":128000}},"minimax/minimax-m2":{"id":"minimax/minimax-m2","name":"Minimax/Minimax-M2","description":"MiniMax model for chat, coding, office work, and agentic tasks","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-10-28","last_updated":"2025-10-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000}},"stepfun/step-3.5-flash":{"id":"stepfun/step-3.5-flash","name":"Stepfun/Step-3.5 Flash","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-02-02","last_updated":"2026-02-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":64000,"output":4096}},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"OpenAI/GPT-5.2","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000}},"openai/gpt-5":{"id":"openai/gpt-5","name":"OpenAI/GPT-5","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-19","last_updated":"2025-09-19","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000}}}},"modelscope":{"id":"modelscope","env":["MODELSCOPE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api-inference.modelscope.cn/v1","name":"ModelScope","doc":"https://modelscope.cn/docs/model-service/API-Inference/intro","models":{"ZhipuAI/GLM-4.6":{"id":"ZhipuAI/GLM-4.6","name":"GLM-4.6","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-07","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":98304},"cost":{"input":0,"output":0}},"ZhipuAI/GLM-4.5":{"id":"ZhipuAI/GLM-4.5","name":"GLM-4.5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0,"output":0}},"Qwen/Qwen3-30B-A3B-Instruct-2507":{"id":"Qwen/Qwen3-30B-A3B-Instruct-2507","name":"Qwen3 30B A3B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0,"output":0}},"Qwen/Qwen3-235B-A22B-Thinking-2507":{"id":"Qwen/Qwen3-235B-A22B-Thinking-2507","name":"Qwen3-235B-A22B-Thinking-2507","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-25","last_updated":"2025-07-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0,"output":0}},"Qwen/Qwen3-235B-A22B-Instruct-2507":{"id":"Qwen/Qwen3-235B-A22B-Instruct-2507","name":"Qwen3 235B A22B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0,"output":0}},"Qwen/Qwen3-30B-A3B-Thinking-2507":{"id":"Qwen/Qwen3-30B-A3B-Thinking-2507","name":"Qwen3 30B A3B Thinking 2507","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0}},"Qwen/Qwen3-Coder-30B-A3B-Instruct":{"id":"Qwen/Qwen3-Coder-30B-A3B-Instruct","name":"Qwen3 Coder 30B A3B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-31","last_updated":"2025-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0,"output":0}}}},"google":{"id":"google","env":["GOOGLE_API_KEY","GOOGLE_GENERATIVE_AI_API_KEY","GEMINI_API_KEY"],"npm":"@ai-sdk/google","name":"Google","doc":"https://ai.google.dev/gemini-api/docs/models","models":{"gemini-flash-latest":{"id":"gemini-flash-latest","name":"Gemini Flash Latest","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"input_audio":0.75}},"gemma-4-31b-it":{"id":"gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768}},"gemini-omni-flash-preview":{"id":"gemini-omni-flash-preview","name":"Gemini Omni Flash Preview","description":"Video generation and editing model for fast, conversational text- and image-to-video workflows","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","video"],"output":["video"]},"open_weights":false,"limit":{"context":131072,"output":65536},"cost":{"input":1.5,"output":17.5},"canonical_model_id":"google/gemini-omni-flash-preview"},"gemini-3.1-flash-image-preview":{"id":"gemini-3.1-flash-image-preview","name":"Nano Banana 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-26","last_updated":"2026-02-26","modalities":{"input":["text","image","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":65536},"cost":{"input":0.5,"output":60}},"veo-3.1-lite-generate-preview":{"id":"veo-3.1-lite-generate-preview","name":"Veo 3.1 lite","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-03-31","last_updated":"2026-03-31","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":480,"output":8192},"canonical_model_id":"google/veo-3.1-lite-generate-preview"},"lyria-3-pro-preview":{"id":"lyria-3-pro-preview","name":"Lyria 3 Pro Preview","description":"Music generation model for full-length songs from text or images with vocals and structure","family":"lyria","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-03-25","last_updated":"2026-03-25","modalities":{"input":["text","image"],"output":["text","audio"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"google/lyria-3-pro-preview"},"gemini-3.1-flash-tts-preview":{"id":"gemini-3.1-flash-tts-preview","name":"Gemini 3.1 Flash TTS Preview","description":"Low-latency speech generation with steerable prompts and expressive audio tags","family":"gemini-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-15","last_updated":"2026-04-15","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":8192,"output":16384},"cost":{"input":1,"output":20},"canonical_model_id":"google/gemini-3.1-flash-tts-preview"},"gemini-2.5-flash-image":{"id":"gemini-2.5-flash-image","name":"Nano Banana","description":"Nano Banana image model for fast generation, edits, and character-consistent assets","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.3,"output":30,"cache_read":0.075},"canonical_model_id":"google/gemini-2.5-flash-image"},"gemini-flash-lite-latest":{"id":"gemini-flash-lite-latest","name":"Gemini Flash-Lite Latest","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03}},"gemini-embedding-2":{"id":"gemini-embedding-2","name":"Gemini Embedding 2","description":"Multimodal embedding model mapping text, images, video, audio, and PDFs into a unified embedding space","family":"gemini","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-11","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1},"cost":{"input":0.2,"output":0,"input_audio":6.5},"canonical_model_id":"google/gemini-embedding-2"},"gemini-3.6-flash":{"id":"gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"input_audio":0.75},"canonical_model_id":"google/gemini-3.6-flash"},"gemma-4-26b-a4b-it":{"id":"gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768}},"gemini-3-pro-image-preview":{"id":"gemini-3-pro-image-preview","name":"Nano Banana Pro","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-20","last_updated":"2025-11-20","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":2,"output":120},"canonical_model_id":"google/gemini-3-pro-image-preview"},"gemini-2.5-pro-preview-tts":{"id":"gemini-2.5-pro-preview-tts","name":"Gemini 2.5 Pro Preview TTS","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gemini-flash","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-05-01","last_updated":"2025-05-01","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":8192,"output":16384},"cost":{"input":1,"output":20}},"gemini-3.5-flash-lite":{"id":"gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"gemini-3.1-flash-image":{"id":"gemini-3.1-flash-image","name":"Nano Banana 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","video","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":60},"canonical_model_id":"google/gemini-3.1-flash-image"},"lyria-3-clip-preview":{"id":"lyria-3-clip-preview","name":"Lyria 3 Clip Preview","description":"Music generation model for short 30-second clips, loops, and previews from text or image prompts","family":"lyria","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-03-25","last_updated":"2026-03-25","modalities":{"input":["text","image"],"output":["text","audio"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"google/lyria-3-clip-preview"},"gemini-3.1-pro-preview":{"id":"gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}}},"gemini-2.5-computer-use-preview-10-2025":{"id":"gemini-2.5-computer-use-preview-10-2025","name":"Gemini 2.5 Computer Use Preview 10-2025","description":"Specialized Gemini 2.5 model for browser-control agents that automate UI tasks","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-10-07","last_updated":"2025-10-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"cost":{"input":1.25,"output":10,"tiers":[{"input":2.5,"output":15,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15}},"canonical_model_id":"google/gemini-2.5-computer-use-preview-10-2025"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"input_audio":1.5}},"gemini-2.5-pro":{"id":"gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro"},"gemini-3-pro-image":{"id":"gemini-3-pro-image","name":"Nano Banana Pro","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":2,"output":120},"canonical_model_id":"google/gemini-3-pro-image"},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"input_audio":1},"canonical_model_id":"google/gemini-2.5-flash"},"gemini-2.5-flash-preview-tts":{"id":"gemini-2.5-flash-preview-tts","name":"Gemini 2.5 Flash Preview TTS","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gemini-flash","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-05-01","last_updated":"2025-05-01","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":8192,"output":16384},"cost":{"input":0.5,"output":10}},"gemini-3.1-flash-lite-image":{"id":"gemini-3.1-flash-lite-image","name":"Nano Banana 2 Lite","description":"Fastest, most cost-efficient Gemini image model for high-volume 1K generation and editing","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":4096},"cost":{"input":0.25,"output":30},"canonical_model_id":"google/gemini-3.1-flash-lite-image"},"deep-research-preview-04-2026":{"id":"deep-research-preview-04-2026","name":"Deep Research Preview (Apr-21-2026)","description":"Agentic model for autonomous multi-step research, synthesis, and cited reports","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/deep-research-preview-04-2026"},"deep-research-max-preview-04-2026":{"id":"deep-research-max-preview-04-2026","name":"Deep Research Max Preview (Apr-21-2026)","description":"Maximum-comprehensiveness agentic researcher for multi-step investigation, synthesis, and cited reports","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/deep-research-max-preview-04-2026"},"veo-3.1-fast-generate-preview":{"id":"veo-3.1-fast-generate-preview","name":"Veo 3.1 fast","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-10-15","last_updated":"2026-01-01","modalities":{"input":["text","image","video"],"output":["video"]},"open_weights":false,"limit":{"context":480,"output":8192},"canonical_model_id":"google/veo-3.1-fast-generate-preview"},"gemini-3.7-flash":{"id":"gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"input_audio":0.75},"canonical_model_id":"google/gemini-3.7-flash"},"veo-3.1-generate-preview":{"id":"veo-3.1-generate-preview","name":"Veo 3.1","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-10-15","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":480,"output":8192},"status":"beta","canonical_model_id":"google/veo-3.1-generate-preview"},"gemini-3.1-pro-preview-customtools":{"id":"gemini-3.1-pro-preview-customtools","name":"Gemini 3.1 Pro Preview Custom Tools","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}}},"gemini-3-flash-preview":{"id":"gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"input_audio":1}},"gemini-3.8-flash":{"id":"gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"input_audio":0.75},"canonical_model_id":"google/gemini-3.8-flash"},"gemini-3.5-live-translate-preview":{"id":"gemini-3.5-live-translate-preview","name":"Gemini 3.5 Live Translate Preview","description":"Low-latency audio-to-audio model for real-time speech translation across 70+ languages","family":"gemini-pro","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["audio"],"output":["audio","text"]},"open_weights":false,"limit":{"context":16384,"output":32768},"cost":{"input":3.5,"output":21,"input_audio":3.5,"output_audio":21},"canonical_model_id":"google/gemini-3.5-live-translate-preview"},"gemini-2.5-flash-lite":{"id":"gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":512,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"input_audio":0.3}},"gemini-embedding-001":{"id":"gemini-embedding-001","name":"Gemini Embedding 001","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-05","release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":2048,"output":1},"cost":{"input":0.15,"output":0}},"gemini-3.1-flash-lite-preview":{"id":"gemini-3.1-flash-lite-preview","name":"Gemini 3.1 Flash Lite Preview","description":"Legacy model retained for compatibility with older integrations","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5}},"gemini-3.1-flash-live-preview":{"id":"gemini-3.1-flash-live-preview","name":"Gemini 3.1 Flash Live Preview","description":"High-quality, low-latency Live API model for real-time dialogue and voice-first AI applications","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-26","last_updated":"2026-03-26","modalities":{"input":["text","image","video","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":131072,"output":65536},"cost":{"input":0.75,"output":4.5,"input_audio":3,"output_audio":12},"canonical_model_id":"google/gemini-3.1-flash-live-preview"},"gemini-4-argon":{"id":"gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":32768},"cost":{"input":2,"output":10,"cache_read":0.1,"input_audio":2},"canonical_model_id":"google/gemini-4-argon"},"gemini-3.1-flash-lite":{"id":"gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5}}}},"vancine":{"id":"vancine","env":["VANCINE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://vancine.com/v1","name":"Vancine","doc":"https://vancine.com/docs","models":{"MiniMax-M3":{"id":"MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.24,"output":0.96,"cache_read":0.048},"canonical_model_id":"minimax/MiniMax-M3"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.12,"output":0.4,"cache_read":0.024},"canonical_model_id":"zhipuai/glm-5.3-flash"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":1.6,"output":4.8,"cache_read":0.2},"canonical_model_id":"alibaba/qwen3.8-max"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":2.4,"output":12,"cache_read":0.24},"canonical_model_id":"moonshotai/kimi-k3"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.24,"output":0.96,"cache_read":0.0048},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.12,"output":0.38,"cache_read":0.013},"canonical_model_id":"alibaba/qwen3.8-flash"},"hy4-preview":{"id":"hy4-preview","name":"Hy4 preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":64000},"cost":{"input":0.67,"output":2,"cache_read":0.034},"canonical_model_id":"tencent/hy4-preview"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.12,"output":3.52,"cache_read":0.208},"canonical_model_id":"zhipuai/glm-5.3"}}},"zhipuai-coding-plan":{"id":"zhipuai-coding-plan","env":["ZHIPU_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://open.bigmodel.cn/api/coding/paas/v4","name":"Zhipu AI Coding Plan","doc":"https://docs.bigmodel.cn/cn/coding-plan/overview","models":{"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"glm-5.3-highspeed":{"id":"glm-5.3-highspeed","name":"GLM-5.3 Highspeed","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"glm-4.6v":{"id":"glm-4.6v","name":"GLM-4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.3,"output":0.9}}}},"lucidquery":{"id":"lucidquery","env":["LUCIDQUERY_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.lucidquery.com/v1","name":"LucidQuery","doc":"https://lucidquery.com/docs","models":{"lucidquery-agi-01-frontier":{"id":"lucidquery-agi-01-frontier","name":"AGI-01 Frontier","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"agi","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2026-06-05","release_date":"2026-06-16","last_updated":"2026-06-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":120000},"cost":{"input":4.5,"output":22}},"lucidquery-nexus-coder":{"id":"lucidquery-nexus-coder","name":"LucidQuery Nexus Coder","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","family":"lucid","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2025-08-01","release_date":"2025-09-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":250000,"output":60000},"cost":{"input":2,"output":5}},"lucidnova-rf1-100b":{"id":"lucidnova-rf1-100b","name":"LucidNova RF1 100B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"nova","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2025-09-16","release_date":"2024-12-28","last_updated":"2025-09-10","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":120000,"output":8000},"cost":{"input":2,"output":5}},"lucidquery-agi-01-swift":{"id":"lucidquery-agi-01-swift","name":"AGI-01 Swift","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"agi","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2026-06-05","release_date":"2026-06-16","last_updated":"2026-06-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":120000},"cost":{"input":2.5,"output":15}}}},"gmicloud":{"id":"gmicloud","env":["GMICLOUD_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.gmi-serving.com/v1","name":"GMI Cloud","doc":"https://docs.gmicloud.ai/inference-engine/api-reference/llm-api-reference","models":{"anthropic/claude-opus-4.6":{"id":"anthropic/claude-opus-4.6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":127999}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":409600,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":409600,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":30,"output":150,"cache_read":3,"cache_write":37.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"cost":{"input":4.5,"output":22.5,"cache_read":0.45},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":409600,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"Qwen/Qwen3.7-Max":{"id":"Qwen/Qwen3.7-Max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":2.5,"output":7.5,"cache_read":0.25,"cache_write":3.125},"canonical_model_id":"alibaba/qwen3.7-max"},"Qwen/Qwen3.8-Max":{"id":"Qwen/Qwen3.8-Max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"Qwen/Qwen3.8-Flash":{"id":"Qwen/Qwen3.8-Flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048575,"output":131072},"cost":{"input":0.16,"output":0.47,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"deepseek-ai/DeepSeek-V4-Flash":{"id":"deepseek-ai/DeepSeek-V4-Flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048575,"output":384000},"cost":{"input":0.112,"output":0.224,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek-ai/DeepSeek-V4-Pro":{"id":"deepseek-ai/DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":1.392,"output":2.784,"cache_read":0.116},"canonical_model_id":"deepseek/deepseek-v4-pro"},"MiniMaxAI/MiniMax-M3":{"id":"MiniMaxAI/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.6,"output":2.4,"cache_read":0.12,"tiers":[{"input":1.2,"output":4.8,"cache_read":0.24,"tier":{"type":"context","size":512000}}],"context_over_200k":{"input":1.2,"output":4.8,"cache_read":0.24}},"canonical_model_id":"minimax/MiniMax-M3"},"MiniMaxAI/MiniMax-M2.7":{"id":"MiniMaxAI/MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7"},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.855,"output":3.6,"cache_read":0.144},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2.7-code-highspeed":{"id":"moonshotai/kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code Highspeed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"zai-org/GLM-5.2-FP8":{"id":"zai-org/GLM-5.2-FP8","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.979,"output":3.08,"cache_read":0.182},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-5-FP8":{"id":"zai-org/GLM-5-FP8","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.6,"output":1.92,"cache_read":0.12},"canonical_model_id":"zhipuai/glm-5"},"zai-org/GLM-5.1-FP8":{"id":"zai-org/GLM-5.1-FP8","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.98,"output":3.08,"cache_read":0.182},"canonical_model_id":"zhipuai/glm-5.1"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5"}}},"oci":{"id":"oci","env":["OCI_GENAI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://inference.generativeai.us-chicago-1.oci.oraclecloud.com/openai/v1","name":"OCI Generative AI","doc":"https://docs.oracle.com/en-us/iaas/Content/generative-ai/pretrained-models.htm","models":{"xai.grok-4.3":{"id":"xai.grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.3"},"xai.grok-4.20-non-reasoning":{"id":"xai.grok-4.20-non-reasoning","name":"Grok 4.20 (Non-Reasoning)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-non-reasoning"},"meta.llama-3.3-70b-instruct":{"id":"meta.llama-3.3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.72,"output":0.72},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"meta.llama-4-scout-17b-16e-instruct":{"id":"meta.llama-4-scout-17b-16e-instruct","name":"Llama 4 Scout 17B Instruct","description":"Open Llama with long-context vision for efficient multimodal agents","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":192000,"output":16384},"cost":{"input":0.72,"output":0.72},"canonical_model_id":"meta/llama-4-scout-17b-instruct"},"xai.grok-4.6":{"id":"xai.grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"meta.llama-4-maverick-17b-128e-instruct-fp8":{"id":"meta.llama-4-maverick-17b-128e-instruct-fp8","name":"Llama 4 Maverick 17B Instruct","description":"Open multimodal Llama for strong reasoning with efficient everyday serving","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"output":16384},"cost":{"input":0.72,"output":0.72},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"openai.gpt-oss-120b":{"id":"openai.gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-120b"},"openai.gpt-oss-20b":{"id":"openai.gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.07,"output":0.3},"canonical_model_id":"openai/gpt-oss-20b"},"xai.grok-4.20-reasoning":{"id":"xai.grok-4.20-reasoning","name":"Grok 4.20 (Reasoning)","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-reasoning"}}},"cloudflare-ai-gateway":{"id":"cloudflare-ai-gateway","env":["CLOUDFLARE_API_TOKEN","CLOUDFLARE_ACCOUNT_ID","CLOUDFLARE_GATEWAY_ID"],"npm":"ai-gateway-provider","name":"Cloudflare AI Gateway","doc":"https://developers.cloudflare.com/ai-gateway/","models":{"anthropic/claude-opus-4.5":{"id":"anthropic/claude-opus-4.5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-opus-4.6":{"id":"anthropic/claude-opus-4.6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic/claude-haiku-5.5":{"id":"anthropic/claude-haiku-5.5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-haiku-4.5":{"id":"anthropic/claude-haiku-4.5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-sonnet-5.5":{"id":"anthropic/claude-sonnet-5.5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-fable-5.1":{"id":"anthropic/claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-sonnet-4.5":{"id":"anthropic/claude-sonnet-4.5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-5.5":{"id":"anthropic/claude-opus-5.5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":384000},"cost":{"input":1.74,"output":3.48,"cache_read":0.145},"canonical_model_id":"deepseek/deepseek-v4-pro"},"unbiased/pareto":{"id":"unbiased/pareto","name":"Pareto","description":"Blended multimodal model that runs multiple language models in parallel and returns a synthesized answer","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":2.5,"output":7.5,"cache_read":0.25},"canonical_model_id":"unbiased/pareto"},"meta/muse-spark-1.3":{"id":"meta/muse-spark-1.3","name":"Muse Spark 1.3","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.16},"canonical_model_id":"meta/muse-spark-1.3"},"meta/muse-spark-1.1":{"id":"meta/muse-spark-1.1","name":"Muse Spark 1.1","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.16},"canonical_model_id":"meta/muse-spark-1.1"},"meta/muse-spark-1.2":{"id":"meta/muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.16},"canonical_model_id":"meta/muse-spark-1.2"},"meta/muse-wonder-1.0":{"id":"meta/muse-wonder-1.0","name":"Muse Wonder","description":"Muse Wonder is a frontier multimodal reasoning model from Meta for personal and professional agents, long-horizon coding, and computer use. It combines Active Memory, which carries relevant context across conversations, with Active Focus, which keeps it working through blockers toward a goal.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":4,"output":20,"cache_read":0.2},"canonical_model_id":"meta/muse-wonder-1.0"},"alibaba/qwen3.7-max":{"id":"alibaba/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":1.25,"output":3.75,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.7-max"},"alibaba/qwen3.8-max":{"id":"alibaba/qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-max"},"alibaba/qwen3-max":{"id":"alibaba/qwen3-max","name":"Qwen3 Max","description":"Flagship Qwen3 model for coding agents, complex reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":1.2,"output":6},"canonical_model_id":"alibaba/qwen3-max"},"alibaba/qwen3.5-397b-a17b":{"id":"alibaba/qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.6,"output":3.6},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"alibaba/qwen3.7-plus":{"id":"alibaba/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.32,"output":1.28,"cache_read":0.064},"canonical_model_id":"alibaba/qwen3.7-plus"},"google/gemini-4-argon":{"id":"google/gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":10,"cache_read":0.1},"canonical_model_id":"google/gemini-4-argon"},"reflection-ai/beam-1.0-501b-a23b":{"id":"reflection-ai/beam-1.0-501b-a23b","name":"Beam 1.0 501B A23B","description":"Sparse mixture-of-experts reasoning model with 23B active parameters for coding and agentic workflows","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-06-30","release_date":"2026-10-05","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"reflection/beam-1.0-501b-a23b"},"xai/grok-4.7":{"id":"xai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"xai/grok-4.3":{"id":"xai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2},"canonical_model_id":"xai/grok-4.3"},"xai/grok-4.20-0309-reasoning":{"id":"xai/grok-4.20-0309-reasoning","name":"Grok 4.20 (Reasoning)","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"xai/grok-4.20-0309-reasoning"},"xai/grok-4.5":{"id":"xai/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.3,"tiers":[{"input":4,"output":12,"cache_read":0.6,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":0.6}},"canonical_model_id":"xai/grok-4.5"},"xai/grok-4.20-0309-non-reasoning":{"id":"xai/grok-4.20-0309-non-reasoning","name":"Grok 4.20 (Non-Reasoning)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"xai/grok-4.20-0309-non-reasoning"},"xai/grok-4.6":{"id":"xai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"fireworks/ember-1":{"id":"fireworks/ember-1","name":"Ember-1","description":"Specialized model from Fireworks built on Kimi K3, producing shorter reasoning traces with approximately 40% fewer tokens while maintaining comparable quality","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1040000,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"fireworks/ember-1"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":2.5,"output":15,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":30,"output":180},"canonical_model_id":"openai/gpt-5.4-pro"},"openai/gpt-5.5-pro":{"id":"openai/gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":30,"output":180},"canonical_model_id":"openai/gpt-5.5-pro"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":1.25,"output":5,"cache_read":0.625},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"openai/o4-mini":{"id":"openai/o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":1.1,"output":4.4,"cache_read":0.275},"canonical_model_id":"openai/o4-mini"},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":0.075,"output":0.3,"cache_read":0.0375},"canonical_model_id":"openai/gpt-4o-mini"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":5,"output":30},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/o3":{"id":"openai/o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":2,"output":10,"cache_read":0.25,"cache_write":3.125},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"}}},"clarifai":{"id":"clarifai","env":["CLARIFAI_PAT"],"npm":"@ai-sdk/openai-compatible","api":"https://api.clarifai.com/v2/ext/openai/v1","name":"Clarifai","doc":"https://docs.clarifai.com/compute/inference/","models":{"minimaxai/chat-completion/models/MiniMax-M2_5-high-throughput":{"id":"minimaxai/chat-completion/models/MiniMax-M2_5-high-throughput","name":"MiniMax-M2.5 High Throughput","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2}},"clarifai/main/models/mm-poly-8b":{"id":"clarifai/main/models/mm-poly-8b","name":"MM Poly 8B","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"mm-poly","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-06","last_updated":"2026-02-25","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":4096},"cost":{"input":0.658,"output":1.11}},"deepseek-ai/deepseek-ocr/models/DeepSeek-OCR":{"id":"deepseek-ai/deepseek-ocr/models/DeepSeek-OCR","name":"DeepSeek OCR","description":"OCR model for extracting structured text from documents and screenshots","family":"deepseek","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-10-20","last_updated":"2026-02-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0.2,"output":0.7}},"mistralai/completion/models/Ministral-3-3B-Reasoning-2512":{"id":"mistralai/completion/models/Ministral-3-3B-Reasoning-2512","name":"Ministral 3 3B Reasoning 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-12","last_updated":"2026-02-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.039,"output":0.54825}},"mistralai/completion/models/Ministral-3-14B-Reasoning-2512":{"id":"mistralai/completion/models/Ministral-3-14B-Reasoning-2512","name":"Ministral 3 14B Reasoning 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-01","last_updated":"2025-12-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":2.5,"output":1.7}},"moonshotai/chat-completion/models/Kimi-K2_6":{"id":"moonshotai/chat-completion/models/Kimi-K2_6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4},"canonical_model_id":"moonshotai/kimi-k2.6"},"arcee_ai/AFM/models/trinity-mini":{"id":"arcee_ai/AFM/models/trinity-mini","name":"Trinity Mini","description":"Reasoning-tuned 26B MoE model with 3B active parameters for agents, tools, and multi-step workloads","family":"trinity","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-12-01","last_updated":"2026-02-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.045,"output":0.15},"canonical_model_id":"arcee-ai/trinity-mini"},"qwen/qwenCoder/models/Qwen3-Coder-30B-A3B-Instruct":{"id":"qwen/qwenCoder/models/Qwen3-Coder-30B-A3B-Instruct","name":"Qwen3 Coder 30B A3B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-31","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.11458,"output":0.74812}},"qwen/qwenLM/models/Qwen3-30B-A3B-Instruct-2507":{"id":"qwen/qwenLM/models/Qwen3-30B-A3B-Instruct-2507","name":"Qwen3 30B A3B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-30","last_updated":"2026-02-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.3,"output":0.5}},"qwen/qwenLM/models/Qwen3-30B-A3B-Thinking-2507":{"id":"qwen/qwenLM/models/Qwen3-30B-A3B-Thinking-2507","name":"Qwen3 30B A3B Thinking 2507","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-31","last_updated":"2026-02-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.36,"output":1.3}},"openai/chat-completion/models/gpt-oss-120b-high-throughput":{"id":"openai/chat-completion/models/gpt-oss-120b-high-throughput","name":"GPT OSS 120B High Throughput","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2026-02-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.09,"output":0.36}},"openai/chat-completion/models/gpt-oss-20b":{"id":"openai/chat-completion/models/gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-12-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.045,"output":0.18}}}},"aiand":{"id":"aiand","env":["AIAND_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.aiand.com/v1","name":"ai&","doc":"https://docs.aiand.com/","models":{"motif-technologies/motif-3":{"id":"motif-technologies/motif-3","name":"Motif 3","description":"Motif 3 is a large-scale, decoder-only Mixture-of-Experts (MoE) language model with 314 billion total parameters and 13.2 billion parameters activated per token.","family":"motif","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-08-07","last_updated":"2026-08-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":2,"cache_read":0.2},"canonical_model_id":"motif-technologies/motif-3"},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"google/gemma-4-31b-it"},"deepseek-ai/deepseek-v4.1-flash":{"id":"deepseek-ai/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.3,"output":0.6,"cache_read":0.02},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek-ai/deepseek-v4-pro":{"id":"deepseek-ai/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":1,"output":2.5,"cache_read":0.25},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek-ai/deepseek-v4-flash":{"id":"deepseek-ai/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.15,"output":0.25,"cache_read":0.08},"canonical_model_id":"deepseek/deepseek-v4-flash"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":12.5,"cache_read":0.5},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.75,"output":3.5,"cache_read":0.2},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"zai-org/glm-5.3-flash":{"id":"zai-org/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1048550,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/glm-5.2":{"id":"zai-org/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1,"output":4,"cache_read":0.3},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/glm-5.3":{"id":"zai-org/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1,"output":4,"cache_read":0.3},"canonical_model_id":"zhipuai/glm-5.3"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.4,"output":3,"cache_read":0.2},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3.6-27b":{"id":"qwen/qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.32,"output":3.2,"cache_read":0.2},"canonical_model_id":"alibaba/qwen3.6-27b"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6,"cache_read":0.08},"canonical_model_id":"openai/gpt-oss-120b"}}},"frogbot":{"id":"frogbot","env":["FROGBOT_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://app.frogbot.ai/api/v1","name":"FrogBot","doc":"https://docs.frogbot.ai","models":{"grok-4-1-fast-reasoning":{"id":"grok-4-1-fast-reasoning","name":"Grok 4.1 Fast (Reasoning)","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-11","release_date":"2025-11-25","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":128000},"cost":{"input":0.2,"output":0.5,"cache_read":0.05}},"gpt-5-4-mini":{"id":"gpt-5-4-mini","name":"GPT-5.4 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075}},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25}},"grok-4-1-fast-non-reasoning":{"id":"grok-4-1-fast-non-reasoning","name":"Grok 4.1 Fast (Non-Reasoning)","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-11","release_date":"2025-11-25","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":128000},"cost":{"input":0.2,"output":0.5,"cache_read":0.05}},"gpt-4o":{"id":"gpt-4o","name":"GPT-4o","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25}},"minimax-m2-5":{"id":"minimax-m2-5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2025-01-15","last_updated":"2025-02-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":192000,"output":8192},"cost":{"input":0.3,"output":1.2,"cache_read":0.03}},"gpt-5-4-nano":{"id":"gpt-5-4-nano","name":"GPT-5.4 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02}},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi-K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"1970-01-01","last_updated":"1970-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.6,"output":3,"cache_read":0.1}},"gpt-oss-20b":{"id":"gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"1970-01-01","last_updated":"1970-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.07,"output":0.2}},"gemini-2.5-pro":{"id":"gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-03-20","last_updated":"2025-06-05","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.31}},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-07-17","last_updated":"2025-07-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.075}},"minimax-m2-7":{"id":"minimax-m2-7","name":"MiniMax-M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":192000,"output":8192},"cost":{"input":0.3,"output":1.2,"cache_read":0.06}},"kimi-k2-6":{"id":"kimi-k2-6","name":"Kimi-K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"1970-01-01","last_updated":"1970-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.95,"output":4,"cache_read":0.16}},"grok-code-fast-1":{"id":"grok-code-fast-1","name":"Grok 4.1 Fast (Reasoning)","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2023-10","release_date":"2025-08-28","last_updated":"2025-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.2,"output":1.5,"cache_read":0.02}},"qwen-3-6-plus":{"id":"qwen-3-6-plus","name":"Qwen 3.6 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-03","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.5,"output":3,"cache_read":0.1}},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"grok-4-3":{"id":"grok-4-3","name":"Grok 4.3","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11","release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2}},"gpt-5-5":{"id":"gpt-5-5","name":"GPT-5.5","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":272000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25}},"gemini-3-flash-preview":{"id":"gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05}},"gemini-3-1-pro-preview":{"id":"gemini-3-1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01","release_date":"2026-02-18","last_updated":"2026-02-18","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":2,"output":12,"cache_read":0.2}},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek v4 Pro","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2026-01","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":1.74,"output":3.48,"cache_read":0.14}},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-02-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75}},"gpt-5-3-codex":{"id":"gpt-5-3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"1970-01-01","last_updated":"1970-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6}},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"zai-glm-5-1":{"id":"zai-glm-5-1","name":"Z.AI GLM-5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-01-20","last_updated":"2025-02-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":198000,"output":8192},"cost":{"input":1.4,"output":4.4,"cache_read":0.26}}}},"stackit":{"id":"stackit","env":["STACKIT_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.openai-compat.model-serving.eu01.onstackit.cloud/v1","name":"STACKIT","doc":"https://docs.stackit.cloud/products/data-and-ai/ai-model-serving/basics/available-shared-models","models":{"google/gemma-3-27b-it":{"id":"google/gemma-3-27b-it","name":"Gemma 3 27B","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-05-17","last_updated":"2025-05-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":37000,"output":4096},"cost":{"input":0.53,"output":0.76}},"intfloat/e5-mistral-7b-instruct":{"id":"intfloat/e5-mistral-7b-instruct","name":"E5 Mistral 7B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"mistral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2023-12-11","last_updated":"2023-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":4096},"cost":{"input":0.02,"output":0.02}},"Qwen/Qwen3-VL-235B-A22B-Instruct-FP8":{"id":"Qwen/Qwen3-VL-235B-A22B-Instruct-FP8","name":"Qwen3-VL 235B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2024-11-01","last_updated":"2024-11-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":218000,"output":16384},"cost":{"input":1.76,"output":2.05}},"Qwen/Qwen3-VL-Embedding-8B":{"id":"Qwen/Qwen3-VL-Embedding-8B","name":"Qwen3-VL Embedding 8B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":4096},"cost":{"input":0.09,"output":0.09}},"Qwen/Qwen3.6-27B":{"id":"Qwen/Qwen3.6-27B","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.53,"output":0.76},"canonical_model_id":"alibaba/qwen3.6-27b"},"cortecs/Llama-3.3-70B-Instruct-FP8-Dynamic":{"id":"cortecs/Llama-3.3-70B-Instruct-FP8-Dynamic","name":"Llama 3.3 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.53,"output":0.76}},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.18,"output":0.29},"canonical_model_id":"openai/gpt-oss-20b"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":8192},"cost":{"input":0.53,"output":0.76},"canonical_model_id":"openai/gpt-oss-120b"}}},"anyapi":{"id":"anyapi","env":["ANYAPI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.anyapi.ai/v1","name":"AnyAPI","doc":"https://docs.anyapi.ai","models":{"anthropic/claude-haiku-4-5":{"id":"anthropic/claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-sonnet-4-5":{"id":"anthropic/claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-opus-4-6":{"id":"anthropic/claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024,"max":127999}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":30,"output":150,"cache_read":3,"cache_write":37.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-sonnet-4-6":{"id":"anthropic/claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-4-7":{"id":"anthropic/claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":30,"output":150,"cache_read":3,"cache_write":37.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"canonical_model_id":"anthropic/claude-opus-4-7"},"cohere/command-r-plus-08-2024":{"id":"cohere/command-r-plus-08-2024","name":"Command R+","description":"Cohere's RAG workhorse for long-context enterprise search and tool use","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"canonical_model_id":"cohere/command-r-plus-08-2024"},"deepseek/deepseek-chat":{"id":"deepseek/deepseek-chat","name":"DeepSeek Chat","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-12-01","last_updated":"2026-02-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"canonical_model_id":"deepseek/deepseek-chat"},"deepseek/deepseek-r1":{"id":"deepseek/deepseek-r1","name":"DeepSeek Reasoner","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-09","release_date":"2025-12-01","last_updated":"2026-02-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"canonical_model_id":"deepseek/deepseek-reasoner"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"canonical_model_id":"deepseek/deepseek-v4-flash"},"perplexity/sonar-pro":{"id":"perplexity/sonar-pro","name":"Sonar Pro","description":"Deeper Sonar search model with broader retrieval and stronger synthesis","family":"sonar-pro","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"canonical_model_id":"perplexity/sonar-pro"},"perplexity/sonar-reasoning-pro":{"id":"perplexity/sonar-reasoning-pro","name":"Sonar Reasoning Pro","description":"Web-grounded Sonar for multi-step research questions that need cited reasoning","family":"sonar-reasoning","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"canonical_model_id":"perplexity/sonar-reasoning-pro"},"google/gemini-3-pro-preview":{"id":"google/gemini-3-pro-preview","name":"Gemini 3 Pro Preview","description":"Preview Gemini flagship for complex reasoning, coding, and rich multimodal prompts","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"canonical_model_id":"google/gemini-3-pro-preview"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"canonical_model_id":"google/gemini-2.5-pro"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"canonical_model_id":"google/gemini-2.5-flash"},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"canonical_model_id":"google/gemini-2.5-flash-lite"},"xai/grok-4.3":{"id":"xai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"canonical_model_id":"xai/grok-4.3"},"mistralai/devstral-2512":{"id":"mistralai/devstral-2512","name":"Devstral 2","description":"Mistral's coding-agent model for repository work, terminal tasks, and software fixes","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","canonical_model_id":"mistral/devstral-2512"},"mistralai/mistral-large-2512":{"id":"mistralai/mistral-large-2512","name":"Mistral Large 3","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"canonical_model_id":"mistral/mistral-large-2512"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":5,"output":30,"cache_read":0.5},"provider":{"body":{"service_tier":"priority"}}}}},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"canonical_model_id":"openai/gpt-5-mini"},"openai/o4-mini":{"id":"openai/o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"canonical_model_id":"openai/o4-mini"},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"canonical_model_id":"openai/o3-mini"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/o3":{"id":"openai/o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"canonical_model_id":"openai/o3"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"canonical_model_id":"openai/gpt-5"}}},"crusoe":{"id":"crusoe","env":["CRUSOE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.inference.crusoecloud.com/v1","name":"Crusoe","doc":"https://docs.crusoecloud.com/managed-inference/overview","models":{"zai/GLM-5.1":{"id":"zai/GLM-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4.4,"cache_read":0.25},"canonical_model_id":"zhipuai/glm-5.1"},"zai/GLM-5.2":{"id":"zai/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"meta-llama/Llama-3.3-70B-Instruct":{"id":"meta-llama/Llama-3.3-70B-Instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.25,"output":0.75,"cache_read":0.13},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.14,"output":0.4,"cache_read":0.14},"canonical_model_id":"google/gemma-4-31b-it"},"Qwen/Qwen3-235B-A22B-Instruct-2507":{"id":"Qwen/Qwen3-235B-A22B-Instruct-2507","name":"Qwen3 235B-A22B Instruct 2507","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.22,"output":0.8,"cache_read":0.11},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"deepseek-ai/DeepSeek-V3-0324":{"id":"deepseek-ai/DeepSeek-V3-0324","name":"DeepSeek V3 0324","description":"March 2025 checkpoint of DeepSeek-V3 with improved reasoning and coding","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-03-24","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":163840},"cost":{"input":0.5,"output":1.5,"cache_read":0.25},"canonical_model_id":"deepseek/deepseek-v3-0324"},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.7,"output":3.5,"cache_read":0.35},"canonical_model_id":"moonshotai/kimi-k2.6"},"nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B":{"id":"nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B","name":"Nemotron 3 Nano 30B A3B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.05,"output":0.2,"cache_read":0.03},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"nvidia/Nemotron-3-Nano-Omni-Reasoning-30B-A3B":{"id":"nvidia/Nemotron-3-Nano-Omni-Reasoning-30B-A3B","name":"Nemotron 3 Nano Omni 30B A3B Reasoning","description":"Open Nemotron omni model combining reasoning with text, vision, and audio","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0.3,"output":1.83,"cache_read":0.3,"input_audio":0.5},"canonical_model_id":"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning"},"nvidia/NVIDIA-Nemotron-3-Super-120B-A12B":{"id":"nvidia/NVIDIA-Nemotron-3-Super-120B-A12B","name":"Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.3,"output":2.4,"cache_read":0.15},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.05,"output":0.2,"cache_read":0.05},"canonical_model_id":"openai/gpt-oss-120b"}}},"volcengine-coding-plan":{"id":"volcengine-coding-plan","env":["ARK_CODING_PLAN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://ark.cn-beijing.volces.com/api/coding/v3","name":"Volcengine Ark Coding Plan","doc":"https://www.volcengine.com/docs/82379/1928261","models":{"doubao-seed-2.0-lite":{"id":"doubao-seed-2.0-lite","name":"Seed 2.0 Lite","description":"Cost-efficient ByteDance Seed 2.0 model for production chat, analysis, and structured generation","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"moonshotai/kimi-k3"},"doubao-seed-2.1-turbo":{"id":"doubao-seed-2.1-turbo","name":"Seed 2.1 Turbo","description":"Faster ByteDance Seed 2.1 model for multimodal reasoning and latency-sensitive agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"bytedance-seed/seed-2.1-turbo"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"minimax/MiniMax-M3"},"doubao-seed-evolving":{"id":"doubao-seed-evolving","name":"Seed Evolving","description":"Rolling ByteDance Seed model for rapidly updated reasoning, coding, and agent capabilities","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"bytedance-seed/seed-evolving"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4-pro"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-5.3"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4-flash"}}},"jiekou":{"id":"jiekou","env":["JIEKOU_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.jiekou.ai/openai","name":"Jiekou.AI","doc":"https://docs.jiekou.ai/docs/support/quickstart?utm_source=github_models.dev","models":{"grok-4-1-fast-reasoning":{"id":"grok-4-1-fast-reasoning","name":"grok-4-1-fast-reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":0.18,"output":0.45}},"grok-4-1-fast-non-reasoning":{"id":"grok-4-1-fast-non-reasoning","name":"grok-4-1-fast-non-reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":0.18,"output":0.45}},"gpt-5.2-codex":{"id":"gpt-5.2-codex","name":"gpt-5.2-codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.75,"output":14}},"gpt-5.1-codex":{"id":"gpt-5.1-codex","name":"gpt-5.1-codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.125,"output":9}},"gemini-3-pro-preview":{"id":"gemini-3-pro-preview","name":"gemini-3-pro-preview","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.8,"output":10.8}},"gpt-5-codex":{"id":"gpt-5-codex","name":"gpt-5-codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.125,"output":9}},"gpt-5-mini":{"id":"gpt-5-mini","name":"gpt-5-mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.225,"output":1.8}},"gpt-5.2-pro":{"id":"gpt-5.2-pro","name":"gpt-5.2-pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":18.9,"output":151.2}},"o4-mini":{"id":"o4-mini","name":"o4-mini","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4}},"o3-mini":{"id":"o3-mini","name":"o3-mini","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":131072},"cost":{"input":1.1,"output":4.4}},"grok-4-fast-reasoning":{"id":"grok-4-fast-reasoning","name":"grok-4-fast-reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":0.18,"output":0.45}},"gpt-5-nano":{"id":"gpt-5-nano","name":"gpt-5-nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.045,"output":0.36}},"gemini-2.5-flash-lite-preview-06-17":{"id":"gemini-2.5-flash-lite-preview-06-17","name":"gemini-2.5-flash-lite-preview-06-17","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","video","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.09,"output":0.36}},"claude-opus-4-20250514":{"id":"claude-opus-4-20250514","name":"claude-opus-4-20250514","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":13.5,"output":67.5}},"grok-4-fast-non-reasoning":{"id":"grok-4-fast-non-reasoning","name":"grok-4-fast-non-reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":0.18,"output":0.45}},"claude-opus-4-1-20250805":{"id":"claude-opus-4-1-20250805","name":"claude-opus-4-1-20250805","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":13.5,"output":67.5}},"gpt-5-pro":{"id":"gpt-5-pro","name":"gpt-5-pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":272000},"cost":{"input":13.5,"output":108}},"gpt-5-chat-latest":{"id":"gpt-5-chat-latest","name":"gpt-5-chat-latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.125,"output":9}},"claude-opus-4-5-20251101":{"id":"claude-opus-4-5-20251101","name":"claude-opus-4-5-20251101","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":65536},"cost":{"input":4.5,"output":22.5}},"gpt-5.1":{"id":"gpt-5.1","name":"gpt-5.1","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02","last_updated":"2026-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.125,"output":9}},"gemini-2.5-pro":{"id":"gemini-2.5-pro","name":"gemini-2.5-pro","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":1.125,"output":9}},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"gemini-2.5-flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.27,"output":2.25}},"gemini-2.5-flash-preview-05-20":{"id":"gemini-2.5-flash-preview-05-20","name":"gemini-2.5-flash-preview-05-20","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":200000},"cost":{"input":0.135,"output":3.15}},"gpt-5.1-codex-max":{"id":"gpt-5.1-codex-max","name":"gpt-5.1-codex-max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.125,"output":9}},"gpt-5.2":{"id":"gpt-5.2","name":"gpt-5.2","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.575,"output":12.6}},"grok-code-fast-1":{"id":"grok-code-fast-1","name":"grok-code-fast-1","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.18,"output":1.35}},"claude-sonnet-4-5-20250929":{"id":"claude-sonnet-4-5-20250929","name":"claude-sonnet-4-5-20250929","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":2.7,"output":13.5}},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"claude-opus-4-6","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024,"max":127999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02","last_updated":"2026-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25}},"gemini-3-flash-preview":{"id":"gemini-3-flash-preview","name":"gemini-3-flash-preview","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3}},"claude-haiku-4-5-20251001":{"id":"claude-haiku-4-5-20251001","name":"claude-haiku-4-5-20251001","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":20000,"output":64000},"cost":{"input":0.9,"output":4.5}},"gemini-2.5-flash-lite-preview-09-2025":{"id":"gemini-2.5-flash-lite-preview-09-2025","name":"gemini-2.5-flash-lite-preview-09-2025","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.09,"output":0.36}},"gemini-2.5-pro-preview-06-05":{"id":"gemini-2.5-pro-preview-06-05","name":"gemini-2.5-pro-preview-06-05","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":200000},"cost":{"input":1.125,"output":9}},"gemini-2.5-flash-lite":{"id":"gemini-2.5-flash-lite","name":"gemini-2.5-flash-lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.09,"output":0.36}},"claude-sonnet-4-20250514":{"id":"claude-sonnet-4-20250514","name":"claude-sonnet-4-20250514","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":2.7,"output":13.5}},"gpt-5.1-codex-mini":{"id":"gpt-5.1-codex-mini","name":"gpt-5.1-codex-mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.225,"output":1.8}},"o3":{"id":"o3","name":"o3","description":"O-series reasoning model for hard analysis, math, coding, and planning","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":131072},"cost":{"input":10,"output":40}},"grok-4-0709":{"id":"grok-4-0709","name":"grok-4-0709","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":8192},"cost":{"input":2.7,"output":13.5}},"deepseek/deepseek-v3-0324":{"id":"deepseek/deepseek-v3-0324","name":"DeepSeek V3 0324","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":163840},"cost":{"input":0.28,"output":1.14}},"deepseek/deepseek-v3.1":{"id":"deepseek/deepseek-v3.1","name":"DeepSeek V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":32767}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":32768},"cost":{"input":0.27,"output":1}},"deepseek/deepseek-r1-0528":{"id":"deepseek/deepseek-r1-0528","name":"DeepSeek R1 0528","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":32768},"cost":{"input":0.7,"output":2.5}},"xiaomimimo/mimo-v2-flash":{"id":"xiaomimimo/mimo-v2-flash","name":"XiaomiMiMo/MiMo-V2-Flash","description":"MiMo flash model for fast multimodal assistance and agent workflows","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0,"output":0}},"baidu/ernie-4.5-vl-424b-a47b":{"id":"baidu/ernie-4.5-vl-424b-a47b","name":"ERNIE 4.5 VL 424B A47B","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ernie","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":123000,"output":16000},"cost":{"input":0.42,"output":1.25}},"baidu/ernie-4.5-300b-a47b-paddle":{"id":"baidu/ernie-4.5-300b-a47b-paddle","name":"ERNIE 4.5 300B A47B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","family":"ernie","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":123000,"output":12000},"cost":{"input":0.28,"output":1.1}},"minimaxai/minimax-m1-80k":{"id":"minimaxai/minimax-m1-80k","name":"MiniMax M1","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":40000},"cost":{"input":0.55,"output":2.2}},"moonshotai/kimi-k2.5":{"id":"moonshotai/kimi-k2.5","name":"Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":262143}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":3}},"moonshotai/kimi-k2-instruct":{"id":"moonshotai/kimi-k2-instruct","name":"Kimi K2 Instruct","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.57,"output":2.3}},"moonshotai/kimi-k2-0905":{"id":"moonshotai/kimi-k2-0905","name":"Kimi K2 0905","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":2.5}},"zai-org/glm-4.5":{"id":"zai-org/glm-4.5","name":"GLM-4.5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.6,"output":2.2}},"zai-org/glm-4.5v":{"id":"zai-org/glm-4.5v","name":"GLM 4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glmv","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":16384},"cost":{"input":0.6,"output":1.8}},"zai-org/glm-4.7-flash":{"id":"zai-org/glm-4.7-flash","name":"GLM-4.7-Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.07,"output":0.4}},"zai-org/glm-4.7":{"id":"zai-org/glm-4.7","name":"GLM-4.7","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2}},"minimax/minimax-m2.1":{"id":"minimax/minimax-m2.1","name":"Minimax M2.1","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":131071}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2}},"qwen/qwen3-235b-a22b-instruct-2507":{"id":"qwen/qwen3-235b-a22b-instruct-2507","name":"Qwen3 235B A22B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.15,"output":0.8}},"qwen/qwen3-next-80b-a3b-thinking":{"id":"qwen/qwen3-next-80b-a3b-thinking","name":"Qwen3 Next 80B A3B Thinking","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.15,"output":1.5}},"qwen/qwen3-coder-next":{"id":"qwen/qwen3-coder-next","name":"qwen/qwen3-coder-next","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02","last_updated":"2026-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.2,"output":1.5}},"qwen/qwen3-235b-a22b-fp8":{"id":"qwen/qwen3-235b-a22b-fp8","name":"Qwen3 235B A22B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":20000},"cost":{"input":0.2,"output":0.8}},"qwen/qwen3-coder-480b-a35b-instruct":{"id":"qwen/qwen3-coder-480b-a35b-instruct","name":"Qwen3 Coder 480B A35B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.29,"output":1.2}},"qwen/qwen3-235b-a22b-thinking-2507":{"id":"qwen/qwen3-235b-a22b-thinking-2507","name":"Qwen3 235B A22b Thinking 2507","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.3,"output":3}},"qwen/qwen3-30b-a3b-fp8":{"id":"qwen/qwen3-30b-a3b-fp8","name":"Qwen3 30B A3B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":20000},"cost":{"input":0.09,"output":0.45}},"qwen/qwen3-next-80b-a3b-instruct":{"id":"qwen/qwen3-next-80b-a3b-instruct","name":"Qwen3 Next 80B A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.15,"output":1.5}},"qwen/qwen3-32b-fp8":{"id":"qwen/qwen3-32b-fp8","name":"Qwen3 32B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":20000},"cost":{"input":0.1,"output":0.45}}}},"ollama-cloud":{"id":"ollama-cloud","env":["OLLAMA_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://ollama.com/v1","name":"Ollama Cloud","doc":"https://docs.ollama.com/cloud","models":{"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"nemotron-3-ultra":{"id":"nemotron-3-ultra","name":"nemotron-3-ultra","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":128000},"cost":{"input":0.1,"output":3,"cache_read":0.1},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"kimi-k3":{"id":"kimi-k3","name":"kimi-k3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"mistral-large-4":{"id":"mistral-large-4","name":"Mistral Large 4","description":"Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":262144},"cost":{"input":1.36,"output":4.18,"cache_read":0.14},"canonical_model_id":"mistral/mistral-large-4"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"minimax-m2.5":{"id":"minimax-m2.5","name":"minimax-m2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"knowledge":"2025-01","release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072}},"kimi-k2.6":{"id":"kimi-k2.6","name":"kimi-k2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16}},"qwen3.5:397b":{"id":"qwen3.5:397b","name":"qwen3.5:397b","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"release_date":"2026-02-15","last_updated":"2026-02-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.6,"output":3.6}},"gpt-oss:20b":{"id":"gpt-oss:20b","name":"gpt-oss:20b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"release_date":"2025-08-05","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.07,"output":0.3,"cache_read":0.035}},"gpt-oss:120b":{"id":"gpt-oss:120b","name":"gpt-oss:120b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"release_date":"2025-08-05","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6,"cache_read":0.014}},"nemotron-3-nano:30b":{"id":"nemotron-3-nano:30b","name":"nemotron-3-nano:30b","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-12-15","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.06,"output":0.24},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"kimi-k2.5":{"id":"kimi-k2.5","name":"kimi-k2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144}},"mistral-large-3:675b":{"id":"mistral-large-3:675b","name":"mistral-large-3:675b","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"release_date":"2025-12-02","last_updated":"2026-01-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":1.5}},"minimax-m2.7":{"id":"minimax-m2.7","name":"minimax-m2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":196608},"cost":{"input":0.3,"output":1.2,"cache_read":0.06}},"deepseek-v4-pro:0813":{"id":"deepseek-v4-pro:0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.66,"output":1.98,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"minimax-m3":{"id":"minimax-m3","name":"minimax-m3","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax-m3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-31","last_updated":"2026-05-31","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.12}},"deepseek-v4-flash:0731":{"id":"deepseek-v4-flash:0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.22,"output":0.66,"cache_read":0.007},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"gemma4:31b":{"id":"gemma4:31b","name":"gemma4:31b","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.14,"output":0.4,"cache_read":0.05}},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":976000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.1":{"id":"glm-5.1","name":"glm-5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"release_date":"2026-03-27","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2}},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"deepseek-v4-pro","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.66,"output":1.98,"cache_read":0.022}},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"kimi-k2.7-code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"nemotron-3-super":{"id":"nemotron-3-super","name":"nemotron-3-super","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.015,"output":0.6,"cache_read":0.015},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"muse-spark-open":{"id":"muse-spark-open","name":"Muse Spark Open","description":"Muse Spark Open is an 816B total / 42B active open-weight multimodal reasoning model from Meta for coding and long-horizon agentic work, with 1M-token context.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-open"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"deepseek-v4-flash","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.22,"output":0.66,"cache_read":0.007}}}},"agentrouter":{"id":"agentrouter","env":["AGENTROUTER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://agentrouter.org/v1","name":"AgentRouter","doc":"https://agentrouter.org/docs/opencode.html","models":{"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://agentrouter.org/v1"},"canonical_model_id":"anthropic/claude-opus-5"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://agentrouter.org/v1"},"canonical_model_id":"anthropic/claude-opus-4-8"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"canonical_model_id":"zhipuai/glm-5.3"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"canonical_model_id":"openai/gpt-5.6-sol"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"canonical_model_id":"deepseek/deepseek-v4-flash"}}},"tencent-tokenhub":{"id":"tencent-tokenhub","env":["TENCENT_TOKENHUB_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://tokenhub.tencentmaas.com/v1","name":"Tencent TokenHub","doc":"https://cloud.tencent.com/document/product/1823/130050","models":{"hy3-preview":{"id":"hy3-preview","name":"Hy3 preview","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"tencent/hy3-preview"},"hy3":{"id":"hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":192000,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"tencent/hy3"},"hy4-preview":{"id":"hy4-preview","name":"Hy4 preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":64000},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"}}},"watsonx":{"id":"watsonx","env":["WATSONX_AI_APIKEY","WATSONX_AI_PROJECT_ID"],"npm":"watsonx-ai-provider","name":"watsonx.ai","doc":"https://www.ibm.com/docs/en/watsonx/saas?topic=solutions-supported-foundation-models","models":{"meta-llama/llama-4-maverick-17b-128e-instruct-fp8":{"id":"meta-llama/llama-4-maverick-17b-128e-instruct-fp8","name":"Llama 4 Maverick 17B 128E Instruct FP8","description":"Open multimodal Llama for strong reasoning with efficient everyday serving","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.371,"output":1.484},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"meta-llama/llama-3-3-70b-instruct":{"id":"meta-llama/llama-3-3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":4096},"cost":{"input":0.7526,"output":0.7526},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"ibm/granite-4-h-small":{"id":"ibm/granite-4-h-small","name":"Granite-4.0-H-Small","description":"Open-weight hybrid model for enterprise chat, coding, retrieval-augmented generation, and tool-calling workloads","family":"granite","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-02","last_updated":"2025-10-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.0636,"output":0.265},"canonical_model_id":"ibm/granite-4-h-small"},"mistralai/mistral-small-3-1-24b-instruct-2503":{"id":"mistralai/mistral-small-3-1-24b-instruct-2503","name":"Mistral Small 3.1 24B","description":"Efficient multimodal model for instruction following, coding, reasoning, and function calling","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-03-17","last_updated":"2025-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.106,"output":0.318},"canonical_model_id":"mistral/mistral-small-3-1-24b-instruct-2503"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.159,"output":0.636},"canonical_model_id":"openai/gpt-oss-120b"}}},"ambient":{"id":"ambient","env":["AMBIENT_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.ambient.xyz/v1","name":"Ambient","doc":"https://ambient.xyz","models":{"unsloth/qwen3.8-27b-gguf":{"id":"unsloth/qwen3.8-27b-gguf","name":"qwen3.8-27b-4q","description":"Tool-capable chat model for instruction following and agentic application workflows","family":"unsloth","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":101072,"output":101072},"cost":{"input":0.001,"output":0.001,"cache_read":0,"cache_write":0}},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.08,"output":0.18,"cache_read":0.016,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.14,"output":0.28,"cache_read":0.028,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4-flash"},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM-5.2","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":202752},"cost":{"input":0.6,"output":2,"cache_read":0.15,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"ambient/small":{"id":"ambient/small","name":"Ambient Small","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":101072,"output":101072},"cost":{"input":0.001,"output":0.001,"cache_read":0,"cache_write":0}},"ambient/large":{"id":"ambient/large","name":"Ambient Large","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":202752},"cost":{"input":0.6,"output":2,"cache_read":0.15,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.2,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.69,"output":3.49,"cache_read":0.14,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"zai-org/GLM-5.2-FP8":{"id":"zai-org/GLM-5.2-FP8","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":202752},"cost":{"input":1.2,"output":4.2,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-5.1-FP8":{"id":"zai-org/GLM-5.1-FP8","name":"GLM 5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.1"},"xiaomi/mimo-v2.5":{"id":"xiaomi/mimo-v2.5","name":"MiMo-V2.5","description":"MiMo omni model for text, image, video, audio, and agents","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.4,"output":2,"cache_read":0.08,"cache_write":0},"canonical_model_id":"xiaomi/mimo-v2.5"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.23,"output":0.96,"cache_read":0.05,"cache_write":0},"canonical_model_id":"minimax/MiniMax-M3"},"stepfun/step-3.7-flash":{"id":"stepfun/step-3.7-flash","name":"Step 3.7 Flash","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.19,"output":1.14,"cache_read":0.03,"cache_write":0},"canonical_model_id":"stepfun/step-3.7-flash"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0.32,"output":3.2,"cache_read":0.16,"cache_write":0},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3.6-35b-a3b":{"id":"qwen/qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.15,"output":1,"cache_read":0.15,"cache_write":0},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"qwen/qwen3-30b-a3b-instruct-2507":{"id":"qwen/qwen3-30b-a3b-instruct-2507","name":"Qwen3 30B A3B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-09","last_updated":"2026-10-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.09,"output":0.3,"cache_read":0.09,"cache_write":0}},"qwen/qwen3.6-27b":{"id":"qwen/qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0.32,"output":3.2,"cache_read":0.16,"cache_write":0},"canonical_model_id":"alibaba/qwen3.6-27b"}}},"model-oracle-ai":{"id":"model-oracle-ai","env":["MODEL_ORACLE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.modeloracle.com/api/v1","name":"Model Oracle AI","doc":"https://modeloracle.com/setup/","models":{"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"canonical_model_id":"openai/gpt-5.4"},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"canonical_model_id":"openai/gpt-5.4-nano"},"o4-mini":{"id":"o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"canonical_model_id":"openai/o4-mini"},"claude-opus-4.8":{"id":"claude-opus-4.8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"canonical_model_id":"anthropic/claude-opus-4-8"},"claude-haiku-4.5":{"id":"claude-haiku-4.5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"canonical_model_id":"anthropic/claude-haiku-4-5"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"canonical_model_id":"anthropic/claude-fable-5"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"canonical_model_id":"openai/gpt-5.4-mini"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"canonical_model_id":"openai/gpt-5.5"},"gpt-4.1":{"id":"gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"canonical_model_id":"openai/gpt-4.1"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"canonical_model_id":"anthropic/claude-sonnet-5"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"canonical_model_id":"zhipuai/glm-5.2"},"gpt-4.1-mini":{"id":"gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"canonical_model_id":"openai/gpt-4.1-mini"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"canonical_model_id":"deepseek/deepseek-v4-pro"},"gpt-5":{"id":"gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"canonical_model_id":"openai/gpt-5"},"auto":{"id":"auto","name":"Auto","description":"Model Oracle AI decision engine that selects and routes among configured coding-agent models","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-29","last_updated":"2026-07-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000}}}},"xai":{"id":"xai","env":["XAI_API_KEY"],"npm":"@ai-sdk/xai","name":"xAI","doc":"https://docs.x.ai/docs/models","models":{"grok-4.7":{"id":"grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"grok-imagine-video-1.5-lite":{"id":"grok-imagine-video-1.5-lite","name":"Grok Imagine Video 1.5 Lite","description":"Cost-efficient video model for text-to-video and image-to-video generation","family":"grok","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-01","last_updated":"2026-10-01","modalities":{"input":["text","image","pdf"],"output":["video"]},"open_weights":false,"limit":{"context":1024,"output":0},"canonical_model_id":"xai/grok-imagine-video-1.5-lite"},"grok-imagine-image":{"id":"grok-imagine-image","name":"Grok Imagine Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"grok","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-01-28","last_updated":"2026-01-28","modalities":{"input":["text","image","pdf"],"output":["image","pdf"]},"open_weights":false,"limit":{"context":16000,"output":0},"canonical_model_id":"xai/grok-imagine-image"},"grok-imagine-video":{"id":"grok-imagine-video","name":"Grok Imagine Video","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"grok","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-01-28","last_updated":"2026-01-28","modalities":{"input":["text","image","video","pdf"],"output":["video"]},"open_weights":false,"limit":{"context":1024,"output":0}},"grok-4.3":{"id":"grok-4.3","name":"Grok 4.3","description":"xAI's Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"grok-4.20-0309-reasoning":{"id":"grok-4.20-0309-reasoning","name":"Grok 4.20 (Reasoning)","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"grok-imagine-video-1.5":{"id":"grok-imagine-video-1.5","name":"Grok Imagine Video 1.5","description":"Video model for image-to-video generation, editing, and extension workflows","family":"grok","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-05-30","last_updated":"2026-05-30","modalities":{"input":["text","image","audio","pdf"],"output":["video"]},"open_weights":false,"limit":{"context":1024,"output":0},"canonical_model_id":"xai/grok-imagine-video-1.5"},"grok-4.5":{"id":"grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.3,"tiers":[{"input":4,"output":12,"cache_read":0.6,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":0.6}},"canonical_model_id":"xai/grok-4.5"},"grok-4.20-0309-non-reasoning":{"id":"grok-4.20-0309-non-reasoning","name":"Grok 4.20 (Non-Reasoning)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"grok-imagine-image-quality":{"id":"grok-imagine-image-quality","name":"Grok Imagine Image Quality","description":"Higher-fidelity Grok Imagine image model for prompt-driven generation, editing, and visual design workflows","family":"grok","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-03","last_updated":"2026-04-03","modalities":{"input":["text","image","pdf"],"output":["image","pdf"]},"open_weights":false,"limit":{"context":16000,"output":0},"canonical_model_id":"xai/grok-imagine-image-quality"},"grok-build-0.1":{"id":"grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.2,"tiers":[{"input":2,"output":4,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2,"output":4,"cache_read":0.4}}},"grok-4.20-multi-agent-0309":{"id":"grok-4.20-multi-agent-0309","name":"Grok 4.20 Multi-Agent","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"grok-4.6":{"id":"grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"}}},"nebius":{"id":"nebius","env":["NEBIUS_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.tokenfactory.nebius.com/v1","name":"Nebius Token Factory","doc":"https://docs.tokenfactory.nebius.com/","models":{"meta-models/muse-spark-open":{"id":"meta-models/muse-spark-open","name":"Muse Spark Open","description":"Muse Spark Open is an 816B total / 42B active open-weight multimodal reasoning model from Meta for coding and long-horizon agentic work, with 1M-token context.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.25,"output":4.25,"cache_read":1.25},"canonical_model_id":"meta/muse-spark-open"},"google/gemma-3-27b-it":{"id":"google/gemma-3-27b-it","name":"Gemma-3-27b-it","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-10","release_date":"2026-01-20","last_updated":"2026-02-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":110000,"input":100000,"output":8192},"cost":{"input":0.1,"output":0.3,"cache_read":0.01,"cache_write":0.125}},"Qwen/Qwen3.8-27B":{"id":"Qwen/Qwen3.8-27B","name":"Qwen3.8 27B","description":"Dense 27B reasoning model for coding, research, and long-horizon agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.45,"output":3,"cache_read":0.45},"canonical_model_id":"alibaba/qwen3.8-27b"},"Qwen/Qwen3-30B-A3B-Instruct-2507":{"id":"Qwen/Qwen3-30B-A3B-Instruct-2507","name":"Qwen3-30B-A3B-Instruct-2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12","release_date":"2026-01-28","last_updated":"2026-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":8192},"cost":{"input":0.1,"output":0.3,"cache_read":0.01,"cache_write":0.125}},"Qwen/Qwen3-235B-A22B-Instruct-2507":{"id":"Qwen/Qwen3-235B-A22B-Instruct-2507","name":"Qwen3 235B A22B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-07","release_date":"2025-07-25","last_updated":"2025-10-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":8192},"cost":{"input":0.2,"output":0.6}},"Qwen/Qwen3-Embedding-8B":{"id":"Qwen/Qwen3-Embedding-8B","name":"Qwen3-Embedding-8B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2025-10","release_date":"2026-01-10","last_updated":"2026-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"input":40960,"output":0},"cost":{"input":0.01,"output":0}},"Qwen/Qwen3.5-397B-A17B":{"id":"Qwen/Qwen3.5-397B-A17B","name":"Qwen3.5-397B-A17B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07","release_date":"2025-07-15","last_updated":"2026-05-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":250000,"output":8192},"cost":{"input":0.6,"output":3.6,"cache_read":0.06,"cache_write":0.75}},"deepseek-ai/DeepSeek-V4-Flash-0731":{"id":"deepseek-ai/DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":1024000},"cost":{"input":0.14,"output":0.28,"cache_read":0.14},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek-ai/DeepSeek-V4-Pro-0813":{"id":"deepseek-ai/DeepSeek-V4-Pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":979000,"output":979000},"cost":{"input":1.32,"output":3.96,"cache_read":1.32},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek-ai/DeepSeek-V4.1-Flash":{"id":"deepseek-ai/DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048000,"output":1048000},"cost":{"input":0.3,"output":1.2,"cache_read":0.3},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek-ai/DeepSeek-V4-Pro":{"id":"deepseek-ai/DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.75,"output":3.5,"cache_read":0.15},"canonical_model_id":"deepseek/deepseek-v4-pro"},"MiniMaxAI/MiniMax-M3":{"id":"MiniMaxAI/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M3"},"moonshotai/Kimi-K3":{"id":"moonshotai/Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":8000},"cost":{"input":3,"output":15,"cache_read":3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/Kimi-K2.7-Code":{"id":"moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8000},"cost":{"input":0.95,"output":4},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.4,"output":4.4},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-5.3-Flash":{"id":"zai-org/GLM-5.3-Flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":1024000},"cost":{"input":0.15,"output":0.5,"cache_read":0.15},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/GLM-5.3":{"id":"zai-org/GLM-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":1024000},"cost":{"input":1.4,"output":4.4,"cache_read":1.4},"canonical_model_id":"zhipuai/glm-5.3"},"nvidia/Nemotron-3.5-Super-VL":{"id":"nvidia/Nemotron-3.5-Super-VL","name":"Nemotron 3.5 Super VL 120B A12B","description":"NVIDIA vision-language reasoning model for coding, visual understanding, and agentic tool use","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.3,"output":0.9,"cache_read":0.3},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"nvidia/nemotron-3-super-120b-a12b":{"id":"nvidia/nemotron-3-super-120b-a12b","name":"Nemotron-3-Super-120B-A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02","release_date":"2026-03-11","last_updated":"2026-03-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.3,"output":0.9},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"nvidia/Nemotron-3_5-Lightning":{"id":"nvidia/Nemotron-3_5-Lightning","name":"Nemotron 3.5 Lightning 30B A3B","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.06,"output":0.24,"cache_read":0.06},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/Nemotron-3-Ultra-550b-a55b":{"id":"nvidia/Nemotron-3-Ultra-550b-a55b","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1,"output":3,"cache_read":1},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"gpt-oss-120b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-01-10","last_updated":"2026-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":124000,"output":8192},"cost":{"input":0.15,"output":0.6,"reasoning":0.6,"cache_read":0.015,"cache_write":0.18}},"NousResearch/Hermes-4-405B":{"id":"NousResearch/Hermes-4-405B","name":"Hermes-4-405B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-11","release_date":"2026-01-30","last_updated":"2026-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":120000,"output":8192},"cost":{"input":1,"output":3,"reasoning":3,"cache_read":0.1,"cache_write":1.25}}}},"minimax-cn":{"id":"minimax-cn","env":["MINIMAX_API_KEY"],"npm":"@ai-sdk/anthropic","api":"https://api.minimax.cn/anthropic/v1","name":"MiniMax (minimax.cn)","doc":"https://platform.minimaxi.com/docs/guides/quickstart","models":{"MiniMax-M3":{"id":"MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-25","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":512000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"tiers":[{"input":0.6,"output":2.4,"cache_read":0.12,"tier":{"type":"context","size":512000}}],"context_over_200k":{"input":0.6,"output":2.4,"cache_read":0.12}}},"MiniMax-M2.1":{"id":"MiniMax-M2.1","name":"MiniMax-M2.1","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375}},"MiniMax-M2.5":{"id":"MiniMax-M2.5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375}},"MiniMax-M2.7":{"id":"MiniMax-M2.7","name":"MiniMax-M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":0.375}},"MiniMax-M2.7-highspeed":{"id":"MiniMax-M2.7-highspeed","name":"MiniMax-M2.7-highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.06,"cache_write":0.375}},"MiniMax-M2":{"id":"MiniMax-M2","name":"MiniMax-M2","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2}},"MiniMax-M2.5-highspeed":{"id":"MiniMax-M2.5-highspeed","name":"MiniMax-M2.5-highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-13","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.06,"cache_write":0.375}}}},"scaleway":{"id":"scaleway","env":["SCALEWAY_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.scaleway.ai/v1","name":"Scaleway","doc":"https://www.scaleway.com/en/docs/generative-apis/","models":{"qwen3.8-27b":{"id":"qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"status":"beta","cost":{"input":0.684,"output":3.762,"reasoning":3.762,"cache_read":0.137},"canonical_model_id":"alibaba/qwen3.8-27b"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32768},"status":"beta","cost":{"input":0.468,"output":0.936,"reasoning":0.936,"cache_read":0.0936},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"qwen3-235b-a22b-instruct-2507":{"id":"qwen3-235b-a22b-instruct-2507","name":"Qwen3 235B A22B Instruct 2507","description":"Large open Qwen MoE for multilingual reasoning, coding, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-01","last_updated":"2026-03-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":260000,"output":16384},"cost":{"input":0.75,"output":2.25,"reasoning":8.4},"canonical_model_id":"alibaba/qwen3-235b-a22b"},"whisper-large-v3":{"id":"whisper-large-v3","name":"Whisper Large v3","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"whisper","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2023-09","release_date":"2023-09-01","last_updated":"2026-03-17","modalities":{"input":["audio"],"output":["text"]},"open_weights":true,"limit":{"context":0,"output":8192},"cost":{"input":0.003,"output":0}},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32768},"status":"beta","cost":{"input":0.672,"output":2.016,"reasoning":2.016,"cache_read":0.134},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"bge-multilingual-gemma2":{"id":"bge-multilingual-gemma2","name":"BGE Multilingual Gemma2","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-07-26","last_updated":"2025-06-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8191,"output":3072},"cost":{"input":0.1,"output":0}},"qwen3-coder-30b-a3b-instruct":{"id":"qwen3-coder-30b-a3b-instruct","name":"Qwen3-Coder 30B-A3B Instruct","description":"Smaller Qwen coder for efficient local agents and repo-level fixes","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2026-03-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.2,"output":0.8},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"gemma-4-26b-a4b-it":{"id":"gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-01","last_updated":"2026-05-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"status":"beta","cost":{"input":0.25,"output":0.5},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"llama-3.3-70b-instruct":{"id":"llama-3.3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2026-03-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":100000,"output":16384},"cost":{"input":0.9,"output":0.9}},"qwen3.6-35b-a3b":{"id":"qwen3.6-35b-a3b","name":"Qwen3.6 35B A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-05-01","last_updated":"2026-05-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"status":"beta","cost":{"input":0.25,"output":1.5},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"pixtral-12b-2409":{"id":"pixtral-12b-2409","name":"Pixtral 12B 2409","description":"Mistral vision-language model for image understanding and multimodal chat","family":"pixtral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2024-09-25","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.2,"output":0.2},"canonical_model_id":"mistral/pixtral-12b"},"qwen3-embedding-8b":{"id":"qwen3-embedding-8b","name":"Qwen3 Embedding 8B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-05","last_updated":"2026-03-17","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":4096},"cost":{"input":0.1,"output":0}},"mistral-medium-3.5-128b":{"id":"mistral-medium-3.5-128b","name":"Mistral Medium 3.5 128B","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":1.5,"output":7.5},"canonical_model_id":"mistral/mistral-medium-2604"},"qwen3.5-397b-a17b":{"id":"qwen3.5-397b-a17b","name":"Qwen3.5 397B A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":0.6,"output":3.6},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":1.8,"output":5.5},"canonical_model_id":"zhipuai/glm-5.2"},"mistral-small-3.2-24b-instruct-2506":{"id":"mistral-small-3.2-24b-instruct-2506","name":"Mistral Small 3.2 24B Instruct (2506)","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2025-06-20","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.15,"output":0.35},"canonical_model_id":"mistral/mistral-small-2506"},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT-OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2024-01-01","last_updated":"2026-03-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.15,"output":0.6}},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"status":"beta","cost":{"input":2.01,"output":6.15},"canonical_model_id":"zhipuai/glm-5.3"}}},"vercel":{"id":"vercel","env":["AI_GATEWAY_API_KEY"],"npm":"@ai-sdk/gateway","name":"Vercel AI Gateway","doc":"https://github.com/vercel/ai/tree/5eb85cc45a259553501f535b8ac79a77d0e79223/packages/gateway","models":{"voyage/rerank-3-lite":{"id":"voyage/rerank-3-lite","name":"Voyage Rerank 3 Lite","description":"Reranking model for improving retrieval quality in search and recommendation systems","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-09-30","last_updated":"2026-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":32000}},"voyage/voyage-law-2":{"id":"voyage/voyage-law-2","name":"voyage-law-2","description":"General-purpose chat model for instruction following, writing, and analysis","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-04-15","last_updated":"2024-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536}},"voyage/rerank-2.5-lite":{"id":"voyage/rerank-2.5-lite","name":"Voyage Rerank 2.5 Lite","description":"Reranking model for improving retrieval quality in search and recommendation systems","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":32000}},"voyage/voyage-3.5":{"id":"voyage/voyage-3.5","name":"voyage-3.5","description":"General-purpose chat model for instruction following, writing, and analysis","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536}},"voyage/rerank-3":{"id":"voyage/rerank-3","name":"Voyage Rerank 3","description":"Reranking model for improving retrieval quality in search and recommendation systems","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-09-30","last_updated":"2026-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":32000}},"voyage/voyage-finance-2":{"id":"voyage/voyage-finance-2","name":"voyage-finance-2","description":"General-purpose chat model for instruction following, writing, and analysis","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-06-03","last_updated":"2024-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536}},"voyage/voyage-4-large":{"id":"voyage/voyage-4-large","name":"voyage-4-large","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-01-15","last_updated":"2026-03-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0}},"voyage/voyage-3.5-lite":{"id":"voyage/voyage-3.5-lite","name":"voyage-3.5-lite","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536}},"voyage/voyage-4":{"id":"voyage/voyage-4","name":"voyage-4","description":"General-purpose chat model for instruction following, writing, and analysis","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-01-15","last_updated":"2026-03-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0}},"voyage/voyage-3-large":{"id":"voyage/voyage-3-large","name":"voyage-3-large","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-01-07","last_updated":"2024-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536}},"voyage/voyage-code-2":{"id":"voyage/voyage-code-2","name":"voyage-code-2","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-01-01","last_updated":"2024-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536}},"voyage/voyage-code-3":{"id":"voyage/voyage-code-3","name":"voyage-code-3","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-12-04","last_updated":"2024-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536}},"voyage/rerank-2.5":{"id":"voyage/rerank-2.5","name":"Voyage Rerank 2.5","description":"Reranking model for improving retrieval quality in search and recommendation systems","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":32000}},"voyage/voyage-4-lite":{"id":"voyage/voyage-4-lite","name":"voyage-4-lite","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-01-15","last_updated":"2026-03-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0}},"interfaze/interfaze-beta":{"id":"interfaze/interfaze-beta","name":"Interfaze Beta","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"temperature":true,"release_date":"2025-10-07","last_updated":"2026-04-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32000},"cost":{"input":1.5,"output":3.5}},"stealth/glyph-cluster":{"id":"stealth/glyph-cluster","name":"Glyph Cluster","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0,"output":0}},"stealth/cat-jam":{"id":"stealth/cat-jam","name":"Cat Jam","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0}},"zai/glm-4.5":{"id":"zai/glm-4.5","name":"GLM 4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-07","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":96000},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5"},"zai/glm-5v-turbo":{"id":"zai/glm-5v-turbo","name":"GLM 5V Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5v-turbo"},"zai/glm-5.3-flash":{"id":"zai/glm-5.3-flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131000},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai/glm-4.6":{"id":"zai/glm-4.6","name":"GLM 4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":96000},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.6"},"zai/glm-5.2-fast":{"id":"zai/glm-5.2-fast","name":"GLM 5.2 Fast","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":2.8,"output":8.8,"cache_read":0.56},"canonical_model_id":"zhipuai/glm-5.2"},"zai/glm-5":{"id":"zai/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202800,"output":131100},"cost":{"input":1,"output":3.2},"canonical_model_id":"zhipuai/glm-5"},"zai/glm-4.5v":{"id":"zai/glm-4.5v","name":"GLM 4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-08","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":66000,"output":16000},"cost":{"input":0.6,"output":1.8,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5v"},"zai/glm-5.3-flashx":{"id":"zai/glm-5.3-flashx","name":"GLM 5.3 FlashX","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.37,"output":1.25,"cache_read":0.075},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai/glm-4.7-flash":{"id":"zai/glm-4.7-flash","name":"GLM 4.7 Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131000},"cost":{"input":0.07,"output":0.4},"canonical_model_id":"zhipuai/glm-4.7-flash"},"zai/glm-4.7":{"id":"zai/glm-4.7","name":"GLM 4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":120000},"cost":{"input":0.6,"output":2.2},"canonical_model_id":"zhipuai/glm-4.7"},"zai/glm-5.2":{"id":"zai/glm-5.2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.8,"output":2.55,"cache_read":0.16},"canonical_model_id":"zhipuai/glm-5.2"},"zai/glm-5.1":{"id":"zai/glm-5.1","name":"GLM 5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202800,"output":64000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"zai/glm-4.7-flashx":{"id":"zai/glm-4.7-flashx","name":"GLM 4.7 FlashX","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.06,"output":0.4,"cache_read":0.01},"canonical_model_id":"zhipuai/glm-4.7-flashx"},"zai/glm-5-turbo":{"id":"zai/glm-5-turbo","name":"GLM 5 Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":202800,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5-turbo"},"zai/glm-4.5-air":{"id":"zai/glm-4.5-air","name":"GLM 4.5 Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":96000},"cost":{"input":0.2,"output":1.1,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-4.5-air"},"zai/glm-5.3":{"id":"zai/glm-5.3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":1000000},"cost":{"input":1.4,"output":4.4,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.3"},"zai/glm-5.3-fast":{"id":"zai/glm-5.3-fast","name":"GLM 5.3 Fast","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":2.1,"output":6.6,"cache_read":0.21},"canonical_model_id":"zhipuai/glm-5.3"},"spacexai/grok-4.20-multi-agent":{"id":"spacexai/grok-4.20-multi-agent","name":"Grok 4.20 Multi-Agent","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"release_date":"2026-03-10","last_updated":"2026-03-10","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"spacexai/grok-tts":{"id":"spacexai/grok-tts","name":"Grok TTS","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"grok","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"spacexai/grok-4.20-reasoning":{"id":"spacexai/grok-4.20-reasoning","name":"Grok 4.20 Reasoning","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"release_date":"2026-03-10","last_updated":"2026-03-10","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"spacexai/grok-4.7":{"id":"spacexai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"spacexai/grok-imagine-video-1.5-lite":{"id":"spacexai/grok-imagine-video-1.5-lite","name":"Grok Imagine Video 1.5 Lite","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"grok","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-01","last_updated":"2026-10-01","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"canonical_model_id":"xai/grok-imagine-video-1.5-lite"},"spacexai/grok-voice-think-fast-1.0":{"id":"spacexai/grok-voice-think-fast-1.0","name":"Grok Voice Think Fast 1.0","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"grok","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"spacexai/grok-4.20-non-reasoning":{"id":"spacexai/grok-4.20-non-reasoning","name":"Grok 4.20 Non-Reasoning","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"release_date":"2026-03-10","last_updated":"2026-03-10","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"spacexai/grok-stt":{"id":"spacexai/grok-stt","name":"Grok STT","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"grok","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0}},"spacexai/grok-imagine-image":{"id":"spacexai/grok-imagine-image","name":"Grok Imagine Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"grok","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-01-28","last_updated":"2026-01-28","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"canonical_model_id":"xai/grok-imagine-image"},"spacexai/grok-imagine-video":{"id":"spacexai/grok-imagine-video","name":"Grok Imagine","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"grok","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-01-28","last_updated":"2026-01-28","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"spacexai/grok-4.1-fast-reasoning":{"id":"spacexai/grok-4.1-fast-reasoning","name":"Grok 4.1 Fast Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"xai/grok-4.1-fast-reasoning"},"spacexai/grok-4.3":{"id":"spacexai/grok-4.3","name":"Grok 4.3","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.3"},"spacexai/grok-imagine-video-1.5":{"id":"spacexai/grok-imagine-video-1.5","name":"Grok Imagine Video 1.5","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"grok","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-05-30","last_updated":"2026-05-30","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"canonical_model_id":"xai/grok-imagine-video-1.5"},"spacexai/grok-4.5":{"id":"spacexai/grok-4.5","name":"Grok 4.5","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.3,"tiers":[{"input":4,"output":12,"cache_read":0.6,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":4,"output":12,"cache_read":0.6}},"canonical_model_id":"xai/grok-4.5"},"spacexai/grok-voice-think-fast-2.0":{"id":"spacexai/grok-voice-think-fast-2.0","name":"Grok Voice Think Fast 2.0","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"grok","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"spacexai/grok-imagine-image-2.0":{"id":"spacexai/grok-imagine-image-2.0","name":"Grok Imagine Image 2.0","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"grok","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-08-07","last_updated":"2026-08-07","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"canonical_model_id":"xai/grok-imagine-image-2.0"},"spacexai/grok-4.20-multi-agent-beta":{"id":"spacexai/grok-4.20-multi-agent-beta","name":"Grok 4.20 Multi Agent Beta","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"spacexai/grok-4.20-non-reasoning-beta":{"id":"spacexai/grok-4.20-non-reasoning-beta","name":"Grok 4.20 Beta Non-Reasoning","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.4,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"spacexai/grok-build-0.1":{"id":"spacexai/grok-build-0.1","name":"Grok Build 0.1","description":"Grok coding model for agentic engineering, edits, and codebase workflows","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.2,"tiers":[{"input":2,"output":4,"cache_read":0.4,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":2,"output":4,"cache_read":0.4}},"canonical_model_id":"xai/grok-build-0.1"},"spacexai/grok-4.1-fast-non-reasoning":{"id":"spacexai/grok-4.1-fast-non-reasoning","name":"Grok 4.1 Fast Non-Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":0.2,"output":0.5,"cache_read":0.05}},"spacexai/grok-4.20-reasoning-beta":{"id":"spacexai/grok-4.20-reasoning-beta","name":"Grok 4.20 Beta Reasoning","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"spacexai/grok-4.6":{"id":"spacexai/grok-4.6","name":"Grok 4.6","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"prodia/flux-fast-schnell":{"id":"prodia/flux-fast-schnell","name":"Flux Schnell","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-08-02","last_updated":"2026-06-08","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":512,"output":0}},"recraft/recraft-v2":{"id":"recraft/recraft-v2","name":"Recraft V2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"recraft","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-03-13","last_updated":"2024-03","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":512,"output":0}},"recraft/recraft-v4-pro":{"id":"recraft/recraft-v4-pro","name":"Recraft V4 Pro","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"recraft","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-02-17","last_updated":"2026-02-17","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0}},"recraft/recraft-v4.1-utility":{"id":"recraft/recraft-v4.1-utility","name":"Recraft V4.1 Utility","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"recraft","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-05-14","last_updated":"2026-05-14","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0}},"recraft/recraft-v4.1-pro":{"id":"recraft/recraft-v4.1-pro","name":"Recraft V4.1 Pro","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"recraft","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-05-14","last_updated":"2026-05-14","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0}},"recraft/recraft-v3":{"id":"recraft/recraft-v3","name":"Recraft V3","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"recraft","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-10-30","last_updated":"2024-10","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":512,"output":0}},"recraft/recraft-v4.1":{"id":"recraft/recraft-v4.1","name":"Recraft V4.1","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"recraft","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-05-14","last_updated":"2026-05-14","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0}},"recraft/recraft-v4.1-flash":{"id":"recraft/recraft-v4.1-flash","name":"Recraft V4.1 Flash","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"recraft","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0}},"recraft/recraft-v4.1-utility-pro":{"id":"recraft/recraft-v4.1-utility-pro","name":"Recraft V4.1 Utility Pro","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"recraft","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-05-14","last_updated":"2026-05-14","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0}},"recraft/recraft-v4":{"id":"recraft/recraft-v4","name":"Recraft V4","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"recraft","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-02-17","last_updated":"2026-02-17","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0}},"poolside/laguna-s-2.1-free":{"id":"poolside/laguna-s-2.1-free","name":"Laguna S 2.1 Free","description":"Free provider route for experiments, demos, and cost-sensitive chat workloads","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"poolside/laguna-s-2.1"},"poolside/laguna-s-2.1":{"id":"poolside/laguna-s-2.1","name":"Laguna S 2.1","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.09,"output":0.18,"cache_read":0.009},"canonical_model_id":"poolside/laguna-s-2.1"},"anthropic/claude-opus-4.5":{"id":"anthropic/claude-opus-4.5","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-opus-4.6":{"id":"anthropic/claude-opus-4.6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic/claude-haiku-5.5":{"id":"anthropic/claude-haiku-5.5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100001}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-opus-5.5-fast":{"id":"anthropic/claude-opus-5.5-fast","name":"Claude Opus 5.5 (Fast)","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":8,"output":40,"cache_read":0.4,"cache_write":10},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-haiku-4.5":{"id":"anthropic/claude-haiku-4.5","name":"Claude Haiku 4.5","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]},{"type":"budget_tokens"}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-sonnet-5.5":{"id":"anthropic/claude-sonnet-5.5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-fable-5.1":{"id":"anthropic/claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]},{"type":"budget_tokens"}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]},{"type":"budget_tokens"}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-opus-4.8-fast":{"id":"anthropic/claude-opus-4.8-fast","name":"Claude Opus 4.8 (Fast)","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]},{"type":"budget_tokens"}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-5.5":{"id":"anthropic/claude-opus-5.5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-opus-5-fast":{"id":"anthropic/claude-opus-5-fast","name":"Claude Opus 5 (Fast)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]},{"type":"budget_tokens"}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-sonnet-4.5":{"id":"anthropic/claude-sonnet-4.5","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75}},"cohere/rerank-v4-fast":{"id":"cohere/rerank-v4-fast","name":"Cohere Rerank 4 Fast","description":"Reranking model for improving retrieval quality in search and recommendation systems","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":32000}},"cohere/rerank-v4-pro":{"id":"cohere/rerank-v4-pro","name":"Cohere Rerank 4 Pro","description":"Reranking model for improving retrieval quality in search and recommendation systems","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":32000}},"cohere/command-a":{"id":"cohere/command-a","name":"Command A","description":"Cohere command model for multilingual enterprise agents, tools, and chat","family":"command-a","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-03-13","last_updated":"2025-03-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8000},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-a"},"cohere/embed-v4.0":{"id":"cohere/embed-v4.0","name":"Embed v4.0","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"cohere-embed","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-04-15","last_updated":"2025-04-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":1536}},"cohere/embed-v5.0-pro":{"id":"cohere/embed-v5.0-pro","name":"Embed 5 Pro","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-09-30","last_updated":"2026-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":0}},"cohere/embed-v5.0-fast":{"id":"cohere/embed-v5.0-fast","name":"Embed 5 Fast","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-09-30","last_updated":"2026-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":0}},"cohere/rerank-v3.5":{"id":"cohere/rerank-v3.5","name":"Cohere Rerank 3.5","description":"Reranking model for improving retrieval quality in search and recommendation systems","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-12-02","last_updated":"2024-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":4096,"output":4096}},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.076,"output":0.153,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":32768},"cost":{"input":0.3,"output":1.2,"cache_read":0.007},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-flash-vision-exp":{"id":"deepseek/deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.2156,"output":0.6468,"cache_read":0.0068},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.66,"output":1.98,"cache_read":0.066},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek/deepseek-v3.2-thinking":{"id":"deepseek/deepseek-v3.2-thinking","name":"DeepSeek V3.2 Thinking","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8000},"cost":{"input":0.62,"output":1.85}},"deepseek/deepseek-v4.1-flash-fast":{"id":"deepseek/deepseek-v4.1-flash-fast","name":"DeepSeek V4.1 Flash Fast","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":32768},"cost":{"input":0.6,"output":2.4,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v3.1":{"id":"deepseek/deepseek-v3.1","name":"DeepSeek-V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":128000},"cost":{"input":0.25,"output":0.95,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-v3.1"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.66,"output":1.98,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v3.2":{"id":"deepseek/deepseek-v3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8000},"cost":{"input":0.62,"output":1.85},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.13,"output":0.26,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-r1":{"id":"deepseek/deepseek-r1","name":"DeepSeek-R1","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":1.35,"output":5.4},"canonical_model_id":"deepseek/deepseek-r1"},"quiverai/arrow-2":{"id":"quiverai/arrow-2","name":"Arrow 2","description":"Fast SVG generation model for creation, vectorization, editing, and animation","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"release_date":"2026-09-16","last_updated":"2026-09-16","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":65536},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5},"canonical_model_id":"quiverai/arrow-2"},"quiverai/arrow-2-telos":{"id":"quiverai/arrow-2-telos","name":"Arrow 2 Telos","description":"High-fidelity SVG generation model for complex vector work and long-context refinement","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"release_date":"2026-09-16","last_updated":"2026-09-16","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":65536},"cost":{"input":6,"output":30,"cache_read":0.6,"cache_write":7.5},"canonical_model_id":"quiverai/arrow-2-telos"},"bfl/flux-kontext-max":{"id":"bfl/flux-kontext-max","name":"FLUX.1 Kontext Max","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-05-29","last_updated":"2025-06","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":512,"output":0}},"bfl/flux-pro-1.1-ultra":{"id":"bfl/flux-pro-1.1-ultra","name":"FLUX1.1 [pro] Ultra","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-11-01","last_updated":"2024-11","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":512,"output":0}},"bfl/flux-3-image":{"id":"bfl/flux-3-image","name":"FLUX 3 Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0}},"bfl/flux-3-video":{"id":"bfl/flux-3-video","name":"Flux 3","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-08-04","last_updated":"2026-08-04","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"bfl/flux-2-flex":{"id":"bfl/flux-2-flex","name":"FLUX.2 [flex]","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-11-25","last_updated":"2026-06-08","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0}},"bfl/flux-2-klein-4b":{"id":"bfl/flux-2-klein-4b","name":"FLUX.2 [klein] 4B","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-01-15","last_updated":"2026-06-08","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0}},"bfl/flux-pro-1.0-fill":{"id":"bfl/flux-pro-1.0-fill","name":"FLUX.1 Fill [pro]","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-10-01","last_updated":"2024-10","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":512,"output":0}},"bfl/flux-2-klein-9b":{"id":"bfl/flux-2-klein-9b","name":"FLUX.2 [klein] 9B","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-01-15","last_updated":"2026-06-08","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0}},"bfl/flux-2-pro":{"id":"bfl/flux-2-pro","name":"FLUX.2 [pro]","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-11-25","last_updated":"2026-06-08","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":67300,"output":67300}},"bfl/flux-2-max":{"id":"bfl/flux-2-max","name":"FLUX.2 [max]","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-12-16","last_updated":"2026-06-08","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":67300,"output":67300}},"bfl/flux-pro-1.1":{"id":"bfl/flux-pro-1.1","name":"FLUX1.1 [pro]","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-10-02","last_updated":"2024-10","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":512,"output":0}},"bfl/flux-kontext-pro":{"id":"bfl/flux-kontext-pro","name":"FLUX.1 Kontext Pro","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-05-29","last_updated":"2025-06","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":512,"output":0}},"tencent/hy-mt2-lite":{"id":"tencent/hy-mt2-lite","name":"Tencent Hy-MT2-Lite","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8000,"output":4000},"cost":{"input":0.044,"output":0.177}},"tencent/hy3":{"id":"tencent/hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.14,"output":0.58,"cache_read":0.035},"canonical_model_id":"tencent/hy3"},"tencent/hy-mt2-plus":{"id":"tencent/hy-mt2-plus","name":"Tencent Hy-MT2-Plus","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8000,"output":4000},"cost":{"input":0.074,"output":0.295}},"tencent/hy-mt2-pro":{"id":"tencent/hy-mt2-pro","name":"Tencent Hy-MT2-Pro","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8000,"output":4000},"cost":{"input":0.074,"output":0.295}},"tencent/hy4-preview":{"id":"tencent/hy4-preview","name":"Tencent Hy4 Preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":64000},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"},"heygen/heygen-video-1":{"id":"heygen/heygen-video-1","name":"HeyGen Video","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"release_date":"2026-10-09","last_updated":"2026-10-09","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"reflection/beam":{"id":"reflection/beam","name":"Beam 1.0","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"release_date":"2026-10-16","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.3,"output":4.3,"cache_read":0.13}},"reflection/beam-free":{"id":"reflection/beam-free","name":"Beam 1.0 (Free)","description":"Free provider route for experiments, demos, and cost-sensitive chat workloads","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"release_date":"2026-10-16","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0}},"inference-net/schematron-v2-small":{"id":"inference-net/schematron-v2-small","name":"Schematron V2 Small","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":0.05,"output":0.23,"cache_read":0.05}},"inference-net/schematron-v2-turbo":{"id":"inference-net/schematron-v2-turbo","name":"Schematron V2 Turbo","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.03,"output":0.15,"cache_read":0.03}},"thinkingmachines/inkling-small":{"id":"thinkingmachines/inkling-small","name":"Inkling Small","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":1000000},"cost":{"input":0.45,"output":1.2,"cache_read":0.1},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/inkling":{"id":"thinkingmachines/inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":4.05,"cache_read":0.17},"canonical_model_id":"thinkingmachines/inkling"},"meituan/longcat-2.5-preview":{"id":"meituan/longcat-2.5-preview","name":"LongCat 2.5 Preview","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"longcat","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"release_date":"2026-09-26","last_updated":"2026-09-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.006}},"perplexity/pplx-embed-v1-4b":{"id":"perplexity/pplx-embed-v1-4b","name":"Embed v1 4b","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-02-26","last_updated":"2026-02-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0}},"perplexity/pplx-embed-v1-0.6b":{"id":"perplexity/pplx-embed-v1-0.6b","name":"Embed v1 0.6b","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"v0","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-02-26","last_updated":"2026-02-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0}},"perplexity/sonar":{"id":"perplexity/sonar","name":"Sonar","description":"Sonar search model for current answers, retrieval, and citation-backed chat","family":"sonar","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-02","release_date":"2025-02-19","last_updated":"2025-02-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":127000,"output":8000},"cost":{"input":0.25,"output":2.5,"cache_write":0.0625}},"meta/muse-spark-1.3":{"id":"meta/muse-spark-1.3","name":"Muse Spark 1.3","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.3"},"meta/muse-glimmer-30b":{"id":"meta/muse-glimmer-30b","name":"Muse Glimmer 30B","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.35,"output":1.5,"cache_read":0.04},"canonical_model_id":"meta/muse-glimmer-30b"},"meta/muse-spark-1.1":{"id":"meta/muse-spark-1.1","name":"Muse Spark 1.1","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"muse","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.1"},"meta/llama-3.1-8b":{"id":"meta/llama-3.1-8b","name":"Llama 3.1 8B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.22,"output":0.22}},"meta/llama-3.1-70b":{"id":"meta/llama-3.1-70b","name":"Llama 3.1 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.72,"output":0.72}},"meta/muse-spark-1.2":{"id":"meta/muse-spark-1.2","name":"Muse Spark 1.2","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"meta/muse-image-1.0":{"id":"meta/muse-image-1.0","name":"Muse Image 1.0","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"muse","attachment":true,"reasoning":false,"tool_call":false,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0}},"meta/muse-spark-1.2-contributor":{"id":"meta/muse-spark-1.2-contributor","name":"Muse Spark 1.2 Contributor","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"meta/muse-wonder-1.0":{"id":"meta/muse-wonder-1.0","name":"Muse Wonder","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":4,"output":20,"cache_read":0.2},"canonical_model_id":"meta/muse-wonder-1.0"},"meta/muse-spark-1.3-contributor":{"id":"meta/muse-spark-1.3-contributor","name":"Muse Spark 1.3 Contributor","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"meta/muse-spark-open":{"id":"meta/muse-spark-open","name":"Muse Spark Open","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-open"},"meta/llama-3.3-70b":{"id":"meta/llama-3.3-70b","name":"Llama-3.3-70B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0,"output":0}},"meta/llama-4-maverick":{"id":"meta/llama-4-maverick","name":"Llama-4-Maverick-17B-128E-Instruct-FP8","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0,"output":0}},"meta/llama-4-scout":{"id":"meta/llama-4-scout","name":"Llama-4-Scout-17B-16E-Instruct-FP8","description":"Open multimodal Llama model for long-context analysis and efficient agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0,"output":0}},"arcee-ai/trinity-large-thinking":{"id":"arcee-ai/trinity-large-thinking","name":"Trinity Large Thinking","description":"Reasoning-optimized 398B MoE agent model with extended thinking for long-horizon and multi-turn tool use","family":"trinity","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262100,"output":80000},"cost":{"input":0.25,"output":0.8},"canonical_model_id":"arcee-ai/trinity-large-thinking"},"alibaba/qwen3.5-flash":{"id":"alibaba/qwen3.5-flash","name":"Qwen 3.5 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]},{"type":"budget_tokens","min":1,"max":81920}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"alibaba/qwen3.5-flash"},"alibaba/qwen-3-32b":{"id":"alibaba/qwen-3-32b","name":"Qwen 3.32B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":38912}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.15,"output":0.6}},"alibaba/wan-v2.6-t2v":{"id":"alibaba/wan-v2.6-t2v","name":"Wan v2.6 Text-to-Video","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"alibaba/qwen3.7-max":{"id":"alibaba/qwen3.7-max","name":"Qwen 3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]},{"type":"budget_tokens","min":1,"max":262144}],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":991000,"output":64000},"cost":{"input":2.5,"output":7.5,"cache_read":0.5,"cache_write":3.125},"canonical_model_id":"alibaba/qwen3.7-max"},"alibaba/qwen3.8-27b":{"id":"alibaba/qwen3.8-27b","name":"Qwen3.8 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.5,"output":3,"cache_read":0.1,"cache_write":0.625},"canonical_model_id":"alibaba/qwen3.8-27b"},"alibaba/qwen3.8-2.4t-a95b":{"id":"alibaba/qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":128000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"alibaba/qwen3-next-80b-a3b-thinking":{"id":"alibaba/qwen3-next-80b-a3b-thinking","name":"Qwen3 Next 80B A3B Thinking","description":"Efficient Qwen thinking model for local reasoning, math, and coding agents","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.15,"output":1.2},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-thinking"},"alibaba/qwen3.8-max":{"id":"alibaba/qwen3.8-max","name":"Qwen 3.8 Max","description":"Preview Qwen flagship for million-token multimodal reasoning and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"temperature":true,"release_date":"2026-07-19","last_updated":"2026-07-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":128000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-max-preview"},"alibaba/qwen3-coder-next":{"id":"alibaba/qwen3-coder-next","name":"Qwen3 Coder Next","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.5,"output":1.2},"canonical_model_id":"alibaba/qwen3-coder-next"},"alibaba/qwen3-vl-instruct":{"id":"alibaba/qwen3-vl-instruct","name":"Qwen3 VL Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.2,"output":0.88,"cache_read":0.11}},"alibaba/qwen3-coder":{"id":"alibaba/qwen3-coder","name":"Qwen3 Coder 480B A35B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-22","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.22,"output":1.8,"cache_read":0.022,"tiers":[{"input":2.7,"output":13.5,"cache_read":0.54,"tier":{"type":"context","size":32001}},{"input":4.5,"output":22.5,"cache_read":0.9,"tier":{"type":"context","size":128001}}]}},"alibaba/qwen3.5-plus":{"id":"alibaba/qwen3.5-plus","name":"Qwen 3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]},{"type":"budget_tokens","min":1,"max":81920}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.4,"output":2.4,"cache_read":0.04,"cache_write":0.5,"tiers":[{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":256001}}],"context_over_200k":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625}},"canonical_model_id":"alibaba/qwen3.5-plus"},"alibaba/wan-v2.6-i2v-flash":{"id":"alibaba/wan-v2.6-i2v-flash","name":"Wan v2.6 Image-to-Video Flash","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"alibaba/wan-v2.6-r2v-flash":{"id":"alibaba/wan-v2.6-r2v-flash","name":"Wan v2.6 Reference-to-Video Flash","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"alibaba/qwen-3-14b":{"id":"alibaba/qwen-3-14b","name":"Qwen3-14B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":40960,"output":16384},"cost":{"input":0.12,"output":0.24}},"alibaba/qwen3.7-flash":{"id":"alibaba/qwen3.7-flash","name":"Qwen 3.7 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":991000,"output":64000},"cost":{"input":0.03,"output":0.13,"cache_read":0.006,"cache_write":0.038,"tiers":[{"input":0.1,"output":0.4,"cache_read":0.02,"cache_write":0.125,"tier":{"type":"context","size":32000}},{"input":0.2,"output":0.8,"cache_read":0.04,"cache_write":0.25,"tier":{"type":"context","size":256000}}]},"canonical_model_id":"alibaba/qwen3.7-flash"},"alibaba/qwen3-embedding-0.6b":{"id":"alibaba/qwen3-embedding-0.6b","name":"Qwen3 Embedding 0.6B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-11-14","last_updated":"2025-11-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":32768}},"alibaba/qwen-3-30b":{"id":"alibaba/qwen-3-30b","name":"Qwen3-30B-A3B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":40960,"output":16384},"cost":{"input":0.12,"output":0.5}},"alibaba/qwen3.8-omni-flash":{"id":"alibaba/qwen3.8-omni-flash","name":"Qwen 3.8 Omni Flash","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-omni-flash"},"alibaba/qwen3-coder-30b-a3b":{"id":"alibaba/qwen3-coder-30b-a3b","name":"Qwen 3 Coder 30B A3B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-31","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":8192},"cost":{"input":0.15,"output":0.6}},"alibaba/qwen3-embedding-4b":{"id":"alibaba/qwen3-embedding-4b","name":"Qwen3 Embedding 4B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":32768}},"alibaba/wan-v2.6-i2v":{"id":"alibaba/wan-v2.6-i2v","name":"Wan v2.6 Image-to-Video","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"alibaba/qwen3-next-80b-a3b-instruct":{"id":"alibaba/qwen3-next-80b-a3b-instruct","name":"Qwen3 Next 80B A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262114,"output":262114},"cost":{"input":0.15,"output":1.2},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"alibaba/wan-v2.5-t2v-preview":{"id":"alibaba/wan-v2.5-t2v-preview","name":"Wan v2.5 Text-to-Video Preview","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-09-24","last_updated":"2025-09-24","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"alibaba/qwen3-max-thinking":{"id":"alibaba/qwen3-max-thinking","name":"Qwen 3 Max Thinking","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1,"max":81920}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-23","last_updated":"2025-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":1.2,"output":6,"cache_read":0.24,"tiers":[{"input":2.4,"output":12,"cache_read":0.48,"tier":{"type":"context","size":32001}},{"input":3,"output":15,"cache_read":0.6,"tier":{"type":"context","size":128001}}]}},"alibaba/qwen3.8-max-prime":{"id":"alibaba/qwen3.8-max-prime","name":"Qwen 3.8 Max Prime","description":"High-throughput edition of Qwen3.8 Max for coding, professional work, multimodal understanding, and long-running agent workflows","family":"qwen3.8-max","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":4,"output":12,"cache_read":0.5,"cache_write":5},"canonical_model_id":"alibaba/qwen3.8-max-prime"},"alibaba/qwen3.8-flash":{"id":"alibaba/qwen3.8-flash","name":"Qwen 3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":991000,"output":128000},"cost":{"input":0.15,"output":0.47,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"alibaba/qwen3-embedding-8b":{"id":"alibaba/qwen3-embedding-8b","type":"embedding","name":"Qwen3 Embedding 8B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"canonical_model_id":"alibaba/qwen3-embedding-8b"},"alibaba/wan-v3.0-video":{"id":"alibaba/wan-v3.0-video","name":"Wan v3.0 Video","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"release_date":"2026-08-23","last_updated":"2026-08-23","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"alibaba/wan-v2.7-r2v":{"id":"alibaba/wan-v2.7-r2v","name":"Wan v2.7 Reference-to-Video","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"alibaba/wan-v3.0-video-prime":{"id":"alibaba/wan-v3.0-video-prime","name":"Wan v3.0 Video Prime","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"alibaba/qwen3.6-27b":{"id":"alibaba/qwen3.6-27b","name":"Qwen 3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":131072}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0.6,"output":3.6},"canonical_model_id":"alibaba/qwen3.6-27b"},"alibaba/qwen-3-235b":{"id":"alibaba/qwen-3-235b","name":"Qwen3 235B A22B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":16384},"cost":{"input":0.22,"output":0.88}},"alibaba/qwen3.6-plus":{"id":"alibaba/qwen3.6-plus","name":"Qwen 3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]},{"type":"budget_tokens","min":1,"max":131072}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625,"tiers":[{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5}},"canonical_model_id":"alibaba/qwen3.6-plus"},"alibaba/qwen3.7-plus":{"id":"alibaba/qwen3.7-plus","name":"Qwen 3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]},{"type":"budget_tokens","min":1,"max":262144}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.4,"output":1.6,"cache_read":0.08,"cache_write":0.5,"tiers":[{"input":1.2,"output":4.8,"cache_read":0.24,"cache_write":1.5,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1.2,"output":4.8,"cache_read":0.24,"cache_write":1.5}},"canonical_model_id":"alibaba/qwen3.7-plus"},"alibaba/wan-v2.6-r2v":{"id":"alibaba/wan-v2.6-r2v","name":"Wan v2.6 Reference-to-Video","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"alibaba/qwen3.8-max-0902":{"id":"alibaba/qwen3.8-max-0902","name":"Qwen3.8 Max 0902","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":991000,"output":128000},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max-0902"},"alibaba/wan-v2.7-t2v":{"id":"alibaba/wan-v2.7-t2v","name":"Wan v2.7 Text-to-Video","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"mixedbread/toast-1":{"id":"mixedbread/toast-1","name":"Toast 1","description":"Specialized search model for knowledge-intensive questions, multi-step retrieval, and evidence synthesis","attachment":false,"reasoning":false,"tool_call":true,"release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":4000},"cost":{"input":0.3,"output":0.72,"cache_read":0.036},"canonical_model_id":"mixedbread/toast-1"},"klingai/kling-v2.6-t2v":{"id":"klingai/kling-v2.6-t2v","name":"Kling v2.6 Text-to-Video","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"ling","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-12-03","last_updated":"2025-12-21","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"klingai/kling-v2.6-i2v":{"id":"klingai/kling-v2.6-i2v","name":"Kling v2.6 Image-to-Video","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"ling","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-12-03","last_updated":"2025-12-21","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"klingai/kling-v2.5-turbo-t2v":{"id":"klingai/kling-v2.5-turbo-t2v","name":"Kling v2.5 Turbo Text-to-Video","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"ling","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"klingai/kling-v3.0-i2v":{"id":"klingai/kling-v3.0-i2v","name":"Kling v3.0 Image-to-Video","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"ling","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"klingai/kling-v3.0-motion-control":{"id":"klingai/kling-v3.0-motion-control","name":"Kling v3.0 Motion Control","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"ling","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-03-04","last_updated":"2026-03-04","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"klingai/kling-v3.0-t2v":{"id":"klingai/kling-v3.0-t2v","name":"Kling v3.0 Text-to-Video","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"ling","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"klingai/kling-v2.6-motion-control":{"id":"klingai/kling-v2.6-motion-control","name":"Kling v2.6 Motion Control","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"ling","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-12-18","last_updated":"2025-12-21","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"klingai/kling-v2.5-turbo-i2v":{"id":"klingai/kling-v2.5-turbo-i2v","name":"Kling v2.5 Turbo Image-to-Video","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"ling","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"bytedance/seedream-5.0-lite":{"id":"bytedance/seedream-5.0-lite","name":"Seedream 5.0 Lite","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-02-13","last_updated":"2026-01-28","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0}},"bytedance/seedream-4.5":{"id":"bytedance/seedream-4.5","name":"Seedream 4.5","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-12-03","last_updated":"2025-11-28","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0}},"bytedance/seed-1.8":{"id":"bytedance/seed-1.8","name":"Seed 1.8","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-09-01","last_updated":"2025-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32768},"cost":{"input":0.25,"output":2,"cache_read":0.05,"tiers":[{"input":0.5,"output":4,"cache_read":0.05,"tier":{"type":"context","size":128001}}]}},"bytedance/seed-2.1-turbo":{"id":"bytedance/seed-2.1-turbo","name":"Seed 2.1 Turbo","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":2.5,"cache_read":0.1}},"bytedance/seedream-4.0":{"id":"bytedance/seedream-4.0","name":"Seedream 4.0","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-09-09","last_updated":"2025-08-28","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0}},"bytedance/seedance-v1.0-pro":{"id":"bytedance/seedance-v1.0-pro","name":"Seedance v1.0 Pro","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-06-11","last_updated":"2025-06-11","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"bytedance/seedance-2.0":{"id":"bytedance/seedance-2.0","name":"Seedance 2.0","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"seed","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-04-14","last_updated":"2026-04-14","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"bytedance/seedance-2.0-fast":{"id":"bytedance/seedance-2.0-fast","name":"Seedance 2.0 Fast","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"seed","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-04-14","last_updated":"2026-04-14","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"bytedance/seedance-v1.5-pro":{"id":"bytedance/seedance-v1.5-pro","name":"Seedance v1.5 Pro","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"bytedance/seedance-2.0-mini":{"id":"bytedance/seedance-2.0-mini","name":"Seedance 2.0 Mini","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"seed","attachment":true,"reasoning":false,"tool_call":false,"release_date":"2026-06-22","last_updated":"2026-06-22","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"bytedance/seedance-2.5":{"id":"bytedance/seedance-2.5","name":"Seedance 2.5","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-08-07","last_updated":"2026-08-07","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"bytedance/seedance-v1.0-pro-fast":{"id":"bytedance/seedance-v1.0-pro-fast","name":"Seedance v1.0 Pro Fast","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-10-24","last_updated":"2025-10-31","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"bytedance/seedream-5.0-pro":{"id":"bytedance/seedream-5.0-pro","name":"Seedream 5.0 Pro","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-07-11","last_updated":"2026-07-11","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0}},"bytedance/seed-1.6":{"id":"bytedance/seed-1.6","name":"Seed 1.6","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-09-01","last_updated":"2025-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.25,"output":2,"cache_read":0.05,"tiers":[{"input":0.5,"output":4,"cache_read":0.05,"tier":{"type":"context","size":128001}}]}},"liquid/lfm2.5-24b-a2b":{"id":"liquid/lfm2.5-24b-a2b","name":"LFM2.5-24B-A2B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"liquid","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8200},"cost":{"input":0.05,"output":0.7,"cache_read":0.025}},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.14,"output":0.4},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemini-omni-flash-preview":{"id":"google/gemini-omni-flash-preview","name":"Gemini Omni Flash Preview","description":"Omni-modal model for text, vision, audio, and multimodal agent tasks","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]},{"type":"budget_tokens"}],"tool_call":false,"temperature":true,"release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":57920},"cost":{"input":1.5,"output":9},"canonical_model_id":"google/gemini-omni-flash-preview"},"google/gemini-3.1-flash-image-preview":{"id":"google/gemini-3.1-flash-image-preview","name":"Gemini 3.1 Flash Image Preview (Nano Banana 2)","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-26","last_updated":"2026-02-26","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":3,"cache_read":0.05},"canonical_model_id":"google/gemini-3.1-flash-image-preview"},"google/gemini-3.5-transcribe-live":{"id":"google/gemini-3.5-transcribe-live","name":"Gemini 3.5 Transcribe Live","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0},"canonical_model_id":"google/gemini-3.5-transcribe-live"},"google/gemini-2.5-flash-image":{"id":"google/gemini-2.5-flash-image","name":"Nano Banana (Gemini 2.5 Flash Image)","description":"Nano Banana image model for fast generation, edits, and character-consistent assets","family":"gemini-flash","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":32768,"output":65535},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-2.5-flash-image"},"google/gemini-3.8-flash-lite-tts":{"id":"google/gemini-3.8-flash-lite-tts","name":"Gemini 3.8 Flash-Lite TTS","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":0.5,"output":6}},"google/text-multilingual-embedding-002":{"id":"google/text-multilingual-embedding-002","name":"Text Multilingual Embedding 002","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-03-01","last_updated":"2024-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536}},"google/gemini-embedding-2":{"id":"google/gemini-embedding-2","name":"Gemini Embedding 2","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-11","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0},"canonical_model_id":"google/gemini-embedding-2"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.6-flash"},"google/veo-3.1-lite-generate-001":{"id":"google/veo-3.1-lite-generate-001","name":"Veo 3.1 Lite Generate","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"google/gemma-4-26b-a4b-it":{"id":"google/gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65000},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemini-3.1-flash-image":{"id":"google/gemini-3.1-flash-image","name":"Nano Banana 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":3,"cache_read":0.05},"canonical_model_id":"google/gemini-3.1-flash-image"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/veo-3.1-fast-generate-001":{"id":"google/veo-3.1-fast-generate-001","name":"Veo 3.1 Fast Generate","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-10-15","last_updated":"2026-06-08","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"google/gemini-3-flash":{"id":"google/gemini-3-flash","name":"Gemini 3 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65000},"cost":{"input":0.5,"output":3,"cache_read":0.05}},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":1.5,"output":9,"cache_read":0.15},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-3-pro-image":{"id":"google/gemini-3-pro-image","name":"Nano Banana Pro","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":2,"output":12,"cache_read":0.2},"canonical_model_id":"google/gemini-3-pro-image"},"google/veo-3.0-fast-generate-001":{"id":"google/veo-3.0-fast-generate-001","name":"Veo 3.0 Fast Generate","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-07-31","last_updated":"2026-06-08","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"google/gemini-3.8-live":{"id":"google/gemini-3.8-live","name":"Gemini 3.8 Live","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-09-15","last_updated":"2026-09-15","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":0.75,"output":4.5}},"google/veo-3.1-generate-001":{"id":"google/veo-3.1-generate-001","name":"Veo 3.1","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-10-15","last_updated":"2026-06-08","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"google/gemini-3.1-flash-lite-image":{"id":"google/gemini-3.1-flash-lite-image","name":"Gemini 3.1 Flash Lite Image (Nano Banana 2 Lite)","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":4096},"cost":{"input":0.25,"output":1.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.1-flash-lite-image"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.7-flash"},"google/text-embedding-005":{"id":"google/text-embedding-005","name":"Text Embedding 005","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-08-01","last_updated":"2024-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536}},"google/gemini-3.5-transcribe":{"id":"google/gemini-3.5-transcribe","name":"Gemini 3.5 Transcribe","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":2,"output":12}},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.1,"output":0.4,"cache_read":0.01},"canonical_model_id":"google/gemini-2.5-flash-lite"},"google/gemini-embedding-001":{"id":"google/gemini-embedding-001","name":"Gemini Embedding 001","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-05","release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536},"canonical_model_id":"google/gemini-embedding-001"},"google/gemini-3.8-flash-tts":{"id":"google/gemini-3.8-flash-tts","name":"Gemini 3.8 Flash TTS","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":0.5,"output":9}},"google/gemini-3.8-live-extended-thinking":{"id":"google/gemini-3.8-live-extended-thinking","name":"Gemini 3.8 Live Extended Thinking","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-09-15","last_updated":"2026-09-15","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":0.75,"output":4.5}},"google/veo-3.0-generate-001":{"id":"google/veo-3.0-generate-001","name":"Veo 3.0","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-05-20","last_updated":"2026-06-08","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"google/gemini-nano-banana-2.1":{"id":"google/gemini-nano-banana-2.1","name":"Gemini Nano Banana 2.1","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"google/gemini-nano-banana-2.1"},"google/gemini-4-argon":{"id":"google/gemini-4-argon","name":"Gemini 4 Argon","description":"Gemini multimodal model for text, image, audio, video, and document tasks","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":2,"output":10,"cache_read":0.1},"canonical_model_id":"google/gemini-4-argon"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65000},"cost":{"input":0.25,"output":1.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.1-flash-lite"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"input_audio":1},"canonical_model_id":"google/gemini-2.5-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro"},"callstack/apex":{"id":"callstack/apex","name":"Apex","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"release_date":"2026-10-08","last_updated":"2026-10-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.5,"output":3,"cache_read":0.2}},"fireworks/ember-1":{"id":"fireworks/ember-1","name":"Ember-1","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":3,"output":15,"cache_read":0.3}},"sakana/fugu-max":{"id":"sakana/fugu-max","name":"Fugu Max","description":"Multi-agent model for routing expert agents across complex analytical tasks","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"sakana/fugu-max"},"sakana/fugu-ultra-v2":{"id":"sakana/fugu-ultra-v2","name":"Fugu Ultra v2","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-08-28","release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272001}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"sakana/fugu-ultra-v2"},"sakana/namazu":{"id":"sakana/namazu","name":"Sakana Namazu","description":"Multi-agent model for routing expert agents across complex analytical tasks","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.95,"output":4,"cache_read":0.15}},"sakana/fugu-ultra":{"id":"sakana/fugu-ultra","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272001}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"sakana/fugu-ultra"},"inclusionai/ling-3.0-flash":{"id":"inclusionai/ling-3.0-flash","name":"Ling 3.0 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"release_date":"2026-08-06","last_updated":"2026-08-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.021,"output":0.063,"cache_read":0.0042}},"inclusionai/ling-3.1-flash":{"id":"inclusionai/ling-3.1-flash","name":"Ling 3.1 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.3,"output":0.9,"cache_read":0.06},"canonical_model_id":"inclusionai/ling-3.1-flash"},"inclusionai/ling-3.0-flash-sante":{"id":"inclusionai/ling-3.0-flash-sante","name":"Ling 3.0 Flash Sante","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.075,"output":0.22,"cache_read":0.015}},"inclusionai/ling-3.0-flash-vl":{"id":"inclusionai/ling-3.0-flash-vl","name":"Ling 3.0 Flash VL","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.075,"output":0.22,"cache_read":0.015}},"inclusionai/ling-3.0-flash-fin":{"id":"inclusionai/ling-3.0-flash-fin","name":"Ling 3.0 Flash Fin","description":"Finance-enhanced model for financial research, multi-step investment workflows, and long-horizon planning and execution","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"release_date":"2026-08-27","last_updated":"2026-09-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32000},"cost":{"input":0.075,"output":0.22,"cache_read":0.015},"canonical_model_id":"inclusionai/ling-3.0-flash-fin"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k3-fast":{"id":"moonshotai/kimi-k3-fast","name":"Kimi K3 Fast","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":4.5,"output":22.5,"cache_read":0.45},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.7-code-highspeed":{"id":"moonshotai/kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code High Speed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2.5":{"id":"moonshotai/kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.6,"output":3},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/kimi-k2":{"id":"moonshotai/kimi-k2","name":"Kimi K2 Instruct","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-12-31","release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.57,"output":2.3},"canonical_model_id":"moonshotai/kimi-k2"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32768},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"topaz/proteus":{"id":"topaz/proteus","name":"Proteus","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"topaz/wonder-3.5":{"id":"topaz/wonder-3.5","name":"Wonder 3.5","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0}},"topaz/starlight-precise-2.6":{"id":"topaz/starlight-precise-2.6","name":"Starlight Precise 2.6","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"nvidia/nemotron-3-nano-30b-a3b":{"id":"nvidia/nemotron-3-nano-30b-a3b","name":"Nemotron 3 Nano 30B A3B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"temperature":true,"release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.05,"output":0.2,"cache_read":0.025},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"nvidia/nemotron-3.5-lightning":{"id":"nvidia/nemotron-3.5-lightning","name":"Nemotron 3.5 Lightning 30B","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.05,"output":0.2,"cache_read":0.01},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/nemotron-nano-9b-v2":{"id":"nvidia/nemotron-nano-9b-v2","name":"Nvidia Nemotron Nano 9B V2","description":"Compact Nemotron model for efficient reasoning and deployable AI agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-08-18","last_updated":"2025-08-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.06,"output":0.23},"canonical_model_id":"nvidia/nemotron-nano-9b-v2"},"nvidia/nemotron-3-super-120b-a12b":{"id":"nvidia/nemotron-3-super-120b-a12b","name":"NVIDIA Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":false,"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32000},"cost":{"input":0.15,"output":0.65},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"nvidia/nemotron-3.5-super-vl":{"id":"nvidia/nemotron-3.5-super-vl","name":"NVIDIA Nemotron 3.5 Super VL","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.2,"output":0.5,"cache_read":0.04}},"nvidia/nemotron-3-ultra-550b-a55b":{"id":"nvidia/nemotron-3-ultra-550b-a55b","name":"Nemotron 3 Ultra","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65000},"cost":{"input":0.6,"output":2.4,"cache_read":0.12},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/nemotron-3.5-lightning-free":{"id":"nvidia/nemotron-3.5-lightning-free","name":"Nemotron 3.5 Lightning Free","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65000},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/nemotron-nano-12b-v2-vl":{"id":"nvidia/nemotron-nano-12b-v2-vl","name":"Nvidia Nemotron Nano 12B V2 VL","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-10-28","last_updated":"2025-10-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.2,"output":0.6},"canonical_model_id":"nvidia/nemotron-nano-12b-v2-vl"},"xiaomi/mimo-v2.6-pro":{"id":"xiaomi/mimo-v2.6-pro","name":"MiMo V2.6 Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"xiaomi/mimo-v2.5":{"id":"xiaomi/mimo-v2.5","name":"MiMo M2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":131100},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.5"},"xiaomi/mimo-v2.6-pro-ultraspeed":{"id":"xiaomi/mimo-v2.6-pro-ultraspeed","name":"MiMo V2.6 Pro UltraSpeed","description":"MiMo pro model for strong multimodal reasoning and agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":4.35,"output":8.7,"cache_read":0.036},"canonical_model_id":"xiaomi/mimo-v2.6-pro-ultraspeed"},"xiaomi/mimo-v2.5-pro":{"id":"xiaomi/mimo-v2.5-pro","name":"MiMo V2.5 Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":131000},"cost":{"input":0.3045,"output":0.609,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"xiaomi/mimo-v2.6-flash":{"id":"xiaomi/mimo-v2.6-flash","name":"MiMo V2.6 Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131000},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5"},"minimax/minimax-m2.1-lightning":{"id":"minimax/minimax-m2.1-lightning","name":"MiniMax M2.1 Lightning","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-12-23","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":2.4,"cache_read":0.03,"cache_write":0.375}},"minimax/minimax-h3":{"id":"minimax/minimax-h3","name":"MiniMax H3","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"minimax","attachment":true,"reasoning":false,"tool_call":false,"release_date":"2026-07-31","last_updated":"2026-10-04","modalities":{"input":["text","image"],"output":["video"]},"open_weights":true,"limit":{"context":0,"output":0},"canonical_model_id":"minimax/MiniMax-H3"},"minimax/minimax-m2.7":{"id":"minimax/minimax-m2.7","name":"Minimax M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/minimax-h3-max":{"id":"minimax/minimax-h3-max","name":"MiniMax H3 Max","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"minimax","attachment":true,"reasoning":false,"tool_call":false,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0}},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"output":512000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"minimax/minimax-m2.7-highspeed":{"id":"minimax/minimax-m2.7-highspeed","name":"MiniMax M2.7 High Speed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131100},"cost":{"input":0.6,"output":2.4,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"minimax/minimax-m2.5-highspeed":{"id":"minimax/minimax-m2.5-highspeed","name":"MiniMax M2.5 High Speed","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"release_date":"2026-02-13","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131000},"cost":{"input":0.6,"output":2.4,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5-highspeed"},"minimax/minimax-m2.1":{"id":"minimax/minimax-m2.1","name":"MiniMax M2.1","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.1"},"minimax/minimax-m2":{"id":"minimax/minimax-m2","name":"MiniMax M2","description":"Efficient open MiniMax model built for coding agents and tool-heavy workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":205000,"output":196608},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2"},"stepfun/step-5-preview":{"id":"stepfun/step-5-preview","name":"Step 5 Preview","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.95,"output":2.565,"cache_read":0.0475},"canonical_model_id":"stepfun/step-5-preview"},"stepfun/step-3.7-flash":{"id":"stepfun/step-3.7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"inception/mercury-coder-small":{"id":"inception/mercury-coder-small","name":"Mercury Coder Small Beta","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","family":"mercury","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-02-26","last_updated":"2025-02-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":16384},"cost":{"input":0.25,"output":1}},"inception/mercury-2.5":{"id":"inception/mercury-2.5","name":"Mercury 2.5","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":260000,"output":65536},"cost":{"input":0.04,"output":0.15,"cache_read":0.004}},"inception/mercury-2":{"id":"inception/mercury-2","name":"Mercury 2","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-02-24","last_updated":"2026-03-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":50000},"cost":{"input":0.25,"output":0.75,"cache_read":0.024999999999999998}},"amazon/titan-embed-text-v2":{"id":"amazon/titan-embed-text-v2","name":"Titan Text Embeddings V2","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"titan-embed","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-04-30","last_updated":"2024-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536}},"amazon/nova-2-lite":{"id":"amazon/nova-2-lite","name":"Nova 2 Lite","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"temperature":true,"knowledge":"2024-10","release_date":"2025-12-02","last_updated":"2024-12-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.3,"output":2.5,"cache_read":0.075}},"amazon/nova-lite":{"id":"amazon/nova-lite","name":"Nova Lite","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.06,"output":0.24,"cache_read":0.015,"cache_write":0.06},"canonical_model_id":"amazon/nova-lite"},"amazon/nova-pro":{"id":"amazon/nova-pro","name":"Nova Pro","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.8,"output":3.2,"cache_read":0.2,"cache_write":0.8},"canonical_model_id":"amazon/nova-pro"},"amazon/nova-micro":{"id":"amazon/nova-micro","name":"Nova Micro","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-micro","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":10000},"cost":{"input":0.035,"output":0.14,"cache_read":0.00875,"cache_write":0.035},"canonical_model_id":"amazon/nova-micro"},"mistral/codestral-embed":{"id":"mistral/codestral-embed","name":"Codestral Embed","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"codestral-embed","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536}},"mistral/mistral-nemo":{"id":"mistral/mistral-nemo","name":"Mistral Nemo","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-07-18","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":131072},"cost":{"input":0.029,"output":0.03}},"mistral/mistral-large-4":{"id":"mistral/mistral-large-4","name":"Mistral Large 4","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":262144},"cost":{"input":0.68,"output":2.09,"cache_read":0.07}},"mistral/mistral-medium-3.5":{"id":"mistral/mistral-medium-3.5","name":"Mistral Medium Latest","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-05-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":256000},"cost":{"input":1.5,"output":7.5,"cache_read":0.15}},"mistral/mistral-small":{"id":"mistral/mistral-small","name":"Mistral Small (latest)","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2024-09-17","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":4000},"cost":{"input":0.15,"output":0.6,"cache_read":0.015}},"mistral/mistral-large-3":{"id":"mistral/mistral-large-3","name":"Mistral Large 3","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-10","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":256000},"cost":{"input":0.5,"output":1.5,"cache_read":0.05}},"mistral/mistral-embed":{"id":"mistral/mistral-embed","name":"Mistral Embed","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"mistral-embed","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2023-12-11","last_updated":"2023-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536}},"mistral/ministral-14b":{"id":"mistral/ministral-14b","name":"Ministral 14B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-10","release_date":"2025-12-02","last_updated":"2025-12-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":256000},"cost":{"input":0.2,"output":0.2,"cache_read":0.02}},"mistral/codestral":{"id":"mistral/codestral","name":"Codestral (latest)","description":"Mistral code model for completions, refactors, and developer IDE workflows","family":"codestral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-05-29","last_updated":"2025-01-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":4096},"cost":{"input":0.3,"output":0.9,"cache_read":0.03}},"mistral/ministral-8b":{"id":"mistral/ministral-8b","name":"Ministral 8B (latest)","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-10-01","last_updated":"2024-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":128000},"cost":{"input":0.1,"output":0.1}},"mistral/ministral-3b":{"id":"mistral/ministral-3b","name":"Ministral 3B (latest)","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-10-01","last_updated":"2024-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":128000},"cost":{"input":0.04,"output":0.04}},"fish-audio/s2.1-pro":{"id":"fish-audio/s2.1-pro","name":"S2.1 Pro","description":"Speech generation model for controllable voice, narration, and audio delivery","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-07-28","last_updated":"2026-07-28","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"fish-audio/drama-3":{"id":"fish-audio/drama-3","name":"Drama 3","description":"Speech generation model for controllable voice, narration, and audio delivery","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"fish-audio/s1":{"id":"fish-audio/s1","name":"S1","description":"Speech generation model for controllable voice, narration, and audio delivery","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2025-10-20","last_updated":"2025-10-20","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"fish-audio/transcribe-1":{"id":"fish-audio/transcribe-1","name":"Transcribe-1","description":"Speech transcription model for accurate audio-to-text and captioning workflows","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-03-01","last_updated":"2026-03-01","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0}},"fish-audio/s2-pro":{"id":"fish-audio/s2-pro","name":"S2 Pro","description":"Speech generation model for controllable voice, narration, and audio delivery","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"morph/morph-v3-fast":{"id":"morph/morph-v3-fast","name":"Morph v3 Fast","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"morph","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-08-15","last_updated":"2024-08-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16000,"output":16000},"cost":{"input":0.8,"output":1.2}},"morph/morph-v3-large":{"id":"morph/morph-v3-large","name":"Morph v3 Large","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"morph","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-08-15","last_updated":"2024-08-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":32000},"cost":{"input":0.9,"output":1.9}},"openai/gpt-4.1-mini-fast":{"id":"openai/gpt-4.1-mini-fast","name":"GPT-4.1 mini (Fast)","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"input":1014808,"output":32768},"cost":{"input":0.7,"output":2.8,"cache_read":0.175},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/o3-fast":{"id":"openai/o3-fast","name":"o3 (Fast)","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":100000,"output":100000},"cost":{"input":3.5,"output":14,"cache_read":0.875},"canonical_model_id":"openai/o3"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT 5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT 5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.4-pro"},"openai/gpt-oss-safeguard-120b":{"id":"openai/gpt-oss-safeguard-120b","name":"GPT OSS Safeguard 120B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":112000,"output":16000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-safeguard-120b"},"openai/gpt-3.5-turbo":{"id":"openai/gpt-3.5-turbo","name":"GPT-3.5 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2021-09","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"input":12289,"output":4096},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"openai/gpt-3.5-turbo"},"openai/gpt-5.2-fast":{"id":"openai/gpt-5.2-fast","name":"GPT 5.2 (Fast)","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":3.5,"output":28,"cache_read":0.35},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-4o-transcribe":{"id":"openai/gpt-4o-transcribe","name":"GPT-4o Transcribe","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-03-13","last_updated":"2024-03-13","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":2.5,"output":10}},"openai/gpt-5.5-pro":{"id":"openai/gpt-5.5-pro","name":"GPT 5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":872000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.5-pro"},"openai/text-embedding-3-small":{"id":"openai/text-embedding-3-small","name":"text-embedding-3-small","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"input":6656,"output":1536}},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT 5.4 Nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-realtime-2.1":{"id":"openai/gpt-realtime-2.1","name":"gpt-realtime-2.1","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gpt","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-09-30","release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":128000,"input":96000,"output":32000},"cost":{"input":4,"output":24,"cache_read":0.4},"canonical_model_id":"openai/gpt-realtime-2.1"},"openai/gpt-5.2-codex":{"id":"openai/gpt-5.2-codex","name":"GPT-5.2-Codex","description":"Code-specialist GPT for repository edits, reviews, and long-running software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-codex"},"openai/gpt-4o-fast":{"id":"openai/gpt-4o-fast","name":"GPT-4o (Fast)","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":111616,"output":16384},"cost":{"input":4.25,"output":17,"cache_read":2.125},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-5.1-codex":{"id":"openai/gpt-5.1-codex","name":"GPT-5.1-Codex","description":"Codex GPT for repository edits, code review, and practical software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.13},"canonical_model_id":"openai/gpt-5.1-codex"},"openai/gpt-6.1-sol-fast":{"id":"openai/gpt-6.1-sol-fast","name":"GPT-6.1 Sol (Fast)","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.4,"cache_write":10,"tier":{"type":"context","size":272001}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.4,"cache_write":10}},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-live-1":{"id":"openai/gpt-live-1","name":"GPT-Live 1","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"openai/gpt-realtime-1.5":{"id":"openai/gpt-realtime-1.5","name":"GPT-Realtime-1.5","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":4,"output":16,"cache_read":0.4}},"openai/gpt-4.1-nano-fast":{"id":"openai/gpt-4.1-nano-fast","name":"GPT-4.1 nano (Fast)","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"input":1014808,"output":32768},"cost":{"input":0.2,"output":0.8,"cache_read":0.05},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5-codex":{"id":"openai/gpt-5-codex","name":"GPT-5-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.13},"canonical_model_id":"openai/gpt-5-codex"},"openai/gpt-image-2":{"id":"openai/gpt-image-2","name":"GPT Image 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":30,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-2"},"openai/gpt-5.6-luna-fast":{"id":"openai/gpt-5.6-luna-fast","name":"GPT 5.6 Luna (Fast)","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.4,"output":2.4,"cache_read":0.04,"cache_write":0.5,"tiers":[{"input":0.8,"output":3.6,"cache_read":0.08,"cache_write":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.8,"output":3.6,"cache_read":0.08,"cache_write":1}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-6-astra-fast":{"id":"openai/gpt-6-astra-fast","name":"GPT-6 Astra (Fast)","description":"Fast variant of GPT-6 Astra for low-latency assistance and high-volume workloads.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":20,"output":100,"cache_read":2,"cache_write":25,"tiers":[{"input":40,"output":150,"cache_read":4,"cache_write":50,"tier":{"type":"context","size":272001}}],"context_over_200k":{"input":40,"output":150,"cache_read":4,"cache_write":50}},"canonical_model_id":"openai/gpt-6-astra-fast"},"openai/gpt-5.2-pro":{"id":"openai/gpt-5.2-pro","name":"GPT 5.2 ","description":"Higher-accuracy GPT-5.2 variant for tougher reasoning and review workflows","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":21,"output":168},"canonical_model_id":"openai/gpt-5.2-pro"},"openai/gpt-5.1-thinking-fast":{"id":"openai/gpt-5.1-thinking-fast","name":"GPT 5.1 Thinking (Fast)","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"release_date":"2025-11-12","last_updated":"2025-11-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":2.5,"output":20,"cache_read":0.25}},"openai/text-embedding-ada-002":{"id":"openai/text-embedding-ada-002","name":"text-embedding-ada-002","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2022-12-15","last_updated":"2022-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"input":6656,"output":1536}},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT 5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/whisper-1":{"id":"openai/whisper-1","name":"Whisper","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"whisper","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2022-09-21","last_updated":"2022-09-21","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0}},"openai/gpt-5.3-codex-fast":{"id":"openai/gpt-5.3-codex-fast","name":"GPT 5.3 Codex (Fast)","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":3.5,"output":28,"cache_read":0.35},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-5.5-fast":{"id":"openai/gpt-5.5-fast","name":"GPT 5.5 (Fast)","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":872000,"output":128000},"cost":{"input":12.5,"output":75,"cache_read":1.25},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-image-2.5-flare":{"id":"openai/gpt-image-2.5-flare","name":"GPT Image 2.5 Flare","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":30,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-2.5-flare"},"openai/gpt-5.4-fast":{"id":"openai/gpt-5.4-fast","name":"GPT 5.4 (Fast)","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.6-sol-fast":{"id":"openai/gpt-5.6-sol-fast","name":"GPT 5.6 Sol (Fast)","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":8,"output":40,"cache_read":0.8,"cache_write":10,"tiers":[{"input":16,"output":60,"cache_read":1.6,"cache_write":20,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":16,"output":60,"cache_read":1.6,"cache_write":20}},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/o4-mini-fast":{"id":"openai/o4-mini-fast","name":"o4-mini (Fast)","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":100000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o4-mini"},"openai/gpt-5-pro":{"id":"openai/gpt-5-pro","name":"GPT-5 pro","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":128000,"output":272000},"cost":{"input":15,"output":120},"canonical_model_id":"openai/gpt-5-pro"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272001}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-5.1-thinking":{"id":"openai/gpt-5.1-thinking","name":"GPT 5.1 Thinking","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-11-12","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125}},"openai/text-embedding-3-large":{"id":"openai/text-embedding-3-large","name":"text-embedding-3-large","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"input":6656,"output":1536}},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272001}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"openai/gpt-5.4-mini-fast":{"id":"openai/gpt-5.4-mini-fast","name":"GPT 5.4 Mini (Fast)","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.5,"output":9,"cache_read":0.15},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-realtime-mini":{"id":"openai/gpt-realtime-mini","name":"GPT-Realtime mini","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-10-10","last_updated":"2025-10-10","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":0.6,"output":2.4,"cache_read":0.06}},"openai/gpt-5-mini-fast":{"id":"openai/gpt-5-mini-fast","name":"GPT-5 mini (Fast)","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.45,"output":3.6,"cache_read":0.045},"canonical_model_id":"openai/gpt-5-mini"},"openai/o3-pro":{"id":"openai/o3-pro","name":"o3 Pro","description":"High-effort o3 tier for difficult technical reasoning and careful answers","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-06-10","last_updated":"2025-06-10","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":100000,"output":100000},"cost":{"input":20,"output":80},"canonical_model_id":"openai/o3-pro"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":122880,"output":8192},"cost":{"input":0.03,"output":0.14},"canonical_model_id":"openai/gpt-oss-20b"},"openai/gpt-oss-safeguard-20b":{"id":"openai/gpt-oss-safeguard-20b","name":"gpt-oss-safeguard-20b","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":112000,"output":16000},"cost":{"input":0.07,"output":0.2},"canonical_model_id":"openai/gpt-oss-safeguard-20b"},"openai/gpt-image-2.5-sunburst":{"id":"openai/gpt-image-2.5-sunburst","name":"GPT Image 2.5 Sunburst","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":30,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-2.5-sunburst"},"openai/gpt-5.6-terra-fast":{"id":"openai/gpt-5.6-terra-fast","name":"GPT 5.6 Terra (Fast)","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":24,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":36,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":36,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-image-1":{"id":"openai/gpt-image-1","name":"GPT Image 1","description":"OpenAI image model for production generation, edits, and brand-safe visual workflows","family":"gpt-image","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-04-24","last_updated":"2025-04-24","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":40,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-1"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT 5.4 Mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT 5.6 Luna","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.1-codex-max":{"id":"openai/gpt-5.1-codex-max","name":"GPT 5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex-max"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT 5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":872000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-6-sol-fast":{"id":"openai/gpt-6-sol-fast","name":"GPT-6 Sol (Fast)","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272001}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-6-sol"},"openai/tts-1":{"id":"openai/tts-1","name":"TTS-1","description":"Speech generation model for controllable voice, narration, and audio delivery","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2023-11-06","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"openai/gpt-6-luna-fast":{"id":"openai/gpt-6-luna-fast","name":"GPT-6 Luna (Fast)","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.5,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272001}}],"context_over_200k":{"input":0.4,"output":1.5,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-5-fast":{"id":"openai/gpt-5-fast","name":"GPT-5 (Fast)","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":2.5,"output":20,"cache_read":0.25},"canonical_model_id":"openai/gpt-5"},"openai/gpt-realtime-2":{"id":"openai/gpt-realtime-2","name":"gpt-realtime-2","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":4,"output":24,"cache_read":0.4}},"openai/gpt-4.1-fast":{"id":"openai/gpt-4.1-fast","name":"GPT-4.1 (Fast)","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"input":1014808,"output":32768},"cost":{"input":3.5,"output":14,"cache_read":0.875},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272001}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-image-1-mini":{"id":"openai/gpt-image-1-mini","name":"GPT Image 1 Mini","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":2,"output":8,"cache_read":0.2}},"openai/gpt-4o-mini-transcribe":{"id":"openai/gpt-4o-mini-transcribe","name":"GPT-4o mini Transcribe","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"o-mini","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-03-13","last_updated":"2024-03-13","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":1.25,"output":5}},"openai/gpt-image-1.5":{"id":"openai/gpt-image-1.5","name":"GPT Image 1.5","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-11-25","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":32,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-1.5"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT 5.6 Terra","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.1,"output":0.5,"cache_read":0.1},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-5.1-codex-mini":{"id":"openai/gpt-5.1-codex-mini","name":"GPT-5.1 Codex mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.03},"canonical_model_id":"openai/gpt-5.1-codex-mini"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT 5.6 Sol","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-4o-mini-fast":{"id":"openai/gpt-4o-mini-fast","name":"GPT-4o mini (Fast)","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":111616,"output":16384},"cost":{"input":0.25,"output":1,"cache_read":0.125},"canonical_model_id":"openai/gpt-4o-mini"},"openai/gpt-realtime-whisper":{"id":"openai/gpt-realtime-whisper","name":"gpt-realtime-whisper","description":"Streaming speech-to-text model for low-latency transcript deltas from live audio","family":"whisper","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0},"canonical_model_id":"openai/gpt-realtime-whisper"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272001}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"openai/tts-1-hd":{"id":"openai/tts-1-hd","name":"TTS-1 HD","description":"Speech generation model for controllable voice, narration, and audio delivery","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2023-11-06","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":2.5,"output":20,"cache_read":0.25},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":0.625,"output":5,"cache_read":0.0625},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"openai/o3":{"id":"openai/o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"experimental":{"modes":{"fast":{"cost":{"input":3.5,"output":14,"cache_read":0.875},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":1,"output":4,"cache_read":0.25},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":2,"output":8,"cache_read":0.5}},"openai/gpt-4-turbo":{"id":"openai/gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":10,"output":30}},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"experimental":{"modes":{"fast":{"cost":{"input":0.7,"output":2.8,"cache_read":0.175},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.4,"output":1.6,"cache_read":0.1}},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"experimental":{"modes":{"fast":{"cost":{"input":3.5,"output":14,"cache_read":0.875},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2,"output":8,"cache_read":0.5}},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"experimental":{"modes":{"fast":{"cost":{"input":0.25,"output":1,"cache_read":0.125},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.15,"output":0.6,"cache_read":0.075}},"openai/o1":{"id":"openai/o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":15,"output":60,"cache_read":7.5}},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"flex":{"cost":{"input":0.025,"output":0.2,"cache_read":0.0025},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":0.05,"output":0.4,"cache_read":0.005}},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"status":"deprecated","experimental":{"modes":{"fast":{"cost":{"input":0.2,"output":0.8,"cache_read":0.05},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.1,"output":0.4,"cache_read":0.025}},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":1.1,"output":4.4,"cache_read":0.55}},"openai/o4-mini":{"id":"openai/o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","experimental":{"modes":{"fast":{"cost":{"input":2,"output":8,"cache_read":0.5},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":0.55,"output":2.2,"cache_read":0.138},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":1.1,"output":4.4,"cache_read":0.275}},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":0.45,"output":3.6,"cache_read":0.045},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":0.125,"output":1,"cache_read":0.0125},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":0.25,"output":2,"cache_read":0.025}},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"experimental":{"modes":{"fast":{"cost":{"input":4.25,"output":17,"cache_read":2.125},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2.5,"output":10,"cache_read":1.25}},"microsoft/mai-voice-2.1-flash":{"id":"microsoft/mai-voice-2.1-flash","name":"MAI-Voice-2.1-Flash","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mai","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-10-01","last_updated":"2026-10-01","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"microsoft/mai-image-2.6":{"id":"microsoft/mai-image-2.6","name":"MAI-Image-2.6","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"mai","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":38}},"microsoft/mai-transcribe-2-streaming":{"id":"microsoft/mai-transcribe-2-streaming","name":"MAI-Transcribe-2-Streaming","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"mai","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-10-01","last_updated":"2026-10-01","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0}},"microsoft/mai-transcribe-2":{"id":"microsoft/mai-transcribe-2","name":"MAI-Transcribe 2","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"mai","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-09-03","last_updated":"2026-09-03","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0}},"microsoft/mai-image-2.6-flash":{"id":"microsoft/mai-image-2.6-flash","name":"MAI-Image-2.6-Flash","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"mai","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":1.75,"output":19}},"microsoft/mai-voice-2":{"id":"microsoft/mai-voice-2","name":"MAI-Voice-2","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mai","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"microsoft/mai-voice-2.1":{"id":"microsoft/mai-voice-2.1","name":"MAI-Voice-2.1","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mai","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-10-01","last_updated":"2026-10-01","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"microsoft/mai-voice-2-flash":{"id":"microsoft/mai-voice-2-flash","name":"MAI-Voice-2-Flash","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mai","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-07-23","last_updated":"2026-07-23","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}}}},"zai-coding-plan":{"id":"zai-coding-plan","env":["ZHIPU_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.z.ai/api/coding/paas/v4","name":"Z.AI Coding Plan","doc":"https://docs.z.ai/devpack/overview","models":{"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"glm-5.3-highspeed":{"id":"glm-5.3-highspeed","name":"GLM-5.3 Highspeed","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"glm-5.2-highspeed":{"id":"glm-5.2-highspeed","name":"GLM-5.2 Highspeed","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"glm-4.7":{"id":"glm-4.7","name":"GLM-4.7","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5-turbo":{"id":"glm-5-turbo","name":"GLM-5-Turbo","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"}}},"ebcloud":{"id":"ebcloud","env":["EBCLOUD_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://maas-api.ebcloud.com/v1","name":"EBCloud","doc":"https://docs.ebtech.com/ai/model-api.html","models":{"Kimi-K2.6":{"id":"Kimi-K2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.9286,"output":3.8571},"canonical_model_id":"moonshotai/kimi-k2.6"},"GLM-5.1":{"id":"GLM-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.8571,"output":3.4286},"canonical_model_id":"zhipuai/glm-5.1"},"DeepSeek-V4-Flash":{"id":"DeepSeek-V4-Flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.143,"output":0.2857},"canonical_model_id":"deepseek/deepseek-v4-flash"},"DeepSeek-V4-Pro":{"id":"DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.4286,"output":0.8571},"canonical_model_id":"deepseek/deepseek-v4-pro"}}},"greenpt":{"id":"greenpt","env":["GREENPT_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.greenpt.ai/v1","name":"GreenPT","doc":"https://docs.greenpt.ai","models":{"glm-5.2-honey-ultra":{"id":"glm-5.2-honey-ultra","name":"GLM-5.2 Honey Ultra","description":"glm-5.2 carrying a built-in ruleset that compresses both generated code and prose. The most aggressive tier, close to answer-only. Same upstream model and price per token as glm-5.2, with fewer output tokens.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.254,"output":5.016,"cache_read":0.3135},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.2-ponytail-lite":{"id":"glm-5.2-ponytail-lite","name":"GLM-5.2 Ponytail Lite","description":"glm-5.2 carrying a built-in ruleset that compresses generated code, preferring platform features over custom code. The gentlest tier: it cuts filler only and keeps the explanation intact. Same upstream model and price per token as glm-5.2, with fewer output tokens.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.254,"output":5.016,"cache_read":0.3135},"canonical_model_id":"zhipuai/glm-5.2"},"gemma-3-27b-it":{"id":"gemma-3-27b-it","name":"Gemma 3 27B","description":"Google Gemma 3 multimodal model for chat, reasoning, and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":40000,"output":8192},"cost":{"input":0.342,"output":0.684}},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.127754,"output":0.511016,"cache_read":0.0255508},"canonical_model_id":"zhipuai/glm-5.3-flash"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.1596,"output":0.399,"cache_read":0.0456},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"qwen3-235b-a22b-instruct-2507":{"id":"qwen3-235b-a22b-instruct-2507","name":"Qwen3 235B A22B Instruct 2507","description":"Qwen3 235B MoE instruct model for long-context multilingual chat and reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":1.026,"output":3.078}},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3.762,"output":18.81,"cache_read":0.9405},"canonical_model_id":"moonshotai/kimi-k3"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.255552,"output":1.27776,"cache_read":0.0127776},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"minimax-m2.5":{"id":"minimax-m2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.1938,"output":1.129,"cache_read":0.0627},"canonical_model_id":"minimax/MiniMax-M2.5"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.7524,"output":4.275,"cache_read":0.2508},"canonical_model_id":"moonshotai/kimi-k2.6"},"green-s":{"id":"green-s","name":"Green S","description":"GreenPT speech-to-text model for pre-recorded and live transcription","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-01","last_updated":"2025-01","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":8192},"cost":{"input":0.00437,"output":0}},"green-l":{"id":"green-l","name":"Green L","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.285,"output":0.912},"canonical_model_id":"mistral/mistral-small-2506"},"qwen3-coder-30b-a3b-instruct":{"id":"qwen3-coder-30b-a3b-instruct","name":"Qwen3-Coder 30B-A3B Instruct","description":"Smaller Qwen coder for efficient local agents and repo-level fixes","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.285,"output":1.083},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"llama-3.3-70b-instruct":{"id":"llama-3.3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":100000,"output":16384},"cost":{"input":1.254,"output":1.254},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"gemma4":{"id":"gemma4","name":"gemma4","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.57,"output":1.71},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"qwen3.6-35b-a3b":{"id":"qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.342,"output":2.052},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"pixtral-12b-2409":{"id":"pixtral-12b-2409","name":"Pixtral 12B","description":"Mistral vision-language model for image understanding and multimodal chat","family":"pixtral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2024-09-01","last_updated":"2024-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.285,"output":0.285},"canonical_model_id":"mistral/pixtral-12b"},"glm-5.2-honey":{"id":"glm-5.2-honey","name":"GLM-5.2 Honey","description":"glm-5.2 carrying a built-in ruleset that compresses both generated code and prose. The middle tier, and the ruleset as its authors wrote it. Same upstream model and price per token as glm-5.2, with fewer output tokens.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.254,"output":5.016,"cache_read":0.3135},"canonical_model_id":"zhipuai/glm-5.2"},"holo2-30b-a3b":{"id":"holo2-30b-a3b","name":"Holo2 30B A3B","description":"H Company Holo2 vision model for GUI navigation and computer-use agents","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-11","last_updated":"2025-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":22016,"output":16384},"cost":{"input":0.399,"output":0.969}},"green-r-raw":{"id":"green-r-raw","name":"Green R Raw","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.399,"output":1.083},"canonical_model_id":"openai/gpt-oss-120b"},"green-s-pro":{"id":"green-s-pro","name":"Green S Pro","description":"GreenPT advanced speech-to-text model with multilingual transcription support","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-02","last_updated":"2025-02","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":8192},"cost":{"input":0.00437,"output":0}},"devstral-2-123b-instruct-2512":{"id":"devstral-2-123b-instruct-2512","name":"Devstral 2","description":"Mistral's coding-agent model for repository work, terminal tasks, and software fixes","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":16384},"cost":{"input":0.57,"output":2.736},"canonical_model_id":"mistral/devstral-2512"},"mistral-medium-3.5-128b":{"id":"mistral-medium-3.5-128b","name":"Mistral Medium 3.5","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":2.052,"output":10.26},"canonical_model_id":"mistral/mistral-medium-2604"},"qwen3.5-397b-a17b":{"id":"qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.798,"output":4.959},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.254,"output":5.016,"cache_read":0.3135},"canonical_model_id":"zhipuai/glm-5.2"},"voxtral-small-24b-2507":{"id":"voxtral-small-24b-2507","name":"Voxtral Small 24B","description":"Mistral Voxtral audio-understanding model for speech and transcription tasks","family":"mistral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-07","release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"cost":{"input":0.228,"output":0.513}},"green-l-raw":{"id":"green-l-raw","name":"Green L Raw","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.285,"output":0.912},"canonical_model_id":"mistral/mistral-small-2506"},"glm-5.2-ponytail-ultra":{"id":"glm-5.2-ponytail-ultra","name":"GLM-5.2 Ponytail Ultra","description":"glm-5.2 carrying a built-in ruleset that compresses generated code, preferring platform features over custom code. The most aggressive tier, close to answer-only. Same upstream model and price per token as glm-5.2, with fewer output tokens.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.254,"output":5.016,"cache_read":0.3135},"canonical_model_id":"zhipuai/glm-5.2"},"green-r":{"id":"green-r","name":"Green R","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.399,"output":1.083},"canonical_model_id":"openai/gpt-oss-120b"},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"status":"deprecated","cost":{"input":1.756,"output":5.518},"canonical_model_id":"zhipuai/glm-5.1"},"mistral-small-3.2-24b-instruct-2506":{"id":"mistral-small-3.2-24b-instruct-2506","name":"Mistral Small 3.2","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.228,"output":0.456},"canonical_model_id":"mistral/mistral-small-2506"},"glm-5.2-caveman":{"id":"glm-5.2-caveman","name":"GLM-5.2 Caveman","description":"glm-5.2 carrying a built-in ruleset that compresses prose, keeping code and technical detail verbatim. The middle tier, and the ruleset as its authors wrote it. Same upstream model and price per token as glm-5.2, with fewer output tokens.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.254,"output":5.016,"cache_read":0.3135},"canonical_model_id":"zhipuai/glm-5.2"},"kimi-k2.6-fast":{"id":"kimi-k2.6-fast","name":"Kimi K2.6 Fast","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":1.655,"output":8.778},"canonical_model_id":"moonshotai/kimi-k2.6"},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.228,"output":0.798},"canonical_model_id":"openai/gpt-oss-120b"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.27754,"output":5.11016,"cache_read":0.319385},"canonical_model_id":"zhipuai/glm-5.3"},"glm-5.2-caveman-ultra":{"id":"glm-5.2-caveman-ultra","name":"GLM-5.2 Caveman Ultra","description":"glm-5.2 carrying a built-in ruleset that compresses prose, keeping code and technical detail verbatim. The most aggressive tier, close to answer-only. Same upstream model and price per token as glm-5.2, with fewer output tokens.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.254,"output":5.016,"cache_read":0.3135},"canonical_model_id":"zhipuai/glm-5.2"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.9006,"output":4.389,"cache_read":0.1881},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"glm-5.2-ponytail":{"id":"glm-5.2-ponytail","name":"GLM-5.2 Ponytail","description":"glm-5.2 carrying a built-in ruleset that compresses generated code, preferring platform features over custom code. The middle tier, and the ruleset as its authors wrote it. Same upstream model and price per token as glm-5.2, with fewer output tokens.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.254,"output":5.016,"cache_read":0.3135},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.2-honey-lite":{"id":"glm-5.2-honey-lite","name":"GLM-5.2 Honey Lite","description":"glm-5.2 carrying a built-in ruleset that compresses both generated code and prose. The gentlest tier: it cuts filler only and keeps the explanation intact. Same upstream model and price per token as glm-5.2, with fewer output tokens.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.254,"output":5.016,"cache_read":0.3135},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.2-caveman-lite":{"id":"glm-5.2-caveman-lite","name":"GLM-5.2 Caveman Lite","description":"glm-5.2 carrying a built-in ruleset that compresses prose, keeping code and technical detail verbatim. The gentlest tier: it cuts filler only and keeps the explanation intact. Same upstream model and price per token as glm-5.2, with fewer output tokens.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.254,"output":5.016,"cache_read":0.3135},"canonical_model_id":"zhipuai/glm-5.2"}}},"mixlayer":{"id":"mixlayer","env":["MIXLAYER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://models.mixlayer.ai/v1","name":"Mixlayer","doc":"https://docs.mixlayer.com","models":{"qwen/qwen3.5-27b":{"id":"qwen/qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.3,"output":2.4}},"qwen/qwen3.5-122b-a10b":{"id":"qwen/qwen3.5-122b-a10b","name":"Qwen3.5 122B A10B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.4,"output":3.2}},"qwen/qwen3.5-9b":{"id":"qwen/qwen3.5-9b","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.1,"output":0.4}},"qwen/qwen3.5-35b-a3b":{"id":"qwen/qwen3.5-35b-a3b","name":"Qwen3.5 35B A3B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.25,"output":1.3}},"qwen/qwen3.5-397b-a17b":{"id":"qwen/qwen3.5-397b-a17b","name":"Qwen3.5 397B A17B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":3.6}}}},"hyper":{"id":"hyper","env":["HYPER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://hyper.charm.land/v1","name":"Charm Hyper","doc":"https://hyper.charm.land","models":{"qwen3.7-max":{"id":"qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-05-28","last_updated":"2026-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":2.5,"output":7.5,"cache_read":0.5},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen3.8-27b":{"id":"qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.5,"output":3,"cache_read":0.1},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen3.8-2.4t-a95b":{"id":"qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-31","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.16332,"output":0.5444,"cache_read":0.031575},"canonical_model_id":"zhipuai/glm-5.3-flash"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-08-02","last_updated":"2026-08-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.44,"output":1.32,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max Preview","description":"Preview Qwen flagship for million-token multimodal reasoning and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-19","last_updated":"2026-07-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-max-preview"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-27","last_updated":"2026-07-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":16000},"cost":{"input":3.2664,"output":16.332,"cache_read":0.32664},"canonical_model_id":"moonshotai/kimi-k3"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":0.33,"output":1.31,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"qwen3.7-flash":{"id":"qwen3.7-flash","name":"Qwen3.7 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-27","last_updated":"2026-07-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":991808,"output":64000},"cost":{"input":0.2,"output":0.8,"cache_read":0.04},"canonical_model_id":"alibaba/qwen3.7-flash"},"kimi-k2-thinking":{"id":"kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Thinking Kimi model for slower research passes, planning, and hard technical questions","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":26214},"cost":{"input":0.6,"output":2.5,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"gemma-4-26b-a4b-it":{"id":"gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-30","last_updated":"2026-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":25600},"cost":{"input":0.098,"output":0.334,"cache_read":0.049},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"minimax-m2.7":{"id":"minimax-m2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-06-05","last_updated":"2026-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262100,"output":6553},"cost":{"input":0.484,"output":1.852,"cache_read":0.242},"canonical_model_id":"minimax/MiniMax-M2.7"},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":262144},"cost":{"input":1.437216,"output":4.311648,"cache_read":0.047907},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"inkling":{"id":"inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-08-15","last_updated":"2026-09-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":1.0888,"output":4.40964,"cache_read":0.185096},"canonical_model_id":"thinkingmachines/inkling"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-31","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"output":512000},"cost":{"input":0.32664,"output":1.30656,"cache_read":0.064239},"canonical_model_id":"minimax/MiniMax-M3"},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-flash"},"prism":{"id":"prism","name":"Prism","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":true,"release_date":"1970-01-01","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":16000},"cost":{"input":3.2664,"output":16.332,"cache_read":0.32664}},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-30","last_updated":"2026-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32768},"cost":{"input":1.52432,"output":4.79072,"cache_read":0.152432},"canonical_model_id":"zhipuai/glm-5.2"},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-13","last_updated":"2026-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":13107},"cost":{"input":0.178,"output":0.68,"cache_read":0.089},"canonical_model_id":"openai/gpt-oss-120b"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":1.52432,"output":4.79072,"cache_read":0.283088},"canonical_model_id":"zhipuai/glm-5.3"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-07-03","last_updated":"2026-07-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16000},"cost":{"input":1.03436,"output":4.3552,"cache_read":0.206872},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-15","last_updated":"2026-07-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":1.2,"output":4.8,"cache_read":0.24},"canonical_model_id":"alibaba/qwen3.7-plus"}}},"jalapeno":{"id":"jalapeno","env":["JALAPENO_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.jalapeno-cloud.ai/v1","name":"Jalapeno Cloud","doc":"https://www.jalapeno-cloud.ai/docs/","models":{"Qwen3-VL-235B-A22B-Instruct":{"id":"Qwen3-VL-235B-A22B-Instruct","name":"Qwen3 VL 235B A22B Instruct","description":"Qwen vision-language instruct model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":129024,"output":32768},"cost":{"input":0.3,"output":1.5},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"MiniMax-M3":{"id":"MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":512000},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M3"},"Qwen3-Next-80B-A3B-Instruct":{"id":"Qwen3-Next-80B-A3B-Instruct","name":"Qwen3-Next 80B-A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":129024,"output":32768},"cost":{"input":0.15,"output":1.5},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"GLM-5.1":{"id":"GLM-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":1.38,"output":4.4},"canonical_model_id":"zhipuai/glm-5.1"},"Hy3":{"id":"Hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"input":192000,"output":128000},"cost":{"input":0.14,"output":0.58},"canonical_model_id":"tencent/hy3"},"GLM-5.2":{"id":"GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4},"canonical_model_id":"zhipuai/glm-5.2"},"Qwen3-VL-235B-A22B-Thinking":{"id":"Qwen3-VL-235B-A22B-Thinking","name":"Qwen3 VL 235B A22B Thinking","description":"Qwen vision-language thinking model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.98,"output":3.95},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-thinking"},"Qwen3.5-27B":{"id":"Qwen3.5-27B","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.3,"output":2.4},"canonical_model_id":"alibaba/qwen3.5-27b"},"Kimi-K3":{"id":"Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15},"canonical_model_id":"moonshotai/kimi-k3"},"Qwen3-Next-80B-A3B-Thinking":{"id":"Qwen3-Next-80B-A3B-Thinking","name":"Qwen3-Next 80B-A3B (Thinking)","description":"Efficient Qwen thinking model for local reasoning, math, and coding agents","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":1.5},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-thinking"},"DeepSeek-V4-Flash":{"id":"DeepSeek-V4-Flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.14,"output":0.28},"canonical_model_id":"deepseek/deepseek-v4-flash"},"DeepSeek-V4-Pro":{"id":"DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":1.6,"output":3.38},"canonical_model_id":"deepseek/deepseek-v4-pro"},"Qwen3.5-35B-A3B":{"id":"Qwen3.5-35B-A3B","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.25,"output":2},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"Qwen3.5-122B-A10B":{"id":"Qwen3.5-122B-A10B","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.4,"output":3.2},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"Qwen3.5-397B-A17B":{"id":"Qwen3.5-397B-A17B","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.6,"output":3.6},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"Kimi-K2.7-Code":{"id":"Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":271360,"output":262144},"cost":{"input":0.95,"output":4},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"Kimi-K2.5":{"id":"Kimi-K2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":180224},"cost":{"input":0.6,"output":3},"canonical_model_id":"moonshotai/kimi-k2.5"}}},"dinference":{"id":"dinference","env":["DINFERENCE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.dinference.com/v1","name":"DInference","doc":"https://dinference.com","models":{"glm-5":{"id":"glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.75,"output":2.4},"canonical_model_id":"zhipuai/glm-5"},"minimax-m2.5":{"id":"minimax-m2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"cost":{"input":0.22,"output":0.88},"canonical_model_id":"minimax/MiniMax-M2.5"},"glm-4.7":{"id":"glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.45,"output":1.65},"canonical_model_id":"zhipuai/glm-4.7"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":1.25,"output":3.89},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":1.25,"output":3.89},"canonical_model_id":"zhipuai/glm-5.1"},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-08","last_updated":"2025-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.0675,"output":0.27}}}},"neosmith":{"id":"neosmith","env":["NEOSMITH_API_KEY"],"npm":"@ai-sdk/openai","api":"https://router.neosmith.ai/v1","name":"NeoSmith","doc":"https://neosmith.ai/docs","models":{"neosmith.neolite":{"id":"neosmith.neolite","name":"NeoSmith NeoLite","description":"Sealed single-model budget tier. 512K context, text and images, tool use, and no escalation of any kind.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-20","last_updated":"2026-08-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":512000,"output":64000},"cost":{"input":0.6,"output":2.4,"cache_read":0.08,"cache_write":0}},"neosmith.intelligent-maestro":{"id":"neosmith.intelligent-maestro","name":"NeoSmith Maestro","description":"Highest-accuracy coding tier. Hard, self-contained problems run NeoSmith's premium multi-model solver; everything else gets the strongest intelligence tier.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.4,"output":12,"cache_read":0.35,"cache_write":0}},"neosmith.intelligent-pro":{"id":"neosmith.intelligent-pro","name":"NeoSmith Pro","description":"Default production tier. Intelligent NeoSmith routing with a Claude Opus ceiling on escalation.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-26","last_updated":"2026-07-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":1.81,"output":8.39,"cache_read":0.3,"cache_write":0}},"neosmith.intelligent-basic":{"id":"neosmith.intelligent-basic","name":"NeoSmith Basic","description":"Cost-capped tier. Intelligent routing with a Claude Sonnet ceiling — Opus is never invoked.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-26","last_updated":"2026-08-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":1.17,"output":4.37,"cache_read":0.22,"cache_write":0}}}},"fireworks-ai":{"id":"fireworks-ai","env":["FIREWORKS_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.fireworks.ai/inference/v1/","name":"Fireworks AI","doc":"https://fireworks.ai/docs/","models":{"accounts/fireworks/models/nemotron-3-ultra-nvfp4":{"id":"accounts/fireworks/models/nemotron-3-ultra-nvfp4","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":128000},"cost":{"input":0.6,"output":2.4,"cache_read":0.12},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"accounts/fireworks/models/kimi-k3":{"id":"accounts/fireworks/models/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-27","last_updated":"2026-07-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"experimental":{"modes":{"priority":{"cost":{"input":3.75,"output":18.75,"cache_read":0.375},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"accounts/fireworks/models/qwen3p8-2p4t-a95b":{"id":"accounts/fireworks/models/qwen3p8-2p4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"accounts/fireworks/models/ember-1":{"id":"accounts/fireworks/models/ember-1","name":"Ember-1","description":"Specialized model from Fireworks built on Kimi K3, producing shorter reasoning traces with approximately 40% fewer tokens while maintaining comparable quality","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3}},"accounts/fireworks/models/deepseek-v4p1-flash":{"id":"accounts/fireworks/models/deepseek-v4p1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"experimental":{"modes":{"priority":{"cost":{"input":0.375,"output":1.5,"cache_read":0.0075},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"accounts/fireworks/models/glm-5p3":{"id":"accounts/fireworks/models/glm-5p3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-09-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048573,"output":262144},"experimental":{"modes":{"priority":{"cost":{"input":1.75,"output":5.5,"cache_read":0.325},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"accounts/fireworks/models/nemotron-lightning-3p5-30b-a3b":{"id":"accounts/fireworks/models/nemotron-lightning-3p5-30b-a3b","name":"Nemotron 3.5 Lightning 30B A3B","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"experimental":{"modes":{"priority":{"cost":{"input":0.0625,"output":0.25,"cache_read":0.0125},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.05,"output":0.2,"cache_read":0.01},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"accounts/fireworks/models/inkling":{"id":"accounts/fireworks/models/inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1,"output":4.05,"cache_read":0.17},"canonical_model_id":"thinkingmachines/inkling"},"accounts/fireworks/models/minimax-m3":{"id":"accounts/fireworks/models/minimax-m3","name":"MiniMax-M3","description":"Fireworks text-only MiniMax coding model for long-context reasoning and agent tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"output":512000},"experimental":{"modes":{"priority":{"cost":{"input":0.45,"output":1.8,"cache_read":0.09},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.3,"output":1.2,"cache_read":0.06}},"accounts/fireworks/models/glm-5p3-flash":{"id":"accounts/fireworks/models/glm-5p3-flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-09-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048573,"output":131072},"experimental":{"modes":{"priority":{"cost":{"input":0.1875,"output":0.625,"cache_read":0.0375},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"accounts/fireworks/models/gpt-oss-120b":{"id":"accounts/fireworks/models/gpt-oss-120b","name":"GPT OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2026-06-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"experimental":{"modes":{"priority":{"cost":{"input":0.18,"output":0.72,"cache_read":0.018},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.15,"output":0.6,"cache_read":0.015}},"accounts/fireworks/models/muse-spark-open":{"id":"accounts/fireworks/models/muse-spark-open","name":"Muse Spark Open","description":"Muse Spark Open is an 816B total / 42B active open-weight multimodal reasoning model from Meta for coding and long-horizon agentic work, with 1M-token context.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-open"},"accounts/fireworks/models/qwen3p8-max":{"id":"accounts/fireworks/models/qwen3p8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"experimental":{"modes":{"priority":{"cost":{"input":3,"output":9,"cache_read":0.375},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-max"},"accounts/fireworks/routers/minimax-latest":{"id":"accounts/fireworks/routers/minimax-latest","name":"MiniMax Latest","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-12","last_updated":"2026-09-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"output":512000},"experimental":{"modes":{"priority":{"cost":{"input":0.45,"output":1.8,"cache_read":0.09},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"accounts/fireworks/routers/glm-flash-latest":{"id":"accounts/fireworks/routers/glm-flash-latest","name":"GLM Flash Latest (GLM 5.3 Flash)","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-09-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048573,"output":131072},"experimental":{"modes":{"priority":{"cost":{"input":0.1875,"output":0.625,"cache_read":0.0375},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"accounts/fireworks/routers/glm-fast-latest":{"id":"accounts/fireworks/routers/glm-fast-latest","name":"GLM 5.3 Fast (Latest)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-09-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048572,"output":262144},"cost":{"input":2.1,"output":6.6,"cache_read":0.39},"canonical_model_id":"zhipuai/glm-5.3"},"accounts/fireworks/routers/kimi-k3-fast":{"id":"accounts/fireworks/routers/kimi-k3-fast","name":"Kimi K3 Fast","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-27","last_updated":"2026-07-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":4.5,"output":22.5,"cache_read":0.45},"canonical_model_id":"moonshotai/kimi-k3"},"accounts/fireworks/routers/glm-5p3-fast":{"id":"accounts/fireworks/routers/glm-5p3-fast","name":"GLM 5.3 Fast","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-09-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048572,"output":262144},"cost":{"input":2.1,"output":6.6,"cache_read":0.39},"canonical_model_id":"zhipuai/glm-5.3"},"accounts/fireworks/routers/kimi-fast-latest":{"id":"accounts/fireworks/routers/kimi-fast-latest","name":"Kimi Fast Latest","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-27","last_updated":"2026-09-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":4.5,"output":22.5,"cache_read":0.45},"canonical_model_id":"moonshotai/kimi-k3"},"accounts/fireworks/routers/qwen-max-latest":{"id":"accounts/fireworks/routers/qwen-max-latest","name":"Qwen Max Latest (Qwen3.8 Max)","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-09-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"experimental":{"modes":{"priority":{"cost":{"input":3,"output":9,"cache_read":0.375},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-max"},"accounts/fireworks/routers/kimi-latest":{"id":"accounts/fireworks/routers/kimi-latest","name":"Kimi Latest","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-27","last_updated":"2026-09-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"experimental":{"modes":{"priority":{"cost":{"input":3.75,"output":18.75,"cache_read":0.375},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"accounts/fireworks/routers/deepseek-flash-latest":{"id":"accounts/fireworks/routers/deepseek-flash-latest","name":"DeepSeek Flash Latest","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"experimental":{"modes":{"priority":{"cost":{"input":0.375,"output":1.5,"cache_read":0.0075},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"accounts/fireworks/routers/glm-latest":{"id":"accounts/fireworks/routers/glm-latest","name":"GLM Latest","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-09-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048573,"output":262144},"experimental":{"modes":{"priority":{"cost":{"input":1.75,"output":5.5,"cache_read":0.325},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"}}},"stepfun-ai":{"id":"stepfun-ai","env":["STEPFUN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.stepfun.ai/v1","name":"StepFun (Global)","doc":"https://platform.stepfun.ai/docs/en/overview/concept","models":{"step-5-preview":{"id":"step-5-preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1024000,"input":1024000,"output":65536},"cost":{"input":1,"output":2.7,"cache_read":0.05},"canonical_model_id":"stepfun/step-5-preview"},"step-3.7-flash":{"id":"step-3.7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-06-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.185,"output":1.11,"cache_read":0.037},"canonical_model_id":"stepfun/step-3.7-flash"},"step-3.5-flash":{"id":"step-3.5-flash","name":"Step 3.5 Flash","description":"StepFun flash lane for quick multimodal reasoning and coding assistance","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-06-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.1,"output":0.3,"cache_read":0.02}},"stepaudio-2.5-asr":{"id":"stepaudio-2.5-asr","name":"StepAudio 2.5 ASR","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"step","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-24","last_updated":"2026-07-02","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0}},"stepaudio-2.5-tts":{"id":"stepaudio-2.5-tts","name":"StepAudio 2.5 TTS","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"step","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-16","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"step-2-16k":{"id":"step-2-16k","name":"Step 2 (16K)","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-01-01","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":5.21,"output":16.44,"cache_read":1.04}},"step-3.5-flash-2603":{"id":"step-3.5-flash-2603","name":"Step 3.5 Flash 2603","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.1,"output":0.3,"cache_read":0.02}},"step-tts-2":{"id":"step-tts-2","name":"Step TTS 2","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"step","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-03-01","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"step-1-32k":{"id":"step-1-32k","name":"Step 1 (32K)","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-01-01","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"input":32768,"output":32768},"cost":{"input":2.05,"output":9.59,"cache_read":0.41}}}},"fastrouter":{"id":"fastrouter","env":["FASTROUTER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://go.fastrouter.ai/api/v1","name":"FastRouter","doc":"https://fastrouter.ai/models","models":{"anthropic/claude-opus-4.1":{"id":"anthropic/claude-opus-4.1","name":"Claude Opus 4.1","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":32000}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1-20250805"},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":32000}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-sonnet-4":{"id":"anthropic/claude-sonnet-4","name":"Claude Sonnet 4","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":32000}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-20250514"},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":32000}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.74,"output":3.48},"canonical_model_id":"deepseek/deepseek-v4-pro"},"z-ai/glm-5":{"id":"z-ai/glm-5","name":"GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-11","last_updated":"2026-02-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.95,"output":3.15}},"z-ai/glm-5.1":{"id":"z-ai/glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":1.05,"output":3.5},"canonical_model_id":"zhipuai/glm-5.1"},"sarvam/sarvam-30b":{"id":"sarvam/sarvam-30b","name":"Sarvam 30B","description":"Efficient Indian-language reasoning model for chat, coding, and multilingual work","family":"sarvam","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-18","last_updated":"2026-02-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0.02,"output":0.1},"canonical_model_id":"sarvam/sarvam-30b"},"sarvam/sarvam-105b":{"id":"sarvam/sarvam-105b","name":"Sarvam 105B","description":"Flagship Indian-language reasoning model for enterprise multilingual applications","family":"sarvam","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-09-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.04,"output":0.16},"canonical_model_id":"sarvam/sarvam-105b"},"x-ai/grok-4":{"id":"x-ai/grok-4","name":"Grok 4","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-07","release_date":"2025-07-09","last_updated":"2025-07-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.75,"cache_write":15}},"x-ai/grok-4.3":{"id":"x-ai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5},"canonical_model_id":"xai/grok-4.3"},"x-ai/grok-build-0.1":{"id":"x-ai/grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2},"canonical_model_id":"xai/grok-build-0.1"},"bytedance/seedance-2":{"id":"bytedance/seedance-2","name":"Seedance 2","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"seed","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":4096,"output":0}},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.13,"output":0.38},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemini-3.1-flash-image-preview":{"id":"google/gemini-3.1-flash-image-preview","name":"Nano Banana 2 Preview","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-26","last_updated":"2026-02-26","modalities":{"input":["text","image","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":65536},"cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3.1-flash-image-preview"},"google/veo3.1":{"id":"google/veo3.1","name":"Veo 3.1","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-05-01","last_updated":"2026-05-01","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":400000,"output":0}},"google/imagen-4.0-ultra":{"id":"google/imagen-4.0-ultra","name":"Imagen 4 Ultra","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"imagen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":480,"output":0}},"google/veo3.1-lite":{"id":"google/veo3.1-lite","name":"Veo 3.1 Lite","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-05-01","last_updated":"2026-05-01","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":400000,"output":0}},"google/gemini-3-pro-image-preview":{"id":"google/gemini-3-pro-image-preview","name":"Nano Banana Pro Preview","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-20","last_updated":"2025-11-20","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":2,"output":12},"canonical_model_id":"google/gemini-3-pro-image-preview"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.31}},"google/veo3.1-fast":{"id":"google/veo3.1-fast","name":"Veo 3.1 Fast","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-05-01","last_updated":"2026-05-01","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":400000,"output":0}},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.0375}},"google/imagen-4.0-fast":{"id":"google/imagen-4.0-fast","name":"Imagen 4 Fast","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"imagen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":480,"output":0}},"deepseek-ai/deepseek-r1-distill-llama-70b":{"id":"deepseek-ai/deepseek-r1-distill-llama-70b","name":"DeepSeek R1 Distill Llama 70B","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2024-10","release_date":"2025-01-23","last_updated":"2025-01-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.03,"output":0.14}},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.75,"output":3.5},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2":{"id":"moonshotai/kimi-k2","name":"Kimi K2","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.55,"output":2.2}},"minimax/minimax-m2.7":{"id":"minimax/minimax-m2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/minimax-m2.7-highspeed":{"id":"minimax/minimax-m2.7-highspeed","name":"MiniMax-M2.7-highspeed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.4},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"wanx/wan-v2-6":{"id":"wanx/wan-v2-6","name":"Wan 2.6","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text","image"],"output":["video"]},"open_weights":true,"limit":{"context":400000,"output":0}},"qwen/qwen3-coder":{"id":"qwen/qwen3-coder","name":"Qwen3 Coder","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":66536},"cost":{"input":0.3,"output":1.2}},"leonardo-ai/lucid-realism":{"id":"leonardo-ai/lucid-realism","name":"Lucid Realism","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"lucid","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-01","last_updated":"2025-06-01","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":4096,"output":0}},"leonardo-ai/lucid-origin":{"id":"leonardo-ai/lucid-origin","name":"Lucid Origin","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"lucid","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-01","last_updated":"2025-06-01","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":4096,"output":0}},"openai/gpt-5.5-pro":{"id":"openai/gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180},"canonical_model_id":"openai/gpt-5.5-pro"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-realtime-1.5":{"id":"openai/gpt-realtime-1.5","name":"GPT Realtime 1.5","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-06-01","last_updated":"2025-06-01","modalities":{"input":["text","audio","image"],"output":["text","audio"]},"open_weights":false,"limit":{"context":32000,"output":4096},"cost":{"input":4,"output":16}},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-10-01","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025}},"openai/gpt-image-2":{"id":"openai/gpt-image-2","name":"GPT Image 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":128000,"output":0}},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-10-01","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005}},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.05,"output":0.2}},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6}},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-10-01","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125}}}},"orcarouter":{"id":"orcarouter","env":["ORCAROUTER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.orcarouter.ai/v1","name":"OrcaRouter","doc":"https://docs.orcarouter.ai","models":{"grok/grok-4.3":{"id":"grok/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.3"},"grok/grok-4.5":{"id":"grok/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.5"},"grok/grok-4.6":{"id":"grok/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"anthropic/claude-opus-4.5":{"id":"anthropic/claude-opus-4.5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-opus-4.6":{"id":"anthropic/claude-opus-4.6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":30,"output":150,"cache_read":3,"cache_write":37.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":30,"output":150,"cache_read":3,"cache_write":37.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-haiku-4.5":{"id":"anthropic/claude-haiku-4.5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":10},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-sonnet-4.5":{"id":"anthropic/claude-sonnet-4.5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.147,"output":0.295,"cache_read":0.02},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v4-flash-vision-exp":{"id":"deepseek/deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.147,"output":0.295,"cache_read":0.02},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"deepseek/deepseek-chat":{"id":"deepseek/deepseek-chat","name":"DeepSeek Chat","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-12-01","last_updated":"2026-02-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.147,"output":0.295,"cache_read":0.02},"canonical_model_id":"deepseek/deepseek-chat"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.442,"output":0.884,"cache_read":0.06},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek/deepseek-v4-flash-free":{"id":"deepseek/deepseek-v4-flash-free","name":"DeepSeek V4 Flash (free)","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-reasoner":{"id":"deepseek/deepseek-reasoner","name":"DeepSeek Reasoner","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-09","release_date":"2025-12-01","last_updated":"2026-02-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.147,"output":0.295,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-reasoner"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.442,"output":0.884,"cache_read":0.06},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.147,"output":0.295,"cache_read":0.02},"canonical_model_id":"deepseek/deepseek-v4-flash"},"tencent/hy3-free":{"id":"tencent/hy3-free","name":"Hy3 (free)","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":192000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"tencent/hy3"},"tencent/hy3":{"id":"tencent/hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":192000,"output":128000},"cost":{"input":0.18,"output":0.59,"cache_read":0.059},"canonical_model_id":"tencent/hy3"},"z-ai/glm-4.5":{"id":"z-ai/glm-4.5","name":"GLM-4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.075,"output":0.25},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-4.6":{"id":"z-ai/glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.6"},"z-ai/glm-5":{"id":"z-ai/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5"},"z-ai/glm-4.7":{"id":"z-ai/glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7"},"z-ai/glm-5.3-flash-free":{"id":"z-ai/glm-5.3-flash-free","name":"GLM-5.3-Flash (free)","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/glm-5.1":{"id":"z-ai/glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.1"},"z-ai/glm-4.5-air":{"id":"z-ai/glm-4.5-air","name":"GLM-4.5-Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.2,"output":1.1,"cache_read":0.03,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5-air"},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.26,"output":3.96,"cache_read":0.234},"canonical_model_id":"zhipuai/glm-5.3"},"meta/muse-spark-1.1":{"id":"meta/muse-spark-1.1","name":"Muse Spark 1.1","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.1"},"meta/muse-spark-1.2":{"id":"meta/muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"google/gemini-flash-latest":{"id":"google/gemini-flash-latest","name":"Gemini Flash Latest","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.1},"canonical_model_id":"google/gemini-flash-latest"},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.13,"output":0.38,"cache_read":0.02},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemini-flash-lite-latest":{"id":"google/gemini-flash-lite-latest","name":"Gemini Flash-Lite Latest","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-flash-lite-latest"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"google/gemini-3.6-flash"},"google/gemini-robotics-er-1.6-preview":{"id":"google/gemini-robotics-er-1.6-preview","name":"Gemini Robotics-ER 1.6 Preview","description":"Vision-language model for embodied reasoning: spatial understanding, task planning, and physical-world agentic robotics","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":0}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-14","last_updated":"2026-04-14","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":65536},"cost":{"input":1,"output":5},"canonical_model_id":"google/gemini-robotics-er-1.6-preview"},"google/gemma-4-26b-a4b-it":{"id":"google/gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.06,"output":0.33,"cache_read":0.0075},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"input_audio":2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"cache_write":0.08333,"input_audio":3},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"input_audio":1},"canonical_model_id":"google/gemini-2.5-flash"},"google/gemini-3.1-pro-preview-customtools":{"id":"google/gemini-3.1-pro-preview-customtools","name":"Gemini 3.1 Pro Preview Custom Tools","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview-customtools"},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"input_audio":1},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"input_audio":0.3},"canonical_model_id":"google/gemini-2.5-flash-lite"},"google/gemini-3.1-flash-lite-preview":{"id":"google/gemini-3.1-flash-lite-preview","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite-preview"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite"},"kimi/kimi-k3":{"id":"kimi/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3.3,"output":16.5,"cache_read":0.33},"canonical_model_id":"moonshotai/kimi-k3"},"kimi/kimi-k2.6":{"id":"kimi/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"kimi/kimi-k2.5":{"id":"kimi/kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.6,"output":3,"cache_read":0.1,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.5"},"kimi/kimi-k2.7-code":{"id":"kimi/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"orcarouter/fusion-mini":{"id":"orcarouter/fusion-mini","name":"OrcaRouter Fusion Mini","description":"Leaner two-model Fusion panel that runs Claude Opus 4.8 and GPT-5.5 in parallel on hard requests, then has a Claude Opus 4.8 judge return the strongest single answer verbatim. Easy requests fall through to a cheaper default and bill as one call.","family":"model-router","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000}},"orcarouter/free":{"id":"orcarouter/free","name":"OrcaRouter Free","description":"Built-in router over the free tier that scores each request's difficulty and sends light work to the smaller free model and harder work to the stronger one. Priced at zero and never falls back to a paid model.","family":"auto","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":0,"output":0}},"orcarouter/fusion":{"id":"orcarouter/fusion","name":"OrcaRouter Fusion","description":"Curated fan-out router that runs Claude Opus 4.8, GPT-5.5 and Gemini 3.1 Pro in parallel on hard requests, then has a Claude Opus 4.8 judge return the strongest single answer verbatim. Easy requests fall through to a cheaper default and bill as one call.","family":"model-router","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000}},"orcarouter/fusion-flash":{"id":"orcarouter/fusion-flash","name":"OrcaRouter Fusion Flash","description":"Budget Fusion panel that runs Gemini 3.5 Flash, MiniMax M2.7 and GLM 5.1 in parallel on hard requests, then has a Claude Opus 4.8 judge return the strongest single answer verbatim. Cost-sensitive fan-out over a 200K window.","family":"model-router","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000}},"orcarouter/auto":{"id":"orcarouter/auto","name":"OrcaRouter Auto","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-01-01","last_updated":"2026-05-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0,"output":0}},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5"},"minimax/minimax-m2.7":{"id":"minimax/minimax-m2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"minimax/minimax-m2.7-highspeed":{"id":"minimax/minimax-m2.7-highspeed","name":"MiniMax-M2.7-highspeed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"minimax/minimax-m2.5-highspeed":{"id":"minimax/minimax-m2.5-highspeed","name":"MiniMax-M2.5-highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-13","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5-highspeed"},"qwen/qwen3.5-flash":{"id":"qwen/qwen3.5-flash","name":"Qwen3.5 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":81920}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.1,"output":0.4},"canonical_model_id":"alibaba/qwen3.5-flash"},"qwen/qwen3-vl-235b-a22b-instruct":{"id":"qwen/qwen3-vl-235b-a22b-instruct","name":"Qwen3 VL 235B A22B Instruct","description":"Qwen vision-language instruct model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.4,"output":1.6},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":1.25,"output":3.75,"cache_read":0.25,"cache_write":1.563},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.33,"output":2.4},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3-vl-235b-a22b-thinking":{"id":"qwen/qwen3-vl-235b-a22b-thinking","name":"Qwen3 VL 235B A22B Thinking","description":"Qwen vision-language thinking model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":81920}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":40960},"cost":{"input":0.4,"output":4},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-thinking"},"qwen/qwen3.5-27b":{"id":"qwen/qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.086,"output":0.688},"canonical_model_id":"alibaba/qwen3.5-27b"},"qwen/qwen3.8-max":{"id":"qwen/qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"qwen/qwen3.5-plus":{"id":"qwen/qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.115,"output":0.688,"reasoning":2.4},"canonical_model_id":"alibaba/qwen3.5-plus"},"qwen/qwen3.7-flash":{"id":"qwen/qwen3.7-flash","name":"Qwen3.7 Flash","description":"Lightweight multimodal Qwen model for high-throughput text, image, and video tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":991808,"output":131072},"cost":{"input":0.03,"output":0.13,"cache_read":0.006,"cache_write":0.038},"canonical_model_id":"alibaba/qwen3.7-flash"},"qwen/qwen3-max":{"id":"qwen/qwen3-max","name":"Qwen3 Max","description":"Flagship Qwen3 model for coding agents, complex reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.359,"output":1.434},"canonical_model_id":"alibaba/qwen3-max"},"qwen/qwen3.5-122b-a10b":{"id":"qwen/qwen3.5-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.115,"output":0.917},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"qwen/qwen3.6-35b-a3b":{"id":"qwen/qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.248,"output":1.485},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"qwen/qwen3.6-flash":{"id":"qwen/qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.25,"output":1.5},"canonical_model_id":"alibaba/qwen3.6-flash"},"qwen/qwen3.5-35b-a3b":{"id":"qwen/qwen3.5-35b-a3b","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.057,"output":0.459},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"qwen/qwen3.5-397b-a17b":{"id":"qwen/qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.172,"output":1.032},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"qwen/qwen3.6-plus":{"id":"qwen/qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625,"tiers":[{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5}},"canonical_model_id":"alibaba/qwen3.6-plus"},"qwen/qwen3.7-plus":{"id":"qwen/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.35,"output":1.42,"cache_read":0.071},"canonical_model_id":"alibaba/qwen3.7-plus"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":5,"output":30,"cache_read":0.5},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.4-pro"},"openai/gpt-3.5-turbo":{"id":"openai/gpt-3.5-turbo","name":"GPT-3.5-turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"output":4096},"cost":{"input":0.5,"output":1.5,"cache_read":0},"canonical_model_id":"openai/gpt-3.5-turbo"},"openai/gpt-5.5-pro":{"id":"openai/gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":100000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.5-pro"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-4o-2024-05-13":{"id":"openai/gpt-4o-2024-05-13","name":"GPT-4o (2024-05-13)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-05-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":5,"output":15},"canonical_model_id":"openai/gpt-4o-2024-05-13"},"openai/gpt-5.2-codex":{"id":"openai/gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Code-specialist GPT for repository edits, reviews, and long-running software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-codex"},"openai/gpt-5.1-codex":{"id":"openai/gpt-5.1-codex","name":"GPT-5.1 Codex","description":"Codex GPT for repository edits, code review, and practical software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex"},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"openai/gpt-5.2-pro":{"id":"openai/gpt-5.2-pro","name":"GPT-5.2 Pro","description":"Higher-accuracy GPT-5.2 variant for tougher reasoning and review workflows","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":21,"output":168},"canonical_model_id":"openai/gpt-5.2-pro"},"openai/gpt-4":{"id":"openai/gpt-4","name":"GPT-4","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-11","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8192},"cost":{"input":30,"output":60},"canonical_model_id":"openai/gpt-4"},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"openai/gpt-5.2-chat-latest":{"id":"openai/gpt-5.2-chat-latest","name":"GPT-5.2 Chat","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-chat-latest"},"openai/gpt-5.1-chat-latest":{"id":"openai/gpt-5.1-chat-latest","name":"GPT-5.1 Chat","description":"Chat-tuned GPT-5.1 for polished assistants, writing, and product conversations","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-chat-latest"},"openai/gpt-5-pro":{"id":"openai/gpt-5-pro","name":"GPT-5 Pro","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":272000},"cost":{"input":15,"output":120},"canonical_model_id":"openai/gpt-5-pro"},"openai/gpt-5-chat-latest":{"id":"openai/gpt-5-chat-latest","name":"GPT-5 Chat (latest)","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":100000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5-chat-latest"},"openai/gpt-4o-2024-08-06":{"id":"openai/gpt-4o-2024-08-06","name":"GPT-4o (2024-08-06)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-08-06","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-08-06"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":1.5,"output":9,"cache_read":0.15},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":12.5,"output":75,"cache_read":1.25},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-4o-2024-11-20":{"id":"openai/gpt-4o-2024-11-20","name":"GPT-4o (2024-11-20)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-11-20","last_updated":"2024-11-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-11-20"},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-4-turbo":{"id":"openai/gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":10,"output":30},"canonical_model_id":"openai/gpt-4-turbo"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.03,"output":0.17},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-5.1-codex-mini":{"id":"openai/gpt-5.1-codex-mini","name":"GPT-5.1 Codex mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5.1-codex-mini"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5},"canonical_model_id":"openai/gpt-5.6-sol"}}},"friendli":{"id":"friendli","env":["FRIENDLI_TOKEN"],"npm":"@ai-sdk/openai-compatible","api":"https://api.friendli.ai/serverless/v1","name":"Friendli","doc":"https://friendli.ai/docs/guides/serverless_endpoints/introduction","models":{"google/gemma-4-31B-it":{"id":"google/gemma-4-31B-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.14,"output":0.4},"canonical_model_id":"google/gemma-4-31b-it"},"deepseek-ai/DeepSeek-V3.2":{"id":"deepseek-ai/DeepSeek-V3.2","name":"DeepSeek V3.2","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":64000},"cost":{"input":0.5,"output":1.5,"cache_read":0.25},"canonical_model_id":"deepseek/deepseek-v3.2"},"MiniMaxAI/MiniMax-M2.5":{"id":"MiniMaxAI/MiniMax-M2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.5"},"zai-org/GLM-5.1":{"id":"zai-org/GLM-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-5.3-Flash":{"id":"zai-org/GLM-5.3-Flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/GLM-5.3":{"id":"zai-org/GLM-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.26,"output":3.96,"cache_read":0.234},"canonical_model_id":"zhipuai/glm-5.3"}}},"kimi-code-plan-cn":{"id":"kimi-code-plan-cn","env":["KIMI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.kimi.com/coding/v1","name":"Kimi For Coding (kimi.com)","doc":"https://www.kimi.com/code/docs/en/kimi-code/models.html","models":{"kimi-for-coding-highspeed":{"id":"kimi-for-coding-highspeed","name":"Kimi For Coding HighSpeed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"kimi-for-coding":{"id":"kimi-for-coding","name":"kimi-for-coding","description":"Kimi coding model with more efficient thinking and up to 1M context, available through Kimi Code","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.8-preview"},"k3-256k":{"id":"k3-256k","name":"Kimi K3-256K","description":"256K-context version of Kimi K3, reducing token consumption for shorter coding sessions","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k3"},"k3":{"id":"k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k3"}}},"inco":{"id":"inco","env":["INCO_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.inco.ai/v1","name":"Inco","doc":"https://platform.inco.ai/docs","models":{"kimi-k3:fast":{"id":"kimi-k3:fast","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":6,"output":30},"canonical_model_id":"moonshotai/kimi-k3"},"glm-5.3:fast":{"id":"glm-5.3:fast","name":"GLM-5.3 Fast","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":2.8,"output":8.8},"canonical_model_id":"zhipuai/glm-5.3"},"glm-5.3-flash:fast":{"id":"glm-5.3-flash:fast","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5},"canonical_model_id":"zhipuai/glm-5.3-flash"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M3"},"deepseek-v4.1-flash:fast":{"id":"deepseek-v4.1-flash:fast","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.6,"output":2.4},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"minimax-m3:fast":{"id":"minimax-m3:fast","name":"MiniMax M3 Fast","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.6,"output":2.4},"canonical_model_id":"minimax/MiniMax-M3"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4},"canonical_model_id":"zhipuai/glm-5.3"}}},"sakana":{"id":"sakana","env":["SAKANA_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.sakana.ai/v1","name":"Sakana AI","doc":"https://console.sakana.ai/models","models":{"fugu-ultra":{"id":"fugu-ultra","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"provider":{"shape":"responses"},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"sakana/fugu-ultra"},"fugu-ultra-20260615":{"id":"fugu-ultra-20260615","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"provider":{"shape":"responses"},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"sakana/fugu-ultra"},"sakana-namazu":{"id":"sakana-namazu","name":"Sakana Namazu","description":"Japanese-specialized reasoning model based on Kimi K2.6 and tuned for Japanese language, culture, and business workflows","family":"sakana-namazu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.95,"output":4,"cache_read":0.15},"canonical_model_id":"sakana/sakana-namazu"},"fugu":{"id":"fugu","name":"Fugu","description":"Multi-agent model for routing expert agents across complex analytical tasks","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"provider":{"shape":"responses"},"canonical_model_id":"sakana/fugu"}}},"scx-ai":{"id":"scx-ai","env":["SCX_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.scx.ai/v1","name":"SCX.ai","doc":"https://platform.scx.ai/docs","models":{"GLM-5.2":{"id":"GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.55,"output":1.784,"cache_read":0.111},"canonical_model_id":"zhipuai/glm-5.2"},"Qwen3.8-Max":{"id":"Qwen3.8-Max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":983616,"output":131072},"cost":{"input":1.815,"output":5.4461,"cache_read":0.17,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"MiniMax-M2.7":{"id":"MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":196608},"cost":{"input":0.48,"output":1.79,"cache_read":0.05},"canonical_model_id":"minimax/MiniMax-M2.7"},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.17,"output":0.55},"canonical_model_id":"openai/gpt-oss-120b"}}},"zenifra":{"id":"zenifra","env":["ZENIFRA_AI_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://ai.zenifra.com/v1","name":"Zenifra","doc":"https://docs.zenifra.com","models":{"alibaba/qwen3.6-35b-a3b":{"id":"alibaba/qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"provider":{"shape":"completions"},"cost":{"input":0.19,"output":0.48},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"}}},"tokenrouter":{"id":"tokenrouter","env":["TOKENROUTER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.tokenrouter.com/v1","name":"TokenRouter","doc":"https://www.tokenrouter.com/docs/tokenrouter-feature-guide/","models":{"z-ai/glm-5.3-free":{"id":"z-ai/glm-5.3-free","name":"GLM-5.3 (free)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-5.3"}}},"google-vertex-anthropic":{"id":"google-vertex-anthropic","env":["GOOGLE_VERTEX_PROJECT","GOOGLE_VERTEX_LOCATION","GOOGLE_APPLICATION_CREDENTIALS"],"npm":"@ai-sdk/google-vertex/anthropic","name":"Vertex (Anthropic)","doc":"https://cloud.google.com/vertex-ai/generative-ai/docs/partner-models/claude","models":{"claude-opus-4-8@default":{"id":"claude-opus-4-8@default","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5}},"canonical_model_id":"anthropic/claude-opus-4-8"},"claude-sonnet-4-5@20250929":{"id":"claude-sonnet-4-5@20250929","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"claude-opus-4-6@default":{"id":"claude-opus-4-6@default","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5}},"canonical_model_id":"anthropic/claude-opus-4-6"},"claude-opus-4@20250514":{"id":"claude-opus-4@20250514","name":"Claude Opus 4","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-20250514"},"claude-sonnet-5-5@default":{"id":"claude-sonnet-5-5@default","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"claude-opus-5-5@default":{"id":"claude-opus-5-5@default","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"claude-opus-5@default":{"id":"claude-opus-5@default","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"claude-sonnet-4-6@default":{"id":"claude-sonnet-4-6@default","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"claude-haiku-4-5@20251001":{"id":"claude-haiku-4-5@20251001","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"claude-opus-4-1@20250805":{"id":"claude-opus-4-1@20250805","name":"Claude Opus 4.1","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1-20250805"},"claude-opus-4-5@20251101":{"id":"claude-opus-4-5@20251101","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-01","last_updated":"2025-11-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"claude-opus-4-7@default":{"id":"claude-opus-4-7@default","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5}},"canonical_model_id":"anthropic/claude-opus-4-7"},"claude-fable-5-1@default":{"id":"claude-fable-5-1@default","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"claude-fable-5@default":{"id":"claude-fable-5@default","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"claude-haiku-5-5@default":{"id":"claude-haiku-5-5@default","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"claude-sonnet-4@20250514":{"id":"claude-sonnet-4@20250514","name":"Claude Sonnet 4","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-20250514"},"claude-sonnet-5@default":{"id":"claude-sonnet-5@default","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"}}},"moonshotai":{"id":"moonshotai","env":["MOONSHOT_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.moonshot.ai/v1","name":"Moonshot AI","doc":"https://platform.moonshot.ai/docs/api/chat","models":{"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3},"canonical_model_id":"moonshotai/kimi-k3"},"kimi-k2.7-code-highspeed":{"id":"kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code HighSpeed","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16}},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"}}},"ainetcafe":{"id":"ainetcafe","env":["AINETCAFE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://microquickjs.com/v1","name":"ainetcafe","doc":"https://ainetcafe.com/k3/guides/","models":{"Kimi-K3":{"id":"Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":2.1,"output":10.5,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"}}},"wallaby":{"id":"wallaby","env":["WALLABY_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.wallabytoken.com/v1","name":"Wallaby","doc":"https://wallabytoken.com/docs","models":{"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":2.7,"output":13.5,"cache_read":0.27},"canonical_model_id":"moonshotai/kimi-k3"}}},"bee":{"id":"bee","env":["BEE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.bee.heossi.com/bee","name":"Bee by HEOSSI","doc":"https://bee.heossi.com/docs/sdks","models":{"bee-buzz":{"id":"bee-buzz","name":"Bee Buzz 1.0","description":"Mid-tier production model for tool-using agents, multi-step workflows, and builder/integration work. Bigger context than Comb, deeper planning, faster than Hive on routine tasks.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-10","last_updated":"2026-09-28","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":24576},"cost":{"input":2.5,"output":10,"cache_read":0.25,"cache_write":3}},"bee-swarm":{"id":"bee-swarm","name":"Bee Swarm 1.0","description":"Premium reasoning, multi-model cloud execution, large-document analysis, and high-value technical work. Includes the evolution engine and stronger eval gates by default.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":false,"structured_output":false,"release_date":"2026-07-10","last_updated":"2026-09-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":25,"output":150,"cache_read":2.5,"cache_write":30}},"bee-comb":{"id":"bee-comb","name":"Bee Comb 2.0","description":"Stronger local/workstation AI for coding, architecture, security reasoning, larger RAG, and domain-specific workflows. The default workhorse for engineers and dev teams.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-10","last_updated":"2026-09-28","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":16384},"cost":{"input":1.25,"output":5,"cache_read":0.125,"cache_write":1.5}},"bee-hive":{"id":"bee-hive","name":"Bee Hive 1.0","description":"Scalable Bee serving with quantum-reasoning routing and multi-base domain-adapter routing for shared knowledge workflows, document intelligence, and lower-cost cloud inference. Domain adapters activate per customer domain after evaluation.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-10","last_updated":"2026-09-28","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":5,"output":20,"cache_read":0.5,"cache_write":6}},"bee-brood":{"id":"bee-brood","name":"Bee Brood 1.0","description":"Production multimodal reasoning for image and video analysis, tool-enabled workflows, and multi-step planning at controlled cost.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-10","last_updated":"2026-09-28","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":16384},"cost":{"input":0.6,"output":2.4,"cache_read":0.06,"cache_write":0.72}},"bee-cell":{"id":"bee-cell","name":"Bee Cell 1.0","description":"Fast hosted AI for chat, coding help, document question answering, image understanding, and lightweight technical reasoning.","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-10","last_updated":"2026-09-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.36}}}},"scnet-token-plan":{"id":"scnet-token-plan","env":["SCNET_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.scnet.cn/api/llm/v1","name":"SCNet Token Plan","doc":"https://www.scnet.cn/ac/openapi/doc/2.0/moduleapi/plans/token-plan.html","models":{"DeepSeek-V4-Flash-0731":{"id":"DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"Kimi-K2.6":{"id":"Kimi-K2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"moonshotai/kimi-k2.6"},"MiniMax-M3":{"id":"MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"minimax/MiniMax-M3"},"GLM-5.1":{"id":"GLM-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-5.1"},"GLM-5.2":{"id":"GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-5.2"},"Qwen3.8-Max":{"id":"Qwen3.8-Max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"alibaba/qwen3.8-max"},"Kimi-K3":{"id":"Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"moonshotai/kimi-k3"},"DeepSeek-V4-Pro-0813":{"id":"DeepSeek-V4-Pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"DeepSeek-V4.1-Flash":{"id":"DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"DeepSeek-V4-Flash":{"id":"DeepSeek-V4-Flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4-flash"},"GLM-5":{"id":"GLM-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-5"},"GLM-5.3-Flash":{"id":"GLM-5.3-Flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"DeepSeek-V4-Pro":{"id":"DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4-pro"},"Qwen3.8-Flash":{"id":"Qwen3.8-Flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"alibaba/qwen3.8-flash"},"MiniMax-M2.5":{"id":"MiniMax-M2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"minimax/MiniMax-M2.5"},"MiniMax-M2.7":{"id":"MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"minimax/MiniMax-M2.7"},"GLM-5.3":{"id":"GLM-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-5.3"},"Kimi-K2.7-Code":{"id":"Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"Kimi-K2.5":{"id":"Kimi-K2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"moonshotai/kimi-k2.5"}}},"ofox":{"id":"ofox","env":["OFOX_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.ofox.ai/v1","name":"Ofox","doc":"https://ofox.ai/docs","models":{"bailian/qwen-flash":{"id":"bailian/qwen-flash","name":"Qwen Flash","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.022,"output":0.22,"cache_read":0.0043,"cache_write":0.027},"canonical_model_id":"alibaba/qwen-flash"},"bailian/qwen3.5-flash":{"id":"bailian/qwen3.5-flash","name":"Qwen3.5 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"alibaba/qwen3.5-flash"},"bailian/qwen3.7-max":{"id":"bailian/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":2.5,"output":7.5,"cache_read":0.5,"cache_write":3.125},"canonical_model_id":"alibaba/qwen3.7-max"},"bailian/qwen3.8-27b":{"id":"bailian/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1131072,"output":131072},"cost":{"input":0.45,"output":3.2,"cache_read":0.05,"cache_write":0.5625},"canonical_model_id":"alibaba/qwen3.8-27b"},"bailian/qwen3.5-27b":{"id":"bailian/qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.29,"output":2.05,"cache_read":0.29},"canonical_model_id":"alibaba/qwen3.5-27b"},"bailian/qwen-max":{"id":"bailian/qwen-max","name":"Qwen Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-03","last_updated":"2025-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":8192},"cost":{"input":0.35,"output":1.38,"cache_read":0.069},"canonical_model_id":"alibaba/qwen-max"},"bailian/qwen3.8-max":{"id":"bailian/qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"bailian/qwen3-coder-next":{"id":"bailian/qwen3-coder-next","name":"Qwen3 Coder Next","description":"Open-weight Qwen coding model for agents, repository edits, and multi-turn tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.2,"output":1.5},"canonical_model_id":"alibaba/qwen3-coder-next"},"bailian/qwen3.5-plus":{"id":"bailian/qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.4,"output":2.4,"cache_read":0.04,"cache_write":0.4},"canonical_model_id":"alibaba/qwen3.5-plus"},"bailian/qwen-plus":{"id":"bailian/qwen-plus","name":"Qwen Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.12,"output":0.29,"cache_read":0.023},"canonical_model_id":"alibaba/qwen-plus"},"bailian/qwen3-max":{"id":"bailian/qwen3-max","name":"Qwen3 Max","description":"Flagship Qwen3 model for coding agents, complex reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.36,"output":1.43,"cache_read":0.072},"canonical_model_id":"alibaba/qwen3-max"},"bailian/qwen-turbo":{"id":"bailian/qwen-turbo","name":"Qwen Turbo","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-11-01","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.05,"output":0.09,"cache_read":0.0086},"canonical_model_id":"alibaba/qwen-turbo"},"bailian/qwen-vl-max":{"id":"bailian/qwen-vl-max","name":"Qwen-VL Max","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-08","last_updated":"2025-08-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.23,"output":0.58,"cache_read":0.046},"canonical_model_id":"alibaba/qwen-vl-max"},"bailian/qwen3.5-122b-a10b":{"id":"bailian/qwen3.5-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.29,"output":2.29,"cache_read":0.29},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"bailian/qwen3.6-flash":{"id":"bailian/qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"cache_write":0.31},"canonical_model_id":"alibaba/qwen3.6-flash"},"bailian/qwen3-coder-flash":{"id":"bailian/qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.5,"output":2.5,"cache_read":0.06,"cache_write":0.27},"canonical_model_id":"alibaba/qwen3-coder-flash"},"bailian/qwen3-coder-plus":{"id":"bailian/qwen3-coder-plus","name":"Qwen3 Coder Plus","description":"Hosted Qwen coder for software agents, repo edits, and long-context code","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.8,"output":9,"cache_read":0.2,"cache_write":1},"canonical_model_id":"alibaba/qwen3-coder-plus"},"bailian/qwen3.8-flash":{"id":"bailian/qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"bailian/qwen3.5-35b-a3b":{"id":"bailian/qwen3.5-35b-a3b","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.29,"output":1.83,"cache_read":0.29},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"bailian/qwen3.6-max-preview":{"id":"bailian/qwen3.6-max-preview","name":"Qwen3.6 Max Preview","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":2.15,"output":12.86,"cache_read":0.2,"cache_write":1.17},"canonical_model_id":"alibaba/qwen3.6-max-preview"},"bailian/qwen3.5-397b-a17b":{"id":"bailian/qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.55,"output":3.5,"cache_read":0.55},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"bailian/qwen3.6-27b":{"id":"bailian/qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.6,"output":3.6},"canonical_model_id":"alibaba/qwen3.6-27b"},"bailian/qwen3.6-plus":{"id":"bailian/qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625},"canonical_model_id":"alibaba/qwen3.6-plus"},"bailian/qwen3.7-plus":{"id":"bailian/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.4,"output":1.6,"cache_read":0.08,"cache_write":0.5},"canonical_model_id":"alibaba/qwen3.7-plus"},"bailian/qwen3.8-max-0902":{"id":"bailian/qwen3.8-max-0902","name":"Qwen3.8 Max 0902","description":"2026-09-02 upgraded snapshot of Qwen3.8 Max with stronger coding, collaborative agents, and multimodal document understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max-0902"},"anthropic/claude-opus-4.5":{"id":"anthropic/claude-opus-4.5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-opus-4.6":{"id":"anthropic/claude-opus-4.6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic/claude-haiku-5.5":{"id":"anthropic/claude-haiku-5.5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-haiku-4.5":{"id":"anthropic/claude-haiku-4.5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-sonnet-5.5":{"id":"anthropic/claude-sonnet-5.5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-fable-5.1":{"id":"anthropic/claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-sonnet-4.5":{"id":"anthropic/claude-sonnet-4.5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-5.5":{"id":"anthropic/claude-opus-5.5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.44,"output":1.32,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v4-flash-0423":{"id":"deepseek/deepseek-v4-flash-0423","name":"DeepSeek V4 Flash 0423","description":"Initial DeepSeek V4 Flash snapshot for economical reasoning, coding, and million-token agent workloads","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.19,"output":0.51,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0423"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-flash-vision-exp":{"id":"deepseek/deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"status":"beta","cost":{"input":0.44,"output":1.32,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek/deepseek-v4-pro-0423":{"id":"deepseek/deepseek-v4-pro-0423","name":"DeepSeek V4 Pro 0423","description":"DeepSeek V4 Pro initial snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.32,"output":3.96,"cache_read":0.15},"canonical_model_id":"deepseek/deepseek-v4-pro-0423"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v3.2":{"id":"deepseek/deepseek-v3.2","name":"DeepSeek V3.2","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"cost":{"input":0.29,"output":0.43,"cache_read":0.06},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.44,"output":1.32,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash"},"z-ai/glm-5v-turbo":{"id":"z-ai/glm-5v-turbo","name":"GLM-5V-Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5v-turbo"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-4.6":{"id":"z-ai/glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.6"},"z-ai/glm-5":{"id":"z-ai/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"z-ai/glm-5.3-flashx":{"id":"z-ai/glm-5.3-flashx","name":"GLM-5.3-FlashX","description":"High-speed GLM-5.3-Flash serving option for coding and agent workflows","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-18","last_updated":"2026-09-18","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-4.7":{"id":"z-ai/glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.4,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.7"},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/glm-5.1":{"id":"z-ai/glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"z-ai/glm-4.7-flashx":{"id":"z-ai/glm-4.7-flashx","name":"GLM-4.7-FlashX","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.072,"output":0.4,"cache_read":0.01},"canonical_model_id":"zhipuai/glm-4.7-flashx"},"z-ai/glm-5-turbo":{"id":"z-ai/glm-5-turbo","name":"GLM-5-Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5-turbo"},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"x-ai/grok-4.7":{"id":"x-ai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":65536},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.7"},"x-ai/grok-4.3":{"id":"x-ai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2},"canonical_model_id":"xai/grok-4.3"},"x-ai/grok-4.5":{"id":"x-ai/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":65536},"cost":{"input":2,"output":6,"cache_read":0.3},"canonical_model_id":"xai/grok-4.5"},"x-ai/grok-4.20":{"id":"x-ai/grok-4.20","name":"Grok 4.20 (Reasoning)","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":128000},"cost":{"input":4,"output":12,"cache_read":0.4},"canonical_model_id":"xai/grok-4.20-0309-reasoning"},"x-ai/grok-4.1-fast":{"id":"x-ai/grok-4.1-fast","name":"Grok 4.1 Fast","description":"xAI's fast agentic tool-calling model with a 2M context window; non-reasoning variant for low-latency responses","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"xai/grok-4.1-fast"},"x-ai/grok-4.6":{"id":"x-ai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":65536},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"volcengine/doubao-seed-2.0-mini":{"id":"volcengine/doubao-seed-2.0-mini","name":"Seed 2.0 Mini","description":"Lightweight ByteDance Seed 2.0 model for low-latency multimodal reasoning and high-volume tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.06,"output":0.56,"cache_read":0.02,"cache_write":0.0024},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"volcengine/doubao-seed-1-6-flash":{"id":"volcengine/doubao-seed-1-6-flash","name":"Seed 1.6 Flash","description":"Low-latency ByteDance Seed model for high-throughput chat, extraction, and lightweight tool use","family":"seed","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-28","last_updated":"2025-08-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.03,"output":0.22,"cache_read":0.0043},"canonical_model_id":"bytedance-seed/seed-1-6-flash"},"volcengine/doubao-seed-2.0-lite":{"id":"volcengine/doubao-seed-2.0-lite","name":"Seed 2.0 Lite","description":"Cost-efficient ByteDance Seed 2.0 model for production chat, analysis, and structured generation","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.13,"output":0.76,"cache_read":0.03,"cache_write":0.0024},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"volcengine/doubao-seed-1-8":{"id":"volcengine/doubao-seed-1-8","name":"Seed 1.8","description":"ByteDance Seed model for multimodal reasoning, long-context analysis, and agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-28","last_updated":"2025-12-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":0.12,"output":0.29,"cache_read":0.023},"canonical_model_id":"bytedance-seed/seed-1-8"},"volcengine/doubao-seed-1-6":{"id":"volcengine/doubao-seed-1-6","name":"Seed 1.6","description":"ByteDance Seed model for long-context reasoning, instruction following, and tool-assisted tasks","family":"seed","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":0.12,"output":0.29,"cache_read":0.023},"canonical_model_id":"bytedance-seed/seed-1-6"},"volcengine/doubao-seed-2.0-pro":{"id":"volcengine/doubao-seed-2.0-pro","name":"Seed 2.0 Pro","description":"Flagship ByteDance Seed 2.0 model for complex multimodal reasoning and long-horizon agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.67,"output":3.36,"cache_read":0.14,"cache_write":0.0024},"canonical_model_id":"bytedance-seed/seed-2.0-pro"},"volcengine/doubao-seed-1-6-vision":{"id":"volcengine/doubao-seed-1-6-vision","name":"Seed 1.6 Vision","description":"ByteDance Seed multimodal model for image understanding, visual reasoning, and tool-assisted tasks","family":"seed","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-15","last_updated":"2025-08-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.12,"output":1.15,"cache_read":0.023},"canonical_model_id":"bytedance-seed/seed-1-6-vision"},"volcengine/doubao-seed-2.1-turbo":{"id":"volcengine/doubao-seed-2.1-turbo","name":"Seed 2.1 Turbo","description":"Faster ByteDance Seed 2.1 model for multimodal reasoning and latency-sensitive agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.3536,"output":1.7696,"cache_read":0.068,"cache_write":0.0019},"canonical_model_id":"bytedance-seed/seed-2.1-turbo"},"volcengine/doubao-seed-2.1-pro":{"id":"volcengine/doubao-seed-2.1-pro","name":"Seed 2.1 Pro","description":"Flagship ByteDance Seed 2.1 model for complex multimodal reasoning, coding, and agents","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.7072,"output":3.536,"cache_read":0.1416,"cache_write":0.002},"canonical_model_id":"bytedance-seed/seed-2.1-pro"},"volcengine/doubao-seed-character":{"id":"volcengine/doubao-seed-character","name":"Seed Character","description":"ByteDance Seed model optimized for character-driven dialogue and consistent conversational behavior","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.177,"output":0.884,"cache_read":0.024,"cache_write":0.0025},"canonical_model_id":"bytedance-seed/seed-character"},"volcengine/doubao-seed-evolving":{"id":"volcengine/doubao-seed-evolving","name":"Seed Evolving","description":"Rolling ByteDance Seed model for rapidly updated reasoning, coding, and agent capabilities","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.884,"output":4.42,"cache_read":0.177,"cache_write":0.0025},"canonical_model_id":"bytedance-seed/seed-evolving"},"volcengine/doubao-seed-2.0-code":{"id":"volcengine/doubao-seed-2.0-code","name":"Seed 2.0 Code","description":"ByteDance Seed coding model for multimodal software engineering and long-running agents","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.67,"output":3.36,"cache_read":0.14,"cache_write":0.0024},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://api.ofox.ai/gemini/v1beta"},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.0415,"input_audio":1.5},"canonical_model_id":"google/gemini-3.6-flash"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://api.ofox.ai/gemini/v1beta"},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":0.083},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://api.ofox.ai/gemini/v1beta"},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":4.5},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://api.ofox.ai/gemini/v1beta"},"cost":{"input":1.5,"output":9,"cache_read":0.15,"cache_write":0.083,"input_audio":3},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125,"cache_write":4.5},"canonical_model_id":"google/gemini-2.5-pro"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":1,"input_audio":1},"canonical_model_id":"google/gemini-2.5-flash"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://api.ofox.ai/gemini/v1beta"},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.0415,"input_audio":1.5},"canonical_model_id":"google/gemini-3.7-flash"},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":1},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://api.ofox.ai/gemini/v1beta"},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.0415,"input_audio":0.75},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":512,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"cache_write":1,"input_audio":0.3},"canonical_model_id":"google/gemini-2.5-flash-lite"},"google/gemini-4-argon":{"id":"google/gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://api.ofox.ai/gemini/v1beta"},"cost":{"input":2,"output":10,"cache_read":0.1,"input_audio":2},"canonical_model_id":"google/gemini-4-argon"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"cache_write":1,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.7-code-highspeed":{"id":"moonshotai/kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code Highspeed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2.5":{"id":"moonshotai/kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":3,"cache_read":0.1},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"minimax/minimax-m2.5-lightning":{"id":"minimax/minimax-m2.5-lightning","name":"MiniMax-M2.5 Lightning","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-13","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":2.4,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5-highspeed"},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5"},"minimax/minimax-m2.1-lightning":{"id":"minimax/minimax-m2.1-lightning","name":"MiniMax-M2.1 Lightning","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":2.4,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.1"},"minimax/minimax-m2.7":{"id":"minimax/minimax-m2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.6,"output":2.4,"cache_read":0.12},"canonical_model_id":"minimax/MiniMax-M3"},"minimax/minimax-m2.7-highspeed":{"id":"minimax/minimax-m2.7-highspeed","name":"MiniMax-M2.7-highspeed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"minimax/m2-her":{"id":"minimax/m2-her","name":"MiniMax-M2 Her","description":"MiniMax M2 variant tuned for conversational and character-driven agent interactions","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-01-23","last_updated":"2026-01-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"output":2048},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2-Her"},"minimax/minimax-m2.1":{"id":"minimax/minimax-m2.1","name":"MiniMax-M2.1","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.1"},"minimax/minimax-m2":{"id":"minimax/minimax-m2","name":"MiniMax-M2","description":"Efficient open MiniMax model built for coding agents and tool-heavy workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2"},"qwen/qwen-flash":{"id":"qwen/qwen-flash","name":"Qwen Flash","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32000},"cost":{"input":0.022,"output":0.22,"cache_read":0.0043,"cache_write":0.027},"canonical_model_id":"alibaba/qwen-flash"},"qwen/qwen3.5-flash":{"id":"qwen/qwen3.5-flash","name":"Qwen3.5 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"alibaba/qwen3.5-flash"},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1064000,"output":64000},"cost":{"input":1.71,"output":5.14,"cache_read":0.17,"cache_write":2.14},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1131072,"output":131072},"cost":{"input":0.5,"output":1.71,"cache_read":0.043,"cache_write":0.63},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3.5-27b":{"id":"qwen/qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.29,"output":2.05,"cache_read":0.29},"canonical_model_id":"alibaba/qwen3.5-27b"},"qwen/qwen-max":{"id":"qwen/qwen-max","name":"Qwen Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-03","last_updated":"2025-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":8000},"cost":{"input":0.35,"output":1.38,"cache_read":0.069},"canonical_model_id":"alibaba/qwen-max"},"qwen/qwen3.8-max":{"id":"qwen/qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":1.71,"output":5.14,"cache_read":0.17,"cache_write":2.14},"canonical_model_id":"alibaba/qwen3.8-max"},"qwen/qwen3-coder-next":{"id":"qwen/qwen3-coder-next","name":"Qwen3 Coder Next","description":"Open-weight Qwen coding model for agents, repository edits, and multi-turn tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.2,"output":1.5},"canonical_model_id":"alibaba/qwen3-coder-next"},"qwen/qwen3.5-plus":{"id":"qwen/qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.4,"output":2.4,"cache_read":0.04,"cache_write":0.4},"canonical_model_id":"alibaba/qwen3.5-plus"},"qwen/qwen-plus":{"id":"qwen/qwen-plus","name":"Qwen Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32000},"cost":{"input":0.12,"output":0.29,"cache_read":0.023},"canonical_model_id":"alibaba/qwen-plus"},"qwen/qwen3-max":{"id":"qwen/qwen3-max","name":"Qwen3 Max","description":"Flagship Qwen3 model for coding agents, complex reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":0.36,"output":1.43,"cache_read":0.072},"canonical_model_id":"alibaba/qwen3-max"},"qwen/qwen-turbo":{"id":"qwen/qwen-turbo","name":"Qwen Turbo","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-11-01","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16000},"cost":{"input":0.043,"output":0.09,"cache_read":0.0086},"canonical_model_id":"alibaba/qwen-turbo"},"qwen/qwen-vl-max":{"id":"qwen/qwen-vl-max","name":"Qwen-VL Max","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-08","last_updated":"2025-08-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8000},"cost":{"input":0.23,"output":0.58,"cache_read":0.023},"canonical_model_id":"alibaba/qwen-vl-max"},"qwen/qwen3.5-122b-a10b":{"id":"qwen/qwen3.5-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.29,"output":2.29,"cache_read":0.29},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"qwen/qwen3.6-flash":{"id":"qwen/qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"cache_write":0.31},"canonical_model_id":"alibaba/qwen3.6-flash"},"qwen/qwen3-coder-flash":{"id":"qwen/qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.5,"output":2.5,"cache_read":0.06,"cache_write":0.27},"canonical_model_id":"alibaba/qwen3-coder-flash"},"qwen/qwen3-coder-plus":{"id":"qwen/qwen3-coder-plus","name":"Qwen3 Coder Plus","description":"Hosted Qwen coder for software agents, repo edits, and long-context code","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":1.8,"output":9,"cache_read":0.2,"cache_write":1},"canonical_model_id":"alibaba/qwen3-coder-plus"},"qwen/qwen3.8-flash":{"id":"qwen/qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.11,"output":0.39,"cache_read":0.011,"cache_write":0.14},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen/qwen3.5-35b-a3b":{"id":"qwen/qwen3.5-35b-a3b","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.29,"output":1.83,"cache_read":0.29},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"qwen/qwen3.6-max-preview":{"id":"qwen/qwen3.6-max-preview","name":"Qwen3.6 Max Preview","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":2.15,"output":12.86,"cache_read":0.2,"cache_write":1.17},"canonical_model_id":"alibaba/qwen3.6-max-preview"},"qwen/qwen3.5-397b-a17b":{"id":"qwen/qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.55,"output":3.5,"cache_read":0.55},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"qwen/qwen3.6-27b":{"id":"qwen/qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.43,"output":2.57},"canonical_model_id":"alibaba/qwen3.6-27b"},"qwen/qwen3.6-plus":{"id":"qwen/qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625},"canonical_model_id":"alibaba/qwen3.6-plus"},"qwen/qwen3.7-plus":{"id":"qwen/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1064000,"output":64000},"cost":{"input":0.4,"output":1.6,"cache_read":0.08,"cache_write":0.5},"canonical_model_id":"alibaba/qwen3.7-plus"},"qwen/qwen3.8-max-0902":{"id":"qwen/qwen3.8-max-0902","name":"Qwen3.8 Max 0902","description":"2026-09-02 upgraded snapshot of Qwen3.8 Max with stronger coding, collaborative agents, and multimodal document understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":1.71,"output":5.14,"cache_read":0.17,"cache_write":2.14},"canonical_model_id":"alibaba/qwen3.8-max-0902"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":2.5,"output":15,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":30,"output":180},"canonical_model_id":"openai/gpt-5.4-pro"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-5.2-codex":{"id":"openai/gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Code-specialist GPT for repository edits, reviews, and long-running software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":1.75,"output":14,"cache_read":0.18},"canonical_model_id":"openai/gpt-5.2-codex"},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32768},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":0.25,"output":2,"cache_read":0.03},"canonical_model_id":"openai/gpt-5-mini"},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":1.75,"output":14,"cache_read":0.18},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":0.05,"output":0.4,"cache_read":0.01},"canonical_model_id":"openai/gpt-5-nano"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"openai/gpt-6-astra"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":1.25,"output":10,"cache_read":0.13},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.1-codex-max":{"id":"openai/gpt-5.1-codex-max","name":"GPT-5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":1.25,"output":10,"cache_read":0.13},"canonical_model_id":"openai/gpt-5.1-codex-max"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":1.75,"output":14,"cache_read":0.18},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-5.1-codex-mini":{"id":"openai/gpt-5.1-codex-mini","name":"GPT-5.1 Codex mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":65536},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":0.25,"output":2,"cache_read":0.03},"canonical_model_id":"openai/gpt-5.1-codex-mini"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":1.25,"output":10,"cache_read":0.13},"canonical_model_id":"openai/gpt-5"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":2.5,"output":15,"cache_read":0.25,"cache_write":3.125},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-6-sol"}}},"neon":{"id":"neon","env":["NEON_AI_GATEWAY_BASE_URL","NEON_AI_GATEWAY_TOKEN"],"npm":"@ai-sdk/openai-compatible","api":"${NEON_AI_GATEWAY_BASE_URL}/v1","name":"Neon","doc":"https://neon.com/docs","models":{"gpt-5-4-mini":{"id":"gpt-5-4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"gpt-5-6-luna":{"id":"gpt-5-6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"glm-5-3-flash":{"id":"glm-5-3-flash","name":"GLM-5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"gpt-5-6-terra":{"id":"gpt-5-6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"llama-4-maverick":{"id":"llama-4-maverick","name":"Llama 4 Maverick 17B Instruct","description":"Open multimodal Llama for strong reasoning with efficient everyday serving","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":8192},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"gpt-5-mini":{"id":"gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"claude-opus-4-5":{"id":"claude-opus-4-5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"gpt-5-nano":{"id":"gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"claude-sonnet-4-5":{"id":"claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"claude-fable-5-1":{"id":"claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"gemini-3-7-flash":{"id":"gemini-3-7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"google/gemini-3.7-flash"},"gpt-5-4-nano":{"id":"gpt-5-4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"gpt-5-6-sol":{"id":"gpt-5-6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":45,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1,"cache_write":12.5}},"canonical_model_id":"openai/gpt-5.6-sol"},"claude-opus-4-1":{"id":"claude-opus-4-1","name":"Claude Opus 4.1 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":31999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1"},"gpt-5-5-pro":{"id":"gpt-5-5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.5-pro"},"gemini-3-1-pro":{"id":"gemini-3-1-pro","name":"Gemini 3.1 Pro Preview Custom Tools","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview-customtools"},"glm-5-2":{"id":"glm-5-2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"qwen3-next-80b-a3b-instruct":{"id":"qwen3-next-80b-a3b-instruct","name":"Qwen3-Next 80B-A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":10000},"cost":{"input":0.15,"output":1.2},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"gemini-3-flash":{"id":"gemini-3-flash","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"input_audio":1},"canonical_model_id":"google/gemini-3-flash-preview"},"gpt-oss-20b":{"id":"gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":25000},"cost":{"input":0.07,"output":0.3}},"gpt-5-4":{"id":"gpt-5-4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"inkling":{"id":"inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":1,"output":4.05,"cache_read":0.17},"canonical_model_id":"thinkingmachines/inkling"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"glm-5-3":{"id":"glm-5-3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"deepseek-v4-1-flash":{"id":"deepseek-v4-1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"gemini-3-8-flash":{"id":"gemini-3-8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"google/gemini-3.8-flash"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":127999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"gemini-3-1-flash-lite":{"id":"gemini-3-1-flash-lite","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite-preview"},"gpt-5-5":{"id":"gpt-5-5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"grok-4-6":{"id":"grok-4-6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":524288},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"qwen35-122b-a10b":{"id":"qwen35-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":25000},"cost":{"input":0.22,"output":2.2},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"gemini-3-6-flash":{"id":"gemini-3-6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.6-flash"},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"meta-llama-3-3-70b-instruct":{"id":"meta-llama-3-3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"gpt-5-2":{"id":"gpt-5-2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"gpt-5-3-codex":{"id":"gpt-5-3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"gemma-3-12b":{"id":"gemma-3-12b","name":"Gemma 3 12B","description":"Google's open-weight Gemma 3 vision-language model for text and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-03-13","last_updated":"2025-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.15,"output":0.5}},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"grok-4-7":{"id":"grok-4-7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":2.5,"output":7.5,"cache_read":0.5},"canonical_model_id":"xai/grok-4.7"},"gemini-3-5-flash-lite":{"id":"gemini-3-5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"gemini-3-5-flash":{"id":"gemini-3-5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.5-flash"},"gpt-5-1":{"id":"gpt-5-1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"gpt-6-1-sol":{"id":"gpt-6-1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":25000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-120b"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"gpt-5":{"id":"gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"meta-llama-3-1-8b-instruct":{"id":"meta-llama-3-1-8b-instruct","name":"Llama 3.1 8B Instruct","description":"Meta's compact open-weight Llama 3.1 model for fast, low-cost text generation","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.15,"output":0.45}},"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"}}},"aihubmix":{"id":"aihubmix","env":["AIHUBMIX_API_KEY"],"npm":"@aihubmix/ai-sdk-provider","name":"AIHubMix","doc":"https://docs.aihubmix.com","models":{"claude-opus-4-5-think":{"id":"claude-opus-4-5-think","name":"Claude Opus 4.5 Thinking","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"glm-4.6v":{"id":"glm-4.6v","name":"GLM-4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.137,"output":0.411,"cache_read":0.0274,"tiers":[{"input":0.274,"output":0.822,"cache_read":0.0548,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.6v"},"qwen3.5-flash":{"id":"qwen3.5-flash","name":"Qwen3.5 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.0282,"output":0.282,"cache_read":0.00282,"cache_write":0.03525,"tiers":[{"input":0.1126,"output":1.126,"cache_read":0.01126,"cache_write":0.14075,"tier":{"type":"context","size":128000}},{"input":0.169,"output":1.69,"cache_read":0.0169,"cache_write":0.21125,"tier":{"type":"context","size":256000}}]},"canonical_model_id":"alibaba/qwen3.5-flash"},"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":5,"output":30,"cache_read":0.5},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}}},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1.1,"output":5.5,"cache_read":0.11,"cache_write":1.375},"canonical_model_id":"anthropic/claude-haiku-4-5"},"mimo-v2.6-pro":{"id":"mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.48,"output":0.96,"cache_read":0.00384},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"coding-minimax-m2.7-free":{"id":"coding-minimax-m2.7-free","name":"Coding MiniMax M2.7 (Free)","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax-free","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":128100},"cost":{"input":0,"output":0}},"qwen3.7-max":{"id":"qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":991000,"output":64000},"cost":{"input":1.69,"output":5.07,"cache_read":0.169,"cache_write":2.1125},"canonical_model_id":"alibaba/qwen3.7-max"},"muse-spark-1.3":{"id":"muse-spark-1.3","name":"Muse Spark 1.3","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.375,"output":4.675,"cache_read":0.165},"canonical_model_id":"meta/muse-spark-1.3"},"deep-deepseek-v4-pro":{"id":"deep-deepseek-v4-pro","name":"DeepSeek V4 Pro (DeepSeek)","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.478,"output":0.956,"cache_read":0.004302}},"mimo-v2.5":{"id":"mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.155,"output":0.31,"cache_read":0.0031},"canonical_model_id":"xiaomi/mimo-v2.5"},"gpt-5.5-pro":{"id":"gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.5-pro"},"grok-4.7":{"id":"grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2.2,"output":6.6,"cache_read":0.55,"tiers":[{"input":4.4,"output":13.2,"cache_read":1.1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4.4,"output":13.2,"cache_read":1.1}},"canonical_model_id":"xai/grok-4.7"},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"qwen3.8-2.4t-a95b":{"id":"qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"gpt-5.2-codex":{"id":"gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"gpt-5.1-codex":{"id":"gpt-5.1-codex","name":"GPT-5.1 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125}},"glm-5v-turbo":{"id":"glm-5v-turbo","name":"GLM 5 Vision Turbo","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glmv","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-05-09","last_updated":"2026-05-09","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":0.7042,"output":3.09848,"cache_read":0.169008}},"gemini-2.5-flash-image":{"id":"gemini-2.5-flash-image","name":"Nano Banana","description":"Nano Banana image model for fast generation, edits, and character-consistent assets","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.3,"output":30,"cache_read":0.03},"canonical_model_id":"google/gemini-2.5-flash-image"},"qwen3-vl-plus":{"id":"qwen3-vl-plus","name":"Qwen3-VL Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.137,"output":1.37,"cache_read":0,"tiers":[{"input":0.2054,"output":2.054,"cache_read":0,"tier":{"type":"context","size":32000}},{"input":0.411,"output":4.11,"cache_read":0,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3-vl-plus"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.11268,"output":0.39438,"cache_read":0.02817},"canonical_model_id":"zhipuai/glm-5.3-flash"},"nemotron-3.5-content-safety-free":{"id":"nemotron-3.5-content-safety-free","name":"Nemotron 3.5 Content Safety (free)","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"interleaved":{"field":"reasoning_details"},"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-content-safety"},"qwen3.5-27b":{"id":"qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.0846,"output":0.6768,"tiers":[{"input":0.2536,"output":2.0288,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3.5-27b"},"glm-4.6":{"id":"glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.273974,"output":1.095896,"cache_read":0.0547948,"tiers":[{"input":0.547946,"output":2.191784,"cache_read":0.1095892,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.6"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.142,"output":0.284,"cache_read":0.0284},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":991000,"output":128000},"cost":{"input":1.69,"output":5.07,"cache_read":0.169,"cache_write":2.1125},"canonical_model_id":"alibaba/qwen3.8-max"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"doubao-seed-2-0-lite-260428":{"id":"doubao-seed-2-0-lite-260428","name":"Doubao Seed 2.0 Lite 260428","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.08,"output":0.51,"cache_read":0.01692,"input_audio":1.269,"tiers":[{"input":0.13,"output":0.76,"cache_read":0.02536,"input_audio":1.902,"tier":{"type":"context","size":32000}},{"input":0.25,"output":1.52,"cache_read":0.05072,"input_audio":3.804,"tier":{"type":"context","size":128000}}]}},"claude-sonnet-4-6-think":{"id":"claude-sonnet-4-6-think","name":"Claude Sonnet 4.6 Thinking","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}}},"gpt-image-2":{"id":"gpt-image-2","name":"GPT-Image-2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":30,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-2"},"qwen3.5-plus":{"id":"qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.1096,"output":0.6576,"cache_read":0.01096,"cache_write":0.137,"tiers":[{"input":0.274,"output":1.644,"cache_read":0.0274,"cache_write":0.3425,"tier":{"type":"context","size":128000}},{"input":0.548,"output":3.288,"cache_read":0.0548,"cache_write":0.685,"tier":{"type":"context","size":256000}}]},"canonical_model_id":"alibaba/qwen3.5-plus"},"o4-mini":{"id":"o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.275},"canonical_model_id":"openai/o4-mini"},"deepseek-v4-flash-0731-fast":{"id":"deepseek-v4-flash-0731-fast","name":"DeepSeek V4 Flash 0731 Fast","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.28,"output":1.4,"cache_read":0.07},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"claude-opus-4-5":{"id":"claude-opus-4-5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"hy3-preview":{"id":"hy3-preview","name":"Hy3 Preview","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":128000},"cost":{"input":0.17,"output":0.566661,"cache_read":0.051},"canonical_model_id":"tencent/hy3-preview"},"alicloud-deepseek-v4-pro":{"id":"alicloud-deepseek-v4-pro","name":"DeepSeek V4 Pro (Alibaba Cloud)","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.69,"output":3.38,"cache_read":0.13}},"zai-glm-5.1":{"id":"zai-glm-5.1","name":"GLM-5.1 (Z.ai)","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-27","last_updated":"2026-03-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.845,"output":3.38,"cache_read":0.183112}},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.155,"output":0.62,"cache_read":0.0031},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"qwen3.8-max-preview":{"id":"qwen3.8-max-preview","name":"Qwen3.8 Max Preview","description":"Preview Qwen flagship for million-token multimodal reasoning and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-07-19","last_updated":"2026-07-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.338,"output":1.014,"cache_read":0.0676,"cache_write":0.4225},"canonical_model_id":"alibaba/qwen3.8-max-preview"},"coding-minimax-m2.7-highspeed":{"id":"coding-minimax-m2.7-highspeed","name":"Coding MiniMax M2.7 Highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":128100},"cost":{"input":0.2,"output":0.2}},"muse-spark-1.1":{"id":"muse-spark-1.1","name":"Muse Spark 1.1","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.375,"output":4.675},"canonical_model_id":"meta/muse-spark-1.1"},"deepseek-v4-flash-vision-exp":{"id":"deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.155,"output":0.62,"cache_read":0.0031},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"kimi-k2.7-code-highspeed":{"id":"kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code Highspeed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":1.9,"output":7.999,"cache_read":0.32167},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"qwen3.7-flash":{"id":"qwen3.7-flash","name":"Qwen3.7 Flash","description":"Lightweight multimodal Qwen model for high-throughput text, image, and video tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":991000,"input":991808,"output":64000},"cost":{"input":0.0282,"output":0.1128,"cache_read":0.00564,"cache_write":0.03525},"canonical_model_id":"alibaba/qwen3.7-flash"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.95,"output":4,"cache_read":0.16}},"claude-sonnet-4-5":{"id":"claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125,"tiers":[{"input":6.6,"output":24.75,"cache_read":0.66,"cache_write":8.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6.6,"output":24.75,"cache_read":0.66,"cache_write":8.25}},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"qwen3-max":{"id":"qwen3-max","name":"Qwen3 Max","description":"Flagship Qwen3 model for coding agents, complex reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.4508,"output":2.7048,"cache_read":0.09016,"cache_write":0.5635,"tiers":[{"input":0.902,"output":5.412,"cache_read":0.1804,"cache_write":1.1275,"tier":{"type":"context","size":32000}},{"input":1.3522,"output":8.1132,"cache_read":0.27044,"cache_write":1.69025,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3-max"},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"coding-glm-5.3-free":{"id":"coding-glm-5.3-free","name":"GLM-5.3 (Coding, free)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-5.3"},"gpt-image-2.5-flare":{"id":"gpt-image-2.5-flare","name":"GPT Image 2.5 Flare","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":30,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-2.5-flare"},"claude-opus-4-8-think":{"id":"claude-opus-4-8-think","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"doubao-seed-2-0-pro":{"id":"doubao-seed-2-0-pro","name":"Doubao Seed 2.0 Pro","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.48,"output":2.41,"cache_read":0.09644,"tiers":[{"input":0.72,"output":3.62,"cache_read":0.144656,"tier":{"type":"context","size":32000}},{"input":1.45,"output":7.23,"cache_read":0.28932,"tier":{"type":"context","size":128000}}]}},"xiaomi-mimo-v2.5":{"id":"xiaomi-mimo-v2.5","name":"Xiaomi MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo-v2.5","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-05-13","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.44,"output":2.2,"cache_read":0.088,"tiers":[{"input":0.88,"output":4.4,"cache_read":0.176,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.88,"output":4.4,"cache_read":0.176}},"canonical_model_id":"xiaomi/mimo-v2.5"},"glm-4.5v":{"id":"glm-4.5v","name":"GLM-4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":16384},"cost":{"input":0.274,"output":1.096,"tiers":[{"input":0.548,"output":1.644,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.5v"},"claude-fable-5-1":{"id":"claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":11,"output":55,"cache_read":0.275,"cache_write":13.75},"canonical_model_id":"anthropic/claude-fable-5-1"},"gemini-3.6-flash":{"id":"gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"google/gemini-3.6-flash"},"step-5-preview":{"id":"step-5-preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":1000000},"cost":{"input":1.08,"output":3.0888,"cache_read":0.054},"canonical_model_id":"stepfun/step-5-preview"},"longcat-2.0":{"id":"longcat-2.0","name":"LongCat-2.0","description":"Meituan LongCat-2.0, a reasoning model with tool calling and a 1M-token context window","family":"longcat","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.7746,"output":3.0984,"cache_read":0.015492},"canonical_model_id":"meituan/longcat-2.0"},"mimo-v2.6-pro-ultraspeed":{"id":"mimo-v2.6-pro-ultraspeed","name":"MiMo-V2.6-Pro-UltraSpeed","description":"MiMo pro model for strong multimodal reasoning and agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":4.8,"output":9.6,"cache_read":0.0384},"canonical_model_id":"xiaomi/mimo-v2.6-pro-ultraspeed"},"doubao-seed-2-0-code-preview":{"id":"doubao-seed-2-0-code-preview","name":"Doubao Seed 2.0 Code Preview","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.48,"output":2.41,"cache_read":0.09644,"tiers":[{"input":0.72,"output":3.62,"cache_read":0.144656,"tier":{"type":"context","size":32000}},{"input":1.45,"output":7.23,"cache_read":0.28932,"tier":{"type":"context","size":128000}}]}},"grok-4.3":{"id":"grok-4.3","name":"Grok 4.3","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-01","last_updated":"2026-05-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"qwen3.8-omni-flash":{"id":"qwen3.8-omni-flash","name":"Qwen3.8 Omni Flash","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.1126,"output":0.380025,"cache_read":0.014075,"cache_write":0.175937},"canonical_model_id":"alibaba/qwen3.8-omni-flash"},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"doubao-seed-2-0-mini-260428":{"id":"doubao-seed-2-0-mini-260428","name":"Doubao Seed 2.0 Mini 260428","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.03,"output":0.28,"cache_read":0.00564,"input_audio":0.423,"tiers":[{"input":0.06,"output":0.56,"cache_read":0.01128,"input_audio":0.846,"tier":{"type":"context","size":32000}},{"input":0.11,"output":1.13,"cache_read":0.02256,"input_audio":1.692,"tier":{"type":"context","size":128000}}]}},"xiaomi-mimo-v2.5-pro-free":{"id":"xiaomi-mimo-v2.5-pro-free","name":"Xiaomi MiMo-V2.5-Pro (free)","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo-v2.5-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-05-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"gemini-3.5-flash-lite":{"id":"gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.499999,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"gemini-3.1-flash-image":{"id":"gemini-3.1-flash-image","name":"Nano Banana 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":false,"interleaved":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","video","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3.1-flash-image"},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"gemini-3.1-pro-preview":{"id":"gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}}},"grok-4.5":{"id":"grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.5"},"qwen3.5-122b-a10b":{"id":"qwen3.5-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.1126,"output":0.9008,"tiers":[{"input":0.2818,"output":2.2544,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.6,"output":3,"cache_read":0.1}},"gpt-5.1":{"id":"gpt-5.1","name":"GPT-5.1","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.13}},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"nemotron-3-ultra-550b-a55b-free":{"id":"nemotron-3-ultra-550b-a55b-free","name":"Nemotron 3 Ultra 550B A55B (free)","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"coding-minimax-m2.7":{"id":"coding-minimax-m2.7","name":"Coding MiniMax M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":128100},"cost":{"input":0.2,"output":0.2}},"qwen3.6-35b-a3b":{"id":"qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.254,"output":1.524},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"minimax-m2.7":{"id":"minimax-m2.7","name":"MiniMax M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":128000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":0.375}},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":1.5,"output":9,"cache_read":1.5},"canonical_model_id":"google/gemini-3.5-flash"},"gemini-2.5-pro":{"id":"gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-03-20","last_updated":"2025-06-05","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}}},"deep-deepseek-v4-flash":{"id":"deep-deepseek-v4-flash","name":"DeepSeek V4 Flash (DeepSeek)","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.154,"output":0.308,"cache_read":0.0308}},"coding-glm-5.3-flash-free":{"id":"coding-glm-5.3-flash-free","name":"GLM-5.3-Flash (Coding, free)","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"qwen3.6-flash":{"id":"qwen3.6-flash","name":"Qwen3.6 Flash","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":991000,"output":64000},"cost":{"input":0.17,"output":1.01,"cache_read":0.0169,"cache_write":0.21125,"tiers":[{"input":0.68,"output":4.06,"cache_read":0.0676,"cache_write":0.845,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.68,"output":4.06,"cache_read":0.0676,"cache_write":0.845}}},"gemini-3-pro-image":{"id":"gemini-3-pro-image","name":"Nano Banana Pro","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":false,"interleaved":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":2,"output":120},"canonical_model_id":"google/gemini-3-pro-image"},"coding-glm-5.1":{"id":"coding-glm-5.1","name":"Coding GLM 5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-11","last_updated":"2026-04-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.06,"output":0.22,"cache_read":0.013}},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-03-20","last_updated":"2025-06-05","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"input_audio":1}},"gpt-image-2.5-sunburst":{"id":"gpt-image-2.5-sunburst","name":"GPT Image 2.5 Sunburst","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":30,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-2.5-sunburst"},"xiaomi-mimo-v2.5-free":{"id":"xiaomi-mimo-v2.5-free","name":"Xiaomi MiMo-V2.5 (free)","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo-v2.5","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-05-13","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.5"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":11,"output":55,"cache_read":1.1,"cache_write":13.75},"canonical_model_id":"anthropic/claude-fable-5"},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.6918,"output":2.0754,"cache_read":0.023058},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"mimo-v2.5-pro":{"id":"mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.48,"output":0.96,"cache_read":0.00384},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"nemotron-3-super-120b-a12b-free":{"id":"nemotron-3-super-120b-a12b-free","name":"Nemotron 3 Super 120B A12B (free)","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"claude-sonnet-4-5-think":{"id":"claude-sonnet-4-5-think","name":"Claude Sonnet 4.5 Thinking","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125,"tiers":[{"input":6.6,"output":24.75,"cache_read":0.66,"cache_write":8.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6.6,"output":24.75,"cache_read":0.66,"cache_write":8.25}},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"muse-spark-1.2":{"id":"muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.375,"output":4.675},"canonical_model_id":"meta/muse-spark-1.2"},"gemini-3.1-flash-lite-image":{"id":"gemini-3.1-flash-lite-image","name":"Nano Banana 2 Lite","description":"Fastest, most cost-efficient Gemini image model for high-volume 1K generation and editing","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":4096},"cost":{"input":0.25,"output":1.5,"cache_read":0.025},"canonical_model_id":"google/gemini-3.1-flash-lite-image"},"mimo-v2.6-flash":{"id":"mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.155,"output":0.31,"cache_read":0.0031},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":1.5,"output":9,"cache_read":0.15},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.75,"output":4.5,"cache_read":0.075}},"glm-4.7":{"id":"glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.273974,"output":1.095896,"cache_read":0.0547948,"tiers":[{"input":0.547946,"output":2.191784,"cache_read":0.1095892,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.7"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.288,"output":1.152},"canonical_model_id":"minimax/MiniMax-M3"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":1,"output":6,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"openai/gpt-5.6-luna"},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.1126,"output":0.380025,"cache_read":0.014075,"cache_write":0.175937},"canonical_model_id":"alibaba/qwen3.8-flash"},"claude-opus-4-6-think":{"id":"claude-opus-4-6-think","name":"Claude Opus 4.6 Thinking","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5}}},"coding-xiaomi-mimo-v2.5":{"id":"coding-xiaomi-mimo-v2.5","name":"Coding Xiaomi MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo-v2.5","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-05-13","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.08,"output":0.4,"cache_read":0.016,"tiers":[{"input":0.16,"output":0.8,"cache_read":0.032,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.16,"output":0.8,"cache_read":0.032}},"canonical_model_id":"xiaomi/mimo-v2.5"},"gpt-5.2":{"id":"gpt-5.2","name":"GPT-5.2","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":12.5,"output":75,"cache_read":1.25},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}}},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"ox-alpha":{"id":"ox-alpha","name":"Ox Alpha","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"glm-4.7-flash-free":{"id":"glm-4.7-flash-free","name":"GLM-4.7-Flash (free)","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-4.7-flash"},"coding-glm-5.2-free":{"id":"coding-glm-5.2-free","name":"GLM-5.2 (Coding, free)","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-5.2"},"qwen3.5-35b-a3b":{"id":"qwen3.5-35b-a3b","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.0564,"output":0.4512,"tiers":[{"input":0.2254,"output":1.8032,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"qwen3.6-max-preview":{"id":"qwen3.6-max-preview","name":"Qwen3.6 Max Preview","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"qwen3.6","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-05-09","last_updated":"2026-05-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":240000,"output":64000},"cost":{"input":1.27,"output":7.61,"cache_read":0.1268,"cache_write":1.585,"tiers":[{"input":2.11,"output":12.67,"cache_read":0.2112,"cache_write":2.64,"tier":{"type":"context","size":128000}}]}},"qwen3.5-397b-a17b":{"id":"qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.1644,"output":0.9864,"tiers":[{"input":0.411,"output":2.466,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"nemotron-3.5-lightning-free":{"id":"nemotron-3.5-lightning-free","name":"Nemotron 3.5 Lightning 30B A3B (free)","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5}}},"gemini-3.7-flash":{"id":"gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.7-flash"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":1.1268,"output":3.9438,"cache_read":0.2817},"canonical_model_id":"zhipuai/glm-5.2"},"hy3":{"id":"hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":192000,"output":128000},"cost":{"input":0.1562,"output":0.6248,"cache_read":0.03905},"canonical_model_id":"tencent/hy3"},"nemotron-3-nano-omni-30b-a3b-reasoning-free":{"id":"nemotron-3-nano-omni-30b-a3b-reasoning-free","name":"Nemotron 3 Nano Omni 30B A3B Reasoning (free)","description":"Open Nemotron omni model combining reasoning with text, vision, and audio","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning"},"gemini-3.1-pro-preview-customtools":{"id":"gemini-3.1-pro-preview-customtools","name":"Gemini 3.1 Pro Preview Custom Tools","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}}},"gemini-3-flash-preview":{"id":"gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"tiers":[{"input":0.5,"output":3,"cache_read":0.05,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":0.5,"output":3,"cache_read":0.05}}},"grok-build-0.1":{"id":"grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.2},"canonical_model_id":"xai/grok-build-0.1"},"claude-opus-4-7-think":{"id":"claude-opus-4-7-think","name":"Claude Opus 4.7 Thinking","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5}}},"alicloud-deepseek-v4-flash":{"id":"alicloud-deepseek-v4-flash","name":"DeepSeek V4 Flash (Alibaba Cloud)","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.028}},"ling-3.0-flash-free":{"id":"ling-3.0-flash-free","name":"Ling 3.0 Flash (free)","description":"Hybrid-linear MoE reasoning model with 124B total and 5.1B active parameters for efficient agents","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-07-23","last_updated":"2026-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"inclusionai/ling-3.0-flash"},"coding-xiaomi-mimo-v2.5-pro":{"id":"coding-xiaomi-mimo-v2.5-pro","name":"Coding Xiaomi MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo-v2.5-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-05-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.2,"output":0.6,"cache_read":0.04,"tiers":[{"input":0.4,"output":1.2,"cache_read":0.08,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.4,"output":1.2,"cache_read":0.08}},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"gemini-3.8-flash":{"id":"gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.8-flash"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"step-3.7-flash":{"id":"step-3.7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.22,"output":1.32,"cache_read":0.044},"canonical_model_id":"stepfun/step-3.7-flash"},"alicloud-glm-5.1":{"id":"alicloud-glm-5.1","name":"GLM-5.1 (Alibaba Cloud)","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-27","last_updated":"2026-03-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.84,"output":3.38,"cache_read":0.169,"cache_write":1.05625}},"gemini-2.5-flash-lite":{"id":"gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":512,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"input_audio":0.3},"canonical_model_id":"google/gemini-2.5-flash-lite"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}}},"coding-glm-5.1-free":{"id":"coding-glm-5.1-free","name":"Coding GLM 5.1 (free)","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm-free","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-11","last_updated":"2026-04-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0,"output":0}},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"gpt-image-1.5":{"id":"gpt-image-1.5","name":"GPT-Image-1.5","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-11-25","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":32},"canonical_model_id":"openai/gpt-image-1.5"},"qwen3.6-plus":{"id":"qwen3.6-plus","name":"Qwen3.6 Plus","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-05-09","last_updated":"2026-05-09","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":991000,"output":64000},"cost":{"input":0.28,"output":1.69,"cache_read":0.0282,"cache_write":0.3525,"tiers":[{"input":1.13,"output":6.77,"cache_read":0.1128,"cache_write":1.41,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1.13,"output":6.77,"cache_read":0.1128,"cache_write":1.41}}},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"cache_write":3.125},"canonical_model_id":"openai/gpt-5.6-terra"},"hy4-preview":{"id":"hy4-preview","name":"Hy4 preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":64000},"cost":{"input":0.845,"output":2.535,"cache_read":0.04225},"canonical_model_id":"tencent/hy4-preview"},"gpt-5.1-codex-mini":{"id":"gpt-5.1-codex-mini","name":"GPT-5.1 Codex mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025}},"o3":{"id":"o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":1.1268,"output":3.9438,"cache_read":0.2817},"canonical_model_id":"zhipuai/glm-5.3"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5}}},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.95,"output":3.9995,"cache_read":0.160835},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"gpt-5":{"id":"gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"grok-4.6":{"id":"grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"xiaomi-mimo-v2.5-pro":{"id":"xiaomi-mimo-v2.5-pro","name":"Xiaomi MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo-v2.5-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-05-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.1,"output":3.3,"cache_read":0.22,"tiers":[{"input":2.2,"output":6.6,"cache_read":0.44,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2.2,"output":6.6,"cache_read":0.44}},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":991000,"output":64000},"cost":{"input":0.282,"output":1.128,"cache_read":0.0564,"cache_write":0.3525},"canonical_model_id":"alibaba/qwen3.7-plus"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"openai/gpt-5.6-sol"},"gemini-4-argon":{"id":"gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":10,"cache_read":0.1,"input_audio":2},"canonical_model_id":"google/gemini-4-argon"},"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"gemini-3.1-flash-lite":{"id":"gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"cache_write":1}}}},"merge-gateway":{"id":"merge-gateway","env":["MERGE_GATEWAY_API_KEY"],"npm":"merge-gateway-ai-sdk-provider","api":"https://api-gateway.merge.dev/v1/ai-sdk","name":"Merge Gateway","doc":"https://docs.merge.dev/merge-gateway","models":{"zai/glm-4.5":{"id":"zai/glm-4.5","name":"GLM-4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":98304},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5"},"zai/glm-5.3-flash":{"id":"zai/glm-5.3-flash","name":"GLM-5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai/glm-4.6":{"id":"zai/glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.6"},"zai/glm-5":{"id":"zai/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2,"cache_write":0},"canonical_model_id":"zhipuai/glm-5"},"zai/glm-4.5v":{"id":"zai/glm-4.5v","name":"Glm 4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"cost":{"input":0.6,"output":1.8,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5v"},"zai/glm-4.7-flash":{"id":"zai/glm-4.7-flash","name":"GLM 4.7 Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.07,"output":0.4},"canonical_model_id":"zhipuai/glm-4.7-flash"},"zai/glm-4.7":{"id":"zai/glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7"},"zai/glm-5.2":{"id":"zai/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":50000}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.05,"output":3.3,"cache_read":0.195},"canonical_model_id":"zhipuai/glm-5.2"},"zai/glm-5.1":{"id":"zai/glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.1"},"zai/glm-4.7-flashx":{"id":"zai/glm-4.7-flashx","name":"GLM-4.7 FlashX","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.07,"output":0.4,"cache_read":0.01,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7-flashx"},"zai/glm-5-turbo":{"id":"zai/glm-5-turbo","name":"GLM-5 Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24,"cache_write":0},"canonical_model_id":"zhipuai/glm-5-turbo"},"zai/glm-4.5-air":{"id":"zai/glm-4.5-air","name":"GLM-4.5 Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":98304},"cost":{"input":0.2,"output":1.1,"cache_read":0.03,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5-air"},"zai/glm-5.3":{"id":"zai/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.7,"output":2.2,"cache_read":0.13},"canonical_model_id":"zhipuai/glm-5.3"},"anthropic/claude-3-7-sonnet-20250219":{"id":"anthropic/claude-3-7-sonnet-20250219","name":"Claude 3.7 Sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-10-31","release_date":"2025-02-19","last_updated":"2025-02-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-3-7-sonnet-20250219"},"anthropic/claude-opus-5-5":{"id":"anthropic/claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-opus-4-20250514":{"id":"anthropic/claude-opus-4-20250514","name":"Claude Opus 4 (20250514)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":31999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-20250514"},"anthropic/claude-fable-5-1":{"id":"anthropic/claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-opus-4-1-20250805":{"id":"anthropic/claude-opus-4-1-20250805","name":"Claude Opus 4.1 (20250805)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":31999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1-20250805"},"anthropic/claude-opus-4-5-20251101":{"id":"anthropic/claude-opus-4-5-20251101","name":"Claude Opus 4.5 (20251101)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-01","last_updated":"2025-11-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-opus-4-8":{"id":"anthropic/claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":128000}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-sonnet-4-5-20250929":{"id":"anthropic/claude-sonnet-4-5-20250929","name":"Claude Sonnet 4.5 (20250929)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-opus-4-6":{"id":"anthropic/claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024,"max":127999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":30,"output":150,"cache_read":3,"cache_write":37.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-haiku-4-5-20251001":{"id":"anthropic/claude-haiku-4-5-20251001","name":"Claude Haiku 4.5 (20251001)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"anthropic/claude-haiku-5-5":{"id":"anthropic/claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-sonnet-4-6":{"id":"anthropic/claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-sonnet-4-20250514":{"id":"anthropic/claude-sonnet-4-20250514","name":"Claude Sonnet 4","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-20250514"},"anthropic/claude-sonnet-5-5":{"id":"anthropic/claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-opus-4-7":{"id":"anthropic/claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":30,"output":150,"cache_read":3,"cache_write":37.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"cohere/command-r-08-2024":{"id":"cohere/command-r-08-2024","name":"Command R 08-2024","description":"Cohere retrieval model for long-context chat and enterprise RAG workflows","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"cohere/command-r-08-2024"},"cohere/command-a-03-2025":{"id":"cohere/command-a-03-2025","name":"Command A 03-2025","description":"Cohere command model for multilingual enterprise agents, tools, and chat","family":"command-a","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2025-03-13","last_updated":"2025-03-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8000},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-a-03-2025"},"cohere/command-r7b-12-2024":{"id":"cohere/command-r7b-12-2024","name":"Command R7B 12-2024","description":"Cohere retrieval model for long-context chat and enterprise RAG workflows","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-12-02","last_updated":"2024-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.0375,"output":0.15},"canonical_model_id":"cohere/command-r7b-12-2024"},"cohere/command-r-plus-08-2024":{"id":"cohere/command-r-plus-08-2024","name":"Command R+ 08-2024","description":"Cohere's RAG workhorse for long-context enterprise search and tool use","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-r-plus-08-2024"},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.035,"output":0.07,"cache_read":0.007},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v4-flash-0423":{"id":"deepseek/deepseek-v4-flash-0423","name":"DeepSeek V4 Flash 0423","description":"Initial DeepSeek V4 Flash snapshot for economical reasoning, coding, and million-token agent workloads","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.139,"output":0.278},"canonical_model_id":"deepseek/deepseek-v4-flash-0423"},"deepseek/deepseek-v4-flash-0731-fast":{"id":"deepseek/deepseek-v4-flash-0731-fast","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.28,"output":0.56,"cache_read":0.07},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v3":{"id":"deepseek/deepseek-v3","name":"DeepSeek V3","description":"Open DeepSeek MoE chat model for coding, math, and general reasoning","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2024-12-26","last_updated":"2024-12-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":81920},"cost":{"input":0.27,"output":1.1},"canonical_model_id":"deepseek/deepseek-v3"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.74,"output":3.48,"cache_read":0.003625},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek/deepseek-v4-pro-0423":{"id":"deepseek/deepseek-v4-pro-0423","name":"DeepSeek V4 Pro 0423","description":"DeepSeek V4 Pro initial snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":1.65,"output":3.3},"canonical_model_id":"deepseek/deepseek-v4-pro-0423"},"deepseek/deepseek-v3.1":{"id":"deepseek/deepseek-v3.1","name":"DeepSeek V3.1","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":41000},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"deepseek/deepseek-v3.1"},"deepseek/deepseek-r1":{"id":"deepseek/deepseek-r1","name":"DeepSeek R1","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":40960},"cost":{"input":1.35,"output":5.4},"canonical_model_id":"deepseek/deepseek-r1"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":262000},"cost":{"input":1.74,"output":3.48,"cache_read":0.145},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-r1-0528":{"id":"deepseek/deepseek-r1-0528","name":"DeepSeek R1 (0528)","description":"May 2025 DeepSeek R1 update with improved mathematics, coding, and reasoning","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":32768},"cost":{"input":1.35,"output":5.4,"cache_read":0.945},"canonical_model_id":"deepseek/deepseek-r1-0528"},"deepseek/deepseek-v3.2":{"id":"deepseek/deepseek-v3.2","name":"DeepSeek V3.2","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.28,"output":0.4,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.3,"output":1.2,"cache_read":0.006,"cache_write":0.1125},"canonical_model_id":"deepseek/deepseek-v4-flash"},"thinkingmachines/inkling":{"id":"thinkingmachines/inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048000,"output":32000},"cost":{"input":1,"output":4.05,"cache_read":0.17},"canonical_model_id":"thinkingmachines/inkling"},"meta/muse-spark-1.1":{"id":"meta/muse-spark-1.1","name":"Muse Spark 1.1","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":262144},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.1"},"meta/llama-3.3-70b-instruct":{"id":"meta/llama-3.3-70b-instruct","name":"Llama 3.3 70B Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.22,"output":0.5,"cache_read":0.11},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"meta/muse-spark-1.2":{"id":"meta/muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":262144},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"meta/llama-3.1-8b-instruct":{"id":"meta/llama-3.1-8b-instruct","name":"Llama 3.1 8B","description":"Compact open Llama model for lightweight chat, drafting, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":2048},"cost":{"input":0.22,"output":0.22},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"meta/llama-3.1-70b-instruct":{"id":"meta/llama-3.1-70b-instruct","name":"Llama 3.1 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":2048},"cost":{"input":0.99,"output":0.99},"canonical_model_id":"meta/llama-3.1-70b-instruct"},"meta/muse-spark-open":{"id":"meta/muse-spark-open","name":"Muse Spark Open","description":"Muse Spark Open is an 816B total / 42B active open-weight multimodal reasoning model from Meta for coding and long-horizon agentic work, with 1M-token context.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-open"},"bytedance/dola-seed-2.0-code-preview":{"id":"bytedance/dola-seed-2.0-code-preview","name":"Dola Seed 2.0 Code (preview)","description":"Preview coding model for repository understanding, refactors, and engineering tasks","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-03-28","last_updated":"2026-03-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":3}},"bytedance/dola-seed-2.0-code":{"id":"bytedance/dola-seed-2.0-code","name":"Seed 2.0 Code","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","family":"seed","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.4,"output":2.4},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"bytedance/dola-seed-2.0-mini":{"id":"bytedance/dola-seed-2.0-mini","name":"Seed 2.0 Mini","description":"Low-cost Seed model for general chat, extraction, and lightweight production tasks","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.1,"output":0.4}},"bytedance/dola-seed-2.0-lite":{"id":"bytedance/dola-seed-2.0-lite","name":"Seed 2.0 Lite","description":"Efficient Seed model for general chat, analysis, and lightweight production tasks","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-02-28","last_updated":"2026-02-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.25,"output":2}},"bytedance/dola-seed-2.0-pro":{"id":"bytedance/dola-seed-2.0-pro","name":"Seed 2.0 Pro","description":"Higher-capability Seed model for complex chat, analysis, and production tasks","family":"seed","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-03-28","last_updated":"2026-03-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":3}},"google/gemini-flash-latest":{"id":"google/gemini-flash-latest","name":"Gemini Flash Latest","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-flash-latest"},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B It","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.14,"output":0.4},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemma-3-27b-it":{"id":"google/gemma-3-27b-it","name":"Gemma 3 27B IT","description":"Largest open Gemma 3 instruction model for multilingual text generation and visual understanding","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.08,"output":0.45,"cache_read":0.04},"canonical_model_id":"google/gemma-3-27b-it"},"google/gemini-3-pro-preview":{"id":"google/gemini-3-pro-preview","name":"Gemini 3 Pro Preview","description":"Preview Gemini flagship for complex reasoning, coding, and rich multimodal prompts","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3-pro-preview"},"google/gemini-2.5-flash-image":{"id":"google/gemini-2.5-flash-image","name":"Gemini 2.5 Flash Image","description":"Nano Banana image model for fast generation, edits, and character-consistent assets","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.3,"output":2.5},"canonical_model_id":"google/gemini-2.5-flash-image"},"google/gemini-flash-lite-latest":{"id":"google/gemini-flash-lite-latest","name":"Gemini Flash-Lite Latest","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-flash-lite-latest"},"google/gemini-embedding-2":{"id":"google/gemini-embedding-2","name":"Gemini Embedding 2","description":"Multimodal embedding model mapping text, images, video, audio, and PDFs into a unified embedding space","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2025-11","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8192},"cost":{"input":0.2,"output":0},"canonical_model_id":"google/gemini-embedding-2"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"google/gemini-3.6-flash"},"google/gemma-4-26b-a4b-it":{"id":"google/gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.13,"output":0.4},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash-Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemini-3.1-flash-image":{"id":"google/gemini-3.1-flash-image","name":"Gemini 3.1 Flash Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3.1-flash-image"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemma-3-12b-it":{"id":"google/gemma-3-12b-it","name":"Gemma 3 12B","description":"Open multimodal Gemma instruction model for multilingual text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.09,"output":0.29},"canonical_model_id":"google/gemma-3-12b-it"},"google/gemini-2.5-computer-use-preview-10-2025":{"id":"google/gemini-2.5-computer-use-preview-10-2025","name":"Gemini 2.5 Computer Use Preview (10-2025)","description":"Specialized Gemini 2.5 model for browser-control agents that automate UI tasks","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-10-07","last_updated":"2025-10-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"cost":{"input":1.25,"output":10},"canonical_model_id":"google/gemini-2.5-computer-use-preview-10-2025"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro"},"google/gemini-3-pro-image":{"id":"google/gemini-3-pro-image","name":"Gemini 3 Pro Image","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":65536},"cost":{"input":2,"output":12},"canonical_model_id":"google/gemini-3-pro-image"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"input_audio":1},"canonical_model_id":"google/gemini-2.5-flash"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.7-flash"},"google/gemini-3.1-pro-preview-customtools":{"id":"google/gemini-3.1-pro-preview-customtools","name":"Gemini 3.1 Pro Preview Custom Tools","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview-customtools"},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"input_audio":1},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemma-3-4b-it":{"id":"google/gemma-3-4b-it","name":"Gemma 3 4B","description":"Open multimodal Gemma instruction model for efficient text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.04,"output":0.08},"canonical_model_id":"google/gemma-3-4b-it"},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":512,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"input_audio":0.3},"canonical_model_id":"google/gemini-2.5-flash-lite"},"google/gemini-embedding-001":{"id":"google/gemini-embedding-001","name":"Gemini Embedding 001","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2025-05","release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":2048,"output":4096},"cost":{"input":0.15,"output":0},"canonical_model_id":"google/gemini-embedding-001"},"google/gemini-3.1-flash-lite-preview":{"id":"google/gemini-3.1-flash-lite-preview","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite-preview"},"google/gemini-4-argon":{"id":"google/gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":10,"cache_read":0.1},"canonical_model_id":"google/gemini-4-argon"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash-Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite"},"writer/palmyra-x4":{"id":"writer/palmyra-x4","name":"Palmyra X4","description":"Enterprise language model for writing, analysis, and tool-assisted workflows","family":"palmyra","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2024-10-09","last_updated":"2024-10-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000},"cost":{"input":2.5,"output":10}},"writer/palmyra-x5":{"id":"writer/palmyra-x5","name":"Palmyra X5","description":"Enterprise multimodal model for writing, analysis, and tool-assisted workflows","family":"palmyra","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":250000},"cost":{"input":0.6,"output":6}},"xai/grok-4.7":{"id":"xai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.7"},"xai/grok-4.3":{"id":"xai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.3"},"xai/grok-4.20-0309-reasoning":{"id":"xai/grok-4.20-0309-reasoning","name":"Grok 4.20","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-reasoning"},"xai/grok-4.5":{"id":"xai/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.5"},"xai/grok-4.20-0309-non-reasoning":{"id":"xai/grok-4.20-0309-non-reasoning","name":"Grok 4.20 Non-Reasoning","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2},"canonical_model_id":"xai/grok-4.20-0309-non-reasoning"},"xai/grok-build-0.1":{"id":"xai/grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.2},"canonical_model_id":"xai/grok-build-0.1"},"xai/grok-4.6":{"id":"xai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"sakana/fugu-max":{"id":"sakana/fugu-max","name":"Fugu Max","description":"Multi-agent model for routing expert agents across complex analytical tasks","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"sakana/fugu-max"},"sakana/fugu-ultra":{"id":"sakana/fugu-ultra","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"sakana/fugu-ultra"},"sakana/sakana-namazu":{"id":"sakana/sakana-namazu","name":"Sakana Namazu","description":"Japanese-specialized reasoning model based on Kimi K2.6 and tuned for Japanese language, culture, and business workflows","family":"sakana-namazu","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.95,"output":4,"cache_read":0.15},"canonical_model_id":"sakana/sakana-namazu"},"moonshotai/kimi-k2-thinking":{"id":"moonshotai/kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Thinking Kimi model for slower research passes, planning, and hard technical questions","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.6,"output":2.5},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"nvidia/nemotron-3-nano-30b-a3b":{"id":"nvidia/nemotron-3-nano-30b-a3b","name":"Nemotron 3 Nano 30B A3B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32000},"cost":{"input":0.05,"output":0.2},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"nvidia/nemotron-3.5-lightning-30b-a3b":{"id":"nvidia/nemotron-3.5-lightning-30b-a3b","name":"Nemotron 3.5 Lightning 30B A3B","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/nemotron-nano-9b-v2":{"id":"nvidia/nemotron-nano-9b-v2","name":"Nemotron Nano 9B","description":"Compact Nemotron model for efficient reasoning and deployable AI agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-08-18","last_updated":"2025-08-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.06,"output":0.23},"canonical_model_id":"nvidia/nemotron-nano-9b-v2"},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":8192},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5"},"minimax/minimax-m2.7":{"id":"minimax/minimax-m2.7","name":"MiniMax M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":8192},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":128000}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"minimax/minimax-m2.7-highspeed":{"id":"minimax/minimax-m2.7-highspeed","name":"MiniMax M2.7 Highspeed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":8192},"cost":{"input":0.6,"output":2.4,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"minimax/minimax-m2.5-highspeed":{"id":"minimax/minimax-m2.5-highspeed","name":"MiniMax M2.5 Highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-13","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":8192},"cost":{"input":0.6,"output":2.4,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5-highspeed"},"minimax/minimax-m2.1":{"id":"minimax/minimax-m2.1","name":"MiniMax M2.1","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":8192},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.1"},"minimax/minimax-m2":{"id":"minimax/minimax-m2","name":"MiniMax M2","description":"Efficient open MiniMax model built for coding agents and tool-heavy workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":8192},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2"},"mistral/codestral-latest":{"id":"mistral/codestral-latest","name":"Codestral (latest)","description":"Mistral code model for completions, refactors, and developer IDE workflows","family":"codestral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-05-29","last_updated":"2025-01-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":4096},"cost":{"input":0.3,"output":0.9},"canonical_model_id":"mistral/codestral-latest"},"mistral/mistral-large-2411":{"id":"mistral/mistral-large-2411","name":"Mistral Large 2.1","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2024-11-18","last_updated":"2024-11-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":2,"output":6},"canonical_model_id":"mistral/mistral-large-2411"},"mistral/mistral-large-latest":{"id":"mistral/mistral-large-latest","name":"Mistral Large (latest)","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2024-11-01","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"mistral/mistral-large-latest"},"mistral/mistral-small-latest":{"id":"mistral/mistral-small-latest","name":"Mistral Small (latest)","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"mistral/mistral-small-latest"},"mistral/devstral-medium-latest":{"id":"mistral/devstral-medium-latest","name":"Devstral 2 (latest)","description":"Mistral coding agent model for repository tasks and software engineering workflows","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.4,"output":2},"canonical_model_id":"mistral/devstral-medium-latest"},"mistral/devstral-2512":{"id":"mistral/devstral-2512","name":"Devstral 2","description":"Mistral's coding-agent model for repository work, terminal tasks, and software fixes","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.4,"output":2,"cache_read":0.04},"canonical_model_id":"mistral/devstral-2512"},"mistral/mistral-medium-2505":{"id":"mistral/mistral-medium-2505","name":"Mistral Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000},"cost":{"input":0.4,"output":2,"cache_read":0.04},"canonical_model_id":"mistral/mistral-medium-2505"},"mistral/magistral-medium-latest":{"id":"mistral/magistral-medium-latest","name":"Magistral Medium (latest)","description":"Mistral reasoning model for transparent analysis, math, and complex decisions","family":"magistral-medium","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2025-03-17","last_updated":"2025-03-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2,"output":5},"canonical_model_id":"mistral/magistral-medium-latest"},"mistral/devstral-medium-2507":{"id":"mistral/devstral-medium-2507","name":"Devstral Medium","description":"Mistral coding agent model for repository tasks and software engineering workflows","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-07-10","last_updated":"2025-07-10","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000},"status":"deprecated","cost":{"input":0.4,"output":2},"canonical_model_id":"mistral/devstral-medium-2507"},"mistral/mistral-large-2512":{"id":"mistral/mistral-large-2512","name":"Mistral Large 3","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.5,"output":1.5,"cache_read":0.05},"canonical_model_id":"mistral/mistral-large-2512"},"mistral/devstral-small-2507":{"id":"mistral/devstral-small-2507","name":"Devstral Small","description":"Mistral coding agent model for repository tasks and software engineering workflows","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-07-10","last_updated":"2025-07-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"status":"deprecated","cost":{"input":0.1,"output":0.3},"canonical_model_id":"mistral/devstral-small-2507"},"mistral/pixtral-large-latest":{"id":"mistral/pixtral-large-latest","name":"Pixtral Large (latest)","description":"Mistral's larger vision model for document-heavy image understanding and chat","family":"pixtral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2024-11-01","last_updated":"2024-11-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":2,"output":6},"canonical_model_id":"mistral/pixtral-large-latest"},"mistral/mistral-medium-latest":{"id":"mistral/mistral-medium-latest","name":"Mistral Medium (latest)","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.4,"output":2},"canonical_model_id":"mistral/mistral-medium-latest"},"qwen/qwen-flash":{"id":"qwen/qwen-flash","name":"Qwen Flash","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":250000},"cost":{"input":0.022,"output":0.216,"cache_read":0.0044,"cache_write":0.0275},"canonical_model_id":"alibaba/qwen-flash"},"qwen/qwen3.5-flash":{"id":"qwen/qwen3.5-flash","name":"Qwen3.5 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":250000},"cost":{"input":0.029,"output":0.287,"cache_read":0.0029,"cache_write":0.03625},"canonical_model_id":"alibaba/qwen3.5-flash"},"qwen/qwen3-vl-235b-a22b-instruct":{"id":"qwen/qwen3-vl-235b-a22b-instruct","name":"Qwen3-VL 235B A22B Instruct","description":"Qwen vision-language instruct model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.21,"output":1.9,"cache_read":0.105},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":250000},"cost":{"input":0.825,"output":2.4755,"cache_read":0.165,"cache_write":1.03125},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen3-vl-235b-a22b-thinking":{"id":"qwen/qwen3-vl-235b-a22b-thinking","name":"Qwen3-VL 235B A22B Thinking","description":"Qwen vision-language thinking model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.287,"output":2.867,"cache_read":0.0574},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-thinking"},"qwen/qwen3.8-2.4t-a95b":{"id":"qwen/qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":1010000},"cost":{"input":2.5,"output":6.25,"cache_read":0.5},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"qwen/qwen3-vl-plus":{"id":"qwen/qwen3-vl-plus","name":"Qwen3-VL Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.143,"output":1.434,"cache_read":0.0286,"cache_write":0.17875},"canonical_model_id":"alibaba/qwen3-vl-plus"},"qwen/qwen3.5-27b":{"id":"qwen/qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.086,"output":0.688,"cache_read":0.0172},"canonical_model_id":"alibaba/qwen3.5-27b"},"qwen/qwen3-235b-a22b-instruct-2507":{"id":"qwen/qwen3-235b-a22b-instruct-2507","name":"Qwen3 235B A22B Instruct 2507","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.1,"output":0.6,"cache_read":0.0574},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"qwen/qwen3-next-80b-a3b-thinking":{"id":"qwen/qwen3-next-80b-a3b-thinking","name":"Qwen3-Next 80B-A3B (Thinking)","description":"Efficient Qwen thinking model for local reasoning, math, and coding agents","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":1.2},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-thinking"},"qwen/qwen3.8-max":{"id":"qwen/qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"qwen/qwen3-coder-next":{"id":"qwen/qwen3-coder-next","name":"Qwen3 Coder Next","description":"Open-weight Qwen coding model for agents, repository edits, and multi-turn tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.15,"output":0.8,"cache_read":0.075},"canonical_model_id":"alibaba/qwen3-coder-next"},"qwen/qwen3.5-plus":{"id":"qwen/qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":250000},"cost":{"input":0.115,"output":0.688,"cache_read":0.0115,"cache_write":0.14375},"canonical_model_id":"alibaba/qwen3.5-plus"},"qwen/qwen3-32b":{"id":"qwen/qwen3-32b","name":"Qwen3 32B","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"alibaba/qwen3-32b"},"qwen/qwen-plus":{"id":"qwen/qwen-plus","name":"Qwen Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":250000},"cost":{"input":0.115,"output":0.287,"cache_read":0.023,"cache_write":0.14375},"canonical_model_id":"alibaba/qwen-plus"},"qwen/qwen3-max":{"id":"qwen/qwen3-max","name":"Qwen3 Max","description":"Flagship Qwen3 model for coding agents, complex reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.359,"output":1.434,"cache_read":0.0718,"cache_write":0.44875},"canonical_model_id":"alibaba/qwen3-max"},"qwen/qwen3-coder-480b-a35b-instruct":{"id":"qwen/qwen3-coder-480b-a35b-instruct","name":"Qwen3 Coder 480B A35B Instruct","description":"Open Qwen coding heavyweight for repository reasoning and agentic engineering","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.22,"output":1.8},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"qwen/qwen3-vl-30b-a3b-instruct":{"id":"qwen/qwen3-vl-30b-a3b-instruct","name":"Qwen3-VL 30B-A3B Instruct","description":"Open vision-language MoE model for image and video understanding, documents, and visual agents","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-04","last_updated":"2025-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6,"cache_read":0.0216},"canonical_model_id":"alibaba/qwen3-vl-30b-a3b-instruct"},"qwen/qwen3-vl-flash":{"id":"qwen/qwen3-vl-flash","name":"Qwen3-VL Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.022,"output":0.215,"cache_read":0.0044,"cache_write":0.0275},"canonical_model_id":"alibaba/qwen3-vl-flash"},"qwen/qwen3-235b-a22b":{"id":"qwen/qwen3-235b-a22b","name":"Qwen3 235B A22B","description":"Large open Qwen MoE for multilingual reasoning, coding, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.287,"output":1.147,"cache_read":0.0574},"canonical_model_id":"alibaba/qwen3-235b-a22b"},"qwen/qwen3.5-122b-a10b":{"id":"qwen/qwen3.5-122b-a10b","name":"Qwen3.5 122B A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.115,"output":0.917,"cache_read":0.023},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"qwen/qwen3-max-preview":{"id":"qwen/qwen3-max-preview","name":"Qwen3 Max Preview","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-05","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":65536},"cost":{"input":1.08,"output":4.8},"canonical_model_id":"alibaba/qwen3-max-preview"},"qwen/qwen3.6-35b-a3b":{"id":"qwen/qwen3.6-35b-a3b","name":"Qwen3.6 35B A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.248,"output":1.485,"cache_read":0.0496},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"qwen/qwen3-next-80b-a3b-instruct":{"id":"qwen/qwen3-next-80b-a3b-instruct","name":"Qwen3-Next 80B-A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.1,"output":1.1,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"qwen/qwen3.6-flash":{"id":"qwen/qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":250000},"cost":{"input":0.165,"output":0.99,"cache_read":0.0165,"cache_write":0.20625},"canonical_model_id":"alibaba/qwen3.6-flash"},"qwen/qwen3-coder-flash":{"id":"qwen/qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":250000},"cost":{"input":0.144,"output":0.574,"cache_read":0.0288,"cache_write":0.18},"canonical_model_id":"alibaba/qwen3-coder-flash"},"qwen/qwen3-coder-plus":{"id":"qwen/qwen3-coder-plus","name":"Qwen3 Coder Plus","description":"Hosted Qwen coder for software agents, repo edits, and long-context code","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":250000},"cost":{"input":0.574,"output":2.294,"cache_read":0.1148,"cache_write":0.7175},"canonical_model_id":"alibaba/qwen3-coder-plus"},"qwen/qwen3.5-9b":{"id":"qwen/qwen3.5-9b","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.09,"output":0.13},"canonical_model_id":"alibaba/qwen3.5-9b"},"qwen/qwen3.8-flash":{"id":"qwen/qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":977000,"output":128000},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen/qwen3.5-35b-a3b":{"id":"qwen/qwen3.5-35b-a3b","name":"Qwen3.5 35B A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.057,"output":0.459,"cache_read":0.020357},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"qwen/qwen3.6-max-preview":{"id":"qwen/qwen3.6-max-preview","name":"Qwen3.6 Max Preview","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":65536},"cost":{"input":1.31,"output":7.88},"canonical_model_id":"alibaba/qwen3.6-max-preview"},"qwen/qwen3-30b-a3b":{"id":"qwen/qwen3-30b-a3b","name":"Qwen3 30B A3B","description":"Sparse MoE Qwen model with 3B active parameters for efficient chat and reasoning","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.108,"output":1.076,"cache_read":0.0216},"canonical_model_id":"alibaba/qwen3-30b-a3b"},"qwen/qwen3.5-397b-a17b":{"id":"qwen/qwen3.5-397b-a17b","name":"Qwen3.5 397B A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.172,"output":1.032,"cache_read":0.0344},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"qwen/qwen3.6-27b":{"id":"qwen/qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.4126,"output":2.4754},"canonical_model_id":"alibaba/qwen3.6-27b"},"qwen/qwen3.6-plus":{"id":"qwen/qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":250000},"cost":{"input":0.276,"output":1.651,"cache_read":0.0276,"cache_write":0.345},"canonical_model_id":"alibaba/qwen3.6-plus"},"qwen/qwen3.7-plus":{"id":"qwen/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.4,"output":1.6},"canonical_model_id":"alibaba/qwen3.7-plus"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":5,"output":30,"cache_read":0.5},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-oss-safeguard-120b":{"id":"openai/gpt-oss-safeguard-120b","name":"GPT OSS Safeguard 120B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":4096},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-safeguard-120b"},"openai/gpt-3.5-turbo":{"id":"openai/gpt-3.5-turbo","name":"GPT-3.5 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"output":4096},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"openai/gpt-3.5-turbo"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 Nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-4o-2024-05-13":{"id":"openai/gpt-4o-2024-05-13","name":"GPT-4o (2024-05-13)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-05-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":5,"output":15},"canonical_model_id":"openai/gpt-4o-2024-05-13"},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"openai/o4-mini":{"id":"openai/o4-mini","name":"o4 Mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.275},"canonical_model_id":"openai/o4-mini"},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3 Mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"openai/gpt-4":{"id":"openai/gpt-4","name":"GPT-4","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-11","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8192},"cost":{"input":30,"output":60},"canonical_model_id":"openai/gpt-4"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1 Nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"openai/gpt-5.2-chat-latest":{"id":"openai/gpt-5.2-chat-latest","name":"GPT-5.2 Chat Latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt-codex","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-chat-latest"},"openai/gpt-5.1-chat-latest":{"id":"openai/gpt-5.1-chat-latest","name":"GPT-5.1 Chat Latest","description":"Chat-tuned GPT-5.1 for polished assistants, writing, and product conversations","family":"gpt-codex","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-chat-latest"},"openai/o1":{"id":"openai/o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":15,"output":60,"cache_read":7.5},"canonical_model_id":"openai/o1"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-5-chat-latest":{"id":"openai/gpt-5-chat-latest","name":"GPT-5 Chat Latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt-codex","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5-chat-latest"},"openai/gpt-4o-2024-08-06":{"id":"openai/gpt-4o-2024-08-06","name":"GPT-4o (2024-08-06)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-08-06","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-08-06"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"openai/gpt-6-astra"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o Mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT-OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"cost":{"input":0.04,"output":0.15,"cache_read":0.02},"canonical_model_id":"openai/gpt-oss-20b"},"openai/gpt-oss-safeguard-20b":{"id":"openai/gpt-oss-safeguard-20b","name":"GPT OSS Safeguard 20B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":4096},"cost":{"input":0.07,"output":0.2,"cache_read":0,"cache_write":0},"canonical_model_id":"openai/gpt-oss-safeguard-20b"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 Mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":1.5,"output":9,"cache_read":0.15},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":12.5,"output":75,"cache_read":1.25},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-4o-2024-11-20":{"id":"openai/gpt-4o-2024-11-20","name":"GPT-4o (2024-11-20)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-11-20","last_updated":"2024-11-20","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-11-20"},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 Mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-5.3-chat-latest":{"id":"openai/gpt-5.3-chat-latest","name":"GPT-5.3 Chat Latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-chat-latest"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-4-turbo":{"id":"openai/gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":10,"output":30},"canonical_model_id":"openai/gpt-4-turbo"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT-OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"cost":{"input":0.05,"output":0.25},"canonical_model_id":"openai/gpt-oss-120b"},"openai/o3":{"id":"openai/o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":5},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-6-sol"},"moonshot/kimi-k3":{"id":"moonshot/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":2.9,"output":14,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshot/kimi-k2.7-code-highspeed":{"id":"moonshot/kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code Highspeed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"moonshot/kimi-k2.6":{"id":"moonshot/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshot/kimi-k2.5":{"id":"moonshot/kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":3,"cache_read":0.1},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshot/kimi-k2.7-code":{"id":"moonshot/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"}}},"opper":{"id":"opper","env":["OPPER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.opper.ai/v3/compat","name":"Opper","doc":"https://opper.ai/models","models":{"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1.1,"output":5.5,"cache_read":0.11,"cache_write":1.375},"canonical_model_id":"anthropic/claude-haiku-4-5"},"gpt-5.4-pro":{"id":"gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.4-pro"},"gemma-4-31b-it":{"id":"gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.46488,"output":2.44062},"canonical_model_id":"google/gemma-4-31b-it"},"muse-spark-1.3":{"id":"muse-spark-1.3","name":"Muse Spark 1.3","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.3"},"qwen3.8-27b":{"id":"qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.5811,"output":3},"canonical_model_id":"alibaba/qwen3.8-27b"},"gpt-5.5-pro":{"id":"gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180},"canonical_model_id":"openai/gpt-5.5-pro"},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"qwen3.8-2.4t-a95b":{"id":"qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":2.5,"output":6,"cache_read":0.63},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.2,"output":0.5,"cache_read":0.07},"canonical_model_id":"zhipuai/glm-5.3-flash"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-max"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15},"canonical_model_id":"moonshotai/kimi-k3"},"qwen3-coder-next":{"id":"qwen3-coder-next","name":"Qwen3 Coder Next","description":"Open-weight Qwen coding model for agents, repository edits, and multi-turn tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.5811,"output":2.3244},"canonical_model_id":"alibaba/qwen3-coder-next"},"claude-opus-4-5":{"id":"claude-opus-4-5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"claude-sonnet-4-5":{"id":"claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125,"tiers":[{"input":6.6,"output":24.75,"cache_read":0.66,"cache_write":8.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6.6,"output":24.75,"cache_read":0.66,"cache_write":8.25}},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"claude-fable-5-1":{"id":"claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"devstral-2512":{"id":"devstral-2512","name":"Devstral 2","description":"Mistral's coding-agent model for repository work, terminal tasks, and software fixes","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.4,"output":2},"canonical_model_id":"mistral/devstral-2512"},"sonar-pro":{"id":"sonar-pro","name":"Sonar Pro","description":"Deeper Sonar search model with broader retrieval and stronger synthesis","family":"sonar-pro","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8000},"cost":{"input":3,"output":15},"canonical_model_id":"perplexity/sonar-pro"},"grok-4.3":{"id":"grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2},"canonical_model_id":"xai/grok-4.3"},"gemini-3.5-flash-lite":{"id":"gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"gemini-3.1-pro-preview":{"id":"gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"grok-4.5":{"id":"grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.5"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-5"},"qwen3.6-35b-a3b":{"id":"qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.248,"output":1.485},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"gpt-oss-20b":{"id":"gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.11622,"output":0.488124},"canonical_model_id":"openai/gpt-oss-20b"},"minimax-m2.7":{"id":"minimax-m2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":131072},"cost":{"input":0.69732,"output":2.78928},"canonical_model_id":"minimax/MiniMax-M2.7"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15},"canonical_model_id":"google/gemini-3.5-flash"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"muse-spark-1.2":{"id":"muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.12,"tiers":[{"input":1.2,"output":4.8,"cache_read":0.24,"tier":{"type":"context","size":524288}}],"context_over_200k":{"input":1.2,"output":4.8,"cache_read":0.24}},"canonical_model_id":"minimax/MiniMax-M3"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"mistral-small-2603":{"id":"mistral-small-2603","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.5811,"output":2.44062},"canonical_model_id":"mistral/mistral-small-2603"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":2.2,"output":11,"cache_read":0.22,"cache_write":2.75},"canonical_model_id":"anthropic/claude-sonnet-5"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"gemini-3.7-flash":{"id":"gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.7-flash"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.62708,"output":5.811},"canonical_model_id":"zhipuai/glm-5.2"},"gemini-3-flash-preview":{"id":"gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05},"canonical_model_id":"google/gemini-3-flash-preview"},"grok-build-0.1":{"id":"grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.2},"canonical_model_id":"xai/grok-build-0.1"},"sonar":{"id":"sonar","name":"Sonar","description":"Fast web-grounded Sonar for current answers, citations, and lightweight retrieval","family":"sonar","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":1,"output":1},"canonical_model_id":"perplexity/sonar"},"mistral-large-2512":{"id":"mistral-large-2512","name":"Mistral Large 3","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"mistral/mistral-large-2512"},"gemini-3.8-flash":{"id":"gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.825,"output":4.125,"cache_read":0.0825},"canonical_model_id":"google/gemini-3.8-flash"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":1.78812,"output":3.57624},"canonical_model_id":"deepseek/deepseek-v4-pro"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"gpt-5.3-chat-latest":{"id":"gpt-5.3-chat-latest","name":"GPT-5.3 Chat (latest)","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"status":"deprecated","cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-chat-latest"},"sonar-reasoning-pro":{"id":"sonar-reasoning-pro","name":"Sonar Reasoning Pro","description":"Web-grounded Sonar for multi-step research questions that need cited reasoning","family":"sonar-reasoning","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":2,"output":8},"canonical_model_id":"perplexity/sonar-reasoning-pro"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":1.1622,"output":4.88124},"canonical_model_id":"openai/gpt-oss-120b"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.75,"output":4.6488,"cache_read":0.44},"canonical_model_id":"zhipuai/glm-5.3"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-7"},"grok-4.6":{"id":"grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":45,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1,"cache_write":12.5}},"canonical_model_id":"openai/gpt-5.6-sol"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.25,"output":0.66},"canonical_model_id":"deepseek/deepseek-v4-flash"}}},"nvidia":{"id":"nvidia","env":["NVIDIA_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://integrate.api.nvidia.com/v1","name":"Nvidia","doc":"https://docs.api.nvidia.com/nim/","models":{"baai/bge-m3":{"id":"baai/bge-m3","name":"BGE M3","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"bge","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-01-30","last_updated":"2026-04-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":1024},"cost":{"input":0,"output":0}},"poolside/laguna-xs-2.1":{"id":"poolside/laguna-xs-2.1","name":"Laguna XS 2.1","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-02","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0,"output":0},"canonical_model_id":"poolside/laguna-xs-2.1"},"abacusai/dracarys-llama-3.1-70b-instruct":{"id":"abacusai/dracarys-llama-3.1-70b-instruct","name":"dracarys-llama-3.1-70b-instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-09-11","last_updated":"2025-05-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"status":"deprecated","cost":{"input":0,"output":0}},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-5.3"},"thinkingmachines/inkling":{"id":"thinkingmachines/inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":16384},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"thinkingmachines/inkling"},"black-forest-labs/flux_1-schnell":{"id":"black-forest-labs/flux_1-schnell","name":"FLUX.1-schnell","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2024-07","release_date":"2024-08-01","last_updated":"2026-02-04","modalities":{"input":["text"],"output":["image"]},"open_weights":true,"limit":{"context":77,"input":77,"output":0},"cost":{"input":0,"output":0}},"black-forest-labs/flux.1-dev":{"id":"black-forest-labs/flux.1-dev","name":"FLUX.1-dev","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-08","release_date":"2024-08-01","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":4096,"output":0},"cost":{"input":0,"output":0}},"black-forest-labs/flux_1-kontext-dev":{"id":"black-forest-labs/flux_1-kontext-dev","name":"FLUX.1-Kontext-dev","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-08-12","last_updated":"2025-08-12","modalities":{"input":["text","image"],"output":["image"]},"open_weights":true,"limit":{"context":40960,"output":40960},"cost":{"input":0,"output":0}},"black-forest-labs/flux_2-klein-4b":{"id":"black-forest-labs/flux_2-klein-4b","name":"FLUX.2 Klein 4B","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-06","release_date":"2026-01-14","last_updated":"2026-01-31","modalities":{"input":["image","text"],"output":["image"]},"open_weights":true,"limit":{"context":40960,"output":40960},"cost":{"input":0,"output":0}},"meta/llama-guard-4-12b":{"id":"meta/llama-guard-4-12b","name":"Llama Guard 4 12B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-04-05","last_updated":"2026-04-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0,"output":0}},"meta/muse-glimmer-30b":{"id":"meta/muse-glimmer-30b","name":"Muse Glimmer 30B","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"meta/muse-glimmer-30b"},"meta/esmfold":{"id":"meta/esmfold","name":"esmfold","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-03-15","last_updated":"2025-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0,"output":0}},"meta/llama-3.3-70b-instruct":{"id":"meta/llama-3.3-70b-instruct","name":"Llama 3.3 70b Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-11-26","last_updated":"2024-11-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0,"output":0}},"meta/llama-3.2-90b-vision-instruct":{"id":"meta/llama-3.2-90b-vision-instruct","name":"Llama-3.2-90B-Vision-Instruct","description":"Open Llama multimodal model for image understanding and text reasoning","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0,"output":0}},"meta/llama-4-maverick-17b-128e-instruct":{"id":"meta/llama-4-maverick-17b-128e-instruct","name":"Llama 4 Maverick 17b 128e Instruct","description":"Open multimodal Llama model for strong reasoning and fast responses","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-02","release_date":"2025-04-01","last_updated":"2025-04-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0,"output":0}},"meta/llama-3.1-8b-instruct":{"id":"meta/llama-3.1-8b-instruct","name":"Llama 3.1 8B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16000,"output":4096},"status":"deprecated","cost":{"input":0,"output":0}},"meta/llama-3.2-11b-vision-instruct":{"id":"meta/llama-3.2-11b-vision-instruct","name":"Llama 3.2 11b Vision Instruct","description":"Open Llama multimodal model for image understanding and text reasoning","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-18","last_updated":"2024-09-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0,"output":0}},"meta/llama-3.2-1b-instruct":{"id":"meta/llama-3.2-1b-instruct","name":"Llama 3.2 1b Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-18","last_updated":"2024-09-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0,"output":0}},"meta/llama-3.2-3b-instruct":{"id":"meta/llama-3.2-3b-instruct","name":"Llama 3.2 3B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2024-09-18","last_updated":"2024-09-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32000},"status":"deprecated","cost":{"input":0,"output":0}},"meta/llama-3.1-70b-instruct":{"id":"meta/llama-3.1-70b-instruct","name":"Llama 3.1 70b Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-07-16","last_updated":"2024-07-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0,"output":0}},"meta/esm2-650m":{"id":"meta/esm2-650m","name":"esm2-650m","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-08-29","last_updated":"2025-03-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0,"output":0}},"upstage/solar-10.7b-instruct":{"id":"upstage/solar-10.7b-instruct","name":"solar-10.7b-instruct","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-06-05","last_updated":"2025-04-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"status":"deprecated","cost":{"input":0,"output":0}},"bytedance/seed-oss-36b-instruct":{"id":"bytedance/seed-oss-36b-instruct","name":"ByteDance-Seed/Seed-OSS-36B-Instruct","description":"Tool-capable chat model for instruction following and agentic application workflows","family":"seed","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-04","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"status":"deprecated","cost":{"input":0,"output":0}},"google/diffusiongemma-26b-a4b-it":{"id":"google/diffusiongemma-26b-a4b-it","name":"DiffusionGemma 26B A4B IT","description":"Gemma 4 based discrete text diffusion model for fast chat, reasoning, and tool use","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-09","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":250000,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"google/diffusiongemma-26b-a4b-it"},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma-4-31B-IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":0,"output":0}},"google/gemma-2-2b-it":{"id":"google/gemma-2-2b-it","name":"Gemma 2 2b It","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-07-16","last_updated":"2024-07-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0,"output":0}},"google/gemma-3-12b-it":{"id":"google/gemma-3-12b-it","name":"Gemma 3 12B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0,"output":0}},"google/gemma-3n-e2b-it":{"id":"google/gemma-3n-e2b-it","name":"Gemma 3n E2b It","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-06-12","last_updated":"2025-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0,"output":0}},"google/google-paligemma":{"id":"google/google-paligemma","name":"paligemma","description":"Gemini multimodal model for text, image, audio, video, and document tasks","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-05-14","last_updated":"2024-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0,"output":0}},"google/gemma-3n-e4b-it":{"id":"google/gemma-3n-e4b-it","name":"Gemma 3n E4b It","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-06-03","last_updated":"2025-06-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0,"output":0}},"google/gemma-3-4b-it":{"id":"google/gemma-3-4b-it","name":"Gemma 3 4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0,"output":0}},"minimaxai/minimax-m2.7":{"id":"minimaxai/minimax-m2.7","name":"MiniMax-M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-04-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","cost":{"input":0,"output":0}},"minimaxai/minimax-m3":{"id":"minimaxai/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":16384},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"minimax/MiniMax-M3"},"deepseek-ai/deepseek-v4-flash-0731":{"id":"deepseek-ai/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek-ai/deepseek-v4.1-flash":{"id":"deepseek-ai/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek-ai/deepseek-v4-pro-0813":{"id":"deepseek-ai/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek-ai/deepseek-v4-pro":{"id":"deepseek-ai/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"status":"deprecated","cost":{"input":0.435,"output":0.87,"cache_read":0.003625},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek-ai/deepseek-v4-flash":{"id":"deepseek-ai/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"status":"deprecated","cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"stepfun-ai/step-3.5-flash":{"id":"stepfun-ai/step-3.5-flash","name":"Step 3.5 Flash","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-02-02","last_updated":"2026-02-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"status":"deprecated","cost":{"input":0,"output":0}},"stepfun-ai/step-3.7-flash":{"id":"stepfun-ai/step-3.7-flash","name":"Step 3.7 Flash","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"status":"deprecated","cost":{"input":0,"output":0}},"mistralai/mistral-nemotron":{"id":"mistralai/mistral-nemotron","name":"mistral-nemotron","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"nemotron","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-06-11","last_updated":"2025-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"nvidia/mistral-nemotron"},"mistralai/mistral-7b-instruct-v0.3":{"id":"mistralai/mistral-7b-instruct-v0.3","name":"Mistral-7B-Instruct-v0.3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-01","last_updated":"2025-04-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0,"output":0}},"mistralai/mistral-large-3-675b-instruct-2512":{"id":"mistralai/mistral-large-3-675b-instruct-2512","name":"Mistral Large 3 675B Instruct 2512","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0,"output":0}},"mistralai/magistral-small-2506":{"id":"mistralai/magistral-small-2506","name":"Magistral Small 2506","description":"Mistral reasoning model for transparent analysis, math, and complex decisions","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-09-25","last_updated":"2025-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"input":32768,"output":32768},"cost":{"input":0,"output":0}},"mistralai/mistral-small-4-119b-2603":{"id":"mistralai/mistral-small-4-119b-2603","name":"mistral-small-4-119b-2603","description":"Efficient Mistral model for fast chat, extraction, and production assistants","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"status":"deprecated","cost":{"input":0,"output":0}},"mistralai/mixtral-8x7b-instruct":{"id":"mistralai/mixtral-8x7b-instruct","name":"Mistral: Mixtral 8x7B Instruct","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2023-12-10","last_updated":"2026-03-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"status":"deprecated","cost":{"input":0,"output":0}},"mistralai/mistral-medium-3.5-128b":{"id":"mistralai/mistral-medium-3.5-128b","name":"Mistral Medium 3.5","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"mistral/mistral-medium-2604"},"mistralai/ministral-14b-instruct-2512":{"id":"mistralai/ministral-14b-instruct-2512","name":"Ministral 3 14B Instruct 2512","description":"Compact Mistral VLM for chat and instruction-based workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"status":"deprecated","cost":{"input":0,"output":0}},"mistralai/mixtral-8x22b-instruct":{"id":"mistralai/mixtral-8x22b-instruct","name":"Mistral: Mixtral 8x22B Instruct","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-04-17","last_updated":"2024-04-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":13108},"status":"deprecated","cost":{"input":0,"output":0}},"mistralai/mistral-medium-3-instruct":{"id":"mistralai/mistral-medium-3-instruct","name":"Mistral Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-09-25","last_updated":"2025-09-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0,"output":0}},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0,"output":0}},"sarvamai/sarvam-m":{"id":"sarvamai/sarvam-m","name":"sarvam-m","description":"Efficient Indian-language reasoning model for chat, coding, and multilingual work","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-25","last_updated":"2025-07-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"status":"deprecated","cost":{"input":0,"output":0}},"nvidia/nvidia-nemotron-nano-9b-v2":{"id":"nvidia/nvidia-nemotron-nano-9b-v2","name":"nvidia-nemotron-nano-9b-v2","description":"Compact Nemotron model for efficient reasoning and deployable AI agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2025-08-18","last_updated":"2025-08-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-nano-9b-v2"},"nvidia/llama-3.1-nemotron-ultra-253b-v1":{"id":"nvidia/llama-3.1-nemotron-ultra-253b-v1","name":"Llama 3.1 Nemotron Ultra 253B","description":"Flagship Nemotron model for high-throughput reasoning and complex agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-04-07","last_updated":"2025-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/llama-3.1-nemotron-ultra-253b"},"nvidia/sparsedrive":{"id":"nvidia/sparsedrive","name":"sparsedrive","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-03-18","last_updated":"2025-07-20","modalities":{"input":["video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0,"output":0}},"nvidia/nemotron-3-nano-30b-a3b":{"id":"nvidia/nemotron-3-nano-30b-a3b","name":"nemotron-3-nano-30b-a3b","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2024-12","last_updated":"2024-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"nvidia/nemotron-3.5-lightning-30b-a3b":{"id":"nvidia/nemotron-3.5-lightning-30b-a3b","name":"Nemotron 3.5 Lightning 30B A3B","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/llama-nemotron-embed-vl-1b-v2":{"id":"nvidia/llama-nemotron-embed-vl-1b-v2","name":"llama-nemotron-embed-vl-1b-v2","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"nemotron","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-02-10","last_updated":"2026-02-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":2048},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/llama-nemotron-embed-vl-1b-v2"},"nvidia/nv-embedcode-7b-v1":{"id":"nvidia/nv-embedcode-7b-v1","name":"nv-embedcode-7b-v1","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-03-17","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":2048},"cost":{"input":0,"output":0}},"nvidia/nemotron-voicechat":{"id":"nvidia/nemotron-voicechat","name":"nemotron-voicechat","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","family":"nemotron","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-voicechat"},"nvidia/bevformer":{"id":"nvidia/bevformer","name":"bevformer","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-03-18","last_updated":"2025-07-20","modalities":{"input":["video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0,"output":0}},"nvidia/cosmos-transfer1-7b":{"id":"nvidia/cosmos-transfer1-7b","name":"cosmos-transfer1-7b","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-13","last_updated":"2025-06-30","modalities":{"input":["text","image","video"],"output":["video"]},"open_weights":true,"limit":{"context":0,"output":4096},"cost":{"input":0,"output":0}},"nvidia/cosmos-predict1-5b":{"id":"nvidia/cosmos-predict1-5b","name":"cosmos-predict1-5b","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-03-18","last_updated":"2025-03-18","modalities":{"input":["text","image","video"],"output":["video"]},"open_weights":true,"limit":{"context":0,"output":4096},"cost":{"input":0,"output":0}},"nvidia/llama-3.1-nemotron-nano-vl-8b-v1":{"id":"nvidia/llama-3.1-nemotron-nano-vl-8b-v1","name":"Llama 3.1 Nemotron Nano VL 8B v1","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-04-10","last_updated":"2025-04-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"status":"deprecated","cost":{"input":0,"output":0}},"nvidia/studiovoice":{"id":"nvidia/studiovoice","name":"studiovoice","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-10-03","last_updated":"2025-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0,"output":0}},"nvidia/nemotron-content-safety-reasoning-4b":{"id":"nvidia/nemotron-content-safety-reasoning-4b","name":"nemotron-content-safety-reasoning-4b","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":false,"release_date":"2026-01-22","last_updated":"2026-01-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-content-safety-reasoning-4b"},"nvidia/llama-3.1-nemotron-safety-guard-8b-v3":{"id":"nvidia/llama-3.1-nemotron-safety-guard-8b-v3","name":"llama-3.1-nemotron-safety-guard-8b-v3","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"nemotron","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-10-28","last_updated":"2025-10-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/llama-3.1-nemotron-safety-guard-8b-v3"},"nvidia/nv-embed-v1":{"id":"nvidia/nv-embed-v1","name":"nv-embed-v1","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-06-07","last_updated":"2025-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":2048},"cost":{"input":0,"output":0}},"nvidia/synthetic-video-detector":{"id":"nvidia/synthetic-video-detector","name":"synthetic-video-detector","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["video"],"output":["text"]},"open_weights":true,"limit":{"context":0,"output":4096},"cost":{"input":0,"output":0}},"nvidia/cosmos-transfer2_5-2b":{"id":"nvidia/cosmos-transfer2_5-2b","name":"cosmos-transfer2.5-2b","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-02-26","last_updated":"2026-02-26","modalities":{"input":["text","image","video"],"output":["video"]},"open_weights":true,"limit":{"context":0,"output":4096},"cost":{"input":0,"output":0}},"nvidia/nemotron-3-ultra-550b-a55b":{"id":"nvidia/nemotron-3-ultra-550b-a55b","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":0.5,"output":2.5,"cache_read":0.15},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning":{"id":"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning","name":"Nemotron 3 Nano Omni","description":"Open Nemotron omni model combining reasoning with text, vision, and audio","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":-1,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning"},"nvidia/llama-3.1-nemotron-nano-8b-v1":{"id":"nvidia/llama-3.1-nemotron-nano-8b-v1","name":"Llama 3.1 Nemotron Nano 8B v1","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-03-18","last_updated":"2025-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"status":"deprecated","cost":{"input":0,"output":0}},"nvidia/active-speaker-detection":{"id":"nvidia/active-speaker-detection","name":"Active Speaker Detection","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["video"],"output":["text"]},"open_weights":true,"limit":{"context":0,"output":4096},"cost":{"input":0,"output":0}},"nvidia/streampetr":{"id":"nvidia/streampetr","name":"streampetr","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0,"output":0}},"nvidia/llama-nemotron-rerank-vl-1b-v2":{"id":"nvidia/llama-nemotron-rerank-vl-1b-v2","name":"llama-nemotron-rerank-vl-1b-v2","description":"Reranking model for improving retrieval quality in search and recommendation systems","family":"nemotron","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-03-31","last_updated":"2026-03-31","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/llama-nemotron-rerank-vl-1b-v2"},"nvidia/nemotron-mini-4b-instruct":{"id":"nvidia/nemotron-mini-4b-instruct","name":"nemotron-mini-4b-instruct","description":"Compact Nemotron model for efficient reasoning and deployable AI agents","family":"nemotron","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-08-21","last_updated":"2024-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-mini-4b-instruct"},"nvidia/cosmos-reason2-8b":{"id":"nvidia/cosmos-reason2-8b","name":"Cosmos Reason2 8B","description":"Vision language model for physical-world understanding with structured reasoning on video and images","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0,"output":0}},"nvidia/nemotron-3-content-safety":{"id":"nvidia/nemotron-3-content-safety","name":"nemotron-3-content-safety","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"nemotron","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-content-safety"},"nvidia/nemotron-3.5-super-vl-120b-a12b":{"id":"nvidia/nemotron-3.5-super-vl-120b-a12b","name":"Nemotron 3.5 Super VL 120B A12B","description":"NVIDIA vision-language reasoning model for text, image, and video understanding and agentic tool use","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"nvidia/llama-3.3-nemotron-super-49b-v1":{"id":"nvidia/llama-3.3-nemotron-super-49b-v1","name":"Llama 3.3 Nemotron Super 49B v1","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-04-07","last_updated":"2025-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"nvidia/llama-3.3-nemotron-super-49b-v1"},"nvidia/magpie-tts-zeroshot":{"id":"nvidia/magpie-tts-zeroshot","name":"magpie-tts-zeroshot","description":"Speech generation model for controllable voice, narration, and audio delivery","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-05-22","last_updated":"2025-06-12","modalities":{"input":["text","audio"],"output":["audio"]},"open_weights":true,"limit":{"context":0,"output":4096},"cost":{"input":0,"output":0}},"nvidia/riva-translate-4b-instruct-v1.1":{"id":"nvidia/riva-translate-4b-instruct-v1.1","name":"riva-translate-4b-instruct-v1_1","description":"Translation model for multilingual conversion, localization, and cross-language workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-12","last_updated":"2025-12-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0,"output":0}},"nvidia/nemotron-nano-12b-v2-vl":{"id":"nvidia/nemotron-nano-12b-v2-vl","name":"Nemotron Nano 12B v2 VL","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-10-28","last_updated":"2025-10-28","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-nano-12b-v2-vl"},"nvidia/nemotron-3.5-content-safety":{"id":"nvidia/nemotron-3.5-content-safety","name":"Nemotron 3.5 Content Safety","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-content-safety"},"nvidia/llama-3.3-nemotron-super-49b-v1.5":{"id":"nvidia/llama-3.3-nemotron-super-49b-v1.5","name":"Llama 3.3 Nemotron Super 49B v1.5","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-07-25","last_updated":"2025-07-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"nvidia/llama-3.3-nemotron-super-49b-v1.5"},"nvidia/llama-3_2-nemoretriever-300m-embed-v1":{"id":"nvidia/llama-3_2-nemoretriever-300m-embed-v1","name":"llama-3_2-nemoretriever-300m-embed-v1","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-07-24","last_updated":"2025-07-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":2048},"cost":{"input":0,"output":0}},"nvidia/gliner-pii":{"id":"nvidia/gliner-pii","name":"gliner-pii","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0,"output":0}},"nvidia/usdcode":{"id":"nvidia/usdcode","name":"usdcode","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-01-01","last_updated":"2026-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":0,"output":0}},"nvidia/usdvalidate":{"id":"nvidia/usdvalidate","name":"usdvalidate","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-07-24","last_updated":"2025-01-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":0,"output":4096},"cost":{"input":0,"output":0}},"nvidia/llama-3.1-nemotron-70b-instruct":{"id":"nvidia/llama-3.1-nemotron-70b-instruct","name":"Llama 3.1 Nemotron 70B Instruct","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-04-15","last_updated":"2025-04-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/llama-3.1-nemotron-70b-instruct"},"nvidia/rerank-qa-mistral-4b":{"id":"nvidia/rerank-qa-mistral-4b","name":"rerank-qa-mistral-4b","description":"Reranking model for improving retrieval quality in search and recommendation systems","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-03-17","last_updated":"2025-01-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0,"output":0}},"qwen/qwen-image-edit":{"id":"qwen/qwen-image-edit","name":"Qwen Image Edit","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-08-19","last_updated":"2025-08-19","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":0,"output":0}},"qwen/qwen3-coder-480b-a35b-instruct":{"id":"qwen/qwen3-coder-480b-a35b-instruct","name":"Qwen3 Coder 480B A35B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":66536},"status":"deprecated","cost":{"input":0,"output":0}},"qwen/qwen3.5-122b-a10b":{"id":"qwen/qwen3.5-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","cost":{"input":0,"output":0}},"qwen/qwen3-next-80b-a3b-instruct":{"id":"qwen/qwen3-next-80b-a3b-instruct","name":"Qwen3-Next-80B-A3B-Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2024-12-01","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":16384},"status":"deprecated","cost":{"input":0,"output":0}},"qwen/qwen3.5-397b-a17b":{"id":"qwen/qwen3.5-397b-a17b","name":"Qwen3.5-397B-A17B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"status":"deprecated","cost":{"input":0,"output":0}},"qwen/qwen2.5-coder-32b-instruct":{"id":"qwen/qwen2.5-coder-32b-instruct","name":"Qwen2.5 Coder 32b Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-11-06","last_updated":"2024-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0,"output":0}},"qwen/qwen-image":{"id":"qwen/qwen-image","name":"Qwen Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":0,"output":0}},"openai/whisper-large-v3":{"id":"openai/whisper-large-v3","name":"Whisper Large v3","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"whisper","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2023-09","release_date":"2023-09-01","last_updated":"2025-09-05","modalities":{"input":["audio"],"output":["text"]},"open_weights":true,"limit":{"context":0,"output":4096},"cost":{"input":0,"output":0}},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0,"output":0}},"microsoft/phi-4-mini-instruct":{"id":"microsoft/phi-4-mini-instruct","name":"Phi-4-Mini","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"phi","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2024-12-01","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0,"output":0}},"microsoft/phi-4-multimodal-instruct":{"id":"microsoft/phi-4-multimodal-instruct","name":"Phi 4 Multimodal","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-07-26","last_updated":"2025-07-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":16384},"status":"deprecated","cost":{"input":0,"output":0}}}},"pioneer":{"id":"pioneer","env":["PIONEER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.fastino.ai/v1","name":"Pioneer","doc":"https://agent.pioneer.ai/llms.txt","models":{"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.4"},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"qwen3.7-max":{"id":"qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":991000,"output":64000},"cost":{"input":1.25,"output":3.75,"cache_read":0.25,"cache_write":1.5625},"canonical_model_id":"alibaba/qwen3.7-max"},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02,"cache_write":0.2},"canonical_model_id":"openai/gpt-5.4-nano"},"gpt-4o":{"id":"gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25,"cache_write":2.5},"canonical_model_id":"openai/gpt-4o"},"ministral-3b":{"id":"ministral-3b","name":"Ministral 3B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-03","release_date":"2024-10-16","last_updated":"2024-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.1,"output":0.1,"cache_read":0.1,"cache_write":0.1},"canonical_model_id":"mistral/ministral-3b"},"magistral-medium":{"id":"magistral-medium","name":"Magistral Medium (latest)","description":"Mistral reasoning model for transparent analysis, math, and complex decisions","family":"magistral-medium","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-06","release_date":"2025-03-17","last_updated":"2025-03-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"cost":{"input":2,"output":5,"cache_read":2,"cache_write":2},"canonical_model_id":"mistral/magistral-medium-latest"},"gpt-5-mini":{"id":"gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025,"cache_write":0.25},"canonical_model_id":"openai/gpt-5-mini"},"claude-opus-4-5":{"id":"claude-opus-4-5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"claude-3-7-sonnet-latest":{"id":"claude-3-7-sonnet-latest","name":"Claude Sonnet 3.7","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-10-31","release_date":"2025-02-19","last_updated":"2025-02-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-3-7-sonnet-20250219"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175,"cache_write":1.75},"canonical_model_id":"openai/gpt-5.3-codex"},"gpt-4.1-nano":{"id":"gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.05,"cache_write":0.1},"canonical_model_id":"openai/gpt-4.1-nano"},"mistral-medium-3.5":{"id":"mistral-medium-3.5","name":"Mistral Medium 3.5","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":131072},"cost":{"input":1.5,"output":7.5,"cache_read":1.5,"cache_write":1.5},"canonical_model_id":"mistral/mistral-medium-2604"},"gpt-5-nano":{"id":"gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005,"cache_write":0.05},"canonical_model_id":"openai/gpt-5-nano"},"claude-sonnet-4-5":{"id":"claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"gemini-3.6-flash":{"id":"gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":1.5,"output":7.5,"cache_read":0.15,"cache_write":1.5},"canonical_model_id":"google/gemini-3.6-flash"},"gemini-3.5-flash-lite":{"id":"gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65000},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":0.3},"canonical_model_id":"google/gemini-3.5-flash-lite"},"claude-opus-4-1":{"id":"claude-opus-4-1","name":"Claude Opus 4.1 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1"},"grok-4.5":{"id":"grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.5,"cache_write":2},"canonical_model_id":"xai/grok-4.5"},"gpt-5.1":{"id":"gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":131072},"cost":{"input":1.25,"output":10,"cache_read":0.125,"cache_write":1.25},"canonical_model_id":"openai/gpt-5.1"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"gpt-4o-mini":{"id":"gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075,"cache_write":0.15},"canonical_model_id":"openai/gpt-4o-mini"},"gemini-3-flash":{"id":"gemini-3-flash","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65000},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.083333},"canonical_model_id":"google/gemini-3-flash-preview"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":1.5,"output":9,"cache_read":0.15,"cache_write":0.083333},"canonical_model_id":"google/gemini-3.5-flash"},"qwen3.6-flash":{"id":"qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.1875,"output":1.125,"cache_read":0.0375,"cache_write":0.234375},"canonical_model_id":"alibaba/qwen3.6-flash"},"mistral-large-3":{"id":"mistral-large-3","name":"Mistral Large 3","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":131072},"cost":{"input":0.5,"output":1.5,"cache_read":0.5,"cache_write":0.5},"canonical_model_id":"mistral/mistral-large-2512"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":11,"output":55,"cache_read":1.1,"cache_write":13.75},"canonical_model_id":"anthropic/claude-fable-5"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075,"cache_write":0.75},"canonical_model_id":"openai/gpt-5.4-mini"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":1,"output":6,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"openai/gpt-5.6-luna"},"devstral-small-2":{"id":"devstral-small-2","name":"Devstral Small 2","description":"Compact multimodal coding model for repository exploration, file editing, and software agents","family":"devstral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":131072},"cost":{"input":0.1,"output":0.3,"cache_read":0.1,"cache_write":0.1},"canonical_model_id":"mistral/devstral-small-2"},"devstral-2":{"id":"devstral-2","name":"Devstral 2","description":"Mistral's coding-agent model for repository work, terminal tasks, and software fixes","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":131072},"cost":{"input":0.4,"output":2,"cache_read":0.4,"cache_write":0.4},"canonical_model_id":"mistral/devstral-2512"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":5},"canonical_model_id":"openai/gpt-5.5"},"gpt-4.1":{"id":"gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":1,"cache_write":2},"canonical_model_id":"openai/gpt-4.1"},"mistral-medium":{"id":"mistral-medium","name":"Mistral Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"cost":{"input":0.4,"output":2,"cache_read":0.4,"cache_write":0.4},"canonical_model_id":"mistral/mistral-medium-2505"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"qwen3.6-max-preview":{"id":"qwen3.6-max-preview","name":"Qwen3.6 Max Preview","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":240000,"output":64000},"cost":{"input":1.04,"output":6.24,"cache_read":0.208,"cache_write":1.3},"canonical_model_id":"alibaba/qwen3.6-max-preview"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"gpt-4.1-mini":{"id":"gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.2,"cache_write":0.4},"canonical_model_id":"openai/gpt-4.1-mini"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"claude-opus-5-fast":{"id":"claude-opus-5-fast","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-opus-5"},"qwen3.6-plus":{"id":"qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.325,"output":1.95,"cache_read":0.065,"cache_write":0.40625},"canonical_model_id":"alibaba/qwen3.6-plus"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"cache_write":3.125},"canonical_model_id":"openai/gpt-5.6-terra"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"ministral-14b":{"id":"ministral-14b","name":"Ministral 14B","description":"Compact multimodal Mistral model for local assistants, edge agents, and efficient tool use","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":131072},"cost":{"input":0.2,"output":0.2,"cache_read":0.2,"cache_write":0.2},"canonical_model_id":"mistral/ministral-14b"},"gemini-3.1-pro":{"id":"gemini-3.1-pro","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":0.375},"canonical_model_id":"google/gemini-3.1-pro-preview"},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.32,"output":1.28,"cache_read":0.064,"cache_write":0.4},"canonical_model_id":"alibaba/qwen3.7-plus"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"openai/gpt-5.6-sol"},"gemini-3.1-flash-lite":{"id":"gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65000},"cost":{"input":0.25,"output":1.5,"cache_read":0.03,"cache_write":0.25},"canonical_model_id":"google/gemini-3.1-flash-lite"},"poolside/laguna-s-2.1":{"id":"poolside/laguna-s-2.1","name":"Laguna S 2.1","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.1,"output":0.2,"cache_read":0.01,"cache_write":0.1},"canonical_model_id":"poolside/laguna-s-2.1"},"meta-llama/Llama-3.2-1B-Instruct":{"id":"meta-llama/Llama-3.2-1B-Instruct","name":"Llama 3.2 1B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-31","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":60000},"cost":{"input":0.1,"output":0.201,"cache_read":0.1,"cache_write":0.1}},"meta-llama/Llama-3.2-3B-Instruct":{"id":"meta-llama/Llama-3.2-3B-Instruct","name":"Llama 3.2 3B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-31","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":80000},"cost":{"input":0.1,"output":0.335,"cache_read":0.1,"cache_write":0.1}},"meta-llama/Llama-3.1-8B-Instruct":{"id":"meta-llama/Llama-3.1-8B-Instruct","name":"Llama 3.1 8B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2023-12-31","release_date":"2024-06-30","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.2,"output":0.2,"cache_read":0.2,"cache_write":0.2}},"meta-llama/Llama-3.2-3B":{"id":"meta-llama/Llama-3.2-3B","name":"Llama-3.2-3B","description":"Small open Llama base model for lightweight text generation and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.1,"output":0.1,"cache_read":0.1,"cache_write":0.1},"canonical_model_id":"meta/llama-3.2-3b"},"meta-llama/Llama-3.2-1B":{"id":"meta-llama/Llama-3.2-1B","name":"Llama-3.2-1B","description":"Compact open Llama base model for lightweight and on-device use","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.1,"output":0.1,"cache_read":0.1,"cache_write":0.1},"canonical_model_id":"meta/llama-3.2-1b"},"meta-llama/Llama-3.3-70B-Instruct":{"id":"meta-llama/Llama-3.3-70B-Instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":16384},"cost":{"input":0.9,"output":0.9,"cache_read":0.9,"cache_write":0.9},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"XiaomiMiMo/MiMo-V2.5-Pro":{"id":"XiaomiMiMo/MiMo-V2.5-Pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":131000},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036,"cache_write":0.435},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"XiaomiMiMo/MiMo-V2.5":{"id":"XiaomiMiMo/MiMo-V2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028,"cache_write":0.14},"canonical_model_id":"xiaomi/mimo-v2.5"},"thinkingmachines/inkling-small":{"id":"thinkingmachines/inkling-small","name":"Inkling Small","description":"Multimodal MoE reasoning model (276B total, 12B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.5,"output":1.2,"cache_read":0.1,"cache_write":0.5},"canonical_model_id":"thinkingmachines/inkling-small"},"meta/muse-spark-1.1":{"id":"meta/muse-spark-1.1","name":"Muse Spark 1.1","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15,"cache_write":1.25},"canonical_model_id":"meta/muse-spark-1.1"},"HuggingFaceTB/SmolLM3-3B-Base":{"id":"HuggingFaceTB/SmolLM3-3B-Base","name":"SmolLM3 3B Base","description":"Tool-capable chat model for instruction following and agentic application workflows","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2025-06-30","last_updated":"2025-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15}},"google/diffusiongemma-26B-A4B-it":{"id":"google/diffusiongemma-26B-A4B-it","name":"DiffusionGemma 26B-A4B IT","description":"Gemini model for general assistance, reasoning, and multimodal workflows","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-05-31","last_updated":"2026-05-31","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.5,"output":0.5,"cache_read":0.5,"cache_write":0.5}},"google/gemma-4-12B-it":{"id":"google/gemma-4-12B-it","name":"Gemma 4 12B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-05-31","last_updated":"2026-05-31","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.25,"output":0.25,"cache_read":0.25,"cache_write":0.25}},"google/gemma-4-E2B-it":{"id":"google/gemma-4-E2B-it","name":"Gemma 4 E2B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.1,"output":0.1,"cache_read":0.1,"cache_write":0.1},"canonical_model_id":"google/gemma-4-E2B-it"},"google/gemma-3-4b-pt":{"id":"google/gemma-3-4b-pt","name":"Gemma 3 4B (Pretrained)","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2025-02-28","last_updated":"2025-02-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15}},"google/gemma-4-31B-it":{"id":"google/gemma-4-31B-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.5,"output":0.5,"cache_read":0.5,"cache_write":0.5},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemma-4-E4B-it":{"id":"google/gemma-4-E4B-it","name":"Gemma 4 E4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.2,"output":0.2,"cache_read":0.2,"cache_write":0.2},"canonical_model_id":"google/gemma-4-E4B-it"},"Qwen/Qwen3-4B-Instruct-2507":{"id":"Qwen/Qwen3-4B-Instruct-2507","name":"Qwen3 4B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2025-07-31","last_updated":"2025-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.2,"output":0.2,"cache_read":0.2,"cache_write":0.2}},"Qwen/Qwen2.5-Coder-0.5B":{"id":"Qwen/Qwen2.5-Coder-0.5B","name":"Qwen2.5-Coder-0.5B","description":"Tiny open Qwen code model for lightweight completion and on-device coding","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-11-12","last_updated":"2024-11-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.1,"output":0.1,"cache_read":0.1,"cache_write":0.1},"canonical_model_id":"alibaba/qwen2.5-coder-0.5b"},"Qwen/Qwen3-1.7B-Base":{"id":"Qwen/Qwen3-1.7B-Base","name":"Qwen3 1.7B Base","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2025-03-31","last_updated":"2025-03-31","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.1,"output":0.1,"cache_read":0.1,"cache_write":0.1}},"Qwen/Qwen3.6-35B-A3B":{"id":"Qwen/Qwen3.6-35B-A3B","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.14,"output":1,"cache_read":0.028,"cache_write":0.175},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"Qwen/Qwen3-235B-A22B-Instruct-2507":{"id":"Qwen/Qwen3-235B-A22B-Instruct-2507","name":"Qwen3 235B-A22B Instruct 2507","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":1.2,"output":1.2,"cache_read":1.2,"cache_write":1.2},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"Qwen/Qwen3-8B":{"id":"Qwen/Qwen3-8B","name":"Qwen3 8B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-03-31","release_date":"2025-03-31","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":40960},"cost":{"input":0.2,"output":0.2,"cache_read":0.2,"cache_write":0.2}},"Qwen/Qwen3-4B-Base":{"id":"Qwen/Qwen3-4B-Base","name":"Qwen3 4B Base","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2025-03-31","last_updated":"2025-03-31","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15}},"Qwen/Qwen3-32B":{"id":"Qwen/Qwen3-32B","name":"Qwen3 32B","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.9,"output":0.9,"cache_read":0.9,"cache_write":0.9},"canonical_model_id":"alibaba/qwen3-32b"},"Qwen/Qwen3.5-9B":{"id":"Qwen/Qwen3.5-9B","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.3,"output":0.3,"cache_read":0.3,"cache_write":0.3},"canonical_model_id":"alibaba/qwen3.5-9b"},"Qwen/Qwen3.6-27B":{"id":"Qwen/Qwen3.6-27B","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.6,"output":0.6,"cache_read":0.6,"cache_write":0.6},"canonical_model_id":"alibaba/qwen3.6-27b"},"LiquidAI/LFM2-24B-A2B":{"id":"LiquidAI/LFM2-24B-A2B","name":"LFM2 24B A2B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","family":"liquid","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-01-31","last_updated":"2026-02-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.03,"output":0.12,"cache_read":0.03,"cache_write":0.03}},"deepseek-ai/DeepSeek-V3.1":{"id":"deepseek-ai/DeepSeek-V3.1","name":"DeepSeek-V3.1","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":131072},"cost":{"input":0.56,"output":1.68,"cache_read":0.56,"cache_write":0.56},"canonical_model_id":"deepseek/deepseek-v3.1"},"deepseek-ai/DeepSeek-V4-Flash":{"id":"deepseek-ai/DeepSeek-V4-Flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.1,"output":0.2,"cache_read":0.0197,"cache_write":0.1},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek-ai/DeepSeek-V4-Pro":{"id":"deepseek-ai/DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.003625,"cache_write":0.435},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek-ai/DeepSeek-V3":{"id":"deepseek-ai/DeepSeek-V3","name":"DeepSeek-V3","description":"Open DeepSeek MoE chat model for coding, math, and general reasoning","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-12-26","last_updated":"2024-12-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":8192},"cost":{"input":0.27,"output":1.12,"cache_read":0.135,"cache_write":0.27},"canonical_model_id":"deepseek/deepseek-v3"},"MiniMaxAI/MiniMax-M3":{"id":"MiniMaxAI/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":0.3},"canonical_model_id":"minimax/MiniMax-M3"},"MiniMaxAI/MiniMax-M2.7":{"id":"MiniMaxAI/MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131000},"cost":{"input":0.279,"output":1.2,"cache_read":0.279,"cache_write":0.279},"canonical_model_id":"minimax/MiniMax-M2.7"},"mistralai/Mistral-Small-4-119B-2603":{"id":"mistralai/Mistral-Small-4-119B-2603","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":32000},"cost":{"input":0.15,"output":0.6,"cache_read":0.015,"cache_write":0.15},"canonical_model_id":"mistral/mistral-small-2603"},"mistralai/Pixtral-12B-2409":{"id":"mistralai/Pixtral-12B-2409","name":"Pixtral 12B","description":"Mistral vision-language model for image understanding and multimodal chat","family":"pixtral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2024-09-01","last_updated":"2024-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15},"canonical_model_id":"mistral/pixtral-12b"},"mistralai/Mistral-Nemo-Instruct-2407":{"id":"mistralai/Mistral-Nemo-Instruct-2407","name":"Mistral Nemo","description":"Efficient Mistral-NVIDIA open model for multilingual chat and local deployment","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0.02,"output":0.03,"cache_read":0.02,"cache_write":0.02},"canonical_model_id":"mistral/mistral-nemo"},"mistralai/Magistral-Small-2506":{"id":"mistralai/Magistral-Small-2506","name":"Magistral Small","description":"Open Mistral reasoning model for transparent step-by-step problem solving","family":"magistral","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2025-06-10","last_updated":"2025-06-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":64000},"cost":{"input":0.5,"output":1.5,"cache_read":0.5,"cache_write":0.5},"canonical_model_id":"mistral/magistral-small-2506"},"mistralai/Ministral-8B-Instruct-2410":{"id":"mistralai/Ministral-8B-Instruct-2410","name":"Ministral 8B Instruct","description":"Efficient open Mistral edge model for on-device chat and function calling","family":"ministral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-10-16","last_updated":"2024-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15},"canonical_model_id":"mistral/ministral-8b-instruct-2410"},"mistralai/Codestral-22B-v0.1":{"id":"mistralai/Codestral-22B-v0.1","name":"Codestral-22B-v0.1","description":"Open Mistral code model for fill-in-the-middle and 80+ programming languages","family":"codestral","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-05-29","last_updated":"2024-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.3,"output":0.9,"cache_read":0.3,"cache_write":0.3},"canonical_model_id":"mistral/codestral-22b-v0.1"},"mistralai/Mistral-7B-Instruct-v0.3":{"id":"mistralai/Mistral-7B-Instruct-v0.3","name":"Mistral 7B Instruct v0.3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2023-04-30","last_updated":"2023-04-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.2,"output":0.2,"cache_read":0.2,"cache_write":0.2}},"sakana/fugu-ultra":{"id":"sakana/fugu-ultra","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":5},"canonical_model_id":"sakana/fugu-ultra"},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":131072},"cost":{"input":0.95,"output":4,"cache_read":0.34,"cache_write":0.95},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/Kimi-K3":{"id":"moonshotai/Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/Kimi-K3-Fast":{"id":"moonshotai/Kimi-K3-Fast","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":4.5,"output":22.5,"cache_read":0.45,"cache_write":4.5},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/Kimi-K2.7-Code":{"id":"moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32768},"cost":{"input":0.95,"output":4,"cache_read":0.19,"cache_write":0.95},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"zai-org/GLM-5.1":{"id":"zai-org/GLM-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202000,"output":131072},"cost":{"input":0.98,"output":3.08,"cache_read":0.182,"cache_write":0.98},"canonical_model_id":"zhipuai/glm-5.1"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1040000,"output":128000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":1.4},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-5.2-Fast":{"id":"zai-org/GLM-5.2-Fast","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":2.1,"output":6.6,"cache_read":0.21,"cache_write":2.1},"canonical_model_id":"zhipuai/glm-5.2"},"nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-NVFP4":{"id":"nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-NVFP4","name":"Nemotron 3.5 Super VL 120B A12B","description":"NVIDIA vision-language reasoning model for text, image, and video understanding and agentic tool use","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":4096},"cost":{"input":0.08,"output":0.45,"cache_read":0.04,"cache_write":0.08},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16":{"id":"nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16","name":"Nemotron 3 Nano 30B A3B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.05,"output":0.2,"cache_read":0.05,"cache_write":0.05},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16":{"id":"nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16","name":"Nemotron 3.5 Lightning 30B A3B","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":4096},"cost":{"input":0.5,"output":0.5,"cache_read":0.5,"cache_write":0.5},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16":{"id":"nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65000},"cost":{"input":0.5,"output":2.5,"cache_read":0.15,"cache_write":0.5},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-FP8":{"id":"nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-FP8","name":"Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32000},"cost":{"input":0.09,"output":0.45,"cache_read":0.09,"cache_write":0.09},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"pioneer/auto":{"id":"pioneer/auto","name":"Pioneer Auto","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2024-01-01","last_updated":"2025-06-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":4096}},"fastino/gliner2-multi-v1":{"id":"fastino/gliner2-multi-v1","name":"GLiNER2 Multi","description":"Tool-capable chat model for instruction following and agentic application workflows","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2025-11-30","last_updated":"2025-11-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8192},"cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15}},"fastino/gliner2.5-base-v1":{"id":"fastino/gliner2.5-base-v1","name":"GLiNER 2.5 Base","description":"English boundary NER and structured extraction with LoRA fine-tuning.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-08-24","last_updated":"2026-08-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":4096},"cost":{"input":0.03,"output":0,"cache_read":0.03,"cache_write":0.03}},"fastino/gliner2-privacy-filter-PII-multi":{"id":"fastino/gliner2-privacy-filter-PII-multi","name":"GLiNER2 Privacy Filter PII (Multi)","description":"Tool-capable chat model for instruction following and agentic application workflows","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8192},"cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15}},"fastino/gliner2.5-multi-v1":{"id":"fastino/gliner2.5-multi-v1","name":"GLiNER 2.5 Multi","description":"Multilingual boundary NER and span extraction; non-trainable encoder.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-08-24","last_updated":"2026-08-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":4096},"cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15}},"fastino/gliguard-LLMGuardrails-300M":{"id":"fastino/gliguard-LLMGuardrails-300M","name":"GLiGuard LLM Guardrails 300M","description":"Tool-capable chat model for instruction following and agentic application workflows","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8192},"cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15}},"fastino/gliner2-large-v1":{"id":"fastino/gliner2-large-v1","name":"GLiNER2 Large","description":"Flagship model for demanding analysis, coding, and production agent workflows","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2025-06-30","last_updated":"2025-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8192},"cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15}},"fastino/gliner2-base-v1":{"id":"fastino/gliner2-base-v1","name":"GLiNER2 Base","description":"Tool-capable chat model for instruction following and agentic application workflows","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2025-06-30","last_updated":"2025-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8192},"cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15}},"fastino/gliguard-PII-multi":{"id":"fastino/gliguard-PII-multi","name":"GLiNER2-Guardrails-PII-Multi","description":"A 300M-parameter multilingual model that runs LLM safety moderation and PII detection in a single forward pass.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15}},"fastino/gliner2-multi-large-v1":{"id":"fastino/gliner2-multi-large-v1","name":"GLiNER2 Multi Large","description":"Flagship model for demanding analysis, coding, and production agent workflows","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2025-11-30","last_updated":"2025-11-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8192},"cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15}},"fastino/GLiNER-2.5-Decide":{"id":"fastino/GLiNER-2.5-Decide","name":"GLiNER-2.5-Decide","description":"Classification-tuned GLiNER2 large. Entities, relations, and JSON extraction still work.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-24","last_updated":"2026-09-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15}},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.07,"output":0.3,"cache_read":0.035,"cache_write":0.07},"canonical_model_id":"openai/gpt-oss-20b"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.15,"output":0.6,"cache_read":0.015,"cache_write":0.15},"canonical_model_id":"openai/gpt-oss-120b"}}},"xiaomi":{"id":"xiaomi","env":["XIAOMI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.xiaomimimo.com/v1","name":"Xiaomi","doc":"https://platform.xiaomimimo.com/#/docs","models":{"mimo-v2.6-pro":{"id":"mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"MiMo Pro model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036}},"mimo-v2-flash":{"id":"mimo-v2-flash","name":"MiMo-V2-Flash","description":"Legacy model retained for compatibility with older integrations","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12-01","release_date":"2025-12-16","last_updated":"2026-06-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","cost":{"input":0.14,"output":0.28,"cache_read":0.0028}},"mimo-v2.5":{"id":"mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-06-24","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0.14,"output":0.28,"cache_read":0.0028}},"mimo-v2-omni":{"id":"mimo-v2-omni","name":"MiMo-V2-Omni","description":"Legacy model retained for compatibility with older integrations","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-03-18","last_updated":"2026-06-24","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"status":"deprecated","cost":{"input":0.14,"output":0.28,"cache_read":0.0028}},"mimo-v2.6-pro-ultraspeed":{"id":"mimo-v2.6-pro-ultraspeed","name":"MiMo-V2.6-Pro-UltraSpeed","description":"MiMo pro model for strong multimodal reasoning and agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":4.35,"output":8.7,"cache_read":0.036}},"mimo-v2-pro":{"id":"mimo-v2-pro","name":"MiMo-V2-Pro","description":"Earlier MiMo Pro model for multimodal agents, reasoning, and code tasks","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-03-18","last_updated":"2026-06-24","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0.435,"output":0.87,"cache_read":0.0036}},"mimo-v2.5-pro":{"id":"mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-06-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0.435,"output":0.87,"cache_read":0.0036}},"mimo-v2.6-flash":{"id":"mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028}},"mimo-v2.5-pro-ultraspeed":{"id":"mimo-v2.5-pro-ultraspeed","name":"MiMo-V2.5-Pro-UltraSpeed","description":"MiMo pro model for strong multimodal reasoning and agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-06-08","last_updated":"2026-06-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":1.305,"output":2.61,"cache_read":0.0108}}}},"xiaomi-token-plan-sgp":{"id":"xiaomi-token-plan-sgp","env":["XIAOMI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://token-plan-sgp.xiaomimimo.com/v1","name":"Xiaomi Token Plan (Singapore)","doc":"https://platform.xiaomimimo.com/#/docs","models":{"mimo-v2.6-pro":{"id":"mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"mimo-v2.6-flash":{"id":"mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"mimo-v2.5-tts-voiceclone":{"id":"mimo-v2.5-tts-voiceclone","name":"MiMo-V2.5-TTS-VoiceClone","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mimo","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["audio"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0,"output":0}},"mimo-v2.5-pro":{"id":"mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"mimo-v2-tts":{"id":"mimo-v2-tts","name":"MiMo-V2-TTS","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mimo","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["audio"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0,"output":0}},"mimo-v2-pro":{"id":"mimo-v2-pro","name":"MiMo-V2-Pro","description":"Earlier MiMo Pro model for multimodal agents, reasoning, and code tasks","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2-pro"},"mimo-v2.5-tts":{"id":"mimo-v2.5-tts","name":"MiMo-V2.5-TTS","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mimo","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["audio"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0,"output":0}},"mimo-v2.5-tts-voicedesign":{"id":"mimo-v2.5-tts-voicedesign","name":"MiMo-V2.5-TTS-VoiceDesign","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mimo","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["audio"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0,"output":0}},"mimo-v2.5":{"id":"mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.5"}}},"minimax":{"id":"minimax","env":["MINIMAX_API_KEY"],"npm":"@ai-sdk/anthropic","api":"https://api.minimax.io/anthropic/v1","name":"MiniMax (minimax.io)","doc":"https://platform.minimax.io/docs/guides/quickstart","models":{"MiniMax-M3":{"id":"MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-25","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":512000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"tiers":[{"input":0.6,"output":2.4,"cache_read":0.12,"tier":{"type":"context","size":512000}}],"context_over_200k":{"input":0.6,"output":2.4,"cache_read":0.12}}},"MiniMax-M2.1":{"id":"MiniMax-M2.1","name":"MiniMax-M2.1","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375}},"MiniMax-M2.5":{"id":"MiniMax-M2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375}},"MiniMax-M2.7":{"id":"MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":0.375}},"MiniMax-M2.7-highspeed":{"id":"MiniMax-M2.7-highspeed","name":"MiniMax-M2.7-highspeed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.06,"cache_write":0.375}},"MiniMax-M2":{"id":"MiniMax-M2","name":"MiniMax-M2","description":"Efficient open MiniMax model built for coding agents and tool-heavy workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2}},"MiniMax-M2.5-highspeed":{"id":"MiniMax-M2.5-highspeed","name":"MiniMax-M2.5-highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-13","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.03,"cache_write":0.375}}}},"github-copilot":{"id":"github-copilot","env":["GITHUB_TOKEN"],"npm":"@ai-sdk/openai-compatible","api":"https://api.githubcopilot.com","name":"GitHub Copilot","doc":"https://docs.github.com/en/copilot","models":{"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"grok-4.7":{"id":"grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"input":372000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"claude-opus-4.7":{"id":"claude-opus-4.7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":168000,"output":32000},"experimental":{"modes":{"fast":{"cost":{"input":30,"output":150,"cache_read":3,"cache_write":37.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.githubcopilot.com/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"claude-haiku-5.5":{"id":"claude-haiku-5.5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.githubcopilot.com/v1"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"gpt-5-mini":{"id":"gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":264000,"input":128000,"output":64000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"claude-opus-4.8":{"id":"claude-opus-4.8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":168000,"output":64000},"experimental":{"modes":{"fast":{"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.githubcopilot.com/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"gemini-3.6-flash":{"id":"gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]},{"type":"budget_tokens","min":256,"max":32000}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":936000,"output":64000},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.6-flash"},"mai-code-1-flash-picker":{"id":"mai-code-1-flash-picker","name":"MAI-Code-1-Flash","description":"Microsoft coding model built for fast, efficient assistance in everyday developer workflows","family":"mai","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12","release_date":"2026-06-02","last_updated":"2026-06-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":128000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"microsoft/mai-code-1-flash"},"mai-code-1.1-flash":{"id":"mai-code-1.1-flash","name":"MAI-Code-1.1-Flash","description":"Microsoft coding model with native vision support, optimized for fast and efficient software development","family":"mai","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":128000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":0.2,"output":1.2,"cache_read":0.02},"canonical_model_id":"microsoft/mai-code-1.1-flash"},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"claude-haiku-4.5":{"id":"claude-haiku-4.5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":32000}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":136000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.githubcopilot.com/v1"},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"grok-4.5":{"id":"grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"input":372000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.5"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":936000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.githubcopilot.com/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"claude-sonnet-5.5":{"id":"claude-sonnet-5.5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.githubcopilot.com/v1"},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]},{"type":"budget_tokens","min":256,"max":24000}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":128000,"output":64000},"cost":{"input":1.5,"output":9,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.5-flash"},"claude-fable-5.1":{"id":"claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.githubcopilot.com/v1"},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.githubcopilot.com/v1"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.githubcopilot.com/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"gemini-3.7-flash":{"id":"gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":936000,"output":64000},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.7-flash"},"claude-sonnet-4.6":{"id":"claude-sonnet-4.6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024,"max":32000}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":168000,"output":32000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.githubcopilot.com/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"gemini-3.8-flash":{"id":"gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":936000,"output":64000},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.8-flash"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"claude-opus-5.5":{"id":"claude-opus-5.5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.githubcopilot.com/v1"},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":224000,"output":32000},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"grok-4.6":{"id":"grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"input":372000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"gemini-4-argon":{"id":"gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":10,"cache_read":0.1},"canonical_model_id":"google/gemini-4-argon"},"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"}}},"inferx":{"id":"inferx","env":["INFERX_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://model.inferx.net/endpoints/v1","name":"InferX","doc":"https://model.inferx.net/endpoints","models":{"gemma-4-31B-it-fp8":{"id":"gemma-4-31B-it-fp8","name":"Gemma 4 31B IT FP8","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemma-4-31b-it"},"Qwen3.6-35B-A3B-fp8-no-thinking":{"id":"Qwen3.6-35B-A3B-fp8-no-thinking","name":"Qwen3.6-35B-A3B-fp8-no-thinking","description":"Qwen3.6-35B-A3B-fp8 disable thinking","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"Devstral-2-123B-Instruct-2512-int4-AutoRound":{"id":"Devstral-2-123B-Instruct-2512-int4-AutoRound","name":"Devstral-2-123B-Instruct-2512-int4-AutoRound","description":"Mistral's coding-agent model for repository work, terminal tasks, and software fixes","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"mistral/devstral-2512"},"Qwen3.6-27B-FP8":{"id":"Qwen3.6-27B-FP8","name":"Qwen3.6 27B FP8","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3.6-27b"},"Qwen3-Coder-Next-FP8":{"id":"Qwen3-Coder-Next-FP8","name":"Qwen3 Coder Next FP8","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256144,"output":65536},"cost":{"input":0,"output":0}},"Qwen3-Coder-Next-FP8-no-thinking":{"id":"Qwen3-Coder-Next-FP8-no-thinking","name":"Qwen3-Coder-Next-FP8-no-thinking","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":260000,"output":65536},"cost":{"input":0,"output":0}},"mimo-v25":{"id":"mimo-v25","name":"mimo-v25","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":100000},"cost":{"input":0,"output":0},"canonical_model_id":"xiaomi/mimo-v2.5"},"Qwen3-Embedding-8B":{"id":"Qwen3-Embedding-8B","name":"Qwen3-Embedding-8B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":0},"cost":{"input":0,"output":0}},"Qwen3.6-35B-A3B-FP8":{"id":"Qwen3.6-35B-A3B-FP8","name":"Qwen3.6 35B A3B FP8","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"Ornith-1.0-35B-FP8":{"id":"Ornith-1.0-35B-FP8","name":"Ornith-1.0-35B-FP8","description":"Large coding-reasoning model for agentic software tasks and RL search","family":"ornith","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-06-25","last_updated":"2026-06-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":100000},"cost":{"input":0,"output":0},"canonical_model_id":"deepreinforce/ornith-1.0-35b"},"Agents-A1":{"id":"Agents-A1","name":"Agents-A1","description":"35B MoE agentic model built for long-horizon search, engineering, and scientific reasoning tasks","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"release_date":"2026-06-26","last_updated":"2026-06-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":100000},"cost":{"input":0,"output":0}},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"deepseek-v4-flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":100000},"cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-v4-flash"}}},"opencode-go":{"id":"opencode-go","env":["OPENCODE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://opencode.ai/inference/go/openai/v1","name":"OpenCode Go","doc":"https://opencode.ai/v2/docs/console/go/","models":{"mimo-v2.6-pro":{"id":"mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.435,"output":0.87,"cache_read":0.003625},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"mimo-v2.5":{"id":"mimo-v2.5","name":"MiMo V2.5","description":"MiMo omni model for text, image, video, audio, and agents","family":"mimo-v2.5","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028}},"grok-4.7":{"id":"grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"longcat-2.5-preview-free":{"id":"longcat-2.5-preview-free","name":"LongCat 2.5 Preview Free","description":"Meituan's multimodal reasoning model for coding and agent tasks, with image understanding and a 1M-token context window","family":"longcat","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-25","last_updated":"2026-09-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"meituan/longcat-2.5-preview"},"gemini-4-argon-contributor":{"id":"gemini-4-argon-contributor","name":"Gemini 4 Argon Contributor","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://opencode.ai/inference/go/google/v1beta"},"cost":{"input":4,"output":20,"cache_read":0.2,"input_audio":4},"canonical_model_id":"google/gemini-4-argon"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter multimodal flagship for coding, professional work, and long-horizon agentic workflows","family":"qwen3.8-max","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","max":262144}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/go/anthropic/v1"},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"step-5-preview":{"id":"step-5-preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":65536},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":1,"output":2.7,"cache_read":0.1},"canonical_model_id":"stepfun/step-5-preview"},"longcat-2.0":{"id":"longcat-2.0","name":"LongCat-2.0","description":"Meituan LongCat-2.0, a reasoning model with tool calling and a 1M-token context window","family":"longcat","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"meituan/longcat-2.0"},"cat-jam-free":{"id":"cat-jam-free","name":"Cat Jam Free","description":"A text-only reasoning model for coding and agentic workflows, with tool calling and structured JSON outputs.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"space-bunny":{"id":"space-bunny","name":"Space Bunny","description":"Anonymous preview reasoning model for coding, agentic tasks, tool use, and multimodal input","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":524288,"output":524288},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.15,"output":0.6,"cache_read":0.03,"cache_write":0}},"minimax-m2.7":{"id":"minimax-m2.7","name":"MiniMax-M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax-m2.7","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/go/anthropic/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":0.375}},"mimo-v2.5-pro":{"id":"mimo-v2.5-pro","name":"MiMo V2.5 Pro","description":"MiMo pro model for strong multimodal reasoning and agent execution","family":"mimo-v2.5-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":128000},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.435,"output":0.87,"cache_read":0.003625}},"mimo-v2.6-flash":{"id":"mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax-m3","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-31","last_updated":"2026-05-31","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/go/anthropic/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"tiers":[{"input":0.6,"output":2.4,"cache_read":0.12,"tier":{"type":"context","size":512000}}],"context_over_200k":{"input":0.6,"output":2.4,"cache_read":0.12}}},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/go/anthropic/v1"},"cost":{"input":0.15,"output":0.47,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"hy3":{"id":"hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":192000,"output":128000},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.14,"output":0.58,"cache_read":0.035},"canonical_model_id":"tencent/hy3"},"muse-spark-1.2-contributor":{"id":"muse-spark-1.2-contributor","name":"Muse Spark 1.2 Contributor","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.1,"output":0.2,"cache_read":0.002},"canonical_model_id":"meta/muse-spark-1.2"},"beam-free":{"id":"beam-free","name":"Beam Free","description":"Sparse mixture-of-experts reasoning model with 23B active parameters for coding and agentic workflows","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-06-30","release_date":"2026-10-05","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"reflection/beam-1.0-501b-a23b"},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/go/anthropic/v1"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro (New)","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.66,"output":1.98,"cache_read":0.022}},"hy4-preview":{"id":"hy4-preview","name":"Hy4 preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":64000},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"},"muse-spark-1.3-contributor":{"id":"muse-spark-1.3-contributor","name":"Muse Spark 1.3 Contributor","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for coding and agentic workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"step-5-preview-free":{"id":"step-5-preview-free","name":"Step 5 Preview Free","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":65536},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"stepfun/step-5-preview"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"qwen3.7-plus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":262144}],"tool_call":true,"temperature":true,"release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/go/anthropic/v1"},"cost":{"input":0.4,"output":1.6,"cache_read":0.04,"cache_write":0.5,"tiers":[{"input":1.2,"output":4.8,"cache_read":0.12,"cache_write":1.5,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1.2,"output":4.8,"cache_read":0.12,"cache_write":1.5}}}}},"openreason":{"id":"openreason","env":["OPENREASON_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.openreason.app/v1","name":"OpenReason","doc":"https://openreason.app/docs","models":{"deepseek-ai/deepseek-v4-flash-0731":{"id":"deepseek-ai/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.1371,"output":0.2743},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.0022,"output":4.22},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.1055,"output":0.422},"canonical_model_id":"openai/gpt-oss-120b"}}},"lmstudio":{"id":"lmstudio","env":["LMSTUDIO_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"http://127.0.0.1:1234/v1","name":"LMStudio","doc":"https://lmstudio.ai/models","models":{"qwen/qwen3-30b-a3b-2507":{"id":"qwen/qwen3-30b-a3b-2507","name":"Qwen3 30B A3B 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0,"output":0}},"qwen/qwen3-coder-30b":{"id":"qwen/qwen3-coder-30b","name":"Qwen3 Coder 30B","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0,"output":0}},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0,"output":0}}}},"aki-io":{"id":"aki-io","env":["AKI_IO_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://aki.io/v1","name":"AKI.IO","doc":"https://aki.io/docs/","models":{"qwen3.8-27b":{"id":"qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.3,"output":2.2,"cache_read":0.1},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen3.6-35b":{"id":"qwen3.6-35b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32768},"cost":{"input":0.15,"output":0.5},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"glm5.3-754b":{"id":"glm5.3-754b","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":81920},"cost":{"input":1,"output":3.5,"cache_read":0.25},"canonical_model_id":"zhipuai/glm-5.3"},"mistral4-119b":{"id":"mistral4-119b","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":81920},"cost":{"input":0.2,"output":0.6},"canonical_model_id":"mistral/mistral-small-2603"},"deepseek-v4.1-flash-552b":{"id":"deepseek-v4.1-flash-552b","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":81920},"cost":{"input":0.25,"output":1,"cache_read":0.1},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.15,"output":0.55},"canonical_model_id":"openai/gpt-oss-120b"},"gemma4-26b":{"id":"gemma4-26b","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32768},"cost":{"input":0.1,"output":0.5},"canonical_model_id":"google/gemma-4-26b-a4b-it"}}},"tensorx":{"id":"tensorx","env":["TENSORX_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.tensorx.ai/v1","name":"TensorX","doc":"https://docs.tensorx.ai/","models":{"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.25,"output":0.3,"cache_read":0.06},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.5,"output":1.5,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":64000},"cost":{"input":2,"output":4,"cache_read":0.5},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":1.75,"output":3.5,"cache_read":0.4375,"cache_write":2.185},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-r1-0528":{"id":"deepseek/deepseek-r1-0528","name":"DeepSeek R1-0528","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":8192},"cost":{"input":0.66,"output":2.6,"cache_read":0.165,"cache_write":0.825},"canonical_model_id":"deepseek/deepseek-r1"},"deepseek/deepseek-v3.2":{"id":"deepseek/deepseek-v3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":163840},"cost":{"input":0.3,"output":0.5,"cache_read":0.075,"cache_write":0.375}},"z-ai/glm-5v-turbo":{"id":"z-ai/glm-5v-turbo","name":"GLM-5V-Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.3,"cache_write":1.5},"canonical_model_id":"zhipuai/glm-5v-turbo"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":64000},"cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-5":{"id":"z-ai/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":202752},"cost":{"input":1,"output":3.2,"cache_read":0.25,"cache_write":1.25},"canonical_model_id":"zhipuai/glm-5"},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.5,"output":4.5,"cache_read":0.375},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/glm-5.1":{"id":"z-ai/glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":202752},"cost":{"input":1.4,"output":4.4,"cache_read":0.35,"cache_write":1.75},"canonical_model_id":"zhipuai/glm-5.1"},"z-ai/glm-5-turbo":{"id":"z-ai/glm-5-turbo","name":"GLM-5-Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.3,"cache_write":1.5},"canonical_model_id":"zhipuai/glm-5-turbo"},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":64000},"cost":{"input":1.75,"output":4.5,"cache_read":0.44},"canonical_model_id":"zhipuai/glm-5.3"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.75},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1,"output":4,"cache_read":0.25,"cache_write":1.25},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2.5":{"id":"moonshotai/kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":2.8,"cache_read":0.125,"cache_write":0.625},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.25,"output":4.5,"cache_read":0.3125},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":65536},"cost":{"input":0.3,"output":1.2,"cache_read":0.075,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.4,"output":2,"cache_read":0.1},"canonical_model_id":"minimax/MiniMax-M3"},"qwen/qwen3-235b-a22b-2507":{"id":"qwen/qwen3-235b-a22b-2507","name":"Qwen3 235B-A22B-2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-06-30","release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":262144},"cost":{"input":0.072,"output":0.464,"cache_read":0.018,"cache_write":0.09}},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.4,"output":2.4,"cache_read":0.1},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3.8-2.4t-a95b":{"id":"qwen/qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":64000},"cost":{"input":2.5,"output":6,"cache_read":0.63},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"qwen/qwen3.5-122b-a10b":{"id":"qwen/qwen3.5-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":3.5,"cache_read":0.125,"cache_write":0.625},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"qwen/qwen3.5-9b":{"id":"qwen/qwen3.5-9b","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.15,"output":0.2,"cache_read":0.0375,"cache_write":0.1875},"canonical_model_id":"alibaba/qwen3.5-9b"},"qwen/qwen3.8-flash-next":{"id":"qwen/qwen3.8-flash-next","name":"Qwen3.8 Flash Next","description":"Open-weight experimental preview of the Qwen4 architecture: hybrid-attention MoE (125B total, 6B active) with vision encoder for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":64000},"cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.8-flash-next"}}},"longcat":{"id":"longcat","env":["LONGCAT_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.longcat.chat/openai","name":"LongCat","doc":"https://longcat.chat/platform/docs/","models":{"LongCat-2.0":{"id":"LongCat-2.0","name":"LongCat-2.0","description":"Meituan LongCat-2.0, a reasoning model with tool calling and a 1M-token context window","family":"longcat","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.75,"output":2.95,"cache_read":0.015},"canonical_model_id":"meituan/longcat-2.0"}}},"pareto":{"id":"pareto","env":["PARETO_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.paretoinference.com/v1","name":"Pareto Inference","doc":"https://docs.paretoinference.com/","models":{"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.03,"output":0.1,"cache_read":0.006},"canonical_model_id":"zhipuai/glm-5.3-flash"}}},"chutes":{"id":"chutes","env":["CHUTES_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://llm.chutes.ai/v1","name":"Chutes","doc":"https://llm.chutes.ai/v1/models","models":{"Nemotron-3-Nano-Omni-30B-TEE":{"id":"Nemotron-3-Nano-Omni-30B-TEE","name":"Nemotron 3 Nano Omni 30B TEE","description":"Omni-modal model for text, vision, audio, and multimodal agent tasks","family":"nemotron","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-07-23","last_updated":"2026-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":0},"cost":{"input":0.0245,"output":0.0978,"cache_read":0.0024499999999999995}},"unsloth/Mistral-Nemo-Instruct-2407-TEE":{"id":"unsloth/Mistral-Nemo-Instruct-2407-TEE","name":"Mistral Nemo Instruct 2407 TEE","description":"Efficient Mistral-NVIDIA open model for multilingual chat and local deployment","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.0245,"output":0.0978,"cache_read":0.0024499999999999995},"canonical_model_id":"mistral/mistral-nemo"},"google/gemma-4-31B-turbo-TEE":{"id":"google/gemma-4-31B-turbo-TEE","name":"gemma 4 31B turbo TEE","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.12,"output":0.37,"cache_read":0.011999999999999997},"canonical_model_id":"google/gemma-4-31b-it"},"Qwen/Qwen3-32B-TEE":{"id":"Qwen/Qwen3-32B-TEE","name":"Qwen3 32B TEE","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":40960},"cost":{"input":0.104,"output":0.416,"cache_read":0.010399999999999998},"canonical_model_id":"alibaba/qwen3-32b"},"Qwen/Qwen3.6-27B-TEE":{"id":"Qwen/Qwen3.6-27B-TEE","name":"Qwen3.6 27B TEE","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.25,"output":2,"cache_read":0.024999999999999994},"canonical_model_id":"alibaba/qwen3.6-27b"},"Qwen/Qwen3-235B-A22B-Thinking-2507-TEE":{"id":"Qwen/Qwen3-235B-A22B-Thinking-2507-TEE","name":"Qwen3 235B A22B Thinking 2507 TEE","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07","last_updated":"2026-06-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.2989,"output":1.1957,"cache_read":0.029889999999999993}},"Qwen/Qwen3.8-27B-TEE":{"id":"Qwen/Qwen3.8-27B-TEE","name":"Qwen3.8 27B TEE","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-16","last_updated":"2026-08-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.039,"output":1.25,"cache_read":0.003899999999999999},"canonical_model_id":"alibaba/qwen3.8-27b"},"Qwen/Qwen3.5-397B-A17B-TEE":{"id":"Qwen/Qwen3.5-397B-A17B-TEE","name":"Qwen3.5 397B A17B TEE","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.45,"output":3,"cache_read":0.04499999999999999},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"deepseek-ai/DeepSeek-V4-Flash-0731-TEE":{"id":"deepseek-ai/DeepSeek-V4-Flash-0731-TEE","name":"DeepSeek V4 Flash 0731 TEE","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-08-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.44,"output":1.32,"cache_read":0.04399999999999999},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek-ai/DeepSeek-V3.2-TEE":{"id":"deepseek-ai/DeepSeek-V3.2-TEE","name":"DeepSeek V3.2 TEE","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12","last_updated":"2026-06-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":1,"output":1,"cache_read":0.09999999999999998},"canonical_model_id":"deepseek/deepseek-v3.2"},"moonshotai/Kimi-K3-TEE":{"id":"moonshotai/Kimi-K3-TEE","name":"Kimi K3 TEE","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65535},"cost":{"input":1.85,"output":9.5,"cache_read":0.18499999999999997},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/Kimi-K2.6-TEE":{"id":"moonshotai/Kimi-K2.6-TEE","name":"Kimi K2.6 TEE","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-12","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65535},"cost":{"input":0.45,"output":1.95,"cache_read":0.04499999999999999},"canonical_model_id":"moonshotai/kimi-k2.6"},"zai-org/GLM-5.2-TEE":{"id":"zai-org/GLM-5.2-TEE","name":"GLM 5.2 TEE","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65535},"cost":{"input":1.25,"output":3.95,"cache_read":0.12499999999999997},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-5.1-TEE":{"id":"zai-org/GLM-5.1-TEE","name":"GLM 5.1 TEE","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":65535},"cost":{"input":0.98,"output":3.08,"cache_read":0.09799999999999998},"canonical_model_id":"zhipuai/glm-5.1"}}},"edenai":{"id":"edenai","env":["EDENAI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.edenai.run/v3","name":"Eden AI","doc":"https://docs.edenai.co","models":{"deepseek-v4-flash-vision-exp":{"id":"deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"deepinfra/nemotron-3-ultra-550b-a55b":{"id":"deepinfra/nemotron-3-ultra-550b-a55b","name":"Nemotron 3 Ultra 550B A55B (Deep Infra)","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":128000},"cost":{"input":0.5,"output":2.2,"cache_read":0.1},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"deepinfra/meta-models/Muse-Glimmer-30B":{"id":"deepinfra/meta-models/Muse-Glimmer-30B","name":"Muse Glimmer 30B (Deep Infra)","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.04},"canonical_model_id":"meta/muse-glimmer-30b"},"deepinfra/tencent/Hy3":{"id":"deepinfra/tencent/Hy3","name":"Hy3 (Deep Infra)","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":128000},"cost":{"input":0.13,"output":0.53,"cache_read":0.033},"canonical_model_id":"tencent/hy3"},"deepinfra/tencent/Hy4-preview":{"id":"deepinfra/tencent/Hy4-preview","name":"Hy4 preview (Deep Infra)","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":64000},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"},"deepinfra/meta-llama/Llama-Guard-3-8B":{"id":"deepinfra/meta-llama/Llama-Guard-3-8B","name":"Llama-Guard-3-8B (Deep Infra)","description":"Llama 3.1-based safety classifier for moderating prompts and model responses","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":4096},"cost":{"input":0.055,"output":0.055},"canonical_model_id":"meta/llama-guard-3-8b"},"deepinfra/meta-llama/Llama-3.2-11B-Vision-Instruct":{"id":"deepinfra/meta-llama/Llama-3.2-11B-Vision-Instruct","name":"Llama-3.2-11B-Vision-Instruct (Deep Infra)","description":"Open multimodal Llama model for image understanding, captioning, and visual QA","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":4096},"cost":{"input":0.345,"output":0.345},"canonical_model_id":"meta/llama-3.2-11b-vision-instruct"},"deepinfra/meta-llama/Llama-3.3-70B-Instruct":{"id":"deepinfra/meta-llama/Llama-3.3-70B-Instruct","name":"Llama-3.3-70B-Instruct (Deep Infra)","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":4096},"cost":{"input":0.1,"output":0.32},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"deepinfra/thinkingmachines/Inkling-Small":{"id":"deepinfra/thinkingmachines/Inkling-Small","name":"Inkling Small (Deep Infra)","description":"Multimodal MoE reasoning model (276B total, 12B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":1048576},"cost":{"input":0.45,"output":1.2,"cache_read":0.1},"canonical_model_id":"thinkingmachines/inkling-small"},"deepinfra/thinkingmachines/Inkling":{"id":"deepinfra/thinkingmachines/Inkling","name":"Inkling (Deep Infra)","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":1048576},"cost":{"input":0.95,"output":4.05,"cache_read":0.16},"canonical_model_id":"thinkingmachines/inkling"},"deepinfra/google/gemma-3-27b-it":{"id":"deepinfra/google/gemma-3-27b-it","name":"Gemma 3 27B IT (Deep Infra)","description":"Largest open Gemma 3 instruction model for multilingual text generation and visual understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.08,"output":0.16},"canonical_model_id":"google/gemma-3-27b-it"},"deepinfra/google/gemma-3-12b-it":{"id":"deepinfra/google/gemma-3-12b-it","name":"Gemma 3 12B IT (Deep Infra)","description":"Open multimodal Gemma instruction model for multilingual text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.05,"output":0.15},"canonical_model_id":"google/gemma-3-12b-it"},"deepinfra/google/gemma-3-4b-it":{"id":"deepinfra/google/gemma-3-4b-it","name":"Gemma 3 4B IT (Deep Infra)","description":"Open multimodal Gemma instruction model for efficient text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.05,"output":0.1},"canonical_model_id":"google/gemma-3-4b-it"},"deepinfra/Gryphe/MythoMax-L2-13b":{"id":"deepinfra/Gryphe/MythoMax-L2-13b","name":"MythoMax L2 13B (Deep Infra)","description":"Llama 2 merge combining MythoLogic and Huginn for creative writing and roleplay","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2023-08-10","last_updated":"2023-08-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":3200},"cost":{"input":0.4,"output":0.4},"canonical_model_id":"gryphe/mythomax-l2-13b"},"deepinfra/Qwen/Qwen3-VL-235B-A22B-Instruct":{"id":"deepinfra/Qwen/Qwen3-VL-235B-A22B-Instruct","name":"Qwen3 VL 235B A22B Instruct (Deep Infra)","description":"Qwen vision-language instruct model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.2,"output":0.88,"cache_read":0.11},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"deepinfra/Qwen/Qwen3-Next-80B-A3B-Instruct":{"id":"deepinfra/Qwen/Qwen3-Next-80B-A3B-Instruct","name":"Qwen3-Next 80B-A3B Instruct (Deep Infra)","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.09,"output":1.1},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"deepinfra/Qwen/Qwen3-VL-30B-A3B-Instruct":{"id":"deepinfra/Qwen/Qwen3-VL-30B-A3B-Instruct","name":"Qwen3 VL 30B A3B Instruct (Deep Infra)","description":"Open vision-language MoE model for image and video understanding, documents, and visual agents","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-04","last_updated":"2025-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"alibaba/qwen3-vl-30b-a3b-instruct"},"deepinfra/Qwen/Qwen3-Max":{"id":"deepinfra/Qwen/Qwen3-Max","name":"Qwen3 Max (Deep Infra)","description":"Flagship Qwen3 model for coding agents, complex reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":65536},"cost":{"input":1.2,"output":6,"cache_read":0.24},"canonical_model_id":"alibaba/qwen3-max"},"deepinfra/Qwen/Qwen3-235B-A22B-Instruct-2507":{"id":"deepinfra/Qwen/Qwen3-235B-A22B-Instruct-2507","name":"Qwen3 235B-A22B Instruct 2507 (Deep Infra)","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.09,"output":0.55},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"deepinfra/Qwen/Qwen3-Coder-480B-A35B-Instruct":{"id":"deepinfra/Qwen/Qwen3-Coder-480B-A35B-Instruct","name":"Qwen3-Coder 480B-A35B Instruct (Deep Infra)","description":"Open Qwen coding heavyweight for repository reasoning and agentic engineering","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.4,"output":1.6},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"deepinfra/deepseek-ai/DeepSeek-V4-Flash-0731":{"id":"deepinfra/deepseek-ai/DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731 (Deep Infra)","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.06,"output":0.18,"cache_read":0.015},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepinfra/deepseek-ai/DeepSeek-R1":{"id":"deepinfra/deepseek-ai/DeepSeek-R1","name":"DeepSeek-R1 (Deep Infra)","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":32768},"cost":{"input":0.7,"output":2.4},"canonical_model_id":"deepseek/deepseek-r1"},"deepinfra/deepseek-ai/DeepSeek-V4-Pro-0813":{"id":"deepinfra/deepseek-ai/DeepSeek-V4-Pro-0813","name":"DeepSeek V4 Pro 0813 (Deep Infra)","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":1.3,"output":2.6,"cache_read":0.1},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepinfra/deepseek-ai/DeepSeek-V4.1-Flash":{"id":"deepinfra/deepseek-ai/DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash (Deep Infra)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.2,"output":0.6,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepinfra/deepseek-ai/DeepSeek-R1-0528":{"id":"deepinfra/deepseek-ai/DeepSeek-R1-0528","name":"DeepSeek R1 0528 (Deep Infra)","description":"May 2025 DeepSeek R1 update with improved mathematics, coding, and reasoning","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":32768},"cost":{"input":0.5,"output":2.15,"cache_read":0.35},"canonical_model_id":"deepseek/deepseek-r1-0528"},"deepinfra/deepseek-ai/DeepSeek-V3":{"id":"deepinfra/deepseek-ai/DeepSeek-V3","name":"DeepSeek-V3 (Deep Infra)","description":"Open DeepSeek MoE chat model for coding, math, and general reasoning","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2024-12-26","last_updated":"2024-12-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":8192},"cost":{"input":0.32,"output":0.89},"canonical_model_id":"deepseek/deepseek-v3"},"deepinfra/deepseek-ai/DeepSeek-V3-0324":{"id":"deepinfra/deepseek-ai/DeepSeek-V3-0324","name":"DeepSeek V3 0324 (Deep Infra)","description":"March 2025 checkpoint of DeepSeek-V3 with improved reasoning and coding","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-03-24","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":163840},"cost":{"input":0.24,"output":0.9,"cache_read":0.135},"canonical_model_id":"deepseek/deepseek-v3-0324"},"deepinfra/stepfun-ai/Step-3.7-Flash":{"id":"deepinfra/stepfun-ai/Step-3.7-Flash","name":"Step 3.7 Flash (Deep Infra)","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"deepinfra/stepfun-ai/Step-5-Preview":{"id":"deepinfra/stepfun-ai/Step-5-Preview","name":"Step 5 Preview (Deep Infra)","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1000000},"cost":{"input":1,"output":2.7,"cache_read":0.05},"canonical_model_id":"stepfun/step-5-preview"},"deepinfra/stepfun-ai/Step-3.5-Flash":{"id":"deepinfra/stepfun-ai/Step-3.5-Flash","name":"Step 3.5 Flash (Deep Infra)","description":"StepFun flash lane for quick multimodal reasoning and coding assistance","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.09,"output":0.3,"cache_read":0.02},"canonical_model_id":"stepfun/step-3.5-flash"},"deepinfra/mistralai/Mistral-Small-24B-Instruct-2501":{"id":"deepinfra/mistralai/Mistral-Small-24B-Instruct-2501","name":"Mistral Small 3 (Deep Infra)","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-01-30","last_updated":"2025-01-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"cost":{"input":0.05,"output":0.08},"canonical_model_id":"mistral/mistral-small-24b-instruct-2501"},"deepinfra/moonshotai/Kimi-K2-Instruct":{"id":"deepinfra/moonshotai/Kimi-K2-Instruct","name":"Kimi K2 Instruct (Deep Infra)","description":"Non-thinking Kimi K2 MoE instruction model for coding and tool-using agents","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":2},"canonical_model_id":"moonshotai/kimi-k2-instruct"},"deepinfra/moonshotai/Kimi-K2.5":{"id":"deepinfra/moonshotai/Kimi-K2.5","name":"Kimi K2.5 (Deep Infra)","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.45,"output":2.25,"cache_read":0.07},"canonical_model_id":"moonshotai/kimi-k2.5"},"deepinfra/zai-org/GLM-4.7-Flash":{"id":"deepinfra/zai-org/GLM-4.7-Flash","name":"GLM-4.7-Flash (Deep Infra)","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.06,"output":0.4,"cache_read":0.01},"canonical_model_id":"zhipuai/glm-4.7-flash"},"deepinfra/nvidia/Nemotron-3-Nano-30B-A3B":{"id":"deepinfra/nvidia/Nemotron-3-Nano-30B-A3B","name":"Nemotron 3 Nano 30B A3B (Deep Infra)","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.05,"output":0.2,"cache_read":0.025},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"deepinfra/nvidia/Llama-3.1-Nemotron-70B-Instruct":{"id":"deepinfra/nvidia/Llama-3.1-Nemotron-70B-Instruct","name":"Llama 3.1 Nemotron 70B Instruct (Deep Infra)","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-04-15","last_updated":"2025-04-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.6,"output":0.6},"canonical_model_id":"nvidia/llama-3.1-nemotron-70b-instruct"},"deepinfra/ByteDance/Seed-2.0-code":{"id":"deepinfra/ByteDance/Seed-2.0-code","name":"Seed 2.0 Code (Deep Infra)","description":"ByteDance Seed coding model for multimodal software engineering and long-running agents","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":131072},"cost":{"input":0.5,"output":3,"cache_read":0.1},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"deepinfra/ByteDance/Seed-2.0-mini":{"id":"deepinfra/ByteDance/Seed-2.0-mini","name":"Seed 2.0 Mini (Deep Infra)","description":"Lightweight ByteDance Seed 2.0 model for low-latency multimodal reasoning and high-volume tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.1,"output":0.4,"cache_read":0.02},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"deepinfra/openai/gpt-oss-20b":{"id":"deepinfra/openai/gpt-oss-20b","name":"GPT OSS 20B (Deep Infra)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.03,"output":0.14},"canonical_model_id":"openai/gpt-oss-20b"},"deepinfra/openai/gpt-oss-120b":{"id":"deepinfra/openai/gpt-oss-120b","name":"GPT OSS 120B (Deep Infra)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.037,"output":0.17},"canonical_model_id":"openai/gpt-oss-120b"},"deepinfra/microsoft/WizardLM-2-8x22B":{"id":"deepinfra/microsoft/WizardLM-2-8x22B","name":"WizardLM 2 8x22B (Deep Infra)","description":"Microsoft WizardLM instruction-tuned Mixtral MoE for multilingual dialogue and complex tasks","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2024-04-15","last_updated":"2024-04-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":8000},"cost":{"input":0.48,"output":0.48},"canonical_model_id":"microsoft/wizardlm-2-8x22b"},"deepinfra/NousResearch/Hermes-3-Llama-3.1-70B":{"id":"deepinfra/NousResearch/Hermes-3-Llama-3.1-70B","name":"Hermes 3 70B Instruct (Deep Infra)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"nousresearch","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-18","last_updated":"2024-08-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.7,"output":0.7},"canonical_model_id":"nousresearch/hermes-3-llama-3.1-70b"},"deepinfra/NousResearch/Hermes-3-Llama-3.1-405B":{"id":"deepinfra/NousResearch/Hermes-3-Llama-3.1-405B","name":"Hermes 3 405B Instruct (Deep Infra)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"nousresearch","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-16","last_updated":"2024-08-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":1,"output":1},"canonical_model_id":"nousresearch/hermes-3-llama-3.1-405b"},"cerebras/gpt-oss-120b":{"id":"cerebras/gpt-oss-120b","name":"GPT OSS 120B (Cerebras)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.35,"output":0.75,"cache_read":0.35},"canonical_model_id":"openai/gpt-oss-120b"},"groq/openai/gpt-oss-20b":{"id":"groq/openai/gpt-oss-20b","name":"GPT OSS 20B (Groq)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.075,"output":0.3,"cache_read":0.0375},"canonical_model_id":"openai/gpt-oss-20b"},"groq/openai/gpt-oss-safeguard-20b":{"id":"groq/openai/gpt-oss-safeguard-20b","name":"GPT OSS Safeguard 20B (Groq)","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.075,"output":0.3,"cache_read":0.0375},"canonical_model_id":"openai/gpt-oss-safeguard-20b"},"groq/openai/gpt-oss-120b":{"id":"groq/openai/gpt-oss-120b","name":"GPT OSS 120B (Groq)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-oss-120b"},"zai/glm-4.6v":{"id":"zai/glm-4.6v","name":"GLM-4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.3,"output":0.9,"cache_read":0.05},"canonical_model_id":"zhipuai/glm-4.6v"},"zai/glm-5v-turbo":{"id":"zai/glm-5v-turbo","name":"GLM-5V-Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5v-turbo"},"zai/glm-5.3-flash":{"id":"zai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai/glm-4.6":{"id":"zai/glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.6"},"zai/glm-5":{"id":"zai/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"zai/glm-4.7":{"id":"zai/glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.7"},"zai/glm-5.2":{"id":"zai/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"zai/glm-5.1":{"id":"zai/glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"zai/glm-5-turbo":{"id":"zai/glm-5-turbo","name":"GLM-5-Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5-turbo"},"zai/glm-5.3":{"id":"zai/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"anthropic/claude-opus-latest":{"id":"anthropic/claude-opus-latest","name":"Claude Opus Latest (Claude Opus 5.5)","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-opus-4-5":{"id":"anthropic/claude-opus-4-5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-haiku-latest":{"id":"anthropic/claude-haiku-latest","name":"Claude Haiku Latest (Claude Haiku 5.5)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-opus-5-5":{"id":"anthropic/claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-fable-5-1":{"id":"anthropic/claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-sonnet-latest":{"id":"anthropic/claude-sonnet-latest","name":"Claude Sonnet Latest (Claude Sonnet 5.5)","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-opus-4-5-20251101":{"id":"anthropic/claude-opus-4-5-20251101","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-01","last_updated":"2025-11-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-fable-latest":{"id":"anthropic/claude-fable-latest","name":"Claude Fable Latest (Claude Fable 5.1)","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-opus-4-8":{"id":"anthropic/claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-opus-4-6":{"id":"anthropic/claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-haiku-5-5":{"id":"anthropic/claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-sonnet-4-6":{"id":"anthropic/claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-sonnet-5-5":{"id":"anthropic/claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-opus-4-7":{"id":"anthropic/claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"cohere/command-r-08-2024":{"id":"cohere/command-r-08-2024","name":"Command R","description":"Cohere retrieval model for long-context chat and enterprise RAG workflows","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"cohere/command-r-08-2024"},"cohere/command-a-03-2025":{"id":"cohere/command-a-03-2025","name":"Command A","description":"Cohere command model for multilingual enterprise agents, tools, and chat","family":"command-a","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2025-03-13","last_updated":"2025-03-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":288000,"output":8000},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-a-03-2025"},"cohere/command-r7b-12-2024":{"id":"cohere/command-r7b-12-2024","name":"Command R7B","description":"Cohere retrieval model for long-context chat and enterprise RAG workflows","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-12-02","last_updated":"2024-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":132000,"output":4000},"cost":{"input":0.0375,"output":0.15},"canonical_model_id":"cohere/command-r7b-12-2024"},"cohere/command-r-plus-08-2024":{"id":"cohere/command-r-plus-08-2024","name":"Command R+","description":"Cohere's RAG workhorse for long-context enterprise search and tool use","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-r-plus-08-2024"},"cohere/c4ai-aya-expanse-32b":{"id":"cohere/c4ai-aya-expanse-32b","name":"Aya Expanse 32B","description":"Open multilingual model optimized for generation across 23 languages","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2024-10-24","last_updated":"2024-10-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"cohere/c4ai-aya-expanse-32b"},"deepseek/deepseek-v4-flash-vision-exp":{"id":"deepseek/deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"deepseek/deepseek-chat":{"id":"deepseek/deepseek-chat","name":"DeepSeek Chat","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-12-01","last_updated":"2026-02-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-chat"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.66,"output":1.98,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4-flash"},"databricks/databricks-inkling":{"id":"databricks/databricks-inkling","name":"Inkling (Databricks)","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":1048576},"cost":{"input":1,"output":4.05,"cache_read":0.1,"cache_write":1.00002},"canonical_model_id":"thinkingmachines/inkling"},"databricks/databricks-qwen3-next-80b-a3b-instruct@eu":{"id":"databricks/databricks-qwen3-next-80b-a3b-instruct@eu","name":"Qwen3-Next 80B-A3B Instruct (Databricks, EU)","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15001,"output":1.20001,"cache_read":0.015001,"cache_write":0.15001},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"databricks/databricks-gpt-oss-20b":{"id":"databricks/databricks-gpt-oss-20b","name":"GPT OSS 20B (Databricks)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.07,"output":0.30002,"cache_read":0.007,"cache_write":0.07},"canonical_model_id":"openai/gpt-oss-20b"},"databricks/databricks-deepseek-v4-flash-0731":{"id":"databricks/databricks-deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731 (Databricks)","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.014,"cache_write":0.14},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"databricks/databricks-gpt-oss-120b@eu":{"id":"databricks/databricks-gpt-oss-120b@eu","name":"GPT OSS 120B (Databricks, EU)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15001,"output":0.59997,"cache_read":0.015001,"cache_write":0.15001},"canonical_model_id":"openai/gpt-oss-120b"},"databricks/databricks-gpt-oss-120b":{"id":"databricks/databricks-gpt-oss-120b","name":"GPT OSS 120B (Databricks)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15001,"output":0.59997,"cache_read":0.015001,"cache_write":0.15001},"canonical_model_id":"openai/gpt-oss-120b"},"databricks/databricks-deepseek-v4-pro-0813":{"id":"databricks/databricks-deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813 (Databricks)","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.32,"output":3.959999,"cache_read":0.132,"cache_write":1.31999},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"databricks/databricks-qwen3-next-80b-a3b-instruct":{"id":"databricks/databricks-qwen3-next-80b-a3b-instruct","name":"Qwen3-Next 80B-A3B Instruct (Databricks)","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15001,"output":1.20001,"cache_read":0.015001,"cache_write":0.15001},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"databricks/databricks-gpt-oss-20b@eu":{"id":"databricks/databricks-gpt-oss-20b@eu","name":"GPT OSS 20B (Databricks, EU)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.07,"output":0.30002,"cache_read":0.007,"cache_write":0.07},"canonical_model_id":"openai/gpt-oss-20b"},"tencent/deepseek-v4.1-flash":{"id":"tencent/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash (Tencent)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"tencent/deepseek-v4-pro-0813":{"id":"tencent/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813 (Tencent)","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.66,"output":1.98,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"tencent/hy3":{"id":"tencent/hy3","name":"Hy3 (Tencent)","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":192000,"output":128000},"cost":{"input":0.132,"output":0.528,"cache_read":0.033},"canonical_model_id":"tencent/hy3"},"tencent/hy4-preview":{"id":"tencent/hy4-preview","name":"Hy4 preview (Tencent)","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":64000},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"},"together_ai/meta-models/Muse-Glimmer-30B":{"id":"together_ai/meta-models/Muse-Glimmer-30B","name":"Muse Glimmer 30B (Together AI)","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.35,"output":1.5,"cache_read":0.04},"canonical_model_id":"meta/muse-glimmer-30b"},"together_ai/thinkingmachines/Inkling":{"id":"together_ai/thinkingmachines/Inkling","name":"Inkling (Together AI)","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":1048576},"cost":{"input":1,"output":4.05,"cache_read":0.17},"canonical_model_id":"thinkingmachines/inkling"},"together_ai/deepseek-ai/DeepSeek-V4-Flash-0731":{"id":"together_ai/deepseek-ai/DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731 (Together AI)","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"together_ai/deepseek-ai/DeepSeek-V4-Pro-0813":{"id":"together_ai/deepseek-ai/DeepSeek-V4-Pro-0813","name":"DeepSeek V4 Pro 0813 (Together AI)","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":1.32,"output":3.96,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"together_ai/deepseek-ai/DeepSeek-V4.1-Flash":{"id":"together_ai/deepseek-ai/DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash (Together AI)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"together_ai/openai/gpt-oss-120b":{"id":"together_ai/openai/gpt-oss-120b","name":"GPT OSS 120B (Together AI)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-120b"},"azure/gpt-5.2-codex":{"id":"azure/gpt-5.2-codex","name":"GPT-5.2 Codex (Azure)","description":"Code-specialist GPT for repository edits, reviews, and long-running software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-codex"},"azure/gpt-5.1-codex":{"id":"azure/gpt-5.1-codex","name":"GPT-5.1 Codex (Azure)","description":"Codex GPT for repository edits, code review, and practical software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex"},"azure/gpt-5.1-codex-max":{"id":"azure/gpt-5.1-codex-max","name":"GPT-5.1 Codex Max (Azure)","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex-max"},"azure/gpt-5.1-codex-mini":{"id":"azure/gpt-5.1-codex-mini","name":"GPT-5.1 Codex mini (Azure)","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5.1-codex-mini"},"flexai/DeepSeek-V4-Flash-0731@eu":{"id":"flexai/DeepSeek-V4-Flash-0731@eu","name":"DeepSeek V4 Flash 0731 (FlexAI, EU)","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.119,"output":0.238,"cache_read":0.0178},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"flexai/Step-3.7-Flash":{"id":"flexai/Step-3.7-Flash","name":"Step 3.7 Flash (FlexAI)","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.2,"output":1.15,"cache_read":0.03},"canonical_model_id":"stepfun/step-3.7-flash"},"flexai/DeepSeek-V4-Flash-0731":{"id":"flexai/DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731 (FlexAI)","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.119,"output":0.238,"cache_read":0.0178},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"flexai/Muse-Glimmer-30B":{"id":"flexai/Muse-Glimmer-30B","name":"Muse Glimmer 30B (FlexAI)","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.045},"canonical_model_id":"meta/muse-glimmer-30b"},"flexai/DeepSeek-V4.1-Flash":{"id":"flexai/DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash (FlexAI)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.1,"output":0.66,"cache_read":0.015},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"flexai/gpt-oss-20b":{"id":"flexai/gpt-oss-20b","name":"GPT OSS 20B (FlexAI)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.02,"output":0.1,"cache_read":0.003},"canonical_model_id":"openai/gpt-oss-20b"},"flexai/gpt-oss-120b":{"id":"flexai/gpt-oss-120b","name":"GPT OSS 120B (FlexAI)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.05,"output":0.25,"cache_read":0.0075},"canonical_model_id":"openai/gpt-oss-120b"},"google/gemini-flash-latest":{"id":"google/gemini-flash-latest","name":"Gemini Flash Latest (Gemini 3.8 Flash)","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"reasoning":7.5,"cache_read":0.15,"cache_write":0.083333,"input_audio":1.5},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-3.1-flash-image-preview":{"id":"google/gemini-3.1-flash-image-preview","name":"Nano Banana 2 Preview","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-26","last_updated":"2026-02-26","modalities":{"input":["image","text"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":65536},"cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3.1-flash-image-preview"},"google/gemini-2.5-flash-image":{"id":"google/gemini-2.5-flash-image","name":"Nano Banana","description":"Nano Banana image model for fast generation, edits, and character-consistent assets","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["audio","image","text","video"],"output":["text","image"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.3,"output":2.5,"reasoning":2.5,"cache_read":0.03,"cache_write":0.083333,"input_audio":1},"canonical_model_id":"google/gemini-2.5-flash-image"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"reasoning":3.75,"cache_read":0.075,"cache_write":0.041667,"input_audio":0.75},"canonical_model_id":"google/gemini-3.6-flash"},"google/gemini-3-pro-image-preview":{"id":"google/gemini-3-pro-image-preview","name":"Nano Banana Pro Preview","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-20","last_updated":"2025-11-20","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":2,"output":12,"reasoning":12,"cache_read":0.2,"cache_write":0.375,"input_audio":2},"canonical_model_id":"google/gemini-3-pro-image-preview"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"reasoning":2.5,"cache_read":0.03,"cache_write":0.083333,"input_audio":0.3},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemini-3.1-flash-image":{"id":"google/gemini-3.1-flash-image","name":"Nano Banana 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["image","text"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3.1-flash-image"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"reasoning":12,"cache_read":0.2,"cache_write":0.375,"input_audio":2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"reasoning":9,"cache_read":0.15,"cache_write":0.083333,"input_audio":3},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-3-pro-image":{"id":"google/gemini-3-pro-image","name":"Nano Banana Pro","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":2,"output":12,"reasoning":12,"cache_read":0.2,"cache_write":0.375,"input_audio":2},"canonical_model_id":"google/gemini-3-pro-image"},"google/gemini-3.1-flash-lite-image":{"id":"google/gemini-3.1-flash-lite-image","name":"Nano Banana 2 Lite","description":"Fastest, most cost-efficient Gemini image model for high-volume 1K generation and editing","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":4096},"cost":{"input":0.25,"output":1.5},"canonical_model_id":"google/gemini-3.1-flash-lite-image"},"google/deep-research-preview-04-2026":{"id":"google/deep-research-preview-04-2026","name":"Gemini Deep Research Preview","description":"Agentic model for autonomous multi-step research, synthesis, and cited reports","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12},"canonical_model_id":"google/deep-research-preview-04-2026"},"google/deep-research-max-preview-04-2026":{"id":"google/deep-research-max-preview-04-2026","name":"Deep Research Max Preview","description":"Maximum-comprehensiveness agentic researcher for multi-step investigation, synthesis, and cited reports","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12},"canonical_model_id":"google/deep-research-max-preview-04-2026"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"reasoning":7.5,"cache_read":0.15,"cache_write":0.083333,"input_audio":1.5},"canonical_model_id":"google/gemini-3.7-flash"},"google/gemini-3.1-pro-preview-customtools":{"id":"google/gemini-3.1-pro-preview-customtools","name":"Gemini 3.1 Pro Preview Custom Tools","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"reasoning":12,"cache_read":0.2,"cache_write":0.375,"input_audio":2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview-customtools"},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"reasoning":3,"cache_read":0.05,"cache_write":0.083333,"input_audio":1},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-pro-latest":{"id":"google/gemini-pro-latest","name":"Gemini Pro Latest (Gemini 4 Argon)","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":4,"output":20,"reasoning":20,"cache_read":0.2,"cache_write":0.375,"input_audio":4},"canonical_model_id":"google/gemini-4-argon"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"reasoning":7.5,"cache_read":0.15,"cache_write":0.083333,"input_audio":1.5},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-3.1-flash-lite-preview":{"id":"google/gemini-3.1-flash-lite-preview","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"reasoning":1.5,"cache_read":0.025,"cache_write":0.083333,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite-preview"},"google/gemini-nano-banana-2.1":{"id":"google/gemini-nano-banana-2.1","name":"Nano Banana 2.1","description":"Image model for prompt-driven generation, multi-turn editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["image","text"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":1.5,"output":7.5},"canonical_model_id":"google/gemini-nano-banana-2.1"},"google/gemini-4-argon":{"id":"google/gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":4,"output":20,"reasoning":20,"cache_read":0.2,"cache_write":0.375,"input_audio":4},"canonical_model_id":"google/gemini-4-argon"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"reasoning":1.5,"cache_read":0.025,"cache_write":0.083333,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite"},"xai/grok-latest":{"id":"xai/grok-latest","name":"Grok Latest (Grok 4.7)","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"xai/grok-4.7":{"id":"xai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"xai/grok-4.3":{"id":"xai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.3"},"xai/grok-4.20-0309-reasoning":{"id":"xai/grok-4.20-0309-reasoning","name":"Grok 4.20 (Reasoning)","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-reasoning"},"xai/grok-4-fast-non-reasoning":{"id":"xai/grok-4-fast-non-reasoning","name":"X-Ai/Grok-4-Fast-Non-Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-18","last_updated":"2025-12-18","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":0.2,"output":0.5,"cache_read":0.05,"tiers":[{"input":0.4,"output":1,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"xai/grok-4-fast-non-reasoning"},"xai/grok-4.5":{"id":"xai/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.3,"tiers":[{"input":4,"output":12,"cache_read":0.6,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":0.6}},"canonical_model_id":"xai/grok-4.5"},"xai/grok-4.20-0309-non-reasoning":{"id":"xai/grok-4.20-0309-non-reasoning","name":"Grok 4.20 (Non-Reasoning)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-non-reasoning"},"xai/grok-build-0.1":{"id":"xai/grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.2,"tiers":[{"input":2,"output":4,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2,"output":4,"cache_read":0.4}},"canonical_model_id":"xai/grok-build-0.1"},"xai/grok-4.6":{"id":"xai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"nebius/meta-models/muse-spark-open":{"id":"nebius/meta-models/muse-spark-open","name":"Muse Spark Open (Nebius)","description":"Muse Spark Open is an 816B total / 42B active open-weight multimodal reasoning model from Meta for coding and long-horizon agentic work, with 1M-token context.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":1.25},"canonical_model_id":"meta/muse-spark-open"},"nebius/google/gemma-3-27b-it":{"id":"nebius/google/gemma-3-27b-it","name":"Gemma 3 27B IT (Nebius)","description":"Largest open Gemma 3 instruction model for multilingual text generation and visual understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":110000,"output":131072},"cost":{"input":0.1,"output":0.3,"cache_read":0.1},"canonical_model_id":"google/gemma-3-27b-it"},"nebius/Qwen/Qwen3-235B-A22B-Instruct-2507":{"id":"nebius/Qwen/Qwen3-235B-A22B-Instruct-2507","name":"Qwen3 235B-A22B Instruct 2507 (Nebius)","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.2,"output":0.6,"cache_read":0.2},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"nebius/deepseek-ai/DeepSeek-V4-Flash-0731":{"id":"nebius/deepseek-ai/DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731 (Nebius)","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.14},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"nebius/deepseek-ai/DeepSeek-V4-Pro-0813":{"id":"nebius/deepseek-ai/DeepSeek-V4-Pro-0813","name":"DeepSeek V4 Pro 0813 (Nebius)","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":979000,"output":384000},"cost":{"input":1.32,"output":3.96,"cache_read":1.32},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"nebius/deepseek-ai/DeepSeek-V4.1-Flash":{"id":"nebius/deepseek-ai/DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash (Nebius)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048000,"output":384000},"cost":{"input":0.3,"output":1.2,"cache_read":0.3},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"nebius/nvidia/nemotron-3-super-120b-a12b":{"id":"nebius/nvidia/nemotron-3-super-120b-a12b","name":"Nemotron 3 Super 120B A12B (Nebius)","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.3,"output":0.9,"cache_read":0.3},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"nebius/nvidia/Nemotron-3-Ultra-550b-a55b":{"id":"nebius/nvidia/Nemotron-3-Ultra-550b-a55b","name":"Nemotron 3 Ultra 550B A55B (Nebius)","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":128000},"cost":{"input":1,"output":3,"cache_read":1},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nebius/openai/gpt-oss-120b":{"id":"nebius/openai/gpt-oss-120b","name":"GPT OSS 120B (Nebius)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6,"cache_read":0.15},"canonical_model_id":"openai/gpt-oss-120b"},"scaleway/gemma-3-27b-it":{"id":"scaleway/gemma-3-27b-it","name":"Gemma 3 27B IT (Scaleway)","description":"Largest open Gemma 3 instruction model for multilingual text generation and visual understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":40000,"output":131072},"cost":{"input":0.287125,"output":0.57425},"canonical_model_id":"google/gemma-3-27b-it"},"scaleway/deepseek-v4-flash-0731":{"id":"scaleway/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731 (Scaleway)","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":384000},"cost":{"input":0.45012,"output":0.90024,"cache_read":0.090024},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"scaleway/qwen3-235b-a22b-instruct-2507":{"id":"scaleway/qwen3-235b-a22b-instruct-2507","name":"Qwen3 235B-A22B Instruct 2507 (Scaleway)","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":250000,"output":16384},"cost":{"input":0.843975,"output":2.531925},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"scaleway/deepseek-v4.1-flash":{"id":"scaleway/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash (Scaleway)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":384000},"cost":{"input":0.67518,"output":2.02554,"cache_read":0.135036},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"scaleway/qwen3-coder-30b-a3b-instruct":{"id":"scaleway/qwen3-coder-30b-a3b-instruct","name":"Qwen3-Coder 30B-A3B Instruct (Scaleway)","description":"Smaller Qwen coder for efficient local agents and repo-level fixes","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":65536},"cost":{"input":0.22506,"output":0.90024},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"scaleway/llama-3.3-70b-instruct":{"id":"scaleway/llama-3.3-70b-instruct","name":"Llama-3.3-70B-Instruct (Scaleway)","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":1.01277,"output":1.01277},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"scaleway/gpt-oss-120b":{"id":"scaleway/gpt-oss-120b","name":"GPT OSS 120B (Scaleway)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.168795,"output":0.67518},"canonical_model_id":"openai/gpt-oss-120b"},"ionos/meta-llama/Llama-3.3-70B-Instruct":{"id":"ionos/meta-llama/Llama-3.3-70B-Instruct","name":"Llama-3.3-70B-Instruct (IONOS)","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.731445,"output":0.731445},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"ionos/Qwen/Qwen3-Coder-Next":{"id":"ionos/Qwen/Qwen3-Coder-Next","name":"Qwen3 Coder Next (IONOS)","description":"Open-weight Qwen coding model for agents, repository edits, and multi-turn tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":65536},"cost":{"input":0.168795,"output":0.90024},"canonical_model_id":"alibaba/qwen3-coder-next"},"ionos/openai/gpt-oss-120b":{"id":"ionos/openai/gpt-oss-120b","name":"GPT OSS 120B (IONOS)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.168795,"output":0.731445},"canonical_model_id":"openai/gpt-oss-120b"},"vertex/gemini-4-argon@us":{"id":"vertex/gemini-4-argon@us","name":"Gemini 4 Argon (Vertex AI, US)","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":4,"output":20,"reasoning":20,"cache_read":0.2,"cache_write":0.375,"input_audio":4},"canonical_model_id":"google/gemini-4-argon"},"vertex/gemini-flash-latest":{"id":"vertex/gemini-flash-latest","name":"Gemini Flash Latest (Gemini 3.8 Flash, Vertex AI)","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"reasoning":7.5,"cache_read":0.15,"cache_write":0.083333,"input_audio":1.5},"canonical_model_id":"google/gemini-3.8-flash"},"vertex/gemini-2.5-flash-image":{"id":"vertex/gemini-2.5-flash-image","name":"Nano Banana (Vertex AI)","description":"Nano Banana image model for fast generation, edits, and character-consistent assets","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.3,"output":2.5,"reasoning":2.5,"cache_read":0.03,"cache_write":0.083333,"input_audio":1},"canonical_model_id":"google/gemini-2.5-flash-image"},"vertex/gemini-3.1-flash-lite@eu":{"id":"vertex/gemini-3.1-flash-lite@eu","name":"Gemini 3.1 Flash Lite (Vertex AI, EU)","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"reasoning":1.5,"cache_read":0.025,"cache_write":0.083333,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite"},"vertex/gemini-3.5-flash-lite@eu":{"id":"vertex/gemini-3.5-flash-lite@eu","name":"Gemini 3.5 Flash Lite (Vertex AI, EU)","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"reasoning":2.5,"cache_read":0.03,"cache_write":0.083333,"input_audio":0.3},"canonical_model_id":"google/gemini-3.5-flash-lite"},"vertex/gemini-3.6-flash@eu":{"id":"vertex/gemini-3.6-flash@eu","name":"Gemini 3.6 Flash (Vertex AI, EU)","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"reasoning":3.75,"cache_read":0.075,"cache_write":0.041667,"input_audio":0.75},"canonical_model_id":"google/gemini-3.6-flash"},"vertex/gemini-3.6-flash":{"id":"vertex/gemini-3.6-flash","name":"Gemini 3.6 Flash (Vertex AI)","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"reasoning":3.75,"cache_read":0.075,"cache_write":0.041667,"input_audio":0.75},"canonical_model_id":"google/gemini-3.6-flash"},"vertex/gemini-4-argon@eu":{"id":"vertex/gemini-4-argon@eu","name":"Gemini 4 Argon (Vertex AI, EU)","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":4,"output":20,"reasoning":20,"cache_read":0.2,"cache_write":0.375,"input_audio":4},"canonical_model_id":"google/gemini-4-argon"},"vertex/gemini-3.5-flash-lite":{"id":"vertex/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite (Vertex AI)","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"reasoning":2.5,"cache_read":0.03,"cache_write":0.083333,"input_audio":0.3},"canonical_model_id":"google/gemini-3.5-flash-lite"},"vertex/gemini-3.1-flash-image":{"id":"vertex/gemini-3.1-flash-image","name":"Nano Banana 2 (Vertex AI)","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["image","text"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3.1-flash-image"},"vertex/gemini-3.1-pro-preview":{"id":"vertex/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview (Vertex AI)","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"reasoning":12,"cache_read":0.2,"cache_write":0.375,"input_audio":2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":0.25}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"vertex/gemini-3.5-flash":{"id":"vertex/gemini-3.5-flash","name":"Gemini 3.5 Flash (Vertex AI)","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"reasoning":9,"cache_read":0.15,"cache_write":0.083333,"input_audio":3},"canonical_model_id":"google/gemini-3.5-flash"},"vertex/gemini-3-pro-image":{"id":"vertex/gemini-3-pro-image","name":"Nano Banana Pro (Vertex AI)","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":2,"output":12,"reasoning":12,"cache_read":0.2,"cache_write":0.375,"input_audio":2},"canonical_model_id":"google/gemini-3-pro-image"},"vertex/gemini-3.7-flash@us":{"id":"vertex/gemini-3.7-flash@us","name":"Gemini 3.7 Flash (Vertex AI, US)","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"reasoning":7.5,"cache_read":0.15,"cache_write":0.083333,"input_audio":1.5},"canonical_model_id":"google/gemini-3.7-flash"},"vertex/gemini-3.7-flash@eu":{"id":"vertex/gemini-3.7-flash@eu","name":"Gemini 3.7 Flash (Vertex AI, EU)","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"reasoning":7.5,"cache_read":0.15,"cache_write":0.083333,"input_audio":1.5},"canonical_model_id":"google/gemini-3.7-flash"},"vertex/gemini-3.1-flash-lite-image":{"id":"vertex/gemini-3.1-flash-lite-image","name":"Nano Banana 2 Lite (Vertex AI)","description":"Fastest, most cost-efficient Gemini image model for high-volume 1K generation and editing","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":4096},"cost":{"input":0.25,"output":1.5},"canonical_model_id":"google/gemini-3.1-flash-lite-image"},"vertex/gemini-3.8-flash@eu":{"id":"vertex/gemini-3.8-flash@eu","name":"Gemini 3.8 Flash (Vertex AI, EU)","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"reasoning":7.5,"cache_read":0.15,"cache_write":0.083333,"input_audio":1.5},"canonical_model_id":"google/gemini-3.8-flash"},"vertex/gemini-3.7-flash":{"id":"vertex/gemini-3.7-flash","name":"Gemini 3.7 Flash (Vertex AI)","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"reasoning":7.5,"cache_read":0.15,"cache_write":0.083333,"input_audio":1.5},"canonical_model_id":"google/gemini-3.7-flash"},"vertex/gemini-3.6-flash@us":{"id":"vertex/gemini-3.6-flash@us","name":"Gemini 3.6 Flash (Vertex AI, US)","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"reasoning":3.75,"cache_read":0.075,"cache_write":0.041667,"input_audio":0.75},"canonical_model_id":"google/gemini-3.6-flash"},"vertex/gemini-3.5-flash-lite@us":{"id":"vertex/gemini-3.5-flash-lite@us","name":"Gemini 3.5 Flash Lite (Vertex AI, US)","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"reasoning":2.5,"cache_read":0.03,"cache_write":0.083333,"input_audio":0.3},"canonical_model_id":"google/gemini-3.5-flash-lite"},"vertex/gemini-3-flash-preview":{"id":"vertex/gemini-3-flash-preview","name":"Gemini 3 Flash Preview (Vertex AI)","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"reasoning":3,"cache_read":0.05,"cache_write":0.083333,"input_audio":1},"canonical_model_id":"google/gemini-3-flash-preview"},"vertex/gemini-3.1-flash-lite@us":{"id":"vertex/gemini-3.1-flash-lite@us","name":"Gemini 3.1 Flash Lite (Vertex AI, US)","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"reasoning":1.5,"cache_read":0.025,"cache_write":0.083333,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite"},"vertex/gemini-pro-latest":{"id":"vertex/gemini-pro-latest","name":"Gemini Pro Latest (Gemini 4 Argon, Vertex AI)","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":4,"output":20,"reasoning":20,"cache_read":0.2,"cache_write":0.375,"input_audio":4},"canonical_model_id":"google/gemini-4-argon"},"vertex/gemini-3.8-flash":{"id":"vertex/gemini-3.8-flash","name":"Gemini 3.8 Flash (Vertex AI)","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"reasoning":7.5,"cache_read":0.15,"cache_write":0.083333,"input_audio":1.5},"canonical_model_id":"google/gemini-3.8-flash"},"vertex/gemini-3.5-flash@eu":{"id":"vertex/gemini-3.5-flash@eu","name":"Gemini 3.5 Flash (Vertex AI, EU)","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"reasoning":9,"cache_read":0.15,"cache_write":0.083333,"input_audio":3},"canonical_model_id":"google/gemini-3.5-flash"},"vertex/gemini-3.8-flash@us":{"id":"vertex/gemini-3.8-flash@us","name":"Gemini 3.8 Flash (Vertex AI, US)","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"reasoning":7.5,"cache_read":0.15,"cache_write":0.083333,"input_audio":1.5},"canonical_model_id":"google/gemini-3.8-flash"},"vertex/gemini-3.5-flash@us":{"id":"vertex/gemini-3.5-flash@us","name":"Gemini 3.5 Flash (Vertex AI, US)","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"reasoning":9,"cache_read":0.15,"cache_write":0.083333,"input_audio":3},"canonical_model_id":"google/gemini-3.5-flash"},"vertex/gemini-nano-banana-2.1":{"id":"vertex/gemini-nano-banana-2.1","name":"Nano Banana 2.1 (Vertex AI)","description":"Image model for prompt-driven generation, multi-turn editing, and visual design workflows","family":"gemini-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","high"]}],"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":1.5,"output":7.5},"canonical_model_id":"google/gemini-nano-banana-2.1"},"vertex/gemini-4-argon":{"id":"vertex/gemini-4-argon","name":"Gemini 4 Argon (Vertex AI)","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":4,"output":20,"reasoning":20,"cache_read":0.2,"cache_write":0.375,"input_audio":4},"canonical_model_id":"google/gemini-4-argon"},"vertex/gemini-3.1-flash-lite":{"id":"vertex/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite (Vertex AI)","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"reasoning":1.5,"cache_read":0.025,"cache_write":0.083333,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite"},"greenpt/deepseek-v4-flash-0731":{"id":"greenpt/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731 (Greenpt)","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.157542,"output":0.393855,"cache_read":0.045012},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"greenpt/qwen3-235b-a22b-instruct-2507":{"id":"greenpt/qwen3-235b-a22b-instruct-2507","name":"Qwen3 235B-A22B Instruct 2507 (Greenpt)","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":250000,"output":16384},"cost":{"input":1.01277,"output":3.03831},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"greenpt/deepseek-v4.1-flash":{"id":"greenpt/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash (Greenpt)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.247566,"output":1.23783,"cache_read":0.012378},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"greenpt/llama-3.3-70b-instruct":{"id":"greenpt/llama-3.3-70b-instruct","name":"Llama-3.3-70B-Instruct (Greenpt)","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":1.23783,"output":1.23783},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"greenpt/gpt-oss-120b":{"id":"greenpt/gpt-oss-120b","name":"GPT OSS 120B (Greenpt)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.22506,"output":0.78771},"canonical_model_id":"openai/gpt-oss-120b"},"greenference/deepseek-v4.1-flash":{"id":"greenference/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash (Greenference)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.22,"output":0.88,"cache_read":0.007},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"greenference/gpt-oss-20b":{"id":"greenference/gpt-oss-20b","name":"GPT OSS 20B (Greenference)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.009,"output":0.045,"cache_read":0.0045},"canonical_model_id":"openai/gpt-oss-20b"},"perplexityai/sonar-pro":{"id":"perplexityai/sonar-pro","name":"Sonar Pro","description":"Deeper Sonar search model with broader retrieval and stronger synthesis","family":"sonar-pro","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":3,"output":15},"canonical_model_id":"perplexity/sonar-pro"},"perplexityai/sonar-deep-research":{"id":"perplexityai/sonar-deep-research","name":"Sonar Deep Research","description":"Sonar search model for autonomous research and citation-backed long-form reports","family":"sonar","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2025-02-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32768},"cost":{"input":2,"output":8,"reasoning":3},"canonical_model_id":"perplexity/sonar-deep-research"},"perplexityai/sonar":{"id":"perplexityai/sonar","name":"Sonar","description":"Fast web-grounded Sonar for current answers, citations, and lightweight retrieval","family":"sonar","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":127072,"output":4096},"cost":{"input":1,"output":1},"canonical_model_id":"perplexity/sonar"},"perplexityai/sonar-reasoning-pro":{"id":"perplexityai/sonar-reasoning-pro","name":"Sonar Reasoning Pro","description":"Web-grounded Sonar for multi-step research questions that need cited reasoning","family":"sonar-reasoning","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":2,"output":8},"canonical_model_id":"perplexity/sonar-reasoning-pro"},"cloudflare/@cf/meta/llama-guard-3-8b":{"id":"cloudflare/@cf/meta/llama-guard-3-8b","name":"Llama-Guard-3-8B (Cloudflare)","description":"Llama 3.1-based safety classifier for moderating prompts and model responses","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":4096},"cost":{"input":0.484,"output":0.03},"canonical_model_id":"meta/llama-guard-3-8b"},"cloudflare/@cf/meta/llama-3.2-1b-instruct":{"id":"cloudflare/@cf/meta/llama-3.2-1b-instruct","name":"Llama 3.2 1B Instruct (Cloudflare)","description":"Compact instruction-tuned Llama model for multilingual dialogue and on-device assistants","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":60000,"output":32000},"cost":{"input":0.027,"output":0.201},"canonical_model_id":"meta/llama-3.2-1b-instruct"},"cloudflare/@cf/aisingapore/gemma-sea-lion-v4-27b-it":{"id":"cloudflare/@cf/aisingapore/gemma-sea-lion-v4-27b-it","name":"Gemma-SEA-LION-v4-27B-IT (Cloudflare)","description":"Gemma 3 27B tuned by AI Singapore for Southeast Asian languages and instruction following","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0.351,"output":0.555},"canonical_model_id":"aisingapore/gemma-sea-lion-v4-27b-it"},"cloudflare/@cf/deepseek-ai/deepseek-v4-flash-0731":{"id":"cloudflare/@cf/deepseek-ai/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731 (Cloudflare)","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.44,"output":1.32,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"cloudflare/@cf/deepseek-ai/deepseek-v4-pro-0813":{"id":"cloudflare/@cf/deepseek-ai/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813 (Cloudflare)","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"cloudflare/@cf/mistralai/mistral-small-3.1-24b-instruct":{"id":"cloudflare/@cf/mistralai/mistral-small-3.1-24b-instruct","name":"Mistral Small 3.1 24B (Cloudflare)","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-03-17","last_updated":"2025-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":102400},"cost":{"input":0.351,"output":0.555},"canonical_model_id":"mistral/mistral-small-3.1-24b-instruct"},"cloudflare/@cf/zai-org/glm-4.7-flash":{"id":"cloudflare/@cf/zai-org/glm-4.7-flash","name":"GLM-4.7-Flash (Cloudflare)","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.0605,"output":0.4},"canonical_model_id":"zhipuai/glm-4.7-flash"},"cloudflare/@cf/qwen/qwen2.5-coder-32b-instruct":{"id":"cloudflare/@cf/qwen/qwen2.5-coder-32b-instruct","name":"Qwen2.5-Coder-32B-Instruct (Cloudflare)","description":"Open coding-focused Qwen model for code generation, repair, and repository reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2024-11-12","last_updated":"2024-11-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0.66,"output":1},"canonical_model_id":"alibaba/qwen2.5-coder-32b-instruct"},"cloudflare/@cf/openai/gpt-oss-20b":{"id":"cloudflare/@cf/openai/gpt-oss-20b","name":"GPT OSS 20B (Cloudflare)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.2,"output":0.3},"canonical_model_id":"openai/gpt-oss-20b"},"cloudflare/@cf/openai/gpt-oss-120b":{"id":"cloudflare/@cf/openai/gpt-oss-120b","name":"GPT OSS 120B (Cloudflare)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.35,"output":0.75},"canonical_model_id":"openai/gpt-oss-120b"},"minimax/MiniMax-M3":{"id":"minimax/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":512000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"minimax/MiniMax-M2.1":{"id":"minimax/MiniMax-M2.1","name":"MiniMax-M2.1","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.1"},"minimax/MiniMax-M2.5":{"id":"minimax/MiniMax-M2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5"},"minimax/MiniMax-M2.7":{"id":"minimax/MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/MiniMax-M2":{"id":"minimax/MiniMax-M2","name":"MiniMax-M2","description":"Efficient open MiniMax model built for coding agents and tool-heavy workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2"},"tensorx/deepseek/deepseek-v4-flash-0731":{"id":"tensorx/deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731 (TensorX)","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.25,"output":0.3,"cache_read":0.0625},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"tensorx/deepseek/deepseek-v4.1-flash":{"id":"tensorx/deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash (TensorX)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.5,"output":1.5,"cache_read":0.125},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"tensorx/deepseek/deepseek-v4-pro-0813":{"id":"tensorx/deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813 (TensorX)","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":2,"output":4,"cache_read":0.5},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"tensorx/deepseek/deepseek-r1-0528":{"id":"tensorx/deepseek/deepseek-r1-0528","name":"DeepSeek R1 0528 (TensorX)","description":"May 2025 DeepSeek R1 update with improved mathematics, coding, and reasoning","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":32768},"cost":{"input":0.66,"output":2.6,"cache_read":0.165},"canonical_model_id":"deepseek/deepseek-r1-0528"},"tensorx/moonshotai/kimi-k2.5":{"id":"tensorx/moonshotai/kimi-k2.5","name":"Kimi K2.5 (TensorX)","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":2.8,"cache_read":0.125},"canonical_model_id":"moonshotai/kimi-k2.5"},"amazon/google.gemma-3-12b-it":{"id":"amazon/google.gemma-3-12b-it","name":"Gemma 3 12B IT (Amazon Bedrock)","description":"Open multimodal Gemma instruction model for multilingual text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":131072},"cost":{"input":0.09,"output":0.29},"canonical_model_id":"google/gemma-3-12b-it"},"amazon/google.gemma-3-4b-it":{"id":"amazon/google.gemma-3-4b-it","name":"Gemma 3 4B IT (Amazon Bedrock)","description":"Open multimodal Gemma instruction model for efficient text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":131072},"cost":{"input":0.04,"output":0.08},"canonical_model_id":"google/gemma-3-4b-it"},"amazon/openai.gpt-oss-safeguard-20b@us":{"id":"amazon/openai.gpt-oss-safeguard-20b@us","name":"GPT OSS Safeguard 20B (Amazon Bedrock, US)","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":131072},"cost":{"input":0.07,"output":0.2},"canonical_model_id":"openai/gpt-oss-safeguard-20b"},"amazon/openai.gpt-oss-safeguard-20b":{"id":"amazon/openai.gpt-oss-safeguard-20b","name":"GPT OSS Safeguard 20B (Amazon Bedrock)","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":131072},"cost":{"input":0.07,"output":0.2},"canonical_model_id":"openai/gpt-oss-safeguard-20b"},"amazon/amazon.nova-lite-v1:0@us":{"id":"amazon/amazon.nova-lite-v1:0@us","name":"Nova Lite (US)","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.06,"output":0.24,"cache_read":0.015},"canonical_model_id":"amazon/nova-lite"},"amazon/mistral.voxtral-mini-3b-2507@us":{"id":"amazon/mistral.voxtral-mini-3b-2507@us","name":"Voxtral Mini 3B 2507 (Amazon Bedrock, US)","description":"Open audio-language model for speech transcription, audio understanding, and voice-driven tool use","family":"voxtral","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.04,"output":0.04},"canonical_model_id":"mistral/voxtral-mini-3b-2507"},"amazon/amazon.nova-micro-v1:0":{"id":"amazon/amazon.nova-micro-v1:0","name":"Nova Micro","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-micro","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":10000},"cost":{"input":0.035,"output":0.14,"cache_read":0.00875},"canonical_model_id":"amazon/nova-micro"},"amazon/amazon.nova-pro-v1:0":{"id":"amazon/amazon.nova-pro-v1:0","name":"Nova Pro","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.8,"output":3.2,"cache_read":0.2},"canonical_model_id":"amazon/nova-pro"},"amazon/mistral.voxtral-small-24b-2507":{"id":"amazon/mistral.voxtral-small-24b-2507","name":"Voxtral Small 24B 2507 (Amazon Bedrock)","description":"Open audio-language model for speech transcription, audio understanding, and voice-driven tool use","family":"voxtral","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"mistral/voxtral-small-24b-2507"},"amazon/amazon.nova-lite-v1:0":{"id":"amazon/amazon.nova-lite-v1:0","name":"Nova Lite","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.06,"output":0.24,"cache_read":0.015},"canonical_model_id":"amazon/nova-lite"},"amazon/mistral.voxtral-small-24b-2507@us":{"id":"amazon/mistral.voxtral-small-24b-2507@us","name":"Voxtral Small 24B 2507 (Amazon Bedrock, US)","description":"Open audio-language model for speech transcription, audio understanding, and voice-driven tool use","family":"voxtral","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"mistral/voxtral-small-24b-2507"},"amazon/google.gemma-3-12b-it@us":{"id":"amazon/google.gemma-3-12b-it@us","name":"Gemma 3 12B IT (Amazon Bedrock, US)","description":"Open multimodal Gemma instruction model for multilingual text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":131072},"cost":{"input":0.09,"output":0.29},"canonical_model_id":"google/gemma-3-12b-it"},"amazon/google.gemma-3-27b-it":{"id":"amazon/google.gemma-3-27b-it","name":"Gemma 3 27B IT (Amazon Bedrock)","description":"Largest open Gemma 3 instruction model for multilingual text generation and visual understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":131072},"cost":{"input":0.23,"output":0.38},"canonical_model_id":"google/gemma-3-27b-it"},"amazon/google.gemma-3-27b-it@us":{"id":"amazon/google.gemma-3-27b-it@us","name":"Gemma 3 27B IT (Amazon Bedrock, US)","description":"Largest open Gemma 3 instruction model for multilingual text generation and visual understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":131072},"cost":{"input":0.23,"output":0.38},"canonical_model_id":"google/gemma-3-27b-it"},"amazon/mistral.pixtral-large-2502-v1:0":{"id":"amazon/mistral.pixtral-large-2502-v1:0","name":"Pixtral Large (25.02) (Amazon Bedrock)","description":"Mistral vision-language model for image understanding and multimodal chat","family":"pixtral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-04-08","last_updated":"2025-04-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":2,"output":6},"canonical_model_id":"mistral/pixtral-large-2502"},"amazon/amazon.nova-micro-v1:0@us":{"id":"amazon/amazon.nova-micro-v1:0@us","name":"Nova Micro (US)","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-micro","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":10000},"cost":{"input":0.035,"output":0.14,"cache_read":0.00875},"canonical_model_id":"amazon/nova-micro"},"amazon/zai.glm-4.7-flash@us":{"id":"amazon/zai.glm-4.7-flash@us","name":"GLM-4.7-Flash (Amazon Bedrock, US)","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":203000,"output":131072},"cost":{"input":0.07,"output":0.4},"canonical_model_id":"zhipuai/glm-4.7-flash"},"amazon/qwen.qwen3-coder-next":{"id":"amazon/qwen.qwen3-coder-next","name":"Qwen3 Coder Next (Amazon Bedrock)","description":"Open-weight Qwen coding model for agents, repository edits, and multi-turn tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.6,"output":1.44},"canonical_model_id":"alibaba/qwen3-coder-next"},"amazon/moonshotai.kimi-k2.5":{"id":"amazon/moonshotai.kimi-k2.5","name":"Kimi K2.5 (Amazon Bedrock)","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":3},"canonical_model_id":"moonshotai/kimi-k2.5"},"amazon/amazon.nova-pro-v1:0@us":{"id":"amazon/amazon.nova-pro-v1:0@us","name":"Nova Pro (US)","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.8,"output":3.2,"cache_read":0.2},"canonical_model_id":"amazon/nova-pro"},"amazon/mistral.pixtral-large-2502-v1:0@us":{"id":"amazon/mistral.pixtral-large-2502-v1:0@us","name":"Pixtral Large (25.02) (Amazon Bedrock, US)","description":"Mistral vision-language model for image understanding and multimodal chat","family":"pixtral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-04-08","last_updated":"2025-04-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":2,"output":6},"canonical_model_id":"mistral/pixtral-large-2502"},"amazon/zai.glm-4.7-flash":{"id":"amazon/zai.glm-4.7-flash","name":"GLM-4.7-Flash (Amazon Bedrock)","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":203000,"output":131072},"cost":{"input":0.07,"output":0.4},"canonical_model_id":"zhipuai/glm-4.7-flash"},"amazon/moonshot.kimi-k2-thinking":{"id":"amazon/moonshot.kimi-k2-thinking","name":"Kimi K2 Thinking (Amazon Bedrock)","description":"Thinking Kimi model for slower research passes, planning, and hard technical questions","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":262144},"cost":{"input":0.6,"output":2.5},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"amazon/google.gemma-3-4b-it@us":{"id":"amazon/google.gemma-3-4b-it@us","name":"Gemma 3 4B IT (Amazon Bedrock, US)","description":"Open multimodal Gemma instruction model for efficient text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":131072},"cost":{"input":0.04,"output":0.08},"canonical_model_id":"google/gemma-3-4b-it"},"amazon/mistral.voxtral-mini-3b-2507":{"id":"amazon/mistral.voxtral-mini-3b-2507","name":"Voxtral Mini 3B 2507 (Amazon Bedrock)","description":"Open audio-language model for speech transcription, audio understanding, and voice-driven tool use","family":"voxtral","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.04,"output":0.04},"canonical_model_id":"mistral/voxtral-mini-3b-2507"},"ovhcloud/gpt-oss-20b":{"id":"ovhcloud/gpt-oss-20b","name":"GPT OSS 20B (OVHcloud)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.05,"output":0.18},"canonical_model_id":"openai/gpt-oss-20b"},"ovhcloud/gpt-oss-120b":{"id":"ovhcloud/gpt-oss-120b","name":"GPT OSS 120B (OVHcloud)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.09,"output":0.47},"canonical_model_id":"openai/gpt-oss-120b"},"fireworks_ai/gpt-oss-120b":{"id":"fireworks_ai/gpt-oss-120b","name":"GPT OSS 120B (Fireworks AI)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6,"cache_read":0.014},"canonical_model_id":"openai/gpt-oss-120b"},"fireworks_ai/accounts/fireworks/models/inkling":{"id":"fireworks_ai/accounts/fireworks/models/inkling","name":"Inkling (Fireworks AI)","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1,"output":4.05,"cache_read":0.17},"canonical_model_id":"thinkingmachines/inkling"},"fireworks_ai/accounts/fireworks/models/gpt-oss-120b":{"id":"fireworks_ai/accounts/fireworks/models/gpt-oss-120b","name":"GPT OSS 120B (Fireworks AI)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"openai/gpt-oss-120b"},"fireworks_ai/accounts/fireworks/models/muse-spark-open":{"id":"fireworks_ai/accounts/fireworks/models/muse-spark-open","name":"Muse Spark Open (Fireworks AI)","description":"Muse Spark Open is an 816B total / 42B active open-weight multimodal reasoning model from Meta for coding and long-horizon agentic work, with 1M-token context.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-open"},"mistral/codestral-latest":{"id":"mistral/codestral-latest","name":"Codestral (latest)","description":"Mistral code model for completions, refactors, and developer IDE workflows","family":"codestral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-05-29","last_updated":"2025-01-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":4096},"cost":{"input":0.3,"output":0.9,"cache_read":0.03},"canonical_model_id":"mistral/codestral-latest"},"mistral/mistral-large-latest":{"id":"mistral/mistral-large-latest","name":"Mistral Large (latest)","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11","release_date":"2024-11-01","last_updated":"2025-12-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"mistral/mistral-large-latest"},"mistral/mistral-small-latest":{"id":"mistral/mistral-small-latest","name":"Mistral Small (latest)","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"mistral/mistral-small-latest"},"mistral/ministral-8b-2512":{"id":"mistral/ministral-8b-2512","name":"Ministral 3 8B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.15,"output":0.15,"cache_read":0.015},"canonical_model_id":"mistral/ministral-8b-2512"},"mistral/devstral-medium-latest":{"id":"mistral/devstral-medium-latest","name":"Devstral 2 (latest)","description":"Mistral coding agent model for repository tasks and software engineering workflows","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.4,"output":2},"canonical_model_id":"mistral/devstral-medium-latest"},"mistral/devstral-2512":{"id":"mistral/devstral-2512","name":"Devstral 2","description":"Mistral's coding-agent model for repository work, terminal tasks, and software fixes","family":"devstral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.4,"output":2,"cache_read":0.04},"canonical_model_id":"mistral/devstral-2512"},"mistral/mistral-medium-2505":{"id":"mistral/mistral-medium-2505","name":"Mistral Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":131072},"cost":{"input":0.4,"output":2},"canonical_model_id":"mistral/mistral-medium-2505"},"mistral/magistral-medium-latest":{"id":"mistral/magistral-medium-latest","name":"Magistral Medium (latest)","description":"Mistral reasoning model for transparent analysis, math, and complex decisions","family":"magistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2025-03-17","last_updated":"2025-03-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":16384},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"mistral/magistral-medium-latest"},"mistral/mistral-medium-3-5":{"id":"mistral/mistral-medium-3-5","name":"Mistral Medium 3.5","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":209715},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"mistral/mistral-medium-3-5"},"mistral/mistral-small-2603":{"id":"mistral/mistral-small-2603","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"mistral/mistral-small-2603"},"mistral/mistral-medium-3":{"id":"mistral/mistral-medium-3","name":"Mistral Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":104857},"cost":{"input":0.4,"output":2,"cache_read":0.04},"canonical_model_id":"mistral/mistral-medium-3"},"mistral/mistral-large-2512":{"id":"mistral/mistral-large-2512","name":"Mistral Large 3","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":1.5,"cache_read":0.05},"canonical_model_id":"mistral/mistral-large-2512"},"mistral/mistral-large-2407":{"id":"mistral/mistral-large-2407","name":"Mistral Large 2407","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-03-31","release_date":"2024-11-19","last_updated":"2024-11-19","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":104857},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"mistral/mistral-large-2407"},"mistral/ministral-14b-2512":{"id":"mistral/ministral-14b-2512","name":"Ministral 3 14B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.2,"output":0.2,"cache_read":0.02},"canonical_model_id":"mistral/ministral-14b-2512"},"mistral/voxtral-small-latest":{"id":"mistral/voxtral-small-latest","name":"Voxtral Small (latest)","description":"Instruct model with native audio input for speech understanding and tool use","family":"voxtral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32000},"cost":{"input":0.1,"output":0.4,"cache_read":0.01},"canonical_model_id":"mistral/voxtral-small-latest"},"mistral/ministral-3b-2512":{"id":"mistral/ministral-3b-2512","name":"Ministral 3 3B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":104857},"cost":{"input":0.1,"output":0.1,"cache_read":0.01},"canonical_model_id":"mistral/ministral-3b-2512"},"mistral/mistral-medium-2604":{"id":"mistral/mistral-medium-2604","name":"Mistral Medium 3.5","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"mistral/mistral-medium-2604"},"mistral/codestral-2508":{"id":"mistral/codestral-2508","name":"Codestral 25.08","description":"Mistral code model for low-latency completion, fill-in-the-middle, and code generation","family":"codestral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":8192},"cost":{"input":0.3,"output":0.9,"cache_read":0.03},"canonical_model_id":"mistral/codestral-2508"},"mistral/mistral-medium-latest":{"id":"mistral/mistral-medium-latest","name":"Mistral Medium (latest)","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"mistral/mistral-medium-latest"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32768},"cost":{"input":0.5,"output":3,"cache_read":0.1,"cache_write":0.625},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3.8-2.4t-a95b":{"id":"qwen/qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"qwen/deepseek-v4-flash-0731":{"id":"qwen/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731 (Alibaba)","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.22,"output":0.66,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"qwen/qwen-max":{"id":"qwen/qwen-max","name":"Qwen Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-03","last_updated":"2025-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":8192},"cost":{"input":1.6,"output":6.4,"cache_read":0.32},"canonical_model_id":"alibaba/qwen-max"},"qwen/qwen3.8-max":{"id":"qwen/qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"qwen/deepseek-v4.1-flash":{"id":"qwen/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash (Alibaba)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"qwen/qwen3.8-omni-flash":{"id":"qwen/qwen3.8-omni-flash","name":"Qwen3.8 Omni Flash","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47},"canonical_model_id":"alibaba/qwen3.8-omni-flash"},"qwen/qwen3-coder-flash":{"id":"qwen/qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.3,"output":1.5,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"alibaba/qwen3-coder-flash"},"qwen/qwen-mt-plus":{"id":"qwen/qwen-mt-plus","name":"Qwen MT Plus","description":"Flagship Qwen translation model with terminology control and support for 92 languages","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-07-24","last_updated":"2025-07-24","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":4096,"output":8192},"cost":{"input":2.46,"output":7.37},"canonical_model_id":"alibaba/qwen-mt-plus"},"qwen/deepseek-v4-pro-0813":{"id":"qwen/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813 (Alibaba)","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.66,"output":1.98,"cache_read":0.066},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"qwen/qwen3.8-flash":{"id":"qwen/qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen/qwen3.8-max-0902":{"id":"qwen/qwen3.8-max-0902","name":"Qwen3.8 Max 0902","description":"2026-09-02 upgraded snapshot of Qwen3.8 Max with stronger coding, collaborative agents, and multimodal document understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max-0902"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.4-pro"},"openai/gpt-3.5-turbo":{"id":"openai/gpt-3.5-turbo","name":"GPT-3.5-turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"output":4096},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"openai/gpt-3.5-turbo"},"openai/gpt-5.5-pro":{"id":"openai/gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.5-pro"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"openai/gpt-5.2-pro":{"id":"openai/gpt-5.2-pro","name":"GPT-5.2 Pro","description":"Higher-accuracy GPT-5.2 variant for tougher reasoning and review workflows","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":21,"output":168},"canonical_model_id":"openai/gpt-5.2-pro"},"openai/o4-mini":{"id":"openai/o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.275},"canonical_model_id":"openai/o4-mini"},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"openai/gpt-4":{"id":"openai/gpt-4","name":"GPT-4","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-11","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8191,"output":8192},"cost":{"input":30,"output":60},"canonical_model_id":"openai/gpt-4"},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"openai/o1":{"id":"openai/o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":15,"output":60,"cache_read":7.5},"canonical_model_id":"openai/o1"},"openai/gpt-latest":{"id":"openai/gpt-latest","name":"GPT Latest (GPT-6 Astra)","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"openai/gpt-5-pro":{"id":"openai/gpt-5-pro","name":"GPT-5 Pro","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":272000},"cost":{"input":15,"output":120},"canonical_model_id":"openai/gpt-5-pro"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-4o-2024-08-06":{"id":"openai/gpt-4o-2024-08-06","name":"GPT-4o (2024-08-06)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-08-06","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-08-06"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"openai/o3-pro":{"id":"openai/o3-pro","name":"o3-pro","description":"High-effort o3 tier for difficult technical reasoning and careful answers","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-06-10","last_updated":"2025-06-10","modalities":{"input":["text","pdf","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":20,"output":80},"canonical_model_id":"openai/o3-pro"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-4o-2024-11-20":{"id":"openai/gpt-4o-2024-11-20","name":"GPT-4o (2024-11-20)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-11-20","last_updated":"2024-11-20","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-11-20"},"openai/gpt-mini-latest":{"id":"openai/gpt-mini-latest","name":"GPT Mini Latest (GPT-5.6 Luna)","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-4-turbo":{"id":"openai/gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":10,"output":30},"canonical_model_id":"openai/gpt-4-turbo"},"openai/o3":{"id":"openai/o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"openai/o1-pro":{"id":"openai/o1-pro","name":"o1-pro","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2025-03-19","last_updated":"2025-03-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":150,"output":600},"canonical_model_id":"openai/o1-pro"},"openai/gpt-pro-latest":{"id":"openai/gpt-pro-latest","name":"GPT Pro Latest (GPT-5.6 Sol)","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"infomaniak/mistralai/Ministral-3-14B-Instruct-2512":{"id":"infomaniak/mistralai/Ministral-3-14B-Instruct-2512","name":"Ministral 3 14B (Infomaniak)","description":"Open vision-language model for efficient local deployment, instruction following, and tool use","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":100000,"output":262144},"cost":{"input":0.33759,"output":0.45012},"canonical_model_id":"mistral/ministral-3-14b-instruct-2512"},"moonshot/kimi-k3":{"id":"moonshot/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshot/kimi-k2.7-code-highspeed":{"id":"moonshot/kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code Highspeed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"moonshot/kimi-k2.6":{"id":"moonshot/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshot/kimi-k2.7-code":{"id":"moonshot/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"}}},"stepfun":{"id":"stepfun","env":["STEPFUN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.stepfun.com/v1","name":"StepFun (China)","doc":"https://platform.stepfun.com/docs/zh/overview/concept","models":{"step-1-32k":{"id":"step-1-32k","name":"Step 1 (32K)","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-01-01","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"input":32768,"output":32768},"cost":{"input":2.05,"output":9.59,"cache_read":0.41}},"step-tts-2":{"id":"step-tts-2","name":"Step TTS 2","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"step","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-03-01","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"step-5-preview":{"id":"step-5-preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":65536},"cost":{"input":0.959,"output":2.741,"cache_read":0.048},"canonical_model_id":"stepfun/step-5-preview"},"step-3.5-flash-2603":{"id":"step-3.5-flash-2603","name":"Step 3.5 Flash 2603","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.1,"output":0.3,"cache_read":0.02}},"step-2-16k":{"id":"step-2-16k","name":"Step 2 (16K)","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-01-01","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":5.21,"output":16.44,"cache_read":1.04}},"stepaudio-2.5-tts":{"id":"stepaudio-2.5-tts","name":"StepAudio 2.5 TTS","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"step","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-16","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"stepaudio-2.5-asr":{"id":"stepaudio-2.5-asr","name":"StepAudio 2.5 ASR","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"step","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-24","last_updated":"2026-07-02","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0}},"step-3.5-flash":{"id":"step-3.5-flash","name":"Step 3.5 Flash","description":"StepFun flash lane for quick multimodal reasoning and coding assistance","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-06-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.1,"output":0.3,"cache_read":0.02}},"step-3.7-flash":{"id":"step-3.7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-06-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.185,"output":1.11,"cache_read":0.037},"canonical_model_id":"stepfun/step-3.7-flash"}}},"hpc-ai":{"id":"hpc-ai","env":["HPC_AI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.hpc-ai.com/inference/v1","name":"HPC-AI","doc":"https://www.hpc-ai.com/doc/docs/quickstart/","models":{"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-7"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1002000,"output":128000},"cost":{"input":1.74,"output":3.48,"cache_read":0.145},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":128000},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"moonshotai/kimi-k2.5":{"id":"moonshotai/kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.6,"output":3,"cache_read":0.1},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"zai-org/glm-5.2":{"id":"zai-org/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/glm-5.1":{"id":"zai-org/glm-5.1","name":"GLM 5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202000,"output":202000},"cost":{"input":0.615,"output":2.46,"cache_read":0.133}},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196000,"output":195000},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"}}},"tencent-coding-plan":{"id":"tencent-coding-plan","env":["TENCENT_CODING_PLAN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.lkeap.cloud.tencent.com/coding/v3","name":"Tencent Coding Plan (China)","doc":"https://cloud.tencent.com/document/product/1772/128947","models":{"hunyuan-2.0-thinking":{"id":"hunyuan-2.0-thinking","name":"Tencent HY 2.0 Think","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"hunyuan","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-03-08","last_updated":"2026-03-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"glm-5":{"id":"glm-5","name":"GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-11","last_updated":"2026-02-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":16384},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"minimax-m2.5":{"id":"minimax-m2.5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"hunyuan-2.0-instruct":{"id":"hunyuan-2.0-instruct","name":"Tencent HY 2.0 Instruct","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"hunyuan","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-03-08","last_updated":"2026-03-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi-K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"tc-code-latest":{"id":"tc-code-latest","name":"Auto","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-03-08","last_updated":"2026-03-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"hunyuan-turbos":{"id":"hunyuan-turbos","name":"Hunyuan-TurboS","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"hunyuan","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-03-08","last_updated":"2026-03-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"hunyuan-t1":{"id":"hunyuan-t1","name":"Hunyuan-T1","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"hunyuan","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-03-08","last_updated":"2026-03-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}}}},"sambanova":{"id":"sambanova","env":["SAMBANOVA_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.sambanova.ai/v1","name":"SambaNova","doc":"https://docs.sambanova.ai/cloud/docs/get-started/supported-models","models":{"DeepSeek-V3.1":{"id":"DeepSeek-V3.1","name":"DeepSeek-V3.1","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":7168},"cost":{"input":3,"output":4.5},"canonical_model_id":"deepseek/deepseek-v3.1"},"MiniMax-M3":{"id":"MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.6,"output":2.4,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"Meta-Llama-3.3-70B-Instruct":{"id":"Meta-Llama-3.3-70B-Instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":3072},"cost":{"input":0.6,"output":1.2},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"DeepSeek-V3.2":{"id":"DeepSeek-V3.2","name":"DeepSeek V3.2","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":7168},"cost":{"input":3,"output":4.5},"canonical_model_id":"deepseek/deepseek-v3.2"},"gemma-4-31B-it":{"id":"gemma-4-31B-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.38,"output":1.15},"canonical_model_id":"google/gemma-4-31b-it"},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.22,"output":0.59},"canonical_model_id":"openai/gpt-oss-120b"}}},"tempr":{"id":"tempr","env":["TEMPR_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.temprhq.io/v1","name":"Tempr Gateway","doc":"https://temprhq.io/docs/gateway-reference.html","models":{"xiaomi-mimo/mimo-v2.6-pro":{"id":"xiaomi-mimo/mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"xiaomi-mimo/mimo-v2.6-pro-ultraspeed":{"id":"xiaomi-mimo/mimo-v2.6-pro-ultraspeed","name":"MiMo-V2.6-Pro-UltraSpeed","description":"MiMo pro model for strong multimodal reasoning and agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":4.35,"output":8.7,"cache_read":0.036},"canonical_model_id":"xiaomi/mimo-v2.6-pro-ultraspeed"},"xiaomi-mimo/mimo-v2.6-flash":{"id":"xiaomi-mimo/mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"cerebras/qwen-3.8-27b":{"id":"cerebras/qwen-3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-09-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":40960},"cost":{"input":0.99,"output":1.49},"canonical_model_id":"alibaba/qwen3.8-27b"},"cerebras/gpt-oss-120b":{"id":"cerebras/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2026-06-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":40960},"cost":{"input":0.35,"output":0.75},"canonical_model_id":"openai/gpt-oss-120b"},"groq/allam-2-7b":{"id":"groq/allam-2-7b","name":"ALLaM-2-7b","description":"ALLaM-2-7b instruction tuned model by SDAIA","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-01-23","last_updated":"2025-01-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":4096},"cost":{"input":0,"output":0},"canonical_model_id":"sdaia/allam-2-7b"},"groq/qwen/qwen3.8-27b":{"id":"groq/qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131042,"output":16384},"cost":{"input":0.8,"output":4},"canonical_model_id":"alibaba/qwen3.8-27b"},"groq/openai/gpt-oss-20b":{"id":"groq/openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.075,"output":0.3,"cache_read":0.0375},"canonical_model_id":"openai/gpt-oss-20b"},"groq/openai/gpt-oss-120b":{"id":"groq/openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-10-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-oss-120b"},"zai/glm-4.6v":{"id":"zai/glm-4.6v","name":"GLM-4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.3,"output":0.9},"canonical_model_id":"zhipuai/glm-4.6v"},"zai/glm-4.5":{"id":"zai/glm-4.5","name":"GLM-4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5"},"zai/glm-5v-turbo":{"id":"zai/glm-5v-turbo","name":"GLM-5V-Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24,"cache_write":0},"canonical_model_id":"zhipuai/glm-5v-turbo"},"zai/glm-5.3-flash":{"id":"zai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai/glm-4.6":{"id":"zai/glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.6"},"zai/glm-5":{"id":"zai/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2,"cache_write":0},"canonical_model_id":"zhipuai/glm-5"},"zai/glm-4.6v-flash":{"id":"zai/glm-4.6v-flash","name":"GLM-4.6V-Flash","description":"Lightweight GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.6v-flash"},"zai/glm-4.5v":{"id":"zai/glm-4.5v","name":"GLM-4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":16384},"cost":{"input":0.6,"output":1.8},"canonical_model_id":"zhipuai/glm-4.5v"},"zai/glm-5.3-flashx":{"id":"zai/glm-5.3-flashx","name":"GLM-5.3-FlashX","description":"High-speed GLM-5.3-Flash serving option for coding and agent workflows","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-18","last_updated":"2026-09-18","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.37,"output":1.25,"cache_read":0.075,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai/glm-4.7-flash":{"id":"zai/glm-4.7-flash","name":"GLM-4.7-Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7-flash"},"zai/glm-4.7":{"id":"zai/glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7"},"zai/glm-4.5-flash":{"id":"zai/glm-4.5-flash","name":"GLM-4.5-Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":98304},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5-flash"},"zai/glm-5.2":{"id":"zai/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"zai/glm-5.1":{"id":"zai/glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.1"},"zai/glm-4.7-flashx":{"id":"zai/glm-4.7-flashx","name":"GLM-4.7-FlashX","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.07,"output":0.4,"cache_read":0.01,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7-flashx"},"zai/glm-5-turbo":{"id":"zai/glm-5-turbo","name":"GLM-5-Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24,"cache_write":0},"canonical_model_id":"zhipuai/glm-5-turbo"},"zai/glm-4.5-air":{"id":"zai/glm-4.5-air","name":"GLM-4.5-Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.2,"output":1.1,"cache_read":0.03,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5-air"},"zai/glm-5.3":{"id":"zai/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"anthropic/claude-haiku-4-5":{"id":"anthropic/claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-opus-4-5":{"id":"anthropic/claude-opus-4-5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-sonnet-4-5":{"id":"anthropic/claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-fable-5-1":{"id":"anthropic/claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-opus-4-5-20251101":{"id":"anthropic/claude-opus-4-5-20251101","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-01","last_updated":"2025-11-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-opus-4-8":{"id":"anthropic/claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-sonnet-4-5-20250929":{"id":"anthropic/claude-sonnet-4-5-20250929","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-opus-4-6":{"id":"anthropic/claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-haiku-4-5-20251001":{"id":"anthropic/claude-haiku-4-5-20251001","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"anthropic/claude-sonnet-4-6":{"id":"anthropic/claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-4-7":{"id":"anthropic/claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"deepseek/deepseek-flash":{"id":"deepseek/deepseek-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"reasoning":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.66,"output":1.98,"reasoning":1.98,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"google/gemini-flash-latest":{"id":"google/gemini-flash-latest","name":"Gemini Flash Latest","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"input_audio":0.75},"canonical_model_id":"google/gemini-flash-latest"},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemini-flash-lite-latest":{"id":"google/gemini-flash-lite-latest","name":"Gemini Flash-Lite Latest","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-flash-lite-latest"},"google/gemini-embedding-2":{"id":"google/gemini-embedding-2","name":"Gemini Embedding 2","description":"Multimodal embedding model mapping text, images, video, audio, and PDFs into a unified embedding space","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-11","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1},"cost":{"input":0.2,"output":0},"canonical_model_id":"google/gemini-embedding-2"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"input_audio":0.75},"canonical_model_id":"google/gemini-3.6-flash"},"google/gemma-4-26b-a4b-it":{"id":"google/gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"input_audio":0.75},"canonical_model_id":"google/gemini-3.7-flash"},"google/gemini-3.1-pro-preview-customtools":{"id":"google/gemini-3.1-pro-preview-customtools","name":"Gemini 3.1 Pro Preview Custom Tools","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview-customtools"},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"input_audio":1},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"input_audio":0.75},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-embedding-001":{"id":"google/gemini-embedding-001","name":"Gemini Embedding 001","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-05","release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":2048,"output":1},"cost":{"input":0.15,"output":0},"canonical_model_id":"google/gemini-embedding-001"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite"},"xai/grok-4.7":{"id":"xai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"xai/grok-4.3":{"id":"xai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.3"},"xai/grok-4.20-0309-reasoning":{"id":"xai/grok-4.20-0309-reasoning","name":"Grok 4.20 (Reasoning)","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-reasoning"},"xai/grok-4.5":{"id":"xai/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.3,"tiers":[{"input":4,"output":12,"cache_read":0.6,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":0.6}},"canonical_model_id":"xai/grok-4.5"},"xai/grok-4.20-0309-non-reasoning":{"id":"xai/grok-4.20-0309-non-reasoning","name":"Grok 4.20 (Non-Reasoning)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-non-reasoning"},"xai/grok-build-0.1":{"id":"xai/grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.2,"tiers":[{"input":2,"output":4,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2,"output":4,"cache_read":0.4}},"canonical_model_id":"xai/grok-build-0.1"},"xai/grok-4.6":{"id":"xai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"minimax/MiniMax-M3":{"id":"minimax/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"tiers":[{"input":0.6,"output":2.4,"cache_read":0.12,"tier":{"type":"context","size":512000}}],"context_over_200k":{"input":0.6,"output":2.4,"cache_read":0.12}},"canonical_model_id":"minimax/MiniMax-M3"},"minimax/MiniMax-M2.7":{"id":"minimax/MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/MiniMax-M2.7-highspeed":{"id":"minimax/MiniMax-M2.7-highspeed","name":"MiniMax-M2.7-highspeed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"mistral/mistral-large-latest":{"id":"mistral/mistral-large-latest","name":"Mistral Large (latest)","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2024-11-01","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"mistral/mistral-large-latest"},"mistral/mistral-small-latest":{"id":"mistral/mistral-small-latest","name":"Mistral Small (latest)","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"mistral/mistral-small-latest"},"mistral/zai-glm-5-2":{"id":"mistral/zai-glm-5-2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"beta","cost":{"input":1.4,"output":4.4,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.2"},"mistral/mistral-embed":{"id":"mistral/mistral-embed","name":"Mistral Embed","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"mistral-embed","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2023-12-11","last_updated":"2023-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8000,"output":3072},"cost":{"input":0.1,"output":0},"canonical_model_id":"mistral/mistral-embed"},"mistral/mistral-small-2603":{"id":"mistral/mistral-small-2603","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"mistral/mistral-small-2603"},"mistral/mistral-large-2512":{"id":"mistral/mistral-large-2512","name":"Mistral Large 3","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"mistral/mistral-large-2512"},"mistral/voxtral-small-latest":{"id":"mistral/voxtral-small-latest","name":"Voxtral Small (latest)","description":"Instruct model with native audio input for speech understanding and tool use","family":"voxtral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":32000},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"mistral/voxtral-small-latest"},"mistral/zai-glm-5-3":{"id":"mistral/zai-glm-5-3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.3"},"mistral/mistral-medium-2604":{"id":"mistral/mistral-medium-2604","name":"Mistral Medium 3.5","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.5,"output":7.5},"canonical_model_id":"mistral/mistral-medium-2604"},"mistral/mistral-medium-latest":{"id":"mistral/mistral-medium-latest","name":"Mistral Medium (latest)","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.5,"output":7.5},"canonical_model_id":"mistral/mistral-medium-latest"},"moonshot/kimi-k3":{"id":"moonshot/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshot/kimi-k2.7-code-highspeed":{"id":"moonshot/kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code Highspeed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"moonshot/kimi-k2.6":{"id":"moonshot/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshot/kimi-k2.7-code":{"id":"moonshot/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"}}},"inception":{"id":"inception","env":["INCEPTION_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.inceptionlabs.ai/v1/","name":"Inception","doc":"https://docs.inceptionlabs.ai/get-started/models","models":{"mercury-edit-2":{"id":"mercury-edit-2","name":"Mercury Edit 2","description":"Code editing dLLM for autocomplete (FIM) and next-edit suggestions","family":"mercury","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-03-30","last_updated":"2026-03-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":8192},"cost":{"input":0.25,"output":0.75,"cache_read":0.025}},"mercury-2.5":{"id":"mercury-2.5","name":"Mercury 2.5","description":"Mercury 2.5 is the fastest reasoning LLM, and the latest diffusion LLM (dLLM) from Inception","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-11-01","release_date":"2026-09-08","last_updated":"2026-09-10","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":260000,"output":65536},"cost":{"input":0.04,"output":0.15,"cache_read":0.004}},"mercury-2":{"id":"mercury-2","name":"Mercury 2","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-02-24","last_updated":"2026-02-24","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":50000},"cost":{"input":0.25,"output":0.75,"cache_read":0.025}}}},"modelis":{"id":"modelis","env":["MODELIS_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://modelishub.com/v1","name":"Modelis","doc":"https://modelishub.com/pricing","models":{"gemini-2.5-pro":{"id":"gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10},"canonical_model_id":"google/gemini-2.5-pro"},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","max"]},{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5},"canonical_model_id":"google/gemini-2.5-flash"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50},"canonical_model_id":"anthropic/claude-fable-5"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]},{"type":"toggle"}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-4-8"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.435,"output":0.87},"canonical_model_id":"deepseek/deepseek-v4-pro"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.0983,"output":0.1966},"canonical_model_id":"deepseek/deepseek-v4-flash"},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":3,"output":9},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen3.7-plus":{"id":"qwen/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.768,"output":3.072},"canonical_model_id":"alibaba/qwen3.7-plus"}}},"opencode":{"id":"opencode","env":["OPENCODE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://opencode.ai/inference/openai/v1","name":"OpenCode","doc":"https://opencode.ai/v2/docs/console/models/","models":{"ling-3.0-flash-fin-free":{"id":"ling-3.0-flash-fin-free","name":"Ling 3.0 Flash Fin Free","description":"Finance-enhanced model for financial research, multi-step investment workflows, and long-horizon planning and execution","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-27","last_updated":"2026-09-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"inclusionai/ling-3.0-flash-fin"},"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"fledge-alpha-free":{"id":"fledge-alpha-free","name":"Fledge Alpha Free","description":"Free-tier preview reasoning model with text and image input and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-10-01","last_updated":"2026-10-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0}},"qwen3.6-plus-free":{"id":"qwen3.6-plus-free","name":"Qwen3.6 Plus Free","description":"Legacy model retained for compatibility with older integrations","family":"qwen-free","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25}},"gpt-5.4-pro":{"id":"gpt-5.4-pro","name":"GPT-5.4 Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":30,"output":180,"cache_read":30}},"mimo-v2-pro-free":{"id":"mimo-v2-pro-free","name":"MiMo V2 Pro Free","description":"Legacy model retained for compatibility with older integrations","family":"mimo-pro-free","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":64000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"muse-spark-1.2-contributor-free":{"id":"muse-spark-1.2-contributor-free","name":"Muse Spark 1.2 Free","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse-free","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"status":"deprecated","provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"meta/muse-spark-1.2"},"ling-3.1-flash-free":{"id":"ling-3.1-flash-free","name":"Ling 3.1 Flash Free","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"inclusionai/ling-3.1-flash"},"muse-spark-1.3":{"id":"muse-spark-1.3","name":"Muse Spark 1.3","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.3"},"glm-5-free":{"id":"glm-5-free","name":"GLM-5 Free","description":"Legacy model retained for compatibility with older integrations","family":"glm-free","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-02-11","last_updated":"2026-02-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"trinity-large-preview-free":{"id":"trinity-large-preview-free","name":"Trinity Large Preview","description":"Legacy model retained for compatibility with older integrations","family":"trinity","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-01-27","last_updated":"2026-01-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0},"canonical_model_id":"arcee-ai/trinity-large-preview"},"gpt-5.5-pro":{"id":"gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":30,"output":180,"cache_read":30}},"grok-4.7":{"id":"grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"longcat-2.5-preview-free":{"id":"longcat-2.5-preview-free","name":"LongCat 2.5 Preview Free","description":"Meituan's multimodal reasoning model for coding and agent tasks, with image understanding and a 1M-token context window","family":"longcat","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-25","last_updated":"2026-09-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"meituan/longcat-2.5-preview"},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.2,"output":1.25,"cache_read":0.02}},"gpt-5.2-codex":{"id":"gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-01-14","last_updated":"2026-01-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"ling-3.0-tiny-free":{"id":"ling-3.0-tiny-free","name":"Ling-3.0-tiny Free","description":"Compact MoE model for responsive agents, instruction following, and multi-turn conversations","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-06","last_updated":"2026-08-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0}},"gpt-5.1-codex":{"id":"gpt-5.1-codex","name":"GPT-5.1 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.07,"output":8.5,"cache_read":0.107}},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"kimi-k2.5-free":{"id":"kimi-k2.5-free","name":"Kimi K2.5 Free","description":"Legacy model retained for compatibility with older integrations","family":"kimi-free","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-10","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"glm-4.7-free":{"id":"glm-4.7-free","name":"GLM-4.7 Free","description":"Legacy model retained for compatibility with older integrations","family":"glm-free","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"glm-4.6":{"id":"glm-4.6","name":"GLM-4.6","description":"Legacy model retained for compatibility with older integrations","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.6,"output":2.2,"cache_read":0.1}},"laguna-s-2.1-free":{"id":"laguna-s-2.1-free","name":"Laguna S 2.1 Free","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"poolside/laguna-s-2.1"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"gpt-5-codex":{"id":"gpt-5-codex","name":"GPT-5 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.07,"output":8.5,"cache_read":0.107}},"qwen3-coder":{"id":"qwen3-coder","name":"Qwen3 Coder","description":"Legacy model retained for compatibility with older integrations","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.45,"output":1.8}},"mistral-large-4":{"id":"mistral-large-4","name":"Mistral Large 4","description":"Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":262144},"provider":{"npm":"@ai-sdk/mistral","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.68,"output":2.09,"cache_read":0.07},"canonical_model_id":"mistral/mistral-large-4"},"minimax-m3-free":{"id":"minimax-m3-free","name":"MiniMax-M3 Free","description":"Legacy model retained for compatibility with older integrations","family":"minimax-m3-free","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-31","last_updated":"2026-05-31","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"qwen3.5-plus":{"id":"qwen3.5-plus","name":"Qwen3.5 Plus","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"qwen3.5","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25}},"claude-opus-4-5":{"id":"claude-opus-4-5","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"glm-5":{"id":"glm-5","name":"GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-02-11","last_updated":"2026-02-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1,"output":3.2,"cache_read":0.2}},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-24","last_updated":"2026-02-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"minimax-m2.5":{"id":"minimax-m2.5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.06}},"exo-free":{"id":"exo-free","name":"Exo Free","description":"Free-tier preview reasoning model with text and image input and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"temperature":false,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0}},"gpt-5-nano":{"id":"gpt-5-nano","name":"GPT-5 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.05,"output":0.4,"cache_read":0.005}},"deepseek-v4-flash-vision-exp":{"id":"deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-10","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.95,"output":4,"cache_read":0.16}},"claude-sonnet-4-5":{"id":"claude-sonnet-4-5","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}}},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"claude-fable-5-1":{"id":"claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"gemini-3.6-flash":{"id":"gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://opencode.ai/inference/google/v1beta"},"cost":{"input":1.5,"output":7.5,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.6-flash"},"kimi-k2-thinking":{"id":"kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Legacy model retained for compatibility with older integrations","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-10","release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.4,"output":2.5,"cache_read":0.4}},"minimax-m2.5-free":{"id":"minimax-m2.5-free","name":"MiniMax-M2.5 Free","description":"Legacy model retained for compatibility with older integrations","family":"minimax-free","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"cat-jam-free":{"id":"cat-jam-free","name":"Cat Jam Free","description":"A text-only reasoning model for coding and agentic workflows, with tool calling and structured JSON outputs.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"gpt-5.3-codex-spark":{"id":"gpt-5.3-codex-spark","name":"GPT-5.3 Codex Spark","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex-spark","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"gemini-3.5-flash-lite":{"id":"gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://opencode.ai/inference/google/v1beta"},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"claude-opus-4-1":{"id":"claude-opus-4-1","name":"Claude Opus 4.1","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75}},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"grok-4.5":{"id":"grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":2,"output":6,"cache_read":0.3,"tiers":[{"input":4,"output":12,"cache_read":0.6,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":0.6}},"canonical_model_id":"xai/grok-4.5"},"ring-2.6-1t-free":{"id":"ring-2.6-1t-free","name":"Ring 2.6 1T Free","description":"Legacy model retained for compatibility with older integrations","family":"ring-1t-free","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-06","release_date":"2026-05-08","last_updated":"2026-05-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":66000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0}},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-10","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.6,"output":3,"cache_read":0.08}},"longcat-2.0-free":{"id":"longcat-2.0-free","name":"LongCat-2.0 Free","description":"Meituan LongCat-2.0, a reasoning model with tool calling and a 1M-token context window","family":"longcat","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"meituan/longcat-2.0"},"gpt-5.1":{"id":"gpt-5.1","name":"GPT-5.1","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.07,"output":8.5,"cache_read":0.107}},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"claude-3-5-haiku":{"id":"claude-3-5-haiku","name":"Claude Haiku 3.5","description":"Legacy model retained for compatibility with older integrations","family":"claude-haiku","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07-31","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":0.8,"output":4,"cache_read":0.08,"cache_write":1}},"hy3-preview-free":{"id":"hy3-preview-free","name":"Hy3 preview Free","description":"Legacy model retained for compatibility with older integrations","family":"hy3-free","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"gemini-3-flash":{"id":"gemini-3-flash","name":"Gemini 3 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://opencode.ai/inference/google/v1beta"},"cost":{"input":0.5,"output":3,"cache_read":0.05}},"minimax-m2.7":{"id":"minimax-m2.7","name":"MiniMax-M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.06}},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://opencode.ai/inference/google/v1beta"},"cost":{"input":1.5,"output":9,"cache_read":0.15,"input_audio":1.5}},"space-bunny-free":{"id":"space-bunny-free","name":"Space Bunny Free","description":"Anonymous preview reasoning model for coding, agentic tasks, tool use, and multimodal input","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":524288,"output":524288},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"ll-alpha-free":{"id":"ll-alpha-free","name":"LL Alpha Free","description":"Best in class local model","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-06","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"nemotron-3-super-free":{"id":"nemotron-3-super-free","name":"Nemotron 3 Super Free","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron-free","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2026-02","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":128000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"minimax-m2.1-free":{"id":"minimax-m2.1-free","name":"MiniMax-M2.1 Free","description":"Legacy model retained for compatibility with older integrations","family":"minimax-free","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"mimo-v2.6-flash-free":{"id":"mimo-v2.6-flash-free","name":"MiMo-V2.6-Flash Free","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"gemini-3-pro":{"id":"gemini-3-pro","name":"Gemini 3 Pro","description":"Legacy model retained for compatibility with older integrations","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","provider":{"npm":"@ai-sdk/google","api":"https://opencode.ai/inference/google/v1beta"},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}}},"nemotron-3-ultra-free":{"id":"nemotron-3-ultra-free","name":"Nemotron 3 Ultra Free","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron-free","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2026-02","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"claude-sonnet-4":{"id":"claude-sonnet-4","name":"Claude Sonnet 4","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}}},"muse-spark-1.2":{"id":"muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.75,"output":4.5,"cache_read":0.075}},"glm-4.7":{"id":"glm-4.7","name":"GLM-4.7","description":"Legacy model retained for compatibility with older integrations","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.6,"output":2.2,"cache_read":0.1}},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"output":128000},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":0.15,"output":0.47,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"gpt-5.1-codex-max":{"id":"gpt-5.1-codex-max","name":"GPT-5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.25,"output":10,"cache_read":0.125}},"mimo-v2.5-free":{"id":"mimo-v2.5-free","name":"MiMo V2.5 Free","description":"MiMo omni model for text, image, video, audio, and agents","family":"mimo-v2.5-free","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"grok-code":{"id":"grok-code","name":"Grok Code Fast 1","description":"Legacy model retained for compatibility with older integrations","family":"grok","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-08-20","last_updated":"2025-08-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"gpt-5.2":{"id":"gpt-5.2","name":"GPT-5.2","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"ling-2.6-flash-free":{"id":"ling-2.6-flash-free","name":"Ling 2.6 Flash Free","description":"Legacy model retained for compatibility with older integrations","family":"ling-flash-free","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262100,"output":32800},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0}},"glm-5.3-flash-free":{"id":"glm-5.3-flash-free","name":"GLM-5.3-Flash Free","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"deepseek-v4-flash-free":{"id":"deepseek-v4-flash-free","name":"DeepSeek V4 Flash Free","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"hy3-free":{"id":"hy3-free","name":"Hy3 Free","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"hy3-free","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":190000,"input":192000,"output":64000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"tencent/hy3"},"nemotron-3.5-lightning-free":{"id":"nemotron-3.5-lightning-free","name":"Nemotron 3.5 Lightning Free","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron-free","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"gemini-3.7-flash":{"id":"gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://opencode.ai/inference/google/v1beta"},"cost":{"input":1.5,"output":7.5,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.7-flash"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"nemotron-3.5-super-vl-free":{"id":"nemotron-3.5-super-vl-free","name":"Nemotron 3.5 Super VL Free","description":"NVIDIA vision-language reasoning model for text, image, and video understanding and agentic tool use","family":"nemotron-free","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"kimi-k2":{"id":"kimi-k2","name":"Kimi K2","description":"Legacy model retained for compatibility with older integrations","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.4,"output":2.5,"cache_read":0.4}},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.4,"output":4.4,"cache_read":0.26}},"mimo-v2-omni-free":{"id":"mimo-v2-omni-free","name":"MiMo V2 Omni Free","description":"Legacy model retained for compatibility with older integrations","family":"mimo-omni-free","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":64000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"grok-build-0.1":{"id":"grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1,"output":2,"cache_read":0.2},"canonical_model_id":"xai/grok-build-0.1"},"deepseek-v4.1-flash-free":{"id":"deepseek-v4.1-flash-free","name":"DeepSeek V4.1 Flash Free","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"beam-free":{"id":"beam-free","name":"Beam Free","description":"Sparse mixture-of-experts reasoning model with 23B active parameters for coding and agentic workflows","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-06-30","release_date":"2026-10-05","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"reflection/beam-1.0-501b-a23b"},"ling-3.0-flash-free":{"id":"ling-3.0-flash-free","name":"Ling-3.0-flash Free","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-23","last_updated":"2026-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"gemini-3.8-flash":{"id":"gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://opencode.ai/inference/google/v1beta"},"cost":{"input":1.5,"output":7.5,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.8-flash"},"north-mini-code-free":{"id":"north-mini-code-free","name":"North Mini Code Free","description":"Cohere coding model for practical software engineering and agentic edits","family":"north-free","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-09-23","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0},"canonical_model_id":"cohere/north-mini-code-1-0"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.74,"output":3.84,"cache_read":0.145},"canonical_model_id":"deepseek/deepseek-v4-pro"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-02-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75}},"big-pickle":{"id":"big-pickle","name":"Big Pickle","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"big-pickle","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-10-17","last_updated":"2025-10-17","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":160000,"output":32000},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"qwen3.6-plus":{"id":"qwen3.6-plus","name":"Qwen3.6 Plus","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625}},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":2.5,"output":15,"cache_read":0.25,"cache_write":3.125,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"cache_write":6.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5,"cache_write":6.25}},"canonical_model_id":"openai/gpt-5.6-terra"},"mimo-v2-flash-free":{"id":"mimo-v2-flash-free","name":"MiMo V2 Flash Free","description":"Legacy model retained for compatibility with older integrations","family":"mimo-flash-free","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"gpt-5.1-codex-mini":{"id":"gpt-5.1-codex-mini","name":"GPT-5.1 Codex Mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.25,"output":2,"cache_read":0.025}},"step-5-preview-free":{"id":"step-5-preview-free","name":"Step 5 Preview Free","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":65536},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"stepfun/step-5-preview"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"gpt-5":{"id":"gpt-5","name":"GPT-5","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.07,"output":8.5,"cache_read":0.107}},"grok-4.6":{"id":"grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"gemini-3.1-pro":{"id":"gemini-3.1-pro","name":"Gemini 3.1 Pro Preview","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://opencode.ai/inference/google/v1beta"},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}}},"minimax-m2.1":{"id":"minimax-m2.1","name":"MiniMax-M2.1","description":"Legacy model retained for compatibility with older integrations","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.1}},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"gemini-4-argon":{"id":"gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://opencode.ai/inference/google/v1beta"},"cost":{"input":2,"output":10,"cache_read":0.1,"input_audio":2},"canonical_model_id":"google/gemini-4-argon"},"x-preview-f-free":{"id":"x-preview-f-free","name":"Ox Alpha Free (Unlimited)","description":"Stealth reasoning model for coding, agentic tasks, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-08-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"muse-spark-1.3-contributor-free":{"id":"muse-spark-1.3-contributor-free","name":"Muse Spark 1.3 Free","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for coding and agentic workflows.","family":"muse-free","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"}}},"kenari":{"id":"kenari","env":["KENARI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://kenari.id/v1","name":"Kenari","doc":"https://kenari.id/docs","models":{"gpt-5-4-mini":{"id":"gpt-5-4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"openai/gpt-5.4-mini"},"gpt-5-6-luna":{"id":"gpt-5-6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"openai/gpt-5.6-luna"},"gemma-4-31b-it":{"id":"gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemma-4-31b-it"},"grok-4-5":{"id":"grok-4-5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":0,"output":0},"canonical_model_id":"xai/grok-4.5"},"gemini-2-5-flash":{"id":"gemini-2-5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemini-2.5-flash"},"nemotron-3-nano-30b-a3b":{"id":"nemotron-3-nano-30b-a3b","name":"Nemotron 3 Nano 30B A3B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"glm-5-3-flash":{"id":"glm-5-3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"kimi-k2-7-code":{"id":"kimi-k2-7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"gpt-5-6-terra":{"id":"gpt-5-6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"openai/gpt-5.6-terra"},"gemini-2-5-flash-lite":{"id":"gemini-2-5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemini-2.5-flash-lite"},"mimo-v2-5":{"id":"mimo-v2-5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"xiaomi/mimo-v2.5"},"grok-build-0-1":{"id":"grok-build-0-1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0,"output":0},"canonical_model_id":"xai/grok-build-0.1"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"moonshotai/kimi-k3"},"glm-4-7-flash:free":{"id":"glm-4-7-flash:free","name":"GLM-4.7-Flash (Free)","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-4.7-flash"},"gpt-image-2":{"id":"gpt-image-2","name":"GPT-Image-2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":272000,"output":16384},"cost":{"input":0,"output":0},"canonical_model_id":"openai/gpt-image-2"},"qwen3-8-max":{"id":"qwen3-8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3.8-max"},"minimax-m2-7-highspeed":{"id":"minimax-m2-7-highspeed","name":"MiniMax-M2.7-highspeed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"grok-imagine-image":{"id":"grok-imagine-image","name":"Grok Imagine Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"grok","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-01-28","last_updated":"2026-01-28","modalities":{"input":["text","image","pdf"],"output":["image","pdf"]},"open_weights":false,"limit":{"context":16000,"output":0},"cost":{"input":0,"output":0},"canonical_model_id":"xai/grok-imagine-image"},"mimo-v2-5-pro":{"id":"mimo-v2-5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"nemotron-3-super-120b-a12b":{"id":"nemotron-3-super-120b-a12b","name":"Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium"]}],"tool_call":true,"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"gemini-3-7-flash":{"id":"gemini-3-7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemini-3.7-flash"},"step-3-7-flash:free":{"id":"step-3-7-flash:free","name":"Step 3.7 Flash (Free)","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0,"output":0},"canonical_model_id":"stepfun/step-3.7-flash"},"kimi-k2-6:free":{"id":"kimi-k2-6:free","name":"Kimi K2.6 (Free)","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"moonshotai/kimi-k2.6"},"gpt-5-6-sol":{"id":"gpt-5-6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"openai/gpt-5.6-sol"},"nemotron-3-ultra-550b-a55b":{"id":"nemotron-3-ultra-550b-a55b","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nano-banana-pro":{"id":"nano-banana-pro","name":"Nano Banana Pro","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemini-3-pro-image"},"gemini-3-1-pro":{"id":"gemini-3-1-pro","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemini-3.1-pro-preview"},"glm-5-2":{"id":"glm-5-2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-5.2"},"nano-banana-2":{"id":"nano-banana-2","name":"Nano Banana 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","video","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemini-3.1-flash-image"},"mistral-large:free":{"id":"mistral-large:free","name":"Mistral Large (Free)","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2024-11-01","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"mistral/mistral-large-latest"},"mimo-v2-5:free":{"id":"mimo-v2-5:free","name":"MiMo-V2.5 (Free)","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"xiaomi/mimo-v2.5"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"anthropic/claude-opus-5"},"gpt-oss-20b":{"id":"gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0,"output":0}},"minimax-m2-7":{"id":"minimax-m2-7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"minimax/MiniMax-M2.7"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"anthropic/claude-fable-5"},"hy3:free":{"id":"hy3:free","name":"Hy3 (Free)","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":192000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"tencent/hy3"},"kimi-k2-6":{"id":"kimi-k2-6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"moonshotai/kimi-k2.6"},"mistral-medium-3-5:free":{"id":"mistral-medium-3-5:free","name":"Mistral Medium 3.5 (Free)","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"mistral/mistral-medium-2604"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0,"output":0},"canonical_model_id":"minimax/MiniMax-M3"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"anthropic/claude-opus-4-8"},"glm-5-3":{"id":"glm-5-3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-5.3"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"anthropic/claude-sonnet-5"},"deepseek-v4-1-flash":{"id":"deepseek-v4-1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"qwen3-7-plus":{"id":"qwen3-7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3.7-plus"},"nano-banana-2-lite":{"id":"nano-banana-2-lite","name":"Nano Banana 2 Lite","description":"Fastest, most cost-efficient Gemini image model for high-volume 1K generation and editing","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":4096},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemini-3.1-flash-lite-image"},"gemini-3-1-flash-lite":{"id":"gemini-3-1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemini-3.1-flash-lite"},"hy3":{"id":"hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":192000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"tencent/hy3"},"glm-5-1":{"id":"glm-5-1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-5.1"},"nemotron-3-super-120b-a12b:free":{"id":"nemotron-3-super-120b-a12b:free","name":"Nemotron 3 Super 120B A12B (Free)","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium"]}],"tool_call":true,"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"gpt-5-5":{"id":"gpt-5-5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"openai/gpt-5.5"},"grok-imagine-image-2-0":{"id":"grok-imagine-image-2-0","name":"Grok Imagine Image 2.0","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"grok","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-08-07","last_updated":"2026-08-07","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":8000,"output":0},"cost":{"input":0,"output":0},"canonical_model_id":"xai/grok-imagine-image-2.0"},"deepseek-v4-flash:free":{"id":"deepseek-v4-flash:free","name":"DeepSeek V4 Flash (Free)","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-v4-flash"},"grok-4-6":{"id":"grok-4-6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":0,"output":0},"canonical_model_id":"xai/grok-4.6"},"whisper-large-v3-turbo":{"id":"whisper-large-v3-turbo","name":"Whisper Large v3 Turbo","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"whisper","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2024-10-01","last_updated":"2024-10-01","modalities":{"input":["audio"],"output":["text"]},"open_weights":true,"limit":{"context":448,"output":448},"cost":{"input":0,"output":0},"canonical_model_id":"openai/whisper-large-v3-turbo"},"gemini-3-6-flash":{"id":"gemini-3-6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemini-3.6-flash"},"gemini-3-1-flash-tts":{"id":"gemini-3-1-flash-tts","name":"Gemini 3.1 Flash TTS Preview","description":"Low-latency speech generation with steerable prompts and expressive audio tags","family":"gemini-flash","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-15","last_updated":"2026-04-15","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":8192,"output":16384},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemini-3.1-flash-tts-preview"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-v4-pro"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0,"output":0},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"kimi-k2-7-code:free":{"id":"kimi-k2-7-code:free","name":"Kimi K2.7 Code (Free)","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"gemini-3-5-flash":{"id":"gemini-3-5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemini-3.5-flash"},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"openai/gpt-oss-120b"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"anthropic/claude-opus-4-7"},"step-3-7-flash":{"id":"step-3-7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0,"output":0},"canonical_model_id":"stepfun/step-3.7-flash"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-v4-flash"}}},"kimi-code-plan-global":{"id":"kimi-code-plan-global","env":["KIMI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.kimi.ai/coding/v1","name":"Kimi For Coding (kimi.ai)","doc":"https://www.kimi.ai/code/docs/en/kimi-code/models.html","models":{"kimi-for-coding-highspeed":{"id":"kimi-for-coding-highspeed","name":"Kimi For Coding HighSpeed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"kimi-for-coding":{"id":"kimi-for-coding","name":"kimi-for-coding","description":"Kimi coding model with more efficient thinking and up to 1M context, available through Kimi Code","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.8-preview"},"k3-256k":{"id":"k3-256k","name":"Kimi K3-256K","description":"256K-context version of Kimi K3, reducing token consumption for shorter coding sessions","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k3"},"k3":{"id":"k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k3"}}},"trustedrouter":{"id":"trustedrouter","env":["TRUSTEDROUTER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.trustedrouter.com/v1","name":"TrustedRouter","doc":"https://trustedrouter.com/docs","models":{"trustedrouter/cheap":{"id":"trustedrouter/cheap","name":"Cheap","description":"TrustedRouter low-cost routing alias that prefers inexpensive healthy model endpoints.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-01","last_updated":"2026-06-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072}},"trustedrouter/synth-code":{"id":"trustedrouter/synth-code","name":"Synth Code","description":"TrustedRouter code synthesis orchestration alias that combines multiple model responses into one answer.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-20","last_updated":"2026-06-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072}},"trustedrouter/e2e":{"id":"trustedrouter/e2e","name":"End-to-End Encrypted","description":"TrustedRouter privacy routing alias for end-to-end encrypted provider routes where available.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072}},"trustedrouter/zdr":{"id":"trustedrouter/zdr","name":"Zero Data Retention","description":"TrustedRouter privacy routing alias that prefers zero data retention model endpoints.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072}},"trustedrouter/fast":{"id":"trustedrouter/fast","name":"Fast","description":"TrustedRouter speed routing alias that prefers low-latency healthy model endpoints.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072}},"trustedrouter/synth":{"id":"trustedrouter/synth","name":"Synth","description":"TrustedRouter synthesis orchestration alias that combines multiple model responses into one answer.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-20","last_updated":"2026-06-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072}},"trustedrouter/auto":{"id":"trustedrouter/auto","name":"Auto","description":"TrustedRouter automatic routing alias that chooses a healthy supported model endpoint for the request.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-01","last_updated":"2026-06-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072}}}},"wafer.ai":{"id":"wafer.ai","env":["WAFER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://pass.wafer.ai/v1","name":"Wafer","doc":"https://docs.wafer.ai/wafer-pass","models":{"Kimi-K2.6":{"id":"Kimi-K2.6","name":"Kimi K2.6","description":"Kimi K2.6 sparse MoE model with a 262K context window. Available serverless and not included in standard Wafer Pass. Non-ZDR only: requests with `Wafer-ZDR: required` are rejected.","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":1.14,"output":4.8,"cache_read":0.19,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.6"},"MiniMax-M3":{"id":"MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.33,"output":1.32,"cache_read":0.07,"cache_write":0,"tiers":[{"input":0.66,"output":2.64,"cache_read":0.13,"cache_write":0,"tier":{"type":"context","size":512000}}],"context_over_200k":{"input":0.66,"output":2.64,"cache_read":0.13,"cache_write":0}},"canonical_model_id":"minimax/MiniMax-M3"},"GLM-5.1":{"id":"GLM-5.1","name":"GLM-5.1","description":"General Language Model 5.1 — high-quality bilingual (EN/ZH) generation with strong coding and reasoning capabilities.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-07","last_updated":"2026-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.1,"cache_write":0}},"GLM-5.2":{"id":"GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.2,"output":4.1,"cache_read":0.2,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"glm5.2-fast":{"id":"glm5.2-fast","name":"GLM5.2-Fast","description":"The same model served for high TPS.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":10.25,"cache_read":0.5,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"}}},"zhipuai":{"id":"zhipuai","env":["ZHIPU_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://open.bigmodel.cn/api/paas/v4","name":"Zhipu AI","doc":"https://docs.z.ai/guides/overview/pricing","models":{"glm-5v-turbo":{"id":"glm-5v-turbo","name":"GLM-5V-Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":5,"output":22,"cache_read":1.2,"cache_write":0}},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"glm-5":{"id":"glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-11","last_updated":"2026-02-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2,"cache_write":0}},"glm-5.3-flashx":{"id":"glm-5.3-flashx","name":"GLM-5.3-FlashX","description":"High-speed GLM-5.3-Flash serving option for coding and agent workflows","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-18","last_updated":"2026-09-18","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.37,"output":1.25,"cache_read":0.075,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0}},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-27","last_updated":"2026-03-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0}},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"glm-4.5-air":{"id":"glm-4.5-air","name":"GLM-4.5-Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.2,"output":1.1,"cache_read":0.03,"cache_write":0}},"glm-4.7-flashx":{"id":"glm-4.7-flashx","name":"GLM-4.7-FlashX","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.07,"output":0.4,"cache_read":0.01,"cache_write":0}},"glm-4.5-flash":{"id":"glm-4.5-flash","name":"GLM-4.5-Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"glm-4.7":{"id":"glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0}},"glm-4.7-flash":{"id":"glm-4.7-flash","name":"GLM-4.7-Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"glm-4.5v":{"id":"glm-4.5v","name":"GLM-4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":16384},"cost":{"input":0.6,"output":1.8}},"glm-4.6v-flash":{"id":"glm-4.6v-flash","name":"GLM-4.6V-Flash","description":"Lightweight GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.6v-flash"},"glm-4.6":{"id":"glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0}},"glm-4.5":{"id":"glm-4.5","name":"GLM-4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0}},"glm-4.6v":{"id":"glm-4.6v","name":"GLM-4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.3,"output":0.9}}}},"lynkr":{"id":"lynkr","env":["LYNKR_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"http://127.0.0.1:8081/v1","name":"Lynkr","doc":"https://github.com/Fast-Editor/Lynkr","models":{"lynkr-auto":{"id":"lynkr-auto","name":"Lynkr Auto (complexity routing)","description":"Virtual model: Lynkr scores each request on complexity and routes it to the tier model the user configured (local Ollama/llama.cpp for simple requests, configured cloud providers for complex ones).","family":"auto","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-12-03","last_updated":"2026-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0,"output":0}}}},"meganova":{"id":"meganova","env":["MEGANOVA_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.meganova.ai/v1","name":"Meganova","doc":"https://docs.meganova.ai","models":{"meta-llama/Llama-3.3-70B-Instruct":{"id":"meta-llama/Llama-3.3-70B-Instruct","name":"Llama 3.3 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.1,"output":0.3}},"XiaomiMiMo/MiMo-V2-Flash":{"id":"XiaomiMiMo/MiMo-V2-Flash","name":"MiMo V2 Flash","description":"MiMo flash model for fast multimodal assistance and agent workflows","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32000},"cost":{"input":0.1,"output":0.3}},"Qwen/Qwen3.5-Plus":{"id":"Qwen/Qwen3.5-Plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02","last_updated":"2026-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.4,"output":2.4,"reasoning":2.4}},"Qwen/Qwen3-235B-A22B-Instruct-2507":{"id":"Qwen/Qwen3-235B-A22B-Instruct-2507","name":"Qwen3 235B A22B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.09,"output":0.6}},"Qwen/Qwen2.5-VL-32B-Instruct":{"id":"Qwen/Qwen2.5-VL-32B-Instruct","name":"Qwen2.5 VL 32B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-03-24","last_updated":"2025-03-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":16384},"cost":{"input":0.2,"output":0.6}},"deepseek-ai/DeepSeek-V3.1":{"id":"deepseek-ai/DeepSeek-V3.1","name":"DeepSeek V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-25","last_updated":"2025-08-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":164000},"cost":{"input":0.27,"output":1}},"deepseek-ai/DeepSeek-V3.2":{"id":"deepseek-ai/DeepSeek-V3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-03","last_updated":"2025-12-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":164000},"cost":{"input":0.26,"output":0.38}},"deepseek-ai/DeepSeek-R1-0528":{"id":"deepseek-ai/DeepSeek-R1-0528","name":"DeepSeek R1 0528","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-07","release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":64000},"cost":{"input":0.5,"output":2.15}},"deepseek-ai/DeepSeek-V3-0324":{"id":"deepseek-ai/DeepSeek-V3-0324","name":"DeepSeek V3 0324","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-03-24","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":163840},"cost":{"input":0.25,"output":0.88}},"deepseek-ai/DeepSeek-V3.2-Exp":{"id":"deepseek-ai/DeepSeek-V3.2-Exp","name":"DeepSeek V3.2 Exp","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-10","last_updated":"2025-10-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":164000},"cost":{"input":0.27,"output":0.4}},"MiniMaxAI/MiniMax-M2.1":{"id":"MiniMaxAI/MiniMax-M2.1","name":"MiniMax M2.1","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":131072},"cost":{"input":0.28,"output":1.2}},"MiniMaxAI/MiniMax-M2.5":{"id":"MiniMaxAI/MiniMax-M2.5","name":"MiniMax M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2}},"mistralai/Mistral-Nemo-Instruct-2407":{"id":"mistralai/Mistral-Nemo-Instruct-2407","name":"Mistral Nemo Instruct 2407","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.02,"output":0.04}},"mistralai/Mistral-Small-3.2-24B-Instruct-2506":{"id":"mistralai/Mistral-Small-3.2-24B-Instruct-2506","name":"Mistral Small 3.2 24B Instruct","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0,"output":0}},"moonshotai/Kimi-K2.5":{"id":"moonshotai/Kimi-K2.5","name":"Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2026-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.45,"output":2.8}},"moonshotai/Kimi-K2-Thinking":{"id":"moonshotai/Kimi-K2-Thinking","name":"Kimi K2 Thinking","description":"Kimi reasoning model for long-horizon research, planning, and tool use","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":2.6}},"zai-org/GLM-4.7":{"id":"zai-org/GLM-4.7","name":"GLM-4.7","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.2,"output":0.8}},"zai-org/GLM-5":{"id":"zai-org/GLM-5","name":"GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-11","last_updated":"2026-02-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.8,"output":2.56}},"zai-org/GLM-4.6":{"id":"zai-org/GLM-4.6","name":"GLM-4.6","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.45,"output":1.9}}}},"ovhcloud":{"id":"ovhcloud","env":["OVHCLOUD_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://oai.endpoints.kepler.ai.cloud.ovh.net/v1","name":"OVHcloud AI Endpoints","doc":"https://www.ovhcloud.com/en/public-cloud/ai-endpoints/catalog//","models":{"qwen3.8-27b":{"id":"qwen3.8-27b","name":"Qwen3.8-27B","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.47,"output":3.19},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen3guard-gen-8b":{"id":"qwen3guard-gen-8b","name":"Qwen3Guard-Gen-8B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-01-22","last_updated":"2026-01-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"cost":{"input":0,"output":0}},"qwen3guard-gen-0.6b":{"id":"qwen3guard-gen-0.6b","name":"Qwen3Guard-Gen-0.6B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-01-22","last_updated":"2026-01-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"cost":{"input":0,"output":0}},"gpt-oss-20b":{"id":"gpt-oss-20b","name":"gpt-oss-20b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2025-08-28","last_updated":"2025-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.05,"output":0.18}},"qwen3.5-9b":{"id":"qwen3.5-9b","name":"Qwen3.5-9B","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.12,"output":0.18}},"meta-llama-3_3-70b-instruct":{"id":"meta-llama-3_3-70b-instruct","name":"Meta-Llama-3_3-70B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-01","last_updated":"2025-04-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.74,"output":0.74}},"qwen3.5-397b-a17b":{"id":"qwen3.5-397b-a17b","name":"Qwen3.5-397B-A17B","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-18","last_updated":"2026-05-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.71,"output":4.25}},"qwen2.5-vl-72b-instruct":{"id":"qwen2.5-vl-72b-instruct","name":"Qwen2.5-VL-72B-Instruct","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-03-31","last_updated":"2025-03-31","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":1.01,"output":1.01}},"qwen3.6-27b":{"id":"qwen3.6-27b","name":"Qwen3.6-27B","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.47,"output":3.19}},"mistral-small-3.2-24b-instruct-2506":{"id":"mistral-small-3.2-24b-instruct-2506","name":"Mistral-Small-3.2-24B-Instruct-2506","description":"Efficient Mistral model for fast chat, extraction, and production assistants","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-16","last_updated":"2025-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.1,"output":0.31}},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"gpt-oss-120b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2025-08-28","last_updated":"2025-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.09,"output":0.47}},"mistral-nemo-instruct-2407":{"id":"mistral-nemo-instruct-2407","name":"Mistral-Nemo-Instruct-2407","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-11-20","last_updated":"2024-11-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.14,"output":0.14}}}},"requesty":{"id":"requesty","env":["REQUESTY_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://router.requesty.ai/v1","name":"Requesty","doc":"https://requesty.ai/solution/llm-routing/models","models":{"ring-2.6-1t":{"id":"ring-2.6-1t","name":"ring-2.6-1t","description":"Inclusion AI ring-2.6-1t","family":"ring","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-05-08","last_updated":"2026-05-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.3,"output":2.5}},"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.75,"output":16.5,"cache_read":0.275},"canonical_model_id":"openai/gpt-5.4"},"nemotron-3-ultra-nvfp4":{"id":"nemotron-3-ultra-nvfp4","name":"nemotron-3-ultra-nvfp4","description":"Nemotron-3-Ultra-550B-A55B-NVFP4 is a frontier-scale large language model (LLM) trained by NVIDIA, designed to deliver strong agentic, reasoning, and conversational capabilities. It is optimized for the most demanding workloads, including complex multi-step agents, long-context analysis, and high-accuracy reasoning over code, math, and science. The model employs a hybrid Latent Mixture-of-Experts (LatentMoE) architecture, utilizing interleaved Mamba-2 and MoE layers, along with select Attention layers. Like the Super model, the Ultra model incorporates Multi-Token Prediction (MTP) layers for faster text generation and improved quality, and it is trained using an NVFP4 pre-training recipe to maximize compute efficiency. The model has 55B active parameters and 550B parameters in total.","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":2.4,"cache_read":0.12}},"gpt-6.1-sol@eu":{"id":"gpt-6.1-sol@eu","name":"GPT-6.1 Sol (EU)","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.4,"output":12,"cache_read":0.12,"cache_write":3,"tiers":[{"input":4.8,"output":18,"cache_read":0.24,"cache_write":6,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4.8,"output":18,"cache_read":0.24,"cache_write":6}},"canonical_model_id":"openai/gpt-6.1-sol"},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"gpt-5.4-pro":{"id":"gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"cache_read":30},"canonical_model_id":"openai/gpt-5.4-pro"},"claude-opus-5@eu":{"id":"claude-opus-5@eu","name":"Claude Opus 5 (EU)","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-5"},"mimo-v2.6-pro":{"id":"mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.43,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"gemma-4-31b-it":{"id":"gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemma-4-31b-it"},"ling-2.6-1t":{"id":"ling-2.6-1t","name":"ling-2.6-1t","description":"Inclusion AI ling-2.6-1t","family":"ling","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.3,"output":2.5}},"claude-haiku-5-5@eu":{"id":"claude-haiku-5-5@eu","name":"Claude Haiku 5.5 (EU)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.11,"output":0.55,"cache_read":0.02,"cache_write":0.14,"tiers":[{"input":0.55,"output":2.75,"cache_read":0.06,"cache_write":0.69,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"gpt-4o-mini@eu":{"id":"gpt-4o-mini@eu","name":"GPT-4o mini (EU)","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16000},"cost":{"input":0.165,"output":0.66,"cache_read":0.0825},"canonical_model_id":"openai/gpt-4o-mini"},"qwen3.7-max":{"id":"qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":2.5,"output":7.5,"cache_read":0.25,"cache_write":3.125},"canonical_model_id":"alibaba/qwen3.7-max"},"muse-spark-1.3":{"id":"muse-spark-1.3","name":"Muse Spark 1.3","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.3"},"nemotron-3.5-lightning-30b-a3b":{"id":"nemotron-3.5-lightning-30b-a3b","name":"nemotron-3.5-lightning-30b-a3b","description":"NVIDIA Nemotron 3.5 Lightning 30B-A3B is a hybrid Mamba-2 + MoE + Attention model with 30B total and 3B active parameters, pre-trained on over 20T tokens with an NVFP4 recipe and Multi-Token Prediction for fast generation. Up to 1M token context for long-running autonomous agents, sub-agent workhorse deployments, and agentic workflows. Supports reasoning and tool calling. English and coding languages plus Spanish, French, German, Italian, and Japanese. Open weights under the OpenMDW License Agreement v1.1. Part of the NVIDIA Nemotron family.","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0}},"mimo-v2.5":{"id":"mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.5"},"gpt-5.5-pro":{"id":"gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180},"canonical_model_id":"openai/gpt-5.5-pro"},"grok-4.7":{"id":"grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"cache_write":2},"canonical_model_id":"xai/grok-4.7"},"mistral-medium-3-5@eu":{"id":"mistral-medium-3-5@eu","name":"Mistral Medium 3.5 (EU)","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":1.65,"output":8.25,"cache_read":1.65},"canonical_model_id":"mistral/mistral-medium-3-5"},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"gpt-5@eu":{"id":"gpt-5@eu","name":"GPT-5 (EU)","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.375,"output":11,"cache_read":0.1375},"canonical_model_id":"openai/gpt-5"},"kimi-k2.5@eu":{"id":"kimi-k2.5@eu","name":"Kimi K2.5 (EU)","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16000},"cost":{"input":0.72,"output":3.6,"cache_read":0.72,"cache_write":0.72},"canonical_model_id":"moonshotai/kimi-k2.5"},"deepseek-v4-flash-0731@eu":{"id":"deepseek-v4-flash-0731@eu","name":"DeepSeek V4 Flash 0731 (EU)","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.28,"output":0.56,"cache_read":0.07},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"seed-2.0-pro":{"id":"seed-2.0-pro","name":"Seed 2.0 Pro","description":"Flagship ByteDance Seed 2.0 model for complex multimodal reasoning and long-horizon agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.5,"output":3,"cache_read":0.1},"canonical_model_id":"bytedance-seed/seed-2.0-pro"},"kimi-k3@eu":{"id":"kimi-k3@eu","name":"Kimi K3 (EU)","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":3,"output":15,"cache_read":0.45},"canonical_model_id":"moonshotai/kimi-k3"},"seed-1.8":{"id":"seed-1.8","name":"seed-1.8","description":"Optimized specifically for multimodal agent scenarios. It features enhanced agent capabilities, upgraded multimodal comprehension, and more flexible context management.","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-05-27","last_updated":"2026-05-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.25,"output":2,"cache_read":0.05}},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":262144},"cost":{"input":0.2,"output":0.6,"cache_read":0.07},"canonical_model_id":"zhipuai/glm-5.3-flash"},"qwen3.5-27b":{"id":"qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.26,"output":2.6},"canonical_model_id":"alibaba/qwen3.5-27b"},"mistral-medium-latest@eu":{"id":"mistral-medium-latest@eu","name":"Mistral Medium (latest) (EU)","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.44,"output":2.2,"cache_read":0.44},"canonical_model_id":"mistral/mistral-medium-latest"},"glm-5.2-fast":{"id":"glm-5.2-fast","name":"glm-5.2-fast","description":"GLM-5.2 introduces a robust 1M-token context and advanced, multi-effort coding capabilities to significantly enhance performance on long-horizon tasks. Its new IndexShare architecture and improved MTP layer simultaneously boost efficiency by reducing per-token FLOPs and increasing speculative decoding lengths. A 743B-parameter model in Zhipu AI's GLM series, designed to plan, execute, and iterate autonomously on extended, engineering-grade tasks.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-07-13","last_updated":"2026-07-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2.1,"output":6.6,"cache_read":0.21}},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.28,"output":0.56,"cache_read":0.07},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek-v4-pro-0813@eu":{"id":"deepseek-v4-pro-0813@eu","name":"DeepSeek V4 Pro 0813 (EU)","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":1.75,"output":3.5,"cache_read":0.44},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"inkling-256k":{"id":"inkling-256k","name":"inkling-256k","description":"Inkling 256K is the extended context variant of Inkling, a large MoE hybrid reasoning model from Thinking Machines with audio and vision input support and a 256K context window.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":1.87,"output":4.68,"cache_read":0.374}},"muse-glimmer-30b":{"id":"muse-glimmer-30b","name":"Muse Glimmer 30B","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":20480},"cost":{"input":0,"output":0},"canonical_model_id":"meta/muse-glimmer-30b"},"claude-opus-4-8@eu":{"id":"claude-opus-4-8@eu","name":"Claude Opus 4.8 (EU)","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-8"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":3,"output":15,"cache_read":0.45},"canonical_model_id":"moonshotai/kimi-k3"},"claude-fable-5@eu":{"id":"claude-fable-5@eu","name":"Claude Fable 5 (EU)","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":11,"output":55,"cache_read":1.1,"cache_write":13.75},"canonical_model_id":"anthropic/claude-fable-5"},"nemotron-3-nano-omni@eu":{"id":"nemotron-3-nano-omni@eu","name":"nemotron-3-nano-omni@eu","description":"The most open, efficient, and accurate omni modal reasoning model for agentic AI.","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-20","last_updated":"2026-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":300000},"cost":{"input":0.06,"output":0.24,"cache_read":0.06}},"gpt-4.1@eu":{"id":"gpt-4.1@eu","name":"GPT-4.1 (EU)","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2.2,"output":8.8,"cache_read":0.55},"canonical_model_id":"openai/gpt-4.1"},"gemini-3.1-flash-lite@eu":{"id":"gemini-3.1-flash-lite@eu","name":"Gemini 3.1 Flash Lite (EU)","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.275,"output":1.65,"cache_read":0.0275,"cache_write":0.091663},"canonical_model_id":"google/gemini-3.1-flash-lite"},"nvidia-nemotron-3-super-120b-a12b":{"id":"nvidia-nemotron-3-super-120b-a12b","name":"nvidia-nemotron-3-super-120b-a12b","description":"NVIDIA Nemotron 3 Super is a hybrid Mixture-of-Experts (MoE) model engineered for highest compute efficiency and accuracy in multi-agent applications and specialized agentic systems. It is optimized to run many collaborating agents per application on a single GPU, delivering high accuracy for reasoning, tool use, and instruction following.","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.1,"output":0.5}},"mistral-large-4":{"id":"mistral-large-4","name":"Mistral Large 4","description":"Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":524288},"cost":{"input":0.68,"output":2.09,"cache_read":0.07},"canonical_model_id":"mistral/mistral-large-4"},"gemini-3.5-flash-lite@eu":{"id":"gemini-3.5-flash-lite@eu","name":"Gemini 3.5 Flash Lite (EU)","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.33,"output":2.75,"cache_read":0.033},"canonical_model_id":"google/gemini-3.5-flash-lite"},"claude-opus-4-5":{"id":"claude-opus-4-5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"kimi-k2.7-code@eu":{"id":"kimi-k2.7-code@eu","name":"Kimi K2.7 Code (EU)","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.25,"output":4.5,"cache_read":0.31},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.5,"output":1.5,"cache_read":0.05},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"glm-5.1@eu":{"id":"glm-5.1@eu","name":"GLM-5.1 (EU)","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":200000},"cost":{"input":1.4,"output":4.4,"cache_read":1.4},"canonical_model_id":"zhipuai/glm-5.1"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"claude-haiku-4-5@eu":{"id":"claude-haiku-4-5@eu","name":"Claude Haiku 4.5 (latest) (EU)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1.1,"output":5.5,"cache_read":0.11,"cache_write":1.375},"canonical_model_id":"anthropic/claude-haiku-4-5"},"claude-sonnet-4-5@eu":{"id":"claude-sonnet-4-5@eu","name":"Claude Sonnet 4.5 (latest) (EU)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3.3,"output":16.5,"cache_read":0.3,"cache_write":4.125,"tiers":[{"input":6.6,"output":24.75,"cache_read":0.6,"cache_write":8.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6.6,"output":24.75,"cache_read":0.6,"cache_write":8.25}},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"laguna-xs.2":{"id":"laguna-xs.2","name":"Laguna XS.2","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"poolside/laguna-xs.2"},"leanstral-1-5@eu":{"id":"leanstral-1-5@eu","name":"leanstral-1-5@eu","description":"Leanstral 1.5 is an updated Lean 4 formal proof engineering model from Mistral AI, optimized for automated theorem proving and autoformalization. It has 119B total parameters with 6.5B active and supports a 256K token context window. It supports native function calling and structured output.","family":"leanstral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-05-27","last_updated":"2026-05-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0}},"claude-sonnet-5-5@eu":{"id":"claude-sonnet-5-5@eu","name":"Claude Sonnet 5.5 (EU)","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.22,"cache_write":2.75},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"claude-sonnet-4-5":{"id":"claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"nemotron-3-super-120b-a12b":{"id":"nemotron-3-super-120b-a12b","name":"Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"claude-sonnet-4-6@eu":{"id":"claude-sonnet-4-6@eu","name":"Claude Sonnet 4.6 (EU)","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3.3,"output":16.5,"cache_read":0.3,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"gemini-3.6-flash":{"id":"gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":1.5,"output":7,"cache_read":0.15},"canonical_model_id":"google/gemini-3.6-flash"},"gpt-5.5@eu":{"id":"gpt-5.5@eu","name":"GPT-5.5 (EU)","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5.5,"output":33,"cache_read":0.55,"tiers":[{"input":11,"output":49.5,"cache_read":1.1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":11,"output":49.5,"cache_read":1.1}},"canonical_model_id":"openai/gpt-5.5"},"ling-3.0-tiny":{"id":"ling-3.0-tiny","name":"ling-3.0-tiny","description":"Ling-3.0-tiny is an efficient 7.9B parameter MoE model from inclusionAI with only 1.3B active parameters per token. Built for responsive agents, reliable instruction following and multi turn conversation, with a 256K context window, native function calling, prompt caching and switchable Thinking and Instant modes.","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0}},"step-5-preview":{"id":"step-5-preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1,"output":2.7,"cache_read":0.05},"canonical_model_id":"stepfun/step-5-preview"},"claude-opus-5-5@eu":{"id":"claude-opus-5-5@eu","name":"Claude Opus 5.5 (EU)","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4.4,"output":22,"cache_read":0.22,"cache_write":5.5},"canonical_model_id":"anthropic/claude-opus-5-5"},"gemini-4-argon@eu":{"id":"gemini-4-argon@eu","name":"Gemini 4 Argon (EU)","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2.2,"output":11,"cache_read":0.11},"canonical_model_id":"google/gemini-4-argon"},"gpt-5-mini@eu":{"id":"gpt-5-mini@eu","name":"GPT-5 Mini (EU)","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":0.275,"output":2.2,"cache_read":0.0275},"canonical_model_id":"openai/gpt-5-mini"},"mistral-medium-3-5":{"id":"mistral-medium-3-5","name":"Mistral Medium 3.5","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":1.65,"output":8.25,"cache_read":1.65},"canonical_model_id":"mistral/mistral-medium-3-5"},"grok-4.3":{"id":"grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"cache_write":1.25,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"cache_write":2.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4,"cache_write":2.5}},"canonical_model_id":"xai/grok-4.3"},"nemotron-3-ultra-550b-a55b":{"id":"nemotron-3-ultra-550b-a55b","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nemotron-3-nano-omni-30b-a3b-reasoning":{"id":"nemotron-3-nano-omni-30b-a3b-reasoning","name":"Nemotron 3 Nano Omni 30B A3B Reasoning","description":"Open Nemotron omni model combining reasoning with text, vision, and audio","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":20480},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning"},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"gemma-4-26b-a4b-it":{"id":"gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.07,"output":0.34,"cache_read":0.07},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"gemini-3.5-flash-lite":{"id":"gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"gpt-5.4@eu":{"id":"gpt-5.4@eu","name":"GPT-5.4 (EU)","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.75,"output":16.5,"cache_read":0.275,"tiers":[{"input":5.5,"output":24.75,"cache_read":0.55,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5.5,"output":24.75,"cache_read":0.55}},"canonical_model_id":"openai/gpt-5.4"},"claude-opus-4-1":{"id":"claude-opus-4-1","name":"Claude Opus 4.1 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1"},"grok-4.2-beta":{"id":"grok-4.2-beta","name":"grok-4.2-beta","description":"Grok 4.20 Beta is xAI's newest flagship model with industry-leading speed and agentic tool calling capabilities. It combines the lowest hallucination rate on the market with strict prompt adherance, delivering consistently precise and truthful responses.","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-03-19","last_updated":"2026-03-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":2,"output":6,"cache_read":0.2,"cache_write":2,"tiers":[{"input":4,"output":12,"cache_read":0.4,"cache_write":4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":0.4,"cache_write":4}}},"gemini-3.1-flash-image":{"id":"gemini-3.1-flash-image","name":"Nano Banana 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","video","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":2},"canonical_model_id":"google/gemini-3.1-flash-image"},"nemotron-lightning-3.5-30b-a3b":{"id":"nemotron-lightning-3.5-30b-a3b","name":"nemotron-lightning-3.5-30b-a3b","description":"Nemotron-Lightning-3.5-30B-A3B is a 30B-parameter Mixture-of-Experts language model (3B active) from NVIDIA's Nemotron-H family, built on a hybrid Mamba-Transformer architecture for efficient long-context inference. Like other models in the family, it responds to queries by first generating a reasoning trace and then concluding with a final response, with reasoning behavior configurable through a flag in the chat template. It includes a multi-token prediction (MTP) speculative decoding head for low-latency serving.","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-15","last_updated":"2026-08-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.05,"output":0.2,"cache_read":0.01}},"gpt-5-nano@eu":{"id":"gpt-5-nano@eu","name":"GPT-5 Nano (EU)","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":0.055,"output":0.44,"cache_read":0.0055},"canonical_model_id":"openai/gpt-5-nano"},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"gemini-3.1-pro-preview":{"id":"gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":4.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":9,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":9}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"grok-4.5":{"id":"grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"cache_write":2,"tiers":[{"input":4,"output":12,"cache_read":1,"cache_write":4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1,"cache_write":4}},"canonical_model_id":"xai/grok-4.5"},"seed-2.0-mini":{"id":"seed-2.0-mini","name":"Seed 2.0 Mini","description":"Lightweight ByteDance Seed 2.0 model for low-latency multimodal reasoning and high-volume tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.1,"output":0.4,"cache_read":0.02},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"kimi-k2.6@eu":{"id":"kimi-k2.6@eu","name":"Kimi K2.6 (EU)","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":128000},"cost":{"input":0.95,"output":4,"cache_read":0.95},"canonical_model_id":"moonshotai/kimi-k2.6"},"qwen3.5-2b":{"id":"qwen3.5-2b","name":"qwen3.5-2b","description":"Qwen3.5-2B is a compact yet capable model from Alibaba's Qwen3.5 series. It features a 262K token context window, support for 201 languages, thinking/reasoning mode, and tool calling for agentic workflows. A strong choice for prototyping, fine-tuning, and efficient multilingual deployments.","family":"qwen3.5","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-03-10","last_updated":"2026-03-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.02,"output":0.1}},"fugu-ultra":{"id":"fugu-ultra","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"sakana/fugu-ultra"},"minimax-m2.7":{"id":"minimax-m2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":1.2},"canonical_model_id":"minimax/MiniMax-M2.7"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":1.5,"output":9,"cache_read":0.15,"cache_write":1.583},"canonical_model_id":"google/gemini-3.5-flash"},"ling-2.6-flash":{"id":"ling-2.6-flash","name":"ling-2.6-flash","description":"Inclusion AI ling-2.6-flash","family":"ling","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.1,"output":0.3}},"gemini-3-pro-image":{"id":"gemini-3-pro-image","name":"Nano Banana Pro","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":1048576,"output":32768},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":4.5},"canonical_model_id":"google/gemini-3-pro-image"},"gemini-3.7-flash@eu":{"id":"gemini-3.7-flash@eu","name":"Gemini 3.7 Flash (EU)","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.825,"output":4.125,"cache_read":0.0825},"canonical_model_id":"google/gemini-3.7-flash"},"claude-fable-5.1":{"id":"claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":11,"output":55,"cache_read":1.1,"cache_write":13.75},"canonical_model_id":"anthropic/claude-fable-5"},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"gpt-4.1-nano@eu":{"id":"gpt-4.1-nano@eu","name":"GPT-4.1 nano (EU)","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.11,"output":0.44,"cache_read":0.0275},"canonical_model_id":"openai/gpt-4.1-nano"},"mimo-v2.5-pro":{"id":"mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"gpt-5.1@eu":{"id":"gpt-5.1@eu","name":"GPT-5.1 (EU)","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.375,"output":11,"cache_read":0.1375},"canonical_model_id":"openai/gpt-5.1"},"gemini-2.5-flash-lite@eu":{"id":"gemini-2.5-flash-lite@eu","name":"Gemini 2.5 Flash-Lite (EU)","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"cache_write":0.18333},"canonical_model_id":"google/gemini-2.5-flash-lite"},"nemotron-3-nano-omni":{"id":"nemotron-3-nano-omni","name":"nemotron-3-nano-omni","description":"The most open, efficient, and accurate omni modal reasoning model for agentic AI.","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-20","last_updated":"2026-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":300000},"cost":{"input":0.06,"output":0.24,"cache_read":0.06}},"claude-sonnet-4@eu":{"id":"claude-sonnet-4@eu","name":"Claude Sonnet 4 (latest) (EU)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}},"canonical_model_id":"anthropic/claude-sonnet-4-0"},"inkling":{"id":"inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":32768},"cost":{"input":1.87,"output":4.68,"cache_read":0.374},"canonical_model_id":"thinkingmachines/inkling"},"mimo-v2.6-flash":{"id":"mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0027},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"deepseek-v4.1-flash@eu":{"id":"deepseek-v4.1-flash@eu","name":"DeepSeek V4.1 Flash (EU)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.5,"output":1.5,"cache_read":0.05},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"qwen3.8-2.4T-A95B@eu":{"id":"qwen3.8-2.4T-A95B@eu","name":"Qwen3.8 2.4T A95B (EU)","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":262144},"cost":{"input":2.5,"output":6,"cache_read":0.63},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.16,"output":0.47,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen3.8-flash-next":{"id":"qwen3.8-flash-next","name":"Qwen3.8 Flash Next","description":"Open-weight experimental preview of the Qwen4 architecture: hybrid-attention MoE (125B total, 6B active) with vision encoder for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.8-flash-next"},"qwen3.8-flash-next@eu":{"id":"qwen3.8-flash-next@eu","name":"Qwen3.8 Flash Next (EU)","description":"Open-weight experimental preview of the Qwen4 architecture: hybrid-attention MoE (125B total, 6B active) with vision encoder for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.8-flash-next"},"mistral-small-2603":{"id":"mistral-small-2603","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.165,"output":0.66,"cache_read":0.165},"canonical_model_id":"mistral/mistral-small-2603"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5.5,"output":33,"cache_read":0.55},"canonical_model_id":"openai/gpt-5.5"},"claude-sonnet-5@eu":{"id":"claude-sonnet-5@eu","name":"Claude Sonnet 5 (EU)","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.22,"cache_write":2.75},"canonical_model_id":"anthropic/claude-sonnet-5"},"gemini-3.8-flash@eu":{"id":"gemini-3.8-flash@eu","name":"Gemini 3.8 Flash (EU)","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.825,"output":4.125,"cache_read":0.0825},"canonical_model_id":"google/gemini-3.8-flash"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"qwen3.5-35b-a3b":{"id":"qwen3.5-35b-a3b","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.14,"output":1,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"glm-5.3@eu":{"id":"glm-5.3@eu","name":"GLM-5.3 (EU)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.2,"output":4.2,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"gemini-2.5-flash@eu":{"id":"gemini-2.5-flash@eu","name":"Gemini 2.5 Flash (EU)","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.3,"output":2.5,"cache_read":0.075,"cache_write":0.55},"canonical_model_id":"google/gemini-2.5-flash"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"gemini-3.7-flash":{"id":"gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.7-flash"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.8,"output":2.55,"cache_read":0.16},"canonical_model_id":"zhipuai/glm-5.2"},"hy3":{"id":"hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.14,"output":0.58,"cache_read":0.035},"canonical_model_id":"tencent/hy3"},"glm-5.2@eu":{"id":"glm-5.2@eu","name":"GLM-5.2 (EU)","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.2,"output":4.2,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"gpt-5.6-sol@eu":{"id":"gpt-5.6-sol@eu","name":"GPT-5.6 Sol (EU)","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4.4,"output":22,"cache_read":0.44,"cache_write":5.5,"tiers":[{"input":8.8,"output":33,"cache_read":0.88,"cache_write":11,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8.8,"output":33,"cache_read":0.88,"cache_write":11}},"canonical_model_id":"openai/gpt-5.6-sol"},"seed-2.0-code":{"id":"seed-2.0-code","name":"Seed 2.0 Code","description":"ByteDance Seed coding model for multimodal software engineering and long-running agents","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.5,"output":3,"cache_read":0.1},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"devstral-latest@eu":{"id":"devstral-latest@eu","name":"devstral-latest@eu","description":"An enterprise grade text model, that excels at using tools to explore codebases, editing multiple files and power software engineering agents.","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-05-27","last_updated":"2026-05-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.44,"output":2.2,"cache_read":0.44}},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"gemini-2.5-pro@eu":{"id":"gemini-2.5-pro@eu","name":"Gemini 2.5 Pro (EU)","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":1.25,"output":10,"cache_read":0.31,"cache_write":2.375,"tiers":[{"input":2.5,"output":15,"cache_read":0.62,"cache_write":4.75,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.62,"cache_write":4.75}},"canonical_model_id":"google/gemini-2.5-pro"},"gpt-5.6-terra@eu":{"id":"gpt-5.6-terra@eu","name":"GPT-5.6 Terra (EU)","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.2,"output":13.2,"cache_read":0.22,"cache_write":2.75,"tiers":[{"input":4.4,"output":19.8,"cache_read":0.44,"cache_write":5.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4.4,"output":19.8,"cache_read":0.44,"cache_write":5.5}},"canonical_model_id":"openai/gpt-5.6-terra"},"grok-build-0.1":{"id":"grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.1},"canonical_model_id":"xai/grok-build-0.1"},"glm-5.3-flash@eu":{"id":"glm-5.3-flash@eu","name":"GLM-5.3-Flash (EU)","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":262144},"cost":{"input":0.2,"output":0.6,"cache_read":0.07},"canonical_model_id":"zhipuai/glm-5.3-flash"},"minimax-m2.7-highspeed":{"id":"minimax-m2.7-highspeed","name":"MiniMax-M2.7-highspeed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.6,"output":2.4,"cache_read":0.06,"cache_write":1.2},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"deepseek-v4-pro@eu":{"id":"deepseek-v4-pro@eu","name":"DeepSeek V4 Pro (EU)","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.75,"output":3.5,"cache_read":0.44},"canonical_model_id":"deepseek/deepseek-v4-pro"},"devstral-latest":{"id":"devstral-latest","name":"devstral-latest","description":"An enterprise grade text model, that excels at using tools to explore codebases, editing multiple files and power software engineering agents.","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-05-27","last_updated":"2026-05-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.44,"output":2.2,"cache_read":0.44}},"o4-mini@eu":{"id":"o4-mini@eu","name":"o4-mini (EU)","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.21,"output":4.84,"cache_read":0.3025},"canonical_model_id":"openai/o4-mini"},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.13,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.63,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"mistral-small-2603@eu":{"id":"mistral-small-2603@eu","name":"Mistral Small 4 (EU)","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.165,"output":0.66,"cache_read":0.165},"canonical_model_id":"mistral/mistral-small-2603"},"qwen3.8-2.4T-A95B":{"id":"qwen3.8-2.4T-A95B","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"gemini-3.8-flash":{"id":"gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.8-flash"},"gemini-3.5-flash@eu":{"id":"gemini-3.5-flash@eu","name":"Gemini 3.5 Flash (EU)","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":1.65,"output":9.9,"cache_read":0.165,"cache_write":1.7413},"canonical_model_id":"google/gemini-3.5-flash"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"nemotron-3.5-content-safety":{"id":"nemotron-3.5-content-safety","name":"Nemotron 3.5 Content Safety","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-content-safety"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro"},"nvidia-nemotron-3-ultra":{"id":"nvidia-nemotron-3-ultra","name":"nvidia-nemotron-3-ultra","description":"NVIDIA Nemotron 3 Ultra is NVIDIA's strongest open-weights reasoning model, positioned near GPT-5.4 Mini (xhigh) and ahead of DeepSeek V4-Flash and Qwen3.5-397B-A17B.","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":false,"structured_output":false,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.5,"output":2.5}},"claude-fable-5.1@eu":{"id":"claude-fable-5.1@eu","name":"Claude Fable 5.1 (EU)","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":11,"output":55,"cache_read":0.275,"cache_write":13.75},"canonical_model_id":"anthropic/claude-fable-5-1"},"step-3.7-flash":{"id":"step-3.7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"gpt-6-luna@eu":{"id":"gpt-6-luna@eu","name":"GPT-6 Luna (EU)","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.12,"output":0.6,"cache_read":0.012,"cache_write":0.15,"tiers":[{"input":0.24,"output":0.9,"cache_read":0.024,"cache_write":0.3,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.24,"output":0.9,"cache_read":0.024,"cache_write":0.3}},"canonical_model_id":"openai/gpt-6-luna"},"claude-opus-4-6@eu":{"id":"claude-opus-4-6@eu","name":"Claude Opus 4.6 (EU)","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-6"},"muse-wonder-1.0":{"id":"muse-wonder-1.0","name":"Muse Wonder","description":"Muse Wonder is a frontier multimodal reasoning model from Meta for personal and professional agents, long-horizon coding, and computer use. It combines Active Memory, which carries relevant context across conversations, with Active Focus, which keeps it working through blockers toward a goal.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":4,"output":20,"cache_read":0.2},"canonical_model_id":"meta/muse-wonder-1.0"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"leanstral-1-5":{"id":"leanstral-1-5","name":"leanstral-1-5","description":"Leanstral 1.5 is an updated Lean 4 formal proof engineering model from Mistral AI, optimized for automated theorem proving and autoformalization. It has 119B total parameters with 6.5B active and supports a 256K token context window. It supports native function calling and structured output.","family":"leanstral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-05-27","last_updated":"2026-05-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0}},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"qwen3.6-plus":{"id":"qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625},"canonical_model_id":"alibaba/qwen3.6-plus"},"gpt-5.6-luna@eu":{"id":"gpt-5.6-luna@eu","name":"GPT-5.6 Luna (EU)","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.22,"output":1.32,"cache_read":0.022,"cache_write":0.275,"tiers":[{"input":0.44,"output":1.98,"cache_read":0.044,"cache_write":0.55,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.44,"output":1.98,"cache_read":0.044,"cache_write":0.55}},"canonical_model_id":"openai/gpt-5.6-luna"},"claude-opus-4-7@eu":{"id":"claude-opus-4-7@eu","name":"Claude Opus 4.7 (EU)","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-7"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"kat-coder-pro":{"id":"kat-coder-pro","name":"kat-coder-pro","description":"KAT-Coder-Pro V2 by KwaiKAT is a non-reasoning model optimized for agentic coding. It delivers strong performance on reasoning-style tasks while requiring significantly fewer output tokens than peer models. With the 1210 release, it achieved a score of 64 on the Artificial Analysis Intelligence Index, placing it in the global Top 10 and ranking first among all non-reasoning models.","family":"kat-coder","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2026-03-27","last_updated":"2026-03-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.3,"output":1.2}},"laguna-m.1":{"id":"laguna-m.1","name":"Laguna M.1","description":"Poolside's open-weight model for agentic coding and long-horizon work","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"poolside/laguna-m.1"},"gpt-6-sol@eu":{"id":"gpt-6-sol@eu","name":"GPT-6 Sol (EU)","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.4,"output":12,"cache_read":0.24,"cache_write":3,"tiers":[{"input":4.8,"output":18,"cache_read":0.48,"cache_write":6,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4.8,"output":18,"cache_read":0.48,"cache_write":6}},"canonical_model_id":"openai/gpt-6-sol"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.2,"output":4.2,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"grok-4.6":{"id":"grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"cache_write":2,"tiers":[{"input":4,"output":12,"cache_read":1,"cache_write":4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1,"cache_write":4}},"canonical_model_id":"xai/grok-4.6"},"mistral-large-4@eu":{"id":"mistral-large-4@eu","name":"Mistral Large 4 (EU)","description":"Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":524288},"cost":{"input":0.68,"output":2.09,"cache_read":0.07},"canonical_model_id":"mistral/mistral-large-4"},"minimax-m3@eu":{"id":"minimax-m3@eu","name":"MiniMax-M3 (EU)","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.4,"output":2,"cache_read":0.1},"canonical_model_id":"minimax/MiniMax-M3"},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.32,"output":1.28,"cache_read":0.032,"cache_write":0.4},"canonical_model_id":"alibaba/qwen3.7-plus"},"gpt-4.1-mini@eu":{"id":"gpt-4.1-mini@eu","name":"GPT-4.1 mini (EU)","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.44,"output":1.76,"cache_read":0.11},"canonical_model_id":"openai/gpt-4.1-mini"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"claude-opus-4-5@eu":{"id":"claude-opus-4-5@eu","name":"Claude Opus 4.5 (latest) (EU)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-5"},"muse-spark-open":{"id":"muse-spark-open","name":"Muse Spark Open","description":"Muse Spark Open is an 816B total / 42B active open-weight multimodal reasoning model from Meta for coding and long-horizon agentic work, with 1M-token context.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-open"},"gemini-4-argon":{"id":"gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":10,"cache_read":0.1},"canonical_model_id":"google/gemini-4-argon"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.28,"output":0.56,"cache_read":0.07},"canonical_model_id":"deepseek/deepseek-v4-flash"},"mistral-medium-latest":{"id":"mistral-medium-latest","name":"Mistral Medium (latest)","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.44,"output":2.2,"cache_read":0.44},"canonical_model_id":"mistral/mistral-medium-latest"},"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"gemini-3.1-flash-lite":{"id":"gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.1-flash-lite"}}},"mistral":{"id":"mistral","env":["MISTRAL_API_KEY"],"npm":"@ai-sdk/mistral","name":"Mistral","doc":"https://docs.mistral.ai/getting-started/models/","models":{"open-mistral-nemo":{"id":"open-mistral-nemo","name":"Open Mistral Nemo","description":"Legacy model retained for compatibility with older integrations","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"status":"deprecated","cost":{"input":0.15,"output":0.15}},"codestral-latest":{"id":"codestral-latest","name":"Codestral (latest)","description":"Mistral code model for completions, refactors, and developer IDE workflows","family":"codestral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-05-29","last_updated":"2025-01-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":4096},"cost":{"input":0.3,"output":0.9,"cache_read":0.03}},"mistral-large-2411":{"id":"mistral-large-2411","name":"Mistral Large 2.1","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2024-11-18","last_updated":"2024-11-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"status":"deprecated","cost":{"input":2,"output":6},"canonical_model_id":"mistral/mistral-large-2411"},"mistral-nemo":{"id":"mistral-nemo","name":"Mistral Nemo","description":"Efficient Mistral-NVIDIA open model for multilingual chat and local deployment","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"status":"deprecated","cost":{"input":0.15,"output":0.15}},"voxtral-mini-tts-latest":{"id":"voxtral-mini-tts-latest","name":"Voxtral Mini TTS (latest)","description":"Multilingual text-to-speech model with zero-shot voice cloning","family":"voxtral","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-03-01","last_updated":"2026-03-01","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"mistral-medium-2508":{"id":"mistral-medium-2508","name":"Mistral Medium 3.1","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-08-12","last_updated":"2025-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.4,"output":2}},"mistral-large-latest":{"id":"mistral-large-latest","name":"Mistral Large (latest)","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2024-11-01","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":1.5,"cache_read":0.05}},"mistral-small-latest":{"id":"mistral-small-latest","name":"Mistral Small (latest)","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.15,"output":0.6,"cache_read":0.015}},"ministral-8b-2512":{"id":"ministral-8b-2512","name":"Ministral 3 8B","description":"Compact open vision-language model for edge deployment, instruction following, and tool use","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.15,"output":0.15,"cache_read":0.015},"canonical_model_id":"mistral/ministral-3-8b-instruct-2512"},"zai-glm-5-2":{"id":"zai-glm-5-2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":1.4,"output":4.4,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.2"},"ministral-8b-latest":{"id":"ministral-8b-latest","name":"Ministral 8B (latest)","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-10-01","last_updated":"2024-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":128000},"cost":{"input":0.1,"output":0.1}},"devstral-medium-latest":{"id":"devstral-medium-latest","name":"Devstral 2 (latest)","description":"Legacy model retained for compatibility with older integrations","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.4,"output":2}},"mistral-large-4":{"id":"mistral-large-4","name":"Mistral Large 4","description":"Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":262144},"status":"beta","cost":{"input":0.68,"output":2.09,"cache_read":0.07},"canonical_model_id":"mistral/mistral-large-4"},"open-mixtral-8x22b":{"id":"open-mixtral-8x22b","name":"Mixtral 8x22B","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mixtral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-17","last_updated":"2024-04-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":64000},"status":"deprecated","cost":{"input":2,"output":6}},"devstral-2512":{"id":"devstral-2512","name":"Devstral 2","description":"Mistral's coding-agent model for repository work, terminal tasks, and software fixes","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.4,"output":2}},"mistral-medium-2505":{"id":"mistral-medium-2505","name":"Mistral Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":131072},"status":"deprecated","cost":{"input":0.4,"output":2}},"magistral-medium-latest":{"id":"magistral-medium-latest","name":"Magistral Medium (latest)","description":"Mistral reasoning model for transparent analysis, math, and complex decisions","family":"magistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2025-03-17","last_updated":"2025-03-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"status":"deprecated","cost":{"input":2,"output":5}},"voxtral-small-2507":{"id":"voxtral-small-2507","name":"Voxtral Small","description":"Instruct model with native audio input for speech understanding and tool use","family":"voxtral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32000},"cost":{"input":0.1,"output":0.4}},"glm-5-2":{"id":"glm-5-2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":1.4,"output":4.4,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.2"},"labs-leanstral-1-5-1":{"id":"labs-leanstral-1-5-1","name":"Leanstral 1.5","description":"An updated Lean 4 formal proof engineering model optimised for automated theorem proving and autoformalization. 119B total parameters, 6.5B active.","family":"leanstral","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":128000},"status":"deprecated","cost":{"input":0,"output":0}},"pixtral-12b":{"id":"pixtral-12b","name":"Pixtral 12B","description":"Mistral vision-language model for image understanding and multimodal chat","family":"pixtral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2024-09-01","last_updated":"2024-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"status":"deprecated","cost":{"input":0.15,"output":0.15}},"mistral-embed":{"id":"mistral-embed","name":"Mistral Embed","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"mistral-embed","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2023-12-11","last_updated":"2023-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8000,"output":3072},"cost":{"input":0.1,"output":0}},"devstral-small-2505":{"id":"devstral-small-2505","name":"Devstral Small 2505","description":"Legacy model retained for compatibility with older integrations","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"status":"deprecated","cost":{"input":0.1,"output":0.3}},"mistral-small-2603":{"id":"mistral-small-2603","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.15,"output":0.6,"cache_read":0.015}},"devstral-medium-2507":{"id":"devstral-medium-2507","name":"Devstral Medium","description":"Legacy model retained for compatibility with older integrations","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-07-10","last_updated":"2025-07-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"status":"deprecated","cost":{"input":0.4,"output":2}},"voxtral-mini-latest":{"id":"voxtral-mini-latest","name":"Voxtral Mini (latest)","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"voxtral","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-02-01","last_updated":"2026-02-01","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0}},"labs-devstral-small-2512":{"id":"labs-devstral-small-2512","name":"Devstral Small 2","description":"Legacy model retained for compatibility with older integrations","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"status":"deprecated","cost":{"input":0,"output":0}},"mistral-large-2512":{"id":"mistral-large-2512","name":"Mistral Large 3","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2024-11-01","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":1.5,"cache_read":0.05}},"devstral-latest":{"id":"devstral-latest","name":"Devstral 2","description":"Legacy model retained for compatibility with older integrations","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.4,"output":2}},"ministral-14b-2512":{"id":"ministral-14b-2512","name":"Ministral 3 14B","description":"Open vision-language model for efficient local deployment, instruction following, and tool use","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.2,"output":0.2,"cache_read":0.02},"canonical_model_id":"mistral/ministral-3-14b-instruct-2512"},"devstral-small-2507":{"id":"devstral-small-2507","name":"Devstral Small","description":"Legacy model retained for compatibility with older integrations","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-07-10","last_updated":"2025-07-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"status":"deprecated","cost":{"input":0.1,"output":0.3}},"pixtral-large-latest":{"id":"pixtral-large-latest","name":"Pixtral Large (latest)","description":"Mistral's larger vision model for document-heavy image understanding and chat","family":"pixtral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2024-11-01","last_updated":"2024-11-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"status":"deprecated","cost":{"input":2,"output":6}},"voxtral-small-latest":{"id":"voxtral-small-latest","name":"Voxtral Small (latest)","description":"Instruct model with native audio input for speech understanding and tool use","family":"voxtral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32000},"cost":{"input":0.1,"output":0.3}},"open-mixtral-8x7b":{"id":"open-mixtral-8x7b","name":"Mixtral 8x7B","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mixtral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-01","release_date":"2023-12-11","last_updated":"2023-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":32000},"status":"deprecated","cost":{"input":0.7,"output":0.7}},"mistral-small-2506":{"id":"mistral-small-2506","name":"Mistral Small 3.2","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"status":"deprecated","cost":{"input":0.1,"output":0.3}},"zai-glm-5-3":{"id":"zai-glm-5-3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.3"},"ministral-3b-2512":{"id":"ministral-3b-2512","name":"Ministral 3 3B","description":"Compact open vision-language model for edge deployment, instruction following, and tool use","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":262144},"cost":{"input":0.1,"output":0.1,"cache_read":0.01},"canonical_model_id":"mistral/ministral-3-3b-instruct-2512"},"mistral-medium-2604":{"id":"mistral-medium-2604","name":"Mistral Medium 3.5","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.5,"output":7.5,"cache_read":0.15}},"open-mistral-7b":{"id":"open-mistral-7b","name":"Mistral 7B","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2023-09-27","last_updated":"2023-09-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8000,"output":8000},"status":"deprecated","cost":{"input":0.25,"output":0.25}},"codestral-2508":{"id":"codestral-2508","name":"Codestral 25.08","description":"Mistral code model for low-latency completion, fill-in-the-middle, and code generation","family":"codestral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":8192},"cost":{"input":0.3,"output":0.9,"cache_read":0.03},"canonical_model_id":"mistral/codestral-2508"},"ministral-3b-latest":{"id":"ministral-3b-latest","name":"Ministral 3B (latest)","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-10-01","last_updated":"2024-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":128000},"cost":{"input":0.04,"output":0.04}},"mistral-medium-latest":{"id":"mistral-medium-latest","name":"Mistral Medium (latest)","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"mistral/mistral-medium-latest"}}},"amazon-bedrock":{"id":"amazon-bedrock","env":["AWS_ACCESS_KEY_ID","AWS_SECRET_ACCESS_KEY","AWS_REGION","AWS_BEARER_TOKEN_BEDROCK"],"npm":"@ai-sdk/amazon-bedrock","name":"Amazon Bedrock","doc":"https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html","models":{"google.gemma-3-12b-it":{"id":"google.gemma-3-12b-it","name":"Gemma 3 12B IT","description":"Open multimodal Gemma instruction model for multilingual text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.09,"output":0.29},"canonical_model_id":"google/gemma-3-12b-it"},"google.gemma-3-4b-it":{"id":"google.gemma-3-4b-it","name":"Gemma 3 4B IT","description":"Open multimodal Gemma instruction model for efficient text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":4096},"cost":{"input":0.04,"output":0.08},"canonical_model_id":"google/gemma-3-4b-it"},"eu.anthropic.claude-fable-5":{"id":"eu.anthropic.claude-fable-5","name":"Claude Fable 5 (EU)","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":11,"output":55,"cache_read":1.1,"cache_write":13.75},"canonical_model_id":"anthropic/claude-fable-5"},"qwen.qwen3-coder-480b-a35b-v1:0":{"id":"qwen.qwen3-coder-480b-a35b-v1:0","name":"Qwen3-Coder 480B-A35B Instruct","description":"Open Qwen coding heavyweight for repository reasoning and agentic engineering","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-09-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.45,"output":1.8},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"google.gemma-4-31b":{"id":"google.gemma-4-31b","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":0.14,"output":0.4},"canonical_model_id":"google/gemma-4-31b-it"},"us.writer.palmyra-x5-v1:0":{"id":"us.writer.palmyra-x5-v1:0","name":"Palmyra X5 (US)","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"palmyra","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1040000,"input":1040000,"output":8192},"cost":{"input":0.6,"output":6},"canonical_model_id":"writer/palmyra-x5"},"google.gemma-4-e2b":{"id":"google.gemma-4-e2b","name":"Gemma 4 E2B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":0.04,"output":0.08},"canonical_model_id":"google/gemma-4-E2B-it"},"us.anthropic.claude-opus-4-7":{"id":"us.anthropic.claude-opus-4-7","name":"Claude Opus 4.7 (US)","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-7"},"global.openai.gpt-6-astra":{"id":"global.openai.gpt-6-astra","name":"GPT-6 Astra (Global)","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"ultrafast":{"cost":{"input":60,"output":300,"cache_read":6,"cache_write":75},"provider":{"body":{"additionalModelRequestFields":{"service_tier":"ultrafast"}}}}}},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"us.openai.gpt-6.1-sol":{"id":"us.openai.gpt-6.1-sol","name":"GPT-6.1 Sol (US)","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"ultrafast":{"cost":{"input":13.2,"output":66,"cache_read":0.66,"cache_write":16.5},"provider":{"body":{"additionalModelRequestFields":{"service_tier":"ultrafast"}}}}}},"cost":{"input":2.2,"output":11,"cache_read":0.11,"cache_write":2.75,"tiers":[{"input":4.4,"output":16.5,"cache_read":0.22,"cache_write":5.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4.4,"output":16.5,"cache_read":0.22,"cache_write":5.5}},"canonical_model_id":"openai/gpt-6.1-sol"},"eu.amazon.nova-lite-v1:0":{"id":"eu.amazon.nova-lite-v1:0","name":"Nova Lite (EU)","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.069,"output":0.276,"cache_read":0.01725,"cache_write":0.069},"canonical_model_id":"amazon/nova-lite"},"global.anthropic.claude-opus-5-5":{"id":"global.anthropic.claude-opus-5-5","name":"Claude Opus 5.5 (Global)","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"deepseek.r1-v1:0":{"id":"deepseek.r1-v1:0","name":"DeepSeek-R1","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":1.35,"output":5.4},"canonical_model_id":"deepseek/deepseek-r1"},"openai.gpt-oss-safeguard-20b":{"id":"openai.gpt-oss-safeguard-20b","name":"GPT OSS Safeguard 20B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.07,"output":0.2},"canonical_model_id":"openai/gpt-oss-safeguard-20b"},"anthropic.claude-opus-5-5":{"id":"anthropic.claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"global.anthropic.claude-haiku-4-5-20251001-v1:0":{"id":"global.anthropic.claude-haiku-4-5-20251001-v1:0","name":"Claude Haiku 4.5 (Global)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"eu.amazon.nova-2-lite-v1:0":{"id":"eu.amazon.nova-2-lite-v1:0","name":"Nova 2 Lite (EU)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-10","release_date":"2025-12-02","last_updated":"2025-12-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.374,"output":3.157,"cache_read":0.0935,"cache_write":0.374},"canonical_model_id":"amazon/nova-2-lite"},"us.amazon.nova-pro-v1:0":{"id":"us.amazon.nova-pro-v1:0","name":"Nova Pro (US)","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.8,"output":3.2,"cache_read":0.2,"cache_write":0.8},"canonical_model_id":"amazon/nova-pro"},"jp.anthropic.claude-opus-5-5":{"id":"jp.anthropic.claude-opus-5-5","name":"Claude Opus 5.5 (JP)","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4.4,"output":22,"cache_read":0.22,"cache_write":5.5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic.claude-sonnet-5-5":{"id":"anthropic.claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"global.anthropic.claude-sonnet-5-5":{"id":"global.anthropic.claude-sonnet-5-5","name":"Claude Sonnet 5.5 (Global)","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"openai.gpt-5.6-luna":{"id":"openai.gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":0.22,"output":1.32,"cache_read":0.022,"cache_write":0.275,"tiers":[{"input":0.44,"output":1.98,"cache_read":0.044,"cache_write":0.55,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.44,"output":1.98,"cache_read":0.044,"cache_write":0.55}},"canonical_model_id":"openai/gpt-5.6-luna"},"us.meta.llama4-maverick-17b-instruct-v1:0":{"id":"us.meta.llama4-maverick-17b-instruct-v1:0","name":"Llama 4 Maverick 17B Instruct (US)","description":"Open multimodal Llama for strong reasoning with efficient everyday serving","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":8192},"cost":{"input":0.24,"output":0.97},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"apac.amazon.nova-micro-v1:0":{"id":"apac.amazon.nova-micro-v1:0","name":"Nova Micro (APAC)","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-micro","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":10000},"cost":{"input":0.037,"output":0.148,"cache_read":0.00925,"cache_write":0.037},"canonical_model_id":"amazon/nova-micro"},"eu.anthropic.claude-sonnet-4-20250514-v1:0":{"id":"eu.anthropic.claude-sonnet-4-20250514-v1:0","name":"Claude Sonnet 4 (EU)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-20250514"},"eu.anthropic.claude-opus-4-5-20251101-v1:0":{"id":"eu.anthropic.claude-opus-4-5-20251101-v1:0","name":"Claude Opus 4.5 (EU)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-01","last_updated":"2025-11-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"global.openai.gpt-6-sol":{"id":"global.openai.gpt-6-sol","name":"GPT-6 Sol (Global)","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"eu.anthropic.claude-haiku-5-5":{"id":"eu.anthropic.claude-haiku-5-5","name":"Claude Haiku 5.5 (EU)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.11,"output":0.55,"cache_read":0.011,"cache_write":0.1375,"tiers":[{"input":0.55,"output":2.75,"cache_read":0.055,"cache_write":0.6875,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"qwen.qwen3-coder-30b-a3b-v1:0":{"id":"qwen.qwen3-coder-30b-a3b-v1:0","name":"Qwen3-Coder 30B-A3B Instruct","description":"Smaller Qwen coder for efficient local agents and repo-level fixes","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-31","last_updated":"2025-09-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"us.amazon.nova-premier-v1:0":{"id":"us.amazon.nova-premier-v1:0","name":"Nova Premier (US)","description":"Multimodal model for complex analysis, long-context understanding, tool use, and model distillation","family":"nova","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10","release_date":"2025-04-30","last_updated":"2025-04-30","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":10000},"status":"deprecated","cost":{"input":2.5,"output":12.5,"cache_read":0.625,"cache_write":2.5},"canonical_model_id":"amazon/nova-premier"},"anthropic.claude-sonnet-4-6":{"id":"anthropic.claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"meta.llama3-1-70b-instruct-v1:0":{"id":"meta.llama3-1-70b-instruct-v1:0","name":"Llama 3.1 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.72,"output":0.72},"canonical_model_id":"meta/llama-3.1-70b-instruct"},"us.writer.palmyra-x4-v1:0":{"id":"us.writer.palmyra-x4-v1:0","name":"Palmyra X4 (US)","description":"Enterprise language model for workflow automation, coding, data analysis, and tool use","family":"palmyra","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2024-10-09","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":122880,"output":8192},"cost":{"input":2.5,"output":10},"canonical_model_id":"writer/palmyra-x4"},"us.zai.glm-5.3":{"id":"us.zai.glm-5.3","name":"GLM-5.3 (US)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":1.848,"output":5.808,"cache_read":0.3432,"cache_write":2.31},"canonical_model_id":"zhipuai/glm-5.3"},"apac.amazon.nova-pro-v1:0":{"id":"apac.amazon.nova-pro-v1:0","name":"Nova Pro (APAC)","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.84,"output":3.36,"cache_read":0.21,"cache_write":0.84},"canonical_model_id":"amazon/nova-pro"},"global.zai.glm-5.3":{"id":"global.zai.glm-5.3","name":"GLM-5.3 (Global)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":1.68,"output":5.28,"cache_read":0.312,"cache_write":2.1},"canonical_model_id":"zhipuai/glm-5.3"},"global.anthropic.claude-fable-5-1":{"id":"global.anthropic.claude-fable-5-1","name":"Claude Fable 5.1 (Global)","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"us.anthropic.claude-sonnet-5":{"id":"us.anthropic.claude-sonnet-5","name":"Claude Sonnet 5 (US)","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.22,"cache_write":2.75},"canonical_model_id":"anthropic/claude-sonnet-5"},"amazon.nova-micro-v1:0":{"id":"amazon.nova-micro-v1:0","name":"Nova Micro","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-micro","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":10000},"cost":{"input":0.035,"output":0.14,"cache_read":0.00875,"cache_write":0.035},"canonical_model_id":"amazon/nova-micro"},"minimax.minimax-m2.5":{"id":"minimax.minimax-m2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":98304},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2.5"},"xai.grok-4.3":{"id":"xai.grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-06-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":1.25,"output":2.5,"cache_read":0.2},"canonical_model_id":"xai/grok-4.3"},"us.amazon.nova-lite-v1:0":{"id":"us.amazon.nova-lite-v1:0","name":"Nova Lite (US)","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.06,"output":0.24,"cache_read":0.015,"cache_write":0.06},"canonical_model_id":"amazon/nova-lite"},"amazon.nova-pro-v1:0":{"id":"amazon.nova-pro-v1:0","name":"Nova Pro","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.8,"output":3.2,"cache_read":0.2,"cache_write":0.8},"canonical_model_id":"amazon/nova-pro"},"qwen.qwen3-32b-v1:0":{"id":"qwen.qwen3-32b-v1:0","name":"Qwen3 32B","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-09-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"alibaba/qwen3-32b"},"openai.gpt-5.5":{"id":"openai.gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-06-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":5.5,"output":33,"cache_read":0.55},"canonical_model_id":"openai/gpt-5.5"},"jp.anthropic.claude-haiku-5-5":{"id":"jp.anthropic.claude-haiku-5-5","name":"Claude Haiku 5.5 (JP)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.11,"output":0.55,"cache_read":0.011,"cache_write":0.1375,"tiers":[{"input":0.55,"output":2.75,"cache_read":0.055,"cache_write":0.6875,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"mistral.voxtral-small-24b-2507":{"id":"mistral.voxtral-small-24b-2507","name":"Voxtral Small 24B 2507","description":"Open audio-language model for speech transcription, audio understanding, and voice-driven tool use","family":"voxtral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"mistral/voxtral-small-24b-2507"},"global.amazon.nova-2-lite-v1:0":{"id":"global.amazon.nova-2-lite-v1:0","name":"Nova 2 Lite (Global)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-10","release_date":"2025-12-02","last_updated":"2025-12-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.3,"output":2.5,"cache_read":0.075,"cache_write":0.3},"canonical_model_id":"amazon/nova-2-lite"},"us.openai.gpt-5.6-terra":{"id":"us.openai.gpt-5.6-terra","name":"GPT-5.6 Terra (US)","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.2,"output":13.2,"cache_read":0.22,"cache_write":2.75,"tiers":[{"input":4.4,"output":19.8,"cache_read":0.44,"cache_write":5.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4.4,"output":19.8,"cache_read":0.44,"cache_write":5.5}},"canonical_model_id":"openai/gpt-5.6-terra"},"mistral.devstral-2-123b":{"id":"mistral.devstral-2-123b","name":"Devstral 2 123B","description":"Mistral's coding-agent model for repository work, terminal tasks, and software fixes","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.4,"output":2},"canonical_model_id":"mistral/devstral-2512"},"us.xai.grok-4.6":{"id":"us.xai.grok-4.6","name":"Grok 4.6 (US)","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2.2,"output":6.6,"cache_read":0.55},"canonical_model_id":"xai/grok-4.6"},"jp.anthropic.claude-sonnet-4-5-20250929-v1:0":{"id":"jp.anthropic.claude-sonnet-4-5-20250929-v1:0","name":"Claude Sonnet 4.5 (JP)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"anthropic.claude-fable-5":{"id":"anthropic.claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"global.anthropic.claude-haiku-5-5":{"id":"global.anthropic.claude-haiku-5-5","name":"Claude Haiku 5.5 (Global)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic.claude-sonnet-4-5-20250929-v1:0":{"id":"anthropic.claude-sonnet-4-5-20250929-v1:0","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"jp.anthropic.claude-opus-4-8":{"id":"jp.anthropic.claude-opus-4-8","name":"Claude Opus 4.8 (JP)","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-8"},"us.openai.gpt-5.6-luna":{"id":"us.openai.gpt-5.6-luna","name":"GPT-5.6 Luna (US)","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.22,"output":1.32,"cache_read":0.022,"cache_write":0.275,"tiers":[{"input":0.44,"output":1.98,"cache_read":0.044,"cache_write":0.55,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.44,"output":1.98,"cache_read":0.044,"cache_write":0.55}},"canonical_model_id":"openai/gpt-5.6-luna"},"in.anthropic.claude-opus-5":{"id":"in.anthropic.claude-opus-5","name":"Claude Opus 5 (India)","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-5"},"us.anthropic.claude-sonnet-4-5-20250929-v1:0":{"id":"us.anthropic.claude-sonnet-4-5-20250929-v1:0","name":"Claude Sonnet 4.5 (US)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"au.anthropic.claude-opus-5":{"id":"au.anthropic.claude-opus-5","name":"Claude Opus 5 (AU)","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-5"},"nvidia.nemotron-nano-12b-v2":{"id":"nvidia.nemotron-nano-12b-v2","name":"NVIDIA Nemotron Nano 12B v2 VL BF16","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","family":"nemotron","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-28","last_updated":"2025-10-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.2,"output":0.6},"canonical_model_id":"nvidia/nemotron-nano-12b-v2-vl"},"openai.gpt-6.1-sol":{"id":"openai.gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"ultrafast":{"cost":{"input":13.2,"output":66,"cache_read":0.66,"cache_write":16.5},"provider":{"body":{"service_tier":"ultrafast"}}}}},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":2.2,"output":11,"cache_read":0.11,"cache_write":2.75,"tiers":[{"input":4.4,"output":16.5,"cache_read":0.22,"cache_write":5.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4.4,"output":16.5,"cache_read":0.22,"cache_write":5.5}},"canonical_model_id":"openai/gpt-6.1-sol"},"us.amazon.nova-2-lite-v1:0":{"id":"us.amazon.nova-2-lite-v1:0","name":"Nova 2 Lite (US)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-10","release_date":"2025-12-02","last_updated":"2025-12-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.33,"output":2.75,"cache_read":0.0825,"cache_write":0.33},"canonical_model_id":"amazon/nova-2-lite"},"us.openai.gpt-6-astra":{"id":"us.openai.gpt-6-astra","name":"GPT-6 Astra (US)","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"ultrafast":{"cost":{"input":66,"output":330,"cache_read":6.6,"cache_write":82.5},"provider":{"body":{"additionalModelRequestFields":{"service_tier":"ultrafast"}}}}}},"cost":{"input":11,"output":55,"cache_read":1.1,"cache_write":13.75,"tiers":[{"input":22,"output":82.5,"cache_read":2.2,"cache_write":27.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":22,"output":82.5,"cache_read":2.2,"cache_write":27.5}},"canonical_model_id":"openai/gpt-6-astra"},"openai.gpt-5.6-terra":{"id":"openai.gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":2.2,"output":13.2,"cache_read":0.22,"cache_write":2.75,"tiers":[{"input":4.4,"output":19.8,"cache_read":0.44,"cache_write":5.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4.4,"output":19.8,"cache_read":0.44,"cache_write":5.5}},"canonical_model_id":"openai/gpt-5.6-terra"},"global.openai.gpt-6.1-sol":{"id":"global.openai.gpt-6.1-sol","name":"GPT-6.1 Sol (Global)","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"ultrafast":{"cost":{"input":12,"output":60,"cache_read":0.6,"cache_write":15},"provider":{"body":{"additionalModelRequestFields":{"service_tier":"ultrafast"}}}}}},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"anthropic.claude-opus-4-6-v1":{"id":"anthropic.claude-opus-4-6-v1","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-6"},"us.anthropic.claude-opus-4-1-20250805-v1:0":{"id":"us.anthropic.claude-opus-4-1-20250805-v1:0","name":"Claude Opus 4.1 (US)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1-20250805"},"us.meta.llama3-1-8b-instruct-v1:0":{"id":"us.meta.llama3-1-8b-instruct-v1:0","name":"Llama 3.1 8B Instruct (US)","description":"Compact open Llama model for lightweight chat, drafting, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.22,"output":0.22},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"eu.anthropic.claude-haiku-4-5-20251001-v1:0":{"id":"eu.anthropic.claude-haiku-4-5-20251001-v1:0","name":"Claude Haiku 4.5 (EU)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1.1,"output":5.5,"cache_read":0.11,"cache_write":1.375},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"global.anthropic.claude-opus-4-7":{"id":"global.anthropic.claude-opus-4-7","name":"Claude Opus 4.7 (Global)","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"apac.anthropic.claude-sonnet-4-20250514-v1:0":{"id":"apac.anthropic.claude-sonnet-4-20250514-v1:0","name":"Claude Sonnet 4 (APAC)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-20250514"},"deepseek.v3.2":{"id":"deepseek.v3.2","name":"DeepSeek V3.2","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2026-02-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":81920},"cost":{"input":0.62,"output":1.85},"canonical_model_id":"deepseek/deepseek-v3.2"},"qwen.qwen3-235b-a22b-2507-v1:0":{"id":"qwen.qwen3-235b-a22b-2507-v1:0","name":"Qwen3 235B-A22B Instruct 2507","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-09-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.22,"output":0.88},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"amazon.nova-lite-v1:0":{"id":"amazon.nova-lite-v1:0","name":"Nova Lite","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.06,"output":0.24,"cache_read":0.015,"cache_write":0.06},"canonical_model_id":"amazon/nova-lite"},"global.anthropic.claude-opus-5":{"id":"global.anthropic.claude-opus-5","name":"Claude Opus 5 (Global)","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"openai.gpt-oss-20b-1:0":{"id":"openai.gpt-oss-20b-1:0","name":"gpt-oss-20b","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":128000},"cost":{"input":0.07,"output":0.3},"canonical_model_id":"openai/gpt-oss-20b"},"anthropic.claude-opus-5":{"id":"anthropic.claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic.claude-haiku-5-5":{"id":"anthropic.claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"meta.llama3-3-70b-instruct-v1:0":{"id":"meta.llama3-3-70b-instruct-v1:0","name":"Llama 3.3 70B Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.72,"output":0.72},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"minimax.minimax-m2":{"id":"minimax.minimax-m2","name":"MiniMax-M2","description":"Efficient open MiniMax model built for coding agents and tool-heavy workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204608,"output":128000},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2"},"mistral.mistral-large-3-675b-instruct":{"id":"mistral.mistral-large-3-675b-instruct","name":"Mistral Large 3","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"mistral/mistral-large-2512"},"in.openai.gpt-5.6-luna":{"id":"in.openai.gpt-5.6-luna","name":"GPT-5.6 Luna (India)","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.22,"output":1.32,"cache_read":0.022,"cache_write":0.275,"tiers":[{"input":0.44,"output":1.98,"cache_read":0.044,"cache_write":0.55,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.44,"output":1.98,"cache_read":0.044,"cache_write":0.55}},"canonical_model_id":"openai/gpt-5.6-luna"},"eu.anthropic.claude-opus-4-8":{"id":"eu.anthropic.claude-opus-4-8","name":"Claude Opus 4.8 (EU)","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-8"},"global.anthropic.claude-sonnet-4-5-20250929-v1:0":{"id":"global.anthropic.claude-sonnet-4-5-20250929-v1:0","name":"Claude Sonnet 4.5 (Global)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"zai.glm-4.7":{"id":"zai.glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.6,"output":2.2},"canonical_model_id":"zhipuai/glm-4.7"},"au.anthropic.claude-sonnet-4-5-20250929-v1:0":{"id":"au.anthropic.claude-sonnet-4-5-20250929-v1:0","name":"Claude Sonnet 4.5 (AU)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"eu.anthropic.claude-opus-5-5":{"id":"eu.anthropic.claude-opus-5-5","name":"Claude Opus 5.5 (EU)","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4.4,"output":22,"cache_read":0.22,"cache_write":5.5},"canonical_model_id":"anthropic/claude-opus-5-5"},"global.anthropic.claude-sonnet-4-6":{"id":"global.anthropic.claude-sonnet-4-6","name":"Claude Sonnet 4.6 (Global)","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"jp.anthropic.claude-sonnet-4-6":{"id":"jp.anthropic.claude-sonnet-4-6","name":"Claude Sonnet 4.6 (JP)","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"google.gemma-3-27b-it":{"id":"google.gemma-3-27b-it","name":"Gemma 3 27B IT","description":"Largest open Gemma 3 instruction model for multilingual text generation and visual understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.23,"output":0.38},"canonical_model_id":"google/gemma-3-27b-it"},"eu.anthropic.claude-opus-4-6-v1":{"id":"eu.anthropic.claude-opus-4-6-v1","name":"Claude Opus 4.6 (EU)","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-6"},"us.anthropic.claude-opus-5-5":{"id":"us.anthropic.claude-opus-5-5","name":"Claude Opus 5.5 (US)","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4.4,"output":22,"cache_read":0.22,"cache_write":5.5},"canonical_model_id":"anthropic/claude-opus-5-5"},"us.anthropic.claude-opus-5":{"id":"us.anthropic.claude-opus-5","name":"Claude Opus 5 (US)","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-5"},"global.xai.grok-4.7":{"id":"global.xai.grok-4.7","name":"Grok 4.7 (Global)","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.7"},"us.openai.gpt-5.6-sol":{"id":"us.openai.gpt-5.6-sol","name":"GPT-5.6 Sol (US)","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4.4,"output":22,"cache_read":0.44,"cache_write":5.5,"tiers":[{"input":8.8,"output":33,"cache_read":0.88,"cache_write":11,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8.8,"output":33,"cache_read":0.88,"cache_write":11}},"canonical_model_id":"openai/gpt-5.6-sol"},"us.moonshotai.kimi-k3":{"id":"us.moonshotai.kimi-k3","name":"Kimi K3 (US)","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":128000},"cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"moonshotai/kimi-k3"},"anthropic.claude-sonnet-5":{"id":"anthropic.claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"mistral.magistral-small-2509":{"id":"mistral.magistral-small-2509","name":"Magistral Small 1.2","description":"Open multimodal reasoning model for transparent analysis of text and images","family":"magistral","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-18","last_updated":"2025-09-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":40000},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"mistral/magistral-small-2509"},"mistral.pixtral-large-2502-v1:0":{"id":"mistral.pixtral-large-2502-v1:0","name":"Pixtral Large (25.02)","description":"Mistral vision-language model for image understanding and multimodal chat","family":"pixtral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-04-08","last_updated":"2025-04-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":2,"output":6},"canonical_model_id":"mistral/pixtral-large-2502"},"anthropic.claude-opus-4-5-20251101-v1:0":{"id":"anthropic.claude-opus-4-5-20251101-v1:0","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-01","last_updated":"2025-11-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"nvidia.nemotron-nano-9b-v2":{"id":"nvidia.nemotron-nano-9b-v2","name":"NVIDIA Nemotron Nano 9B v2","description":"Compact Nemotron model for efficient reasoning and deployable AI agents","family":"nemotron","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-18","last_updated":"2025-08-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.06,"output":0.23},"canonical_model_id":"nvidia/nemotron-nano-9b-v2"},"eu.amazon.nova-micro-v1:0":{"id":"eu.amazon.nova-micro-v1:0","name":"Nova Micro (EU)","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-micro","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":10000},"cost":{"input":0.04,"output":0.16,"cache_read":0.01,"cache_write":0.04},"canonical_model_id":"amazon/nova-micro"},"zai.glm-5":{"id":"zai.glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":1,"output":3.2},"canonical_model_id":"zhipuai/glm-5"},"us.meta.llama3-1-70b-instruct-v1:0":{"id":"us.meta.llama3-1-70b-instruct-v1:0","name":"Llama 3.1 70B Instruct (US)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.72,"output":0.72},"canonical_model_id":"meta/llama-3.1-70b-instruct"},"jp.anthropic.claude-haiku-4-5-20251001-v1:0":{"id":"jp.anthropic.claude-haiku-4-5-20251001-v1:0","name":"Claude Haiku 4.5 (JP)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1.1,"output":5.5,"cache_read":0.11,"cache_write":1.375},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"nvidia.nemotron-nano-3-30b":{"id":"nvidia.nemotron-nano-3-30b","name":"NVIDIA Nemotron Nano 3 30B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-15","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.06,"output":0.24},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"mistral.ministral-3-3b-instruct":{"id":"mistral.ministral-3-3b-instruct","name":"Ministral 3 3B","description":"Compact open vision-language model for edge deployment, instruction following, and tool use","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.1,"output":0.1},"canonical_model_id":"mistral/ministral-3-3b-instruct-2512"},"us.xai.grok-4.7":{"id":"us.xai.grok-4.7","name":"Grok 4.7 (US)","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2.2,"output":6.6,"cache_read":0.55},"canonical_model_id":"xai/grok-4.7"},"us.openai.gpt-6-luna":{"id":"us.openai.gpt-6-luna","name":"GPT-6 Luna (US)","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.11,"output":0.55,"cache_read":0.011,"cache_write":0.1375,"tiers":[{"input":0.22,"output":0.825,"cache_read":0.022,"cache_write":0.275,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.22,"output":0.825,"cache_read":0.022,"cache_write":0.275}},"canonical_model_id":"openai/gpt-6-luna"},"global.openai.gpt-5.6-sol":{"id":"global.openai.gpt-5.6-sol","name":"GPT-5.6 Sol (Global)","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"google.gemma-4-26b-a4b":{"id":"google.gemma-4-26b-a4b","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":0.13,"output":0.4},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"xai.grok-4.6":{"id":"xai.grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":2.2,"output":6.6,"cache_read":0.55},"canonical_model_id":"xai/grok-4.6"},"global.xai.grok-4.6":{"id":"global.xai.grok-4.6","name":"Grok 4.6 (Global)","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"au.anthropic.claude-opus-4-6-v1":{"id":"au.anthropic.claude-opus-4-6-v1","name":"AU Anthropic Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-6"},"qwen.qwen3-vl-235b-a22b":{"id":"qwen.qwen3-vl-235b-a22b","name":"Qwen3 VL 235B A22B Instruct","description":"Qwen vision-language instruct model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262000},"cost":{"input":0.53,"output":2.66},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"anthropic.claude-fable-5-1":{"id":"anthropic.claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"jp.anthropic.claude-sonnet-5":{"id":"jp.anthropic.claude-sonnet-5","name":"Claude Sonnet 5 (JP)","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.22,"cache_write":2.75},"canonical_model_id":"anthropic/claude-sonnet-5"},"us.anthropic.claude-sonnet-5-5":{"id":"us.anthropic.claude-sonnet-5-5","name":"Claude Sonnet 5.5 (US)","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.11,"cache_write":2.75},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"qwen.qwen3-coder-next":{"id":"qwen.qwen3-coder-next","name":"Qwen3 Coder Next","description":"Open-weight Qwen coding model for agents, repository edits, and multi-turn tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.5,"output":1.2},"canonical_model_id":"alibaba/qwen3-coder-next"},"anthropic.claude-opus-4-8":{"id":"anthropic.claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"au.anthropic.claude-sonnet-5":{"id":"au.anthropic.claude-sonnet-5","name":"Claude Sonnet 5 (AU)","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.22,"cache_write":2.75},"canonical_model_id":"anthropic/claude-sonnet-5"},"meta.llama4-scout-17b-instruct-v1:0":{"id":"meta.llama4-scout-17b-instruct-v1:0","name":"Llama 4 Scout 17B Instruct","description":"Open Llama with long-context vision for efficient multimodal agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":10000000,"output":8192},"cost":{"input":0.17,"output":0.66},"canonical_model_id":"meta/llama-4-scout-17b-instruct"},"openai.gpt-oss-safeguard-120b":{"id":"openai.gpt-oss-safeguard-120b","name":"GPT OSS Safeguard 120B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-safeguard-120b"},"us.meta.llama3-3-70b-instruct-v1:0":{"id":"us.meta.llama3-3-70b-instruct-v1:0","name":"Llama 3.3 70B Instruct (US)","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.72,"output":0.72},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"global.openai.gpt-5.6-luna":{"id":"global.openai.gpt-5.6-luna","name":"GPT-5.6 Luna (Global)","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"au.anthropic.claude-sonnet-4-6":{"id":"au.anthropic.claude-sonnet-4-6","name":"AU Anthropic Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"openai.gpt-oss-120b":{"id":"openai.gpt-oss-120b","name":"gpt-oss-120b","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/v1","shape":"responses"},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-120b"},"deepseek.v3-v1:0":{"id":"deepseek.v3-v1:0","name":"DeepSeek-V3.1","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-09-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":81920},"cost":{"input":0.58,"output":1.68},"canonical_model_id":"deepseek/deepseek-v3.1"},"moonshotai.kimi-k2.5":{"id":"moonshotai.kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-02-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.6,"output":3},"canonical_model_id":"moonshotai/kimi-k2.5"},"eu.anthropic.claude-sonnet-4-6":{"id":"eu.anthropic.claude-sonnet-4-6","name":"Claude Sonnet 4.6 (EU)","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"us-gov.openai.gpt-oss-120b-1:0":{"id":"us-gov.openai.gpt-oss-120b-1:0","name":"gpt-oss-120b (GovCloud)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.18,"output":0.72},"canonical_model_id":"openai/gpt-oss-120b"},"us.anthropic.claude-fable-5":{"id":"us.anthropic.claude-fable-5","name":"Claude Fable 5 (US)","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":11,"output":55,"cache_read":1.1,"cache_write":13.75},"canonical_model_id":"anthropic/claude-fable-5"},"openai.gpt-6-sol":{"id":"openai.gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":2.2,"output":11,"cache_read":0.22,"cache_write":2.75,"tiers":[{"input":4.4,"output":16.5,"cache_read":0.44,"cache_write":5.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4.4,"output":16.5,"cache_read":0.44,"cache_write":5.5}},"canonical_model_id":"openai/gpt-6-sol"},"us.deepseek.r1-v1:0":{"id":"us.deepseek.r1-v1:0","name":"DeepSeek-R1 (US)","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":1.35,"output":5.4},"canonical_model_id":"deepseek/deepseek-r1"},"eu.anthropic.claude-opus-5":{"id":"eu.anthropic.claude-opus-5","name":"Claude Opus 5 (EU)","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-5"},"ca.amazon.nova-lite-v1:0":{"id":"ca.amazon.nova-lite-v1:0","name":"Nova Lite (CA)","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.064,"output":0.256,"cache_read":0.016,"cache_write":0.064},"canonical_model_id":"amazon/nova-lite"},"us.openai.gpt-6-sol":{"id":"us.openai.gpt-6-sol","name":"GPT-6 Sol (US)","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.22,"cache_write":2.75,"tiers":[{"input":4.4,"output":16.5,"cache_read":0.44,"cache_write":5.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4.4,"output":16.5,"cache_read":0.44,"cache_write":5.5}},"canonical_model_id":"openai/gpt-6-sol"},"au.anthropic.claude-opus-4-7":{"id":"au.anthropic.claude-opus-4-7","name":"Claude Opus 4.7 (AU)","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-7"},"us.meta.llama4-scout-17b-instruct-v1:0":{"id":"us.meta.llama4-scout-17b-instruct-v1:0","name":"Llama 4 Scout 17B Instruct (US)","description":"Open Llama with long-context vision for efficient multimodal agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":10000000,"output":8192},"cost":{"input":0.17,"output":0.66},"canonical_model_id":"meta/llama-4-scout-17b-instruct"},"global.anthropic.claude-sonnet-5":{"id":"global.anthropic.claude-sonnet-5","name":"Claude Sonnet 5 (Global)","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"global.anthropic.claude-fable-5":{"id":"global.anthropic.claude-fable-5","name":"Claude Fable 5 (Global)","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"apac.amazon.nova-lite-v1:0":{"id":"apac.amazon.nova-lite-v1:0","name":"Nova Lite (APAC)","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.063,"output":0.252,"cache_read":0.01575,"cache_write":0.063},"canonical_model_id":"amazon/nova-lite"},"in.anthropic.claude-sonnet-5":{"id":"in.anthropic.claude-sonnet-5","name":"Claude Sonnet 5 (India)","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.22,"cache_write":2.75},"canonical_model_id":"anthropic/claude-sonnet-5"},"us.anthropic.claude-opus-4-8":{"id":"us.anthropic.claude-opus-4-8","name":"Claude Opus 4.8 (US)","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-8"},"nvidia.nemotron-super-3-120b":{"id":"nvidia.nemotron-super-3-120b","name":"NVIDIA Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.15,"output":0.65},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"global.openai.gpt-6-luna":{"id":"global.openai.gpt-6-luna","name":"GPT-6 Luna (Global)","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"us-gov.openai.gpt-oss-20b-1:0":{"id":"us-gov.openai.gpt-oss-20b-1:0","name":"gpt-oss-20b (GovCloud)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.084,"output":0.36},"canonical_model_id":"openai/gpt-oss-20b"},"us.anthropic.claude-opus-4-6-v1":{"id":"us.anthropic.claude-opus-4-6-v1","name":"Claude Opus 4.6 (US)","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-6"},"meta.llama3-1-8b-instruct-v1:0":{"id":"meta.llama3-1-8b-instruct-v1:0","name":"Llama 3.1 8B Instruct","description":"Compact open Llama model for lightweight chat, drafting, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.22,"output":0.22},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"writer.palmyra-x5-v1:0":{"id":"writer.palmyra-x5-v1:0","name":"Palmyra X5","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"palmyra","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1040000,"input":1040000,"output":8192},"cost":{"input":0.6,"output":6},"canonical_model_id":"writer/palmyra-x5"},"anthropic.claude-opus-4-1-20250805-v1:0":{"id":"anthropic.claude-opus-4-1-20250805-v1:0","name":"Claude Opus 4.1","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1-20250805"},"us.anthropic.claude-sonnet-4-6":{"id":"us.anthropic.claude-sonnet-4-6","name":"Claude Sonnet 4.6 (US)","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"global.anthropic.claude-opus-4-6-v1":{"id":"global.anthropic.claude-opus-4-6-v1","name":"Claude Opus 4.6 (Global)","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"eu.anthropic.claude-sonnet-4-5-20250929-v1:0":{"id":"eu.anthropic.claude-sonnet-4-5-20250929-v1:0","name":"Claude Sonnet 4.5 (EU)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"jp.anthropic.claude-opus-4-7":{"id":"jp.anthropic.claude-opus-4-7","name":"Claude Opus 4.7 (JP)","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-7"},"us.anthropic.claude-haiku-5-5":{"id":"us.anthropic.claude-haiku-5-5","name":"Claude Haiku 5.5 (US)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.11,"output":0.55,"cache_read":0.011,"cache_write":0.1375,"tiers":[{"input":0.55,"output":2.75,"cache_read":0.055,"cache_write":0.6875,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"au.anthropic.claude-opus-5-5":{"id":"au.anthropic.claude-opus-5-5","name":"Claude Opus 5.5 (AU)","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4.4,"output":22,"cache_read":0.22,"cache_write":5.5},"canonical_model_id":"anthropic/claude-opus-5-5"},"openai.gpt-6-luna":{"id":"openai.gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":0.11,"output":0.55,"cache_read":0.011,"cache_write":0.1375,"tiers":[{"input":0.22,"output":0.825,"cache_read":0.022,"cache_write":0.275,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.22,"output":0.825,"cache_read":0.022,"cache_write":0.275}},"canonical_model_id":"openai/gpt-6-luna"},"writer.palmyra-x4-v1:0":{"id":"writer.palmyra-x4-v1:0","name":"Palmyra X4","description":"Enterprise language model for workflow automation, coding, data analysis, and tool use","family":"palmyra","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2024-10-09","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":122880,"output":8192},"cost":{"input":2.5,"output":10},"canonical_model_id":"writer/palmyra-x4"},"global.anthropic.claude-opus-4-5-20251101-v1:0":{"id":"global.anthropic.claude-opus-4-5-20251101-v1:0","name":"Claude Opus 4.5 (Global)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-01","last_updated":"2025-11-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"anthropic.claude-opus-4-7":{"id":"anthropic.claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"us.anthropic.claude-sonnet-4-20250514-v1:0":{"id":"us.anthropic.claude-sonnet-4-20250514-v1:0","name":"Claude Sonnet 4 (US)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-20250514"},"anthropic.claude-haiku-4-5-20251001-v1:0":{"id":"anthropic.claude-haiku-4-5-20251001-v1:0","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"eu.anthropic.claude-sonnet-5":{"id":"eu.anthropic.claude-sonnet-5","name":"Claude Sonnet 5 (EU)","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.22,"cache_write":2.75},"canonical_model_id":"anthropic/claude-sonnet-5"},"zai.glm-4.7-flash":{"id":"zai.glm-4.7-flash","name":"GLM-4.7-Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.07,"output":0.4},"canonical_model_id":"zhipuai/glm-4.7-flash"},"moonshot.kimi-k2-thinking":{"id":"moonshot.kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Thinking Kimi model for slower research passes, planning, and hard technical questions","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16000},"cost":{"input":0.6,"output":2.5},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"eu.amazon.nova-pro-v1:0":{"id":"eu.amazon.nova-pro-v1:0","name":"Nova Pro (EU)","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.92,"output":3.68,"cache_read":0.23,"cache_write":0.92},"canonical_model_id":"amazon/nova-pro"},"global.openai.gpt-5.6-terra":{"id":"global.openai.gpt-5.6-terra","name":"GPT-5.6 Terra (Global)","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai.gpt-6-astra":{"id":"openai.gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"ultrafast":{"cost":{"input":66,"output":330,"cache_read":6.6,"cache_write":82.5},"provider":{"body":{"service_tier":"ultrafast"}}}}},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":11,"output":55,"cache_read":1.1,"cache_write":13.75,"tiers":[{"input":22,"output":82.5,"cache_read":2.2,"cache_write":27.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":22,"output":82.5,"cache_read":2.2,"cache_write":27.5}},"canonical_model_id":"openai/gpt-6-astra"},"us.anthropic.claude-haiku-4-5-20251001-v1:0":{"id":"us.anthropic.claude-haiku-4-5-20251001-v1:0","name":"Claude Haiku 4.5 (US)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1.1,"output":5.5,"cache_read":0.11,"cache_write":1.375},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"meta.llama4-maverick-17b-instruct-v1:0":{"id":"meta.llama4-maverick-17b-instruct-v1:0","name":"Llama 4 Maverick 17B Instruct","description":"Open multimodal Llama for strong reasoning with efficient everyday serving","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":8192},"cost":{"input":0.24,"output":0.97},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"qwen.qwen3-next-80b-a3b":{"id":"qwen.qwen3-next-80b-a3b","name":"Qwen3-Next 80B-A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-11","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262000},"cost":{"input":0.15,"output":1.2},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"eu.mistral.pixtral-large-2502-v1:0":{"id":"eu.mistral.pixtral-large-2502-v1:0","name":"Pixtral Large (25.02) (EU)","description":"Mistral vision-language model for image understanding and multimodal chat","family":"pixtral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-04-08","last_updated":"2025-04-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":2,"output":6},"canonical_model_id":"mistral/pixtral-large-2502"},"au.anthropic.claude-opus-4-8":{"id":"au.anthropic.claude-opus-4-8","name":"Claude Opus 4.8 (AU)","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-8"},"au.anthropic.claude-haiku-5-5":{"id":"au.anthropic.claude-haiku-5-5","name":"Claude Haiku 5.5 (AU)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.11,"output":0.55,"cache_read":0.011,"cache_write":0.1375,"tiers":[{"input":0.55,"output":2.75,"cache_read":0.055,"cache_write":0.6875,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"us.anthropic.claude-fable-5-1":{"id":"us.anthropic.claude-fable-5-1","name":"Claude Fable 5.1 (US)","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":11,"output":55,"cache_read":0.275,"cache_write":13.75},"canonical_model_id":"anthropic/claude-fable-5-1"},"global.moonshotai.kimi-k3":{"id":"global.moonshotai.kimi-k3","name":"Kimi K3 (Global)","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"moonshotai/kimi-k3"},"in.openai.gpt-5.6-terra":{"id":"in.openai.gpt-5.6-terra","name":"GPT-5.6 Terra (India)","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.2,"output":13.2,"cache_read":0.22,"cache_write":2.75,"tiers":[{"input":4.4,"output":19.8,"cache_read":0.44,"cache_write":5.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4.4,"output":19.8,"cache_read":0.44,"cache_write":5.5}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai.gpt-oss-20b":{"id":"openai.gpt-oss-20b","name":"gpt-oss-20b","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/v1","shape":"responses"},"cost":{"input":0.07,"output":0.3},"canonical_model_id":"openai/gpt-oss-20b"},"mistral.ministral-3-14b-instruct":{"id":"mistral.ministral-3-14b-instruct","name":"Ministral 14B 3.0","description":"Open vision-language model for efficient local deployment, instruction following, and tool use","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.2,"output":0.2},"canonical_model_id":"mistral/ministral-3-14b-instruct-2512"},"au.anthropic.claude-haiku-4-5-20251001-v1:0":{"id":"au.anthropic.claude-haiku-4-5-20251001-v1:0","name":"Claude Haiku 4.5 (AU)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1.1,"output":5.5,"cache_read":0.11,"cache_write":1.375},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"openai.gpt-5.6-sol":{"id":"openai.gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":4.4,"output":22,"cache_read":0.44,"cache_write":5.5,"tiers":[{"input":8.8,"output":33,"cache_read":0.88,"cache_write":11,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8.8,"output":33,"cache_read":0.88,"cache_write":11}},"canonical_model_id":"openai/gpt-5.6-sol"},"minimax.minimax-m2.1":{"id":"minimax.minimax-m2.1","name":"MiniMax-M2.1","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":131072},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2.1"},"us.anthropic.claude-opus-4-5-20251101-v1:0":{"id":"us.anthropic.claude-opus-4-5-20251101-v1:0","name":"Claude Opus 4.5 (US)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-01","last_updated":"2025-11-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"eu.anthropic.claude-opus-4-7":{"id":"eu.anthropic.claude-opus-4-7","name":"Claude Opus 4.7 (EU)","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-7"},"jp.amazon.nova-2-lite-v1:0":{"id":"jp.amazon.nova-2-lite-v1:0","name":"Nova 2 Lite (JP)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-10","release_date":"2025-12-02","last_updated":"2025-12-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.396,"output":3.311,"cache_read":0.099,"cache_write":0.396},"canonical_model_id":"amazon/nova-2-lite"},"us.mistral.pixtral-large-2502-v1:0":{"id":"us.mistral.pixtral-large-2502-v1:0","name":"Pixtral Large (25.02) (US)","description":"Mistral vision-language model for image understanding and multimodal chat","family":"pixtral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-04-08","last_updated":"2025-04-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":2,"output":6},"canonical_model_id":"mistral/pixtral-large-2502"},"jp.anthropic.claude-opus-5":{"id":"jp.anthropic.claude-opus-5","name":"Claude Opus 5 (JP)","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-5"},"global.anthropic.claude-sonnet-4-20250514-v1:0":{"id":"global.anthropic.claude-sonnet-4-20250514-v1:0","name":"Claude Sonnet 4 (Global)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-20250514"},"global.anthropic.claude-opus-4-8":{"id":"global.anthropic.claude-opus-4-8","name":"Claude Opus 4.8 (Global)","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"openai.gpt-5.4":{"id":"openai.gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-06-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":2.75,"output":16.5,"cache_read":0.275},"canonical_model_id":"openai/gpt-5.4"},"mistral.voxtral-mini-3b-2507":{"id":"mistral.voxtral-mini-3b-2507","name":"Voxtral Mini 3B 2507","description":"Open audio-language model for speech transcription, audio understanding, and voice-driven tool use","family":"voxtral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":4096},"cost":{"input":0.04,"output":0.04},"canonical_model_id":"mistral/voxtral-mini-3b-2507"},"openai.gpt-oss-120b-1:0":{"id":"openai.gpt-oss-120b-1:0","name":"gpt-oss-120b","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":128000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-120b"},"amazon.nova-2-lite-v1:0":{"id":"amazon.nova-2-lite-v1:0","name":"Nova 2 Lite","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-10","release_date":"2025-12-02","last_updated":"2025-12-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.33,"output":2.75,"cache_read":0.0825,"cache_write":0.33},"canonical_model_id":"amazon/nova-2-lite"},"eu.anthropic.claude-sonnet-5-5":{"id":"eu.anthropic.claude-sonnet-5-5","name":"Claude Sonnet 5.5 (EU)","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.11,"cache_write":2.75},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"us.amazon.nova-micro-v1:0":{"id":"us.amazon.nova-micro-v1:0","name":"Nova Micro (US)","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-micro","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":10000},"cost":{"input":0.035,"output":0.14,"cache_read":0.00875,"cache_write":0.035},"canonical_model_id":"amazon/nova-micro"},"mistral.ministral-3-8b-instruct":{"id":"mistral.ministral-3-8b-instruct","name":"Ministral 3 8B","description":"Compact open vision-language model for edge deployment, instruction following, and tool use","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.15,"output":0.15},"canonical_model_id":"mistral/ministral-3-8b-instruct-2512"},"in.anthropic.claude-haiku-4-5-20251001-v1:0":{"id":"in.anthropic.claude-haiku-4-5-20251001-v1:0","name":"Claude Haiku 4.5 (India)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1.1,"output":5.5,"cache_read":0.11,"cache_write":1.375},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"}}},"synthetic":{"id":"synthetic","env":["SYNTHETIC_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.synthetic.new/openai/v1","name":"Synthetic","doc":"https://synthetic.new/pricing","models":{"hf:moonshotai/Kimi-K3":{"id":"hf:moonshotai/Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-16","last_updated":"2026-07-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":65536},"cost":{"input":3,"output":15,"cache_read":0.45},"canonical_model_id":"moonshotai/kimi-k3"},"hf:moonshotai/Kimi-K2.7-Code":{"id":"hf:moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.95,"output":4,"cache_read":0.95},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"hf:nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-NVFP4":{"id":"hf:nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-NVFP4","name":"Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.3,"output":1,"cache_read":0.3},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"hf:zai-org/GLM-5.2":{"id":"hf:zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":65536},"cost":{"input":1.4,"output":4.4,"cache_read":1.4},"canonical_model_id":"zhipuai/glm-5.2"},"hf:zai-org/GLM-5.3-Flash":{"id":"hf:zai-org/GLM-5.3-Flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":65536},"cost":{"input":0.15,"output":0.5,"cache_read":0.04},"canonical_model_id":"zhipuai/glm-5.3-flash"},"hf:zai-org/GLM-4.7-Flash":{"id":"hf:zai-org/GLM-4.7-Flash","name":"GLM-4.7-Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":65536},"cost":{"input":0.1,"output":0.5,"cache_read":0.1},"canonical_model_id":"zhipuai/glm-4.7-flash"},"hf:zai-org/GLM-5.3":{"id":"hf:zai-org/GLM-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":65536},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"hf:deepseek-ai/DeepSeek-V4.1-Flash":{"id":"hf:deepseek-ai/DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","xhigh","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":65536},"cost":{"input":0.6,"output":1.2,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"hf:Qwen/Qwen3.6-27B":{"id":"hf:Qwen/Qwen3.6-27B","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.45,"output":3.6,"cache_read":0.45},"canonical_model_id":"alibaba/qwen3.6-27b"},"hf:openai/gpt-oss-120b":{"id":"hf:openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.1,"output":0.1,"cache_read":0.1}},"hf:MiniMaxAI/MiniMax-M3":{"id":"hf:MiniMaxAI/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":65536},"cost":{"input":0.6,"output":1.2,"cache_read":0.6},"canonical_model_id":"minimax/MiniMax-M3"}}},"llmgateway":{"id":"llmgateway","env":["LLMGATEWAY_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.llmgateway.io/v1","name":"DevPass (LLM Gateway)","doc":"https://llmgateway.io/docs","models":{"grok-4-1-fast-reasoning":{"id":"grok-4-1-fast-reasoning","name":"Grok 4.1 Fast Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":0.2,"output":0.5,"cache_read":0.05}},"glm-4.6v":{"id":"glm-4.6v","name":"GLM-4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.3,"output":0.9,"cache_read":0.05},"canonical_model_id":"zhipuai/glm-4.6v"},"qwen-flash":{"id":"qwen-flash","name":"Qwen Flash","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.05,"output":0.4,"cache_read":0.01,"cache_write":0.0625},"canonical_model_id":"alibaba/qwen-flash"},"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.4"},"glm-4.5":{"id":"glm-4.5","name":"GLM-4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":98304},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5"},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"gpt-5.4-pro":{"id":"gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180},"canonical_model_id":"openai/gpt-5.4-pro"},"mimo-v2.6-pro":{"id":"mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"gemma-4-31b-it":{"id":"gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.1,"output":0.25,"cache_read":0.01},"canonical_model_id":"google/gemma-4-31b-it"},"reka-edge-2603":{"id":"reka-edge-2603","name":"Reka Edge 2603","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"reka","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-09","last_updated":"2026-10-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":16384},"cost":{"input":0.1,"output":0.1}},"grok-4-5":{"id":"grok-4-5","name":"Grok 4.5","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.3}},"gpt-3.5-turbo":{"id":"gpt-3.5-turbo","name":"GPT-3.5-turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"output":4096},"cost":{"input":0.5,"output":1.5,"cache_read":0},"canonical_model_id":"openai/gpt-3.5-turbo"},"grok-4-1-fast-non-reasoning":{"id":"grok-4-1-fast-non-reasoning","name":"Grok 4.1 Fast Non-Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":0.2,"output":0.5,"cache_read":0.05}},"qwen3-vl-235b-a22b-instruct":{"id":"qwen3-vl-235b-a22b-instruct","name":"Qwen3 VL 235B A22B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.2,"output":0.88,"cache_read":0.11}},"seed-1-6-flash-250715":{"id":"seed-1-6-flash-250715","name":"Seed 1.6 Flash (250715)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-26","last_updated":"2025-07-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.07,"output":0.3,"cache_read":0.015}},"qwen3.7-max":{"id":"qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":1.25,"output":3.75,"cache_read":0.25,"cache_write":3.125},"canonical_model_id":"alibaba/qwen3.7-max"},"muse-spark-1.3":{"id":"muse-spark-1.3","name":"Muse Spark 1.3","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.3"},"Qwen3.8-27B":{"id":"Qwen3.8-27B","name":"Qwen3.8 27B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":32768},"cost":{"input":0.08,"output":0.35,"cache_read":0.05}},"gpt-4o-transcribe":{"id":"gpt-4o-transcribe","name":"GPT-4o Transcribe","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-03-20","last_updated":"2025-03-20","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":false,"limit":{"context":16000,"output":16000},"cost":{"input":2.5,"output":10}},"mimo-v2.5":{"id":"mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.168,"output":0.336,"cache_read":0.0034,"tiers":[{"input":0.8,"output":4,"cache_read":0.16,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.8,"output":4,"cache_read":0.16}},"canonical_model_id":"xiaomi/mimo-v2.5"},"gpt-5.5-pro":{"id":"gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.5-pro"},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"mistral-large-latest":{"id":"mistral-large-latest","name":"Mistral Large (latest)","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2024-11-01","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":262144},"cost":{"input":4,"output":12},"canonical_model_id":"mistral/mistral-large-latest"},"seed-2-0-code-preview-260328":{"id":"seed-2-0-code-preview-260328","name":"Seed 2.0 Code Preview (260328)","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-28","last_updated":"2026-03-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":3,"cache_read":0.1}},"qwen3-vl-235b-a22b-thinking":{"id":"qwen3-vl-235b-a22b-thinking","name":"Qwen3 VL 235B A22B Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.98,"output":3.95}},"qwen3.8-2.4t-a95b":{"id":"qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1010000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"gpt-5.2-codex":{"id":"gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Code-specialist GPT for repository edits, reviews, and long-running software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-codex"},"gpt-5.1-codex":{"id":"gpt-5.1-codex","name":"GPT-5.1 Codex","description":"Codex GPT for repository edits, code review, and practical software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex"},"glm-5v-turbo":{"id":"glm-5v-turbo","name":"GLM-5V-Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5v-turbo"},"gpt-4o":{"id":"gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"qwen3-vl-plus":{"id":"qwen3-vl-plus","name":"Qwen3-VL Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.2,"output":1.6,"reasoning":4.8,"cache_read":0.04,"cache_write":0.25},"canonical_model_id":"alibaba/qwen3-vl-plus"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.088,"output":0.25,"cache_read":0.025},"canonical_model_id":"zhipuai/glm-5.3-flash"},"fugu-max":{"id":"fugu-max","name":"Fugu Max","description":"Multi-agent model for routing expert agents across complex analytical tasks","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":2,"output":6,"cache_read":0.25}},"ministral-8b-2512":{"id":"ministral-8b-2512","name":"Ministral 8B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"mistral","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.15,"output":0.15}},"qwen3.5-27b":{"id":"qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.3,"output":2.4},"canonical_model_id":"alibaba/qwen3.5-27b"},"glm-4.6":{"id":"glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.55,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.6"},"glm-5.2-fast":{"id":"glm-5.2-fast","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":2.156,"output":6.776,"cache_read":0.429},"canonical_model_id":"zhipuai/glm-5.2"},"muse-glimmer-30b":{"id":"muse-glimmer-30b","name":"Muse Glimmer 30B","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.04},"canonical_model_id":"meta/muse-glimmer-30b"},"grok-build-0-1":{"id":"grok-build-0-1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.2,"tiers":[{"input":2,"output":4,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2,"output":4,"cache_read":0.4}},"canonical_model_id":"xai/grok-build-0.1"},"qwen3-235b-a22b-instruct-2507":{"id":"qwen3-235b-a22b-instruct-2507","name":"Qwen3 235B A22B Instruct (2507)","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-08","last_updated":"2025-07-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.09,"output":0.58}},"qwen-max":{"id":"qwen-max","name":"Qwen Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-03","last_updated":"2025-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":8192},"cost":{"input":1.6,"output":6.4},"canonical_model_id":"alibaba/qwen-max"},"qwen3-next-80b-a3b-thinking":{"id":"qwen3-next-80b-a3b-thinking","name":"Qwen3-Next 80B-A3B (Thinking)","description":"Efficient Qwen thinking model for local reasoning, math, and coding agents","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":1.2},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-thinking"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max Preview","description":"Preview Qwen flagship for million-token multimodal reasoning and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"release_date":"2026-07-19","last_updated":"2026-07-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":1.54,"output":4.631,"cache_read":0.198,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max-preview"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"qwen3-coder-next":{"id":"qwen3-coder-next","name":"Qwen3 Coder Next","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.108,"output":0.675,"cache_read":0.06}},"glm-4.5-x":{"id":"glm-4.5-x","name":"GLM-4.5 X","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"status":"beta","cost":{"input":2.2,"output":8.9,"cache_read":0.45}},"grok-4":{"id":"grok-4","name":"Grok 4","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-07-09","last_updated":"2025-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":3,"output":15,"cache_read":0.75}},"gpt-5-mini":{"id":"gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"mistral-large-4":{"id":"mistral-large-4","name":"Mistral Large 4","description":"Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":262144},"cost":{"input":1.36,"output":4.18,"cache_read":0.14},"canonical_model_id":"mistral/mistral-large-4"},"llama-4-maverick-17b-instruct":{"id":"llama-4-maverick-17b-instruct","name":"Llama 4 Maverick 17B Instruct","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":2048},"cost":{"input":0.27,"output":0.85}},"gpt-5.2-pro":{"id":"gpt-5.2-pro","name":"GPT-5.2 Pro","description":"Higher-accuracy GPT-5.2 variant for tougher reasoning and review workflows","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":21,"output":168},"canonical_model_id":"openai/gpt-5.2-pro"},"o4-mini":{"id":"o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.275},"canonical_model_id":"openai/o4-mini"},"o3-mini":{"id":"o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"glm-5":{"id":"glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":203000,"output":131072},"cost":{"input":0.72,"output":2.3,"cache_read":0.144,"cache_write":0},"canonical_model_id":"zhipuai/glm-5"},"fugu-ultra-v2.0":{"id":"fugu-ultra-v2.0","name":"Fugu Ultra v2.0","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":5,"output":30,"cache_read":0.5}},"gpt-4":{"id":"gpt-4","name":"GPT-4","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-11","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8192},"cost":{"input":30,"output":60},"canonical_model_id":"openai/gpt-4"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":384000},"cost":{"input":0.135,"output":0.54,"cache_read":0.0027},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"gpt-4.1-nano":{"id":"gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"minimax-m2.5":{"id":"minimax-m2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":228700,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5"},"kimi-k3-fast":{"id":"kimi-k3-fast","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1040384,"output":131072},"cost":{"input":4.5,"output":22.5,"cache_read":0.45},"canonical_model_id":"moonshotai/kimi-k3"},"qwen3-32b":{"id":"qwen3-32b","name":"Qwen3 32B","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":16384},"cost":{"input":0.36,"output":0.87,"reasoning":8.4},"canonical_model_id":"alibaba/qwen3-32b"},"muse-spark-1.1":{"id":"muse-spark-1.1","name":"Muse Spark 1.1","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.1"},"gpt-5-nano":{"id":"gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"qwen-plus":{"id":"qwen-plus","name":"Qwen Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.4,"output":1.2,"reasoning":4,"cache_read":0.08,"cache_write":0.5},"canonical_model_id":"alibaba/qwen-plus"},"kimi-k2.7-code-highspeed":{"id":"kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code Highspeed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"qwen3.7-flash":{"id":"qwen3.7-flash","name":"Qwen3.7 Flash","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-27","last_updated":"2026-07-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"output":1000000},"cost":{"input":0.03,"output":0.13,"cache_read":0.006,"cache_write":0.0375}},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":3.05,"cache_read":0.13},"canonical_model_id":"moonshotai/kimi-k2.6"},"minimax-m2.1-lightning":{"id":"minimax-m2.1-lightning","name":"MiniMax M2.1 Lightning","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":131072},"cost":{"input":0.12,"output":0.48}},"claude-sonnet-4-5":{"id":"claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":63999},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"qwen3-max":{"id":"qwen3-max","name":"Qwen3 Max","description":"Flagship Qwen3 model for coding agents, complex reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.845,"output":3.38,"cache_read":0.6,"cache_write":3.75},"canonical_model_id":"alibaba/qwen3-max"},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"glm-4.5-airx":{"id":"glm-4.5-airx","name":"GLM-4.5 AirX","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1.1,"output":4.5,"cache_read":0.22}},"glm-4.5v":{"id":"glm-4.5v","name":"GLM-4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.6,"output":1.8,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5v"},"claude-fable-5-1":{"id":"claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"devstral-2512":{"id":"devstral-2512","name":"Devstral 2","description":"Mistral's coding-agent model for repository work, terminal tasks, and software fixes","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.4,"output":2},"canonical_model_id":"mistral/devstral-2512"},"llama-4-scout-17b-instruct":{"id":"llama-4-scout-17b-instruct","name":"Llama 4 Scout 17B Instruct","description":"Open multimodal Llama model for long-context analysis and efficient agents","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":2048},"cost":{"input":0.18,"output":0.59}},"gemini-3.6-flash":{"id":"gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.6-flash"},"qwen3-235b-a22b-fp8":{"id":"qwen3-235b-a22b-fp8","name":"Qwen3 235B A22B FP8","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":8192},"cost":{"input":0.2,"output":0.8}},"o1":{"id":"o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":15,"output":60,"cache_read":7.5},"canonical_model_id":"openai/o1"},"glm-4-32b-0414-128k":{"id":"glm-4-32b-0414-128k","name":"GLM-4 32B (0414-128k)","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.1,"output":0.1}},"qwen3-coder-480b-a35b-instruct":{"id":"qwen3-coder-480b-a35b-instruct","name":"Qwen3-Coder 480B-A35B Instruct","description":"Open Qwen coding heavyweight for repository reasoning and agentic engineering","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.38,"output":1.55},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"qwen3-coder-30b-a3b-instruct":{"id":"qwen3-coder-30b-a3b-instruct","name":"Qwen3-Coder 30B-A3B Instruct","description":"Smaller Qwen coder for efficient local agents and repo-level fixes","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":65536},"cost":{"input":0.07,"output":0.27},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"mistral-medium-3-5":{"id":"mistral-medium-3-5","name":"Mistral Medium 3.5","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-01","last_updated":"2026-05-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":1.5,"output":7.5}},"ling-3.0-flash":{"id":"ling-3.0-flash","name":"InclusionAI Ling 3.0 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-02","last_updated":"2026-08-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.06,"output":0.18,"cache_read":0.012}},"kimi-k2-thinking":{"id":"kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Thinking Kimi model for slower research passes, planning, and hard technical questions","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":2.5,"cache_read":0.06},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"claude-opus-4-1-20250805":{"id":"claude-opus-4-1-20250805","name":"Claude Opus 4.1","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":31999},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1-20250805"},"gpt-5-pro":{"id":"gpt-5-pro","name":"GPT-5 Pro","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":272000},"cost":{"input":15,"output":120},"canonical_model_id":"openai/gpt-5-pro"},"qwen3-vl-30b-a3b-instruct":{"id":"qwen3-vl-30b-a3b-instruct","name":"Qwen3 VL 30B A3B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-02","last_updated":"2025-10-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.15,"output":0.6}},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"openai/gpt-6.1-sol"},"seed-1-6-250915":{"id":"seed-1-6-250915","name":"Seed 1.6 (250915)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.25,"output":2,"cache_read":0.05}},"ling-3.1-flash":{"id":"ling-3.1-flash","name":"Ling 3.1 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"inclusionai/ling-3.1-flash"},"seed-2-0-mini-260428":{"id":"seed-2-0-mini-260428","name":"Seed 2.0 Mini (260428)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.1,"output":0.4,"cache_read":0.02}},"gemma-4-26b-a4b-it":{"id":"gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.07,"output":0.34},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"claude-opus-4-5-20251101":{"id":"claude-opus-4-5-20251101","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":31999},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-01","last_updated":"2025-11-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"gemini-3.5-flash-lite":{"id":"gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.5-flash-lite"},"llama-3-70b-instruct":{"id":"llama-3-70b-instruct","name":"Llama 3 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2024-04-18","last_updated":"2024-04-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8000},"cost":{"input":0.51,"output":0.74}},"seed-2-0-pro-260328":{"id":"seed-2-0-pro-260328","name":"Seed 2.0 Pro (260328)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-28","last_updated":"2026-03-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":3,"cache_read":0.1}},"ling-3.0-flash-vl":{"id":"ling-3.0-flash-vl","name":"Ling 3.0 Flash VL","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":131072},"cost":{"input":0.06,"output":0.18,"cache_read":0.012}},"qwen3-235b-a22b-thinking-2507":{"id":"qwen3-235b-a22b-thinking-2507","name":"Qwen3 235B A22B Thinking (2507)","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-08","last_updated":"2025-07-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":8192},"cost":{"input":0.3,"output":3}},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-03","last_updated":"2026-09-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":1050000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5}},"minimax-text-01":{"id":"minimax-text-01","name":"MiniMax Text 01","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-01-15","last_updated":"2025-01-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.2,"output":1.1}},"gemini-3.1-pro-preview":{"id":"gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"glm-4.6v-flashx":{"id":"glm-4.6v-flashx","name":"GLM-4.6V FlashX","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16000},"cost":{"input":0.04,"output":0.4,"cache_read":0.004}},"qwen3.5-122b-a10b":{"id":"qwen3.5-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.4,"output":3.2},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"grok-4-20-beta-0309-non-reasoning":{"id":"grok-4-20-beta-0309-non-reasoning","name":"Grok 4.20 (Non-Reasoning)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":2,"output":6,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-non-reasoning"},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.405,"output":1.98,"cache_read":0.225},"canonical_model_id":"moonshotai/kimi-k2.5"},"gpt-5.1":{"id":"gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"llama-3.3-70b-instruct":{"id":"llama-3.3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":4096},"cost":{"input":0.135,"output":0.4},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"gpt-4o-mini":{"id":"gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"qwen3.6-35b-a3b":{"id":"qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.248,"output":1.485},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"qwen3-next-80b-a3b-instruct":{"id":"qwen3-next-80b-a3b-instruct","name":"Qwen3-Next 80B-A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":1.2},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"granite-4.2-8b":{"id":"granite-4.2-8b","name":"Granite 4.2 8B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"granite","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":131072},"cost":{"input":0.06,"output":0.25,"cache_read":0.015}},"fugu-ultra":{"id":"fugu-ultra","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-22","last_updated":"2026-06-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":5,"output":30,"cache_read":0.5}},"gpt-oss-20b":{"id":"gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32766},"cost":{"input":0.04,"output":0.19,"cache_read":0.01}},"minimax-m2.7":{"id":"minimax-m2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.08,"output":0.32,"cache_read":0.017,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.5-flash"},"qwen3.6-flash":{"id":"qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.05,"cache_write":0.3125},"canonical_model_id":"alibaba/qwen3.6-flash"},"qwen3-coder-flash":{"id":"qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":997952,"output":65536},"cost":{"input":0.3,"output":1.5,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"alibaba/qwen3-coder-flash"},"nemotron-3-ultra-550b":{"id":"nemotron-3-ultra-550b","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":128000},"cost":{"input":0.5,"output":2.2,"cache_read":0.1},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"llama-3.2-11b-instruct":{"id":"llama-3.2-11b-instruct","name":"Llama 3.2 11B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.07,"output":0.33}},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"mimo-v2.5-pro":{"id":"mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036,"tiers":[{"input":2,"output":6,"cache_read":0.4,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.4}},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"glm-4.7-flash":{"id":"glm-4.7-flash","name":"GLM-4.7-Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.06,"output":0.4,"cache_read":0.01,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7-flash"},"qwen3.5-9b":{"id":"qwen3.5-9b","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.1,"output":0.15},"canonical_model_id":"alibaba/qwen3.5-9b"},"inkling":{"id":"inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":1048576},"cost":{"input":0.95,"output":4.05,"cache_read":0.16},"canonical_model_id":"thinkingmachines/inkling"},"muse-spark-1.2":{"id":"muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"mimo-v2.6-flash":{"id":"mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.12,"output":0.25,"cache_read":0.0025},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"seed-1-8-251228":{"id":"seed-1-8-251228","name":"Seed 1.8 (251228)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-18","last_updated":"2025-12-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.25,"output":2,"cache_read":0.05}},"glm-4.7":{"id":"glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.38,"output":1.98,"cache_read":0.19,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.28,"output":1.1,"cache_read":0.05},"canonical_model_id":"minimax/MiniMax-M3"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25},"canonical_model_id":"openai/gpt-5.6-luna"},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"mistral-small-2603":{"id":"mistral-small-2603","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"mistral/mistral-small-2603"},"gpt-5.2":{"id":"gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"seed-1-6-250615":{"id":"seed-1-6-250615","name":"Seed 1.6 (250615)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-06-25","last_updated":"2025-06-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.25,"output":2,"cache_read":0.05}},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"claude-sonnet-4-5-20250929":{"id":"claude-sonnet-4-5-20250929","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":63999},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"qwen35-397b-a17b":{"id":"qwen35-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.6,"output":3.6},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"gpt-4.1":{"id":"gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":false,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"qwen3.5-35b-a3b":{"id":"qwen3.5-35b-a3b","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.25,"output":2},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"gemini-3.7-flash":{"id":"gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.7-flash"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.605,"output":2.123,"cache_read":0.154,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"ernie-4.5-vl-424b-a47b":{"id":"ernie-4.5-vl-424b-a47b","name":"ERNIE 4.5 VL 424B A47B","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ernie","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-06-30","last_updated":"2025-06-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":123000,"output":123000},"cost":{"input":0.42,"output":1.25}},"hy3":{"id":"hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":192000,"output":128000},"cost":{"input":0.132,"output":0.528,"cache_read":0.033},"canonical_model_id":"tencent/hy3"},"seed-2-0-lite-260428":{"id":"seed-2-0-lite-260428","name":"Seed 2.0 Lite (260428)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.25,"output":2,"cache_read":0.05}},"kimi-k2":{"id":"kimi-k2","name":"Kimi K2","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":0.57,"output":2.3,"cache_read":0.5}},"hy-mt2-plus":{"id":"hy-mt2-plus","name":"Hy-MT2 Plus","description":"Tool-capable chat model for instruction following and agentic application workflows","family":"Hy","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8192},"cost":{"input":0.074,"output":0.295}},"grok-4-3":{"id":"grok-4-3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.3"},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.931,"output":2.93,"cache_read":0.173,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.1"},"grok-4-20-non-reasoning":{"id":"grok-4-20-non-reasoning","name":"Grok 4.20 (Non-Reasoning)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-non-reasoning"},"gemini-3-flash-preview":{"id":"gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05},"canonical_model_id":"google/gemini-3-flash-preview"},"grok-4-20-beta-0309-reasoning":{"id":"grok-4-20-beta-0309-reasoning","name":"Grok 4.20 (Reasoning)","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":2,"output":6,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-reasoning"},"minimax-m2.7-highspeed":{"id":"minimax-m2.7-highspeed","name":"MiniMax-M2.7-highspeed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"claude-haiku-4-5-20251001":{"id":"claude-haiku-4-5-20251001","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"glm-4.7-flashx":{"id":"glm-4.7-flashx","name":"GLM-4.7-FlashX","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.07,"output":0.4,"cache_read":0.01,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7-flashx"},"muse-spark-1.2-contributor":{"id":"muse-spark-1.2-contributor","name":"Muse Spark 1.2 Contributor","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-06","last_updated":"2026-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"sonar":{"id":"sonar","name":"Sonar","description":"Fast web-grounded Sonar for current answers, citations, and lightweight retrieval","family":"sonar","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":130000,"output":4096},"cost":{"input":0.25,"output":2.5,"cache_write":0.25},"canonical_model_id":"perplexity/sonar"},"mistral-large-2512":{"id":"mistral-large-2512","name":"Mistral Large 3","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"mistral/mistral-large-2512"},"grok-4-6":{"id":"grok-4-6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"gemini-pro-latest":{"id":"gemini-pro-latest","name":"Gemini Pro Latest","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-27","last_updated":"2026-02-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2}},"gpt-4.1-mini":{"id":"gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"minimax-m2.5-highspeed":{"id":"minimax-m2.5-highspeed","name":"MiniMax-M2.5-highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-02-13","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5-highspeed"},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"anthropic/claude-haiku-5-5"},"gemini-3.8-flash":{"id":"gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.08333}},"ministral-14b-2512":{"id":"ministral-14b-2512","name":"Ministral 14B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"mistral","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.2,"output":0.2}},"glm-5-turbo":{"id":"glm-5-turbo","name":"GLM-5-Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5-turbo"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"openai/gpt-6-luna"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":384000},"cost":{"input":0.435,"output":0.87,"cache_read":0.003625},"canonical_model_id":"deepseek/deepseek-v4-pro"},"step-3.7-flash":{"id":"step-3.7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"muse-wonder-1.0":{"id":"muse-wonder-1.0","name":"Muse Wonder","description":"Muse Wonder is a frontier multimodal reasoning model from Meta for personal and professional agents, long-horizon coding, and computer use. It combines Active Memory, which carries relevant context across conversations, with Active Focus, which keeps it working through blockers toward a goal.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":4,"output":20,"cache_read":0.2},"canonical_model_id":"meta/muse-wonder-1.0"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":63999},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"gpt-4o-mini-transcribe":{"id":"gpt-4o-mini-transcribe","name":"GPT-4o Mini Transcribe","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-03-20","last_updated":"2025-03-20","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":false,"limit":{"context":16000,"output":16000},"cost":{"input":1.25,"output":5}},"llama-3.2-3b-instruct":{"id":"llama-3.2-3b-instruct","name":"Llama 3.2 3B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2024-09-18","last_updated":"2024-09-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32000},"cost":{"input":0.03,"output":0.05}},"qwen3.6-plus":{"id":"qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625,"tiers":[{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5}},"canonical_model_id":"alibaba/qwen3.6-plus"},"mistral-small-2506":{"id":"mistral-small-2506","name":"Mistral Small 3.2","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"mistral/mistral-small-2506"},"grok-4-20-reasoning":{"id":"grok-4-20-reasoning","name":"Grok 4.20 (Reasoning)","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-reasoning"},"grok-4-7":{"id":"grok-4-7","name":"Grok 4.7","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5}},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.6-terra"},"deepseek-v3.2":{"id":"deepseek-v3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":16384},"cost":{"input":0.26,"output":0.38,"cache_read":0.13}},"gpt-4-turbo":{"id":"gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":10,"output":30},"canonical_model_id":"openai/gpt-4-turbo"},"hy4-preview":{"id":"hy4-preview","name":"Hy4 preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":64000},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"},"muse-spark-1.3-contributor":{"id":"muse-spark-1.3-contributor","name":"Muse Spark 1.3 Contributor","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"glm-4.5-air":{"id":"glm-4.5-air","name":"GLM-4.5-Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":98304},"cost":{"input":0.13,"output":0.85,"cache_read":0.025,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5-air"},"qwen-plus-latest":{"id":"qwen-plus-latest","name":"Qwen Plus Latest","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-01-25","last_updated":"2025-01-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":8192},"cost":{"input":0.4,"output":1.2,"cache_read":0.08,"cache_write":0.5}},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32766},"cost":{"input":0.032,"output":0.14,"cache_read":0.032}},"gpt-5.1-codex-mini":{"id":"gpt-5.1-codex-mini","name":"GPT-5.1 Codex mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5.1-codex-mini"},"ministral-3b-2512":{"id":"ministral-3b-2512","name":"Ministral 3B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"mistral","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.1,"output":0.1}},"o3":{"id":"o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.5,"output":2,"cache_read":0.15},"canonical_model_id":"zhipuai/glm-5.3"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.737,"output":3.08,"cache_read":0.143},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"gpt-5":{"id":"gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"glm-5.3-fast":{"id":"glm-5.3-fast","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":2.8,"output":8.8,"cache_read":0.56},"canonical_model_id":"zhipuai/glm-5.3"},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"output":64000},"cost":{"input":0.4,"output":1.6,"cache_read":0.08,"cache_write":0.5},"canonical_model_id":"alibaba/qwen3.7-plus"},"minimax-m2.1":{"id":"minimax-m2.1","name":"MiniMax-M2.1","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.27,"output":1.1},"canonical_model_id":"minimax/MiniMax-M2.1"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5},"canonical_model_id":"openai/gpt-5.6-sol"},"auto":{"id":"auto","name":"Auto Route","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0,"output":0}},"llama-3.1-70b-instruct":{"id":"llama-3.1-70b-instruct","name":"Llama 3.1 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":2048},"status":"beta","cost":{"input":0.72,"output":0.72}},"gemini-4-argon":{"id":"gemini-4-argon","name":"Gemini 4 Argon","description":"Gemini multimodal model for text, image, audio, video, and document tasks","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-30","last_updated":"2026-09-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":0.375}},"minimax-m2":{"id":"minimax-m2","name":"MiniMax-M2","description":"Efficient open MiniMax model built for coding agents and tool-heavy workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":131072},"cost":{"input":0.2,"output":1,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2"},"custom":{"id":"custom","name":"Custom Model","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0,"output":0}},"codestral-2508":{"id":"codestral-2508","name":"Codestral","description":"Mistral coding model for code completion, generation, and developer workflows","family":"mistral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":0.3,"output":0.9}},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":384000},"cost":{"input":0.076,"output":0.153,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash"},"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-6-sol"},"gemini-3.1-flash-lite":{"id":"gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.1-flash-lite"}}},"sap-ai-core":{"id":"sap-ai-core","env":["AICORE_SERVICE_KEY"],"npm":"@jerome-benoit/sap-ai-provider-v2","name":"SAP AI Core","doc":"https://help.sap.com/docs/sap-ai-core","models":{"anthropic--claude-4-opus":{"id":"anthropic--claude-4-opus","name":"anthropic--claude-4-opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-20250514"},"gpt-5.4":{"id":"gpt-5.4","name":"gpt-5.4","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.4"},"nvidia--llama-3.2-nv-embedqa-1b":{"id":"nvidia--llama-3.2-nv-embedqa-1b","name":"nvidia--llama-3.2-nv-embedqa-1b","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":4096},"cost":{"input":0.07,"output":0}},"text-embedding-3-small":{"id":"text-embedding-3-small","name":"text-embedding-3-small","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8191,"output":1536},"cost":{"input":0.02,"output":0}},"sap-abap-1":{"id":"sap-abap-1","name":"sap-abap-1","description":"SAP-hosted model for ABAP code generation and enterprise development tasks","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-11-26","last_updated":"2025-11-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":4096},"cost":{"input":0.48,"output":1.7}},"anthropic--claude-4.8-opus":{"id":"anthropic--claude-4.8-opus","name":"anthropic--claude-4.8-opus","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"gpt-5-mini":{"id":"gpt-5-mini","name":"gpt-5-mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"anthropic--claude-3-haiku":{"id":"anthropic--claude-3-haiku","name":"anthropic--claude-3-haiku","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-08-31","release_date":"2024-03-13","last_updated":"2024-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":4096},"cost":{"input":0.25,"output":1.25,"cache_read":0.03,"cache_write":0.3},"canonical_model_id":"anthropic/claude-3-haiku-20240307"},"gpt-4.1-nano":{"id":"gpt-4.1-nano","name":"gpt-4.1-nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.08,"output":0.26},"canonical_model_id":"openai/gpt-4.1-nano"},"gpt-5-nano":{"id":"gpt-5-nano","name":"gpt-5-nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"nvidia--llama-nemotron-embed-1b":{"id":"nvidia--llama-nemotron-embed-1b","type":"embedding","name":"Llama Nemotron Embed 1B v2","description":"Multilingual text embedding model for retrieval and question answering pipelines","family":"nemotron","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-10-16","last_updated":"2025-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":2048},"canonical_model_id":"nvidia/llama-nemotron-embed-1b-v2"},"anthropic--claude-4.5-haiku":{"id":"anthropic--claude-4.5-haiku","name":"anthropic--claude-4.5-haiku","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic--claude-4.7-opus":{"id":"anthropic--claude-4.7-opus","name":"anthropic--claude-4.7-opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"gemini-embedding":{"id":"gemini-embedding","name":"Gemini Embedding 001","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-05","release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":2048,"output":1},"canonical_model_id":"google/gemini-embedding-001"},"gemini-embedding-2":{"id":"gemini-embedding-2","name":"Gemini Embedding 2","description":"Multimodal embedding model mapping text, images, video, audio, and PDFs into a unified embedding space","family":"gemini","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-11","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":3072},"canonical_model_id":"google/gemini-embedding-2"},"gemini-3.6-flash":{"id":"gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"canonical_model_id":"google/gemini-3.6-flash"},"amazon--nova-pro":{"id":"amazon--nova-pro","name":"amazon--nova-pro","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":8192},"cost":{"input":0.56,"output":2.13}},"amazon--nova-lite":{"id":"amazon--nova-lite","name":"amazon--nova-lite","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.3,"output":2.37}},"sonar-pro":{"id":"sonar-pro","name":"sonar-pro","description":"Advanced Sonar search model for deeper research and cited synthesis","family":"sonar-pro","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":3,"output":15},"canonical_model_id":"perplexity/sonar-pro"},"anthropic--claude-3.5-sonnet":{"id":"anthropic--claude-3.5-sonnet","name":"anthropic--claude-3.5-sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04-30","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-3-5-sonnet-20241022"},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"canonical_model_id":"openai/gpt-6.1-sol"},"text-embedding-3-large":{"id":"text-embedding-3-large","name":"text-embedding-3-large","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8191,"output":3072},"cost":{"input":0.09,"output":0}},"gemini-3.5-flash-lite":{"id":"gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"canonical_model_id":"google/gemini-3.5-flash-lite"},"amazon--nova-micro":{"id":"amazon--nova-micro","name":"amazon--nova-micro","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-micro","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.03,"output":0.1}},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"canonical_model_id":"openai/gpt-6-astra"},"anthropic--claude-4.5-opus":{"id":"anthropic--claude-4.5-opus","name":"anthropic--claude-4.5-opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic--claude-4-sonnet":{"id":"anthropic--claude-4-sonnet","name":"anthropic--claude-4-sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-20250514"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"gemini-3.5-flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.5-flash"},"gemini-2.5-pro":{"id":"gemini-2.5-pro","name":"gemini-2.5-pro","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-03-25","last_updated":"2025-06-05","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"google/gemini-2.5-pro"},"anthropic--claude-3-sonnet":{"id":"anthropic--claude-3-sonnet","name":"anthropic--claude-3-sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-08-31","release_date":"2024-03-04","last_updated":"2024-03-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":4096},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75}},"sonar-deep-research":{"id":"sonar-deep-research","name":"sonar-deep-research","description":"Sonar search model for current answers, retrieval, and citation-backed chat","family":"sonar-deep-research","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":false,"temperature":false,"knowledge":"2025-01","release_date":"2025-02-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32768},"cost":{"input":2,"output":8,"reasoning":3}},"mistralai--mistral-small":{"id":"mistralai--mistral-small","name":"mistralai--mistral-small","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0.07,"output":0.28},"canonical_model_id":"mistral/mistral-small-2603"},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"gemini-2.5-flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-04-17","last_updated":"2025-06-05","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"input_audio":1},"canonical_model_id":"google/gemini-2.5-flash"},"anthropic--claude-3.7-sonnet":{"id":"anthropic--claude-3.7-sonnet","name":"anthropic--claude-3.7-sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2024-10-31","release_date":"2025-02-24","last_updated":"2025-02-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-3-7-sonnet-20250219"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"gpt-5.6-luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":1,"output":6,"cache_read":0.1,"tiers":[{"input":2,"output":9,"cache_read":0.2,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":2,"output":9,"cache_read":0.2}},"canonical_model_id":"openai/gpt-5.6-luna"},"gpt-5.2":{"id":"gpt-5.2","name":"gpt-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":9.44,"cache_read":0.12},"canonical_model_id":"openai/gpt-5.2"},"gpt-5.5":{"id":"gpt-5.5","name":"gpt-5.5","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5"},"anthropic--claude-4.6-opus":{"id":"anthropic--claude-4.6-opus","name":"anthropic--claude-4.6-opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"mistralai--mistral-medium-instruct":{"id":"mistralai--mistral-medium-instruct","name":"mistralai--mistral-medium-instruct","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000},"cost":{"input":0.36,"output":1.22},"canonical_model_id":"mistral/mistral-medium-2505"},"gpt-4.1":{"id":"gpt-4.1","name":"gpt-4.1","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.32},"canonical_model_id":"openai/gpt-4.1"},"anthropic--claude-3-opus":{"id":"anthropic--claude-3-opus","name":"anthropic--claude-3-opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-08-31","release_date":"2024-02-29","last_updated":"2024-02-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":4096},"status":"deprecated","cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75}},"anthropic--claude-4.6-sonnet":{"id":"anthropic--claude-4.6-sonnet","name":"anthropic--claude-4.6-sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-08","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"sonar":{"id":"sonar","name":"sonar","description":"Sonar search model for current answers, retrieval, and citation-backed chat","family":"sonar","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":1,"output":1},"canonical_model_id":"perplexity/sonar"},"amazon--titan-embed-text":{"id":"amazon--titan-embed-text","name":"amazon--titan-embed-text","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-04-30","last_updated":"2024-04-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536},"cost":{"input":0.14,"output":0}},"gpt-4.1-mini":{"id":"gpt-4.1-mini","name":"gpt-4.1-mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"gemini-3.8-flash":{"id":"gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"canonical_model_id":"google/gemini-3.8-flash"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"canonical_model_id":"openai/gpt-6-luna"},"gemini-2.5-flash-lite":{"id":"gemini-2.5-flash-lite","name":"gemini-2.5-flash-lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":512,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"input_audio":0.3},"canonical_model_id":"google/gemini-2.5-flash-lite"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"gpt-5.6-terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.6-terra"},"mistralai--mistral-medium":{"id":"mistralai--mistral-medium","name":"Mistral Medium 3.5","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"canonical_model_id":"mistral/mistral-medium-2604"},"gpt-5":{"id":"gpt-5","name":"gpt-5","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"anthropic--claude-4.5-sonnet":{"id":"anthropic--claude-4.5-sonnet","name":"anthropic--claude-4.5-sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"gpt-5.6-sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.6-sol"},"cohere--command-a-reasoning":{"id":"cohere--command-a-reasoning","name":"cohere--command-a-reasoning","description":"Cohere reasoning model for multilingual enterprise agents, tools, and complex workflows","family":"command-a","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high"]},{"type":"budget_tokens","min":1}],"tool_call":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32000},"cost":{"input":0.63,"output":5.05},"canonical_model_id":"cohere/command-a-reasoning-08-2025"},"gemini-3.1-flash-lite":{"id":"gemini-3.1-flash-lite","name":"gemini-3.1-flash-lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite"}}},"vivgrid":{"id":"vivgrid","env":["VIVGRID_API_KEY"],"npm":"@ai-sdk/openai","api":"https://api.vivgrid.com/v1","name":"Vivgrid","doc":"https://docs.vivgrid.com/models","models":{"viv-fast":{"id":"viv-fast","name":"Viv Fast","description":"Fast coding model","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-09","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":256000},"cost":{"input":0.13,"output":0.4,"cache_read":0.05},"canonical_model_id":"vivgrid/viv-fast"},"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":2.5,"output":15,"cache_read":0.25}},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.2,"output":1.25,"cache_read":0.02}},"gpt-5.2-codex":{"id":"gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-01-14","last_updated":"2026-01-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"gpt-5.1-codex":{"id":"gpt-5.1-codex","name":"GPT-5.1 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125}},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.04},"canonical_model_id":"zhipuai/glm-5.3-flash"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"gpt-5-mini":{"id":"gpt-5-mini","name":"GPT-5 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.25,"output":2,"cache_read":0.03}},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.31,"output":1.23,"cache_read":0.01},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-24","last_updated":"2026-02-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"claude-fable-5-1":{"id":"claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":10,"output":50,"cache_read":0.5,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"gemini-3.1-pro-preview":{"id":"gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}}},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":10,"output":50,"cache_read":1.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.35,"output":3,"reasoning":3,"cache_read":0.05},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.75,"output":4.5,"cache_read":0.075}},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT 5.6 Luna","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":1,"output":6,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"openai/gpt-5.6-luna"},"gpt-5.1-codex-max":{"id":"gpt-5.1-codex-max","name":"GPT-5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125}},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"gemini-3.7-flash":{"id":"gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.7-flash"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":1.2,"output":4.2,"cache_read":0.3},"canonical_model_id":"zhipuai/glm-5.2"},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"gemini-3.8-flash":{"id":"gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":128000},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.75,"output":3.75,"cache_read":0.15},"canonical_model_id":"google/gemini-3.8-flash"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.435,"output":0.87,"cache_read":0.003625},"canonical_model_id":"deepseek/deepseek-v4-pro"},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT 5.6 Terra","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"cache_write":3.125},"canonical_model_id":"openai/gpt-5.6-terra"},"deepseek-v3.2":{"id":"deepseek-v3.2","name":"DeepSeek-V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.28,"output":0.42}},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.2,"output":4.2,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"gemini-3.1-flash-lite-preview":{"id":"gemini-3.1-flash-lite-preview","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"cache_write":1}},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT 5.6 Sol","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"openai/gpt-5.6-sol"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.3,"reasoning":0.3,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"}}},"prime":{"id":"prime","env":["PRIME_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.pinference.ai/api/v1","name":"Prime Inference","doc":"https://docs.primeintellect.ai/inference/overview","models":{"anthropic/claude-opus-4.6":{"id":"anthropic/claude-opus-4.6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-sonnet-5.5":{"id":"anthropic/claude-sonnet-5.5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-fable-5.1":{"id":"anthropic/claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3,"output":15},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-5.5":{"id":"anthropic/claude-opus-5.5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20},"canonical_model_id":"anthropic/claude-opus-5-5"},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":0.44,"output":1.32},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.3},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro 0423","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":1.91,"output":3.83},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash 0423","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943717},"cost":{"input":0.44,"output":1.32},"canonical_model_id":"deepseek/deepseek-v4-flash"},"meta-llama/llama-3.3-70b-instruct":{"id":"meta-llama/llama-3.3-70b-instruct","name":"Llama 3.3 70B Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":1.04,"output":2.253},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":0.15,"output":0.5},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":1.54,"output":4.84},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":1.4},"canonical_model_id":"zhipuai/glm-5.3"},"meta/muse-spark-open":{"id":"meta/muse-spark-open","name":"Muse Spark Open","description":"Muse Spark Open is an 816B total / 42B active open-weight multimodal reasoning model from Meta for coding and long-horizon agentic work, with 1M-token context.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":1.25,"output":4.25},"canonical_model_id":"meta/muse-spark-open"},"x-ai/grok-4.7":{"id":"x-ai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":450000},"cost":{"input":1.6,"output":4.8},"canonical_model_id":"xai/grok-4.7"},"x-ai/grok-4.6":{"id":"x-ai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":450000},"cost":{"input":2,"output":6},"canonical_model_id":"xai/grok-4.6"},"google/gemma-3-27b-it":{"id":"google/gemma-3-27b-it","name":"Gemma 3 27B","description":"Largest open Gemma 3 instruction model for multilingual text generation and visual understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.119,"output":0.3},"canonical_model_id":"google/gemma-3-27b-it"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5},"canonical_model_id":"google/gemini-3.6-flash"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["audio","image","text","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.35,"output":6.75},"canonical_model_id":"google/gemini-3.7-flash"},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-4-argon":{"id":"google/gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["audio","image","text","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":10},"canonical_model_id":"google/gemini-4-argon"},"mistralai/mistral-nemo":{"id":"mistralai/mistral-nemo","name":"Mistral Nemo","description":"Efficient Mistral-NVIDIA open model for multilingual chat and local deployment","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.165,"output":0.17},"canonical_model_id":"mistral/mistral-nemo"},"mistralai/mistral-small-2603":{"id":"mistralai/mistral-small-2603","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.165,"output":0.66},"canonical_model_id":"mistral/mistral-small-2603"},"mistralai/mistral-large-2512":{"id":"mistralai/mistral-large-2512","name":"Mistral Large 3 2512","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"mistral/mistral-large-2512"},"mistralai/mixtral-8x22b-instruct":{"id":"mistralai/mixtral-8x22b-instruct","name":"Mixtral 8x22B Instruct","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-01-31","release_date":"2024-04-17","last_updated":"2024-04-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":52428},"cost":{"input":2.2,"output":6.6},"canonical_model_id":"mistral/mixtral-8x22b-instruct"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":3.45,"output":17.25},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2-0905":{"id":"moonshotai/kimi-k2-0905","name":"Kimi K2 0905","description":"September 2025 Kimi K2 instruction update with a 256K context and improved agentic coding","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":0.6,"output":2.5},"canonical_model_id":"moonshotai/kimi-k2-0905"},"qwen/qwen3-vl-235b-a22b-instruct":{"id":"qwen/qwen3-vl-235b-a22b-instruct","name":"Qwen3 VL 235B A22B Instruct","description":"Qwen vision-language instruct model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.3,"output":1.5},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"qwen/qwen3-coder-next":{"id":"qwen/qwen3-coder-next","name":"Qwen3 Coder Next","description":"Open-weight Qwen coding model for agents, repository edits, and multi-turn tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.3,"output":1.5},"canonical_model_id":"alibaba/qwen3-coder-next"},"qwen/qwen3-vl-30b-a3b-instruct":{"id":"qwen/qwen3-vl-30b-a3b-instruct","name":"Qwen3 VL 30B A3B Instruct","description":"Open vision-language MoE model for image and video understanding, documents, and visual agents","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-04","last_updated":"2025-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.2,"output":0.7},"canonical_model_id":"alibaba/qwen3-vl-30b-a3b-instruct"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2.5,"output":15},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":30,"output":180},"canonical_model_id":"openai/gpt-5.4-pro"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 Nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.2,"output":1.25},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-5.6-sol-pro":{"id":"openai/gpt-5.6-sol-pro","name":"GPT-5.6 Sol Pro","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":5,"output":30},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.25,"output":2},"canonical_model_id":"openai/gpt-5-mini"},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT-5.3-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.75,"output":14},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1 Nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.1,"output":0.4},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.05,"output":0.4},"canonical_model_id":"openai/gpt-5-nano"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2,"output":10},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":10,"output":50},"canonical_model_id":"openai/gpt-6-astra"},"openai/gpt-5.6-luna-pro":{"id":"openai/gpt-5.6-luna-pro","name":"GPT-5.6 Luna Pro","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":1,"output":6},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.25,"output":10},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o-mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-4o-mini"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"gpt-oss-20b","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.07,"output":0.3},"canonical_model_id":"openai/gpt-oss-20b"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 Mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.75,"output":4.5},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":0.2,"output":1.2},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.75,"output":14},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":5,"output":30},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 Mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-5.6-terra-pro":{"id":"openai/gpt-5.6-terra-pro","name":"GPT-5.6 Terra Pro","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2.5,"output":15},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":0.1,"output":0.5},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2.5,"output":15},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"gpt-oss-120b","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.35,"output":0.75},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.25,"output":10},"canonical_model_id":"openai/gpt-5"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":5,"output":30},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2,"output":10},"canonical_model_id":"openai/gpt-6-sol"}}},"klokintegration":{"id":"klokintegration","env":["KLOKINTEGRATION_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api-gw.klok.ipaas.se/proxy/kloker-key/v1","name":"klokintegration.se","doc":"https://klokintegration.se/docs/ai-api","models":{"Kloker-Integration-Developer":{"id":"Kloker-Integration-Developer","name":"Kloker Integration Developer","description":"Knows the customer integration environment and Klok best practices. Opinionated about implementation. The gateway runs ecosystem lookup tools server-side and appends a system-prompt injection. Client system prompts and OpenAI tool calls are preserved.","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-29","last_updated":"2026-08-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":50000},"status":"beta","cost":{"input":0.23,"output":1.16}},"Kloker":{"id":"Kloker","name":"Kloker","description":"Cheap general model with a clean context. Nothing from the customer environment is packed in. It tracks the current best open source model. The Klok team verifies it and upgrades it periodically.","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-29","last_updated":"2026-08-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":50000},"status":"beta","cost":{"input":0.23,"output":1.16}},"Kloker-Integration-Architect":{"id":"Kloker-Integration-Architect","name":"Kloker Integration Architect","description":"Knows the customer integration environment and Klok best practices. Opinionated about structure. The gateway runs ecosystem lookup tools server-side and appends a system-prompt injection (data contracts, CloudEvents, event-driven flows). Client system prompts and OpenAI tool calls are preserved.","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-29","last_updated":"2026-08-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":50000},"status":"beta","cost":{"input":0.23,"output":1.16}}}},"google-vertex":{"id":"google-vertex","env":["GOOGLE_VERTEX_PROJECT","GOOGLE_VERTEX_LOCATION","GOOGLE_APPLICATION_CREDENTIALS"],"npm":"@ai-sdk/google-vertex","name":"Vertex","doc":"https://cloud.google.com/vertex-ai/generative-ai/docs/models","models":{"claude-opus-4-8@default":{"id":"claude-opus-4-8@default","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"gemini-2.5-flash-tts":{"id":"gemini-2.5-flash-tts","name":"Gemini 2.5 Flash TTS","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gemini-flash","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-01","release_date":"2025-09-30","last_updated":"2025-12-10","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":32768,"input":8192,"output":16384},"cost":{"input":0.5,"output":10},"canonical_model_id":"google/gemini-2.5-flash-tts"},"claude-sonnet-4-5@20250929":{"id":"claude-sonnet-4-5@20250929","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"gemini-2.5-flash-image":{"id":"gemini-2.5-flash-image","name":"Nano Banana","description":"Nano Banana image model for fast generation, edits, and character-consistent assets","family":"gemini-flash","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.3,"output":30},"canonical_model_id":"google/gemini-2.5-flash-image"},"claude-opus-4-6@default":{"id":"claude-opus-4-6@default","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"claude-opus-4@20250514":{"id":"claude-opus-4@20250514","name":"Claude Opus 4","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-20250514"},"claude-sonnet-5-5@default":{"id":"claude-sonnet-5-5@default","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"claude-opus-5-5@default":{"id":"claude-opus-5-5@default","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"gemini-3.6-flash":{"id":"gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":0.75,"output":3.75,"cache_read":0.075,"input_audio":0.75},"canonical_model_id":"google/gemini-3.6-flash"},"claude-opus-5@default":{"id":"claude-opus-5@default","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"claude-sonnet-4-6@default":{"id":"claude-sonnet-4-6@default","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"claude-haiku-4-5@20251001":{"id":"claude-haiku-4-5@20251001","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"gemini-3.5-flash-lite":{"id":"gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"gemini-3.1-flash-image":{"id":"gemini-3.1-flash-image","name":"Nano Banana 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","video","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":60,"cache_read":0.05},"canonical_model_id":"google/gemini-3.1-flash-image"},"codestral-2":{"id":"codestral-2","name":"Codestral 2","description":"Mistral code model for low-latency completion, fill-in-the-middle, and code generation","family":"codestral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"provider":{"npm":"@ai-sdk/mistral","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/publishers/mistralai/models"},"cost":{"input":0.3,"output":0.9},"canonical_model_id":"mistral/codestral-2508"},"gemini-3.1-pro-preview":{"id":"gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"beta","cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"claude-opus-4-1@20250805":{"id":"claude-opus-4-1@20250805","name":"Claude Opus 4.1","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1-20250805"},"claude-opus-4-5@20251101":{"id":"claude-opus-4-5@20251101","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-01","last_updated":"2025-11-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"claude-opus-4-7@default":{"id":"claude-opus-4-7@default","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.5-flash"},"gemini-2.5-pro":{"id":"gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":1.25,"output":10,"cache_read":0.125,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro"},"gemini-3-pro-image":{"id":"gemini-3-pro-image","name":"Nano Banana Pro","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":2,"output":120,"cache_read":0.2},"canonical_model_id":"google/gemini-3-pro-image"},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":0.3,"output":2.5,"cache_read":0.03,"input_audio":1}},"gemini-3.1-flash-lite-image":{"id":"gemini-3.1-flash-lite-image","name":"Nano Banana 2 Lite","description":"Fastest, most cost-efficient Gemini image model for high-volume 1K generation and editing","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":4096},"cost":{"input":0.25,"output":30,"cache_read":0.025},"canonical_model_id":"google/gemini-3.1-flash-lite-image"},"claude-fable-5-1@default":{"id":"claude-fable-5-1@default","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"mistral-medium-3":{"id":"mistral-medium-3","name":"Mistral Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":131072},"provider":{"npm":"@ai-sdk/mistral","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/publishers/mistralai/models"},"cost":{"input":0.4,"output":2},"canonical_model_id":"mistral/mistral-medium-2505"},"mistral-small-2503":{"id":"mistral-small-2503","name":"Mistral Small 3.1 24B","description":"Efficient multimodal model for instruction following, coding, reasoning, and function calling","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-03-17","last_updated":"2025-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"provider":{"npm":"@ai-sdk/mistral","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/publishers/mistralai/models"},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"mistral/mistral-small-3-1-24b-instruct-2503"},"gemini-3.7-flash":{"id":"gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"input_audio":0.75},"canonical_model_id":"google/gemini-3.7-flash"},"gemini-3.1-pro-preview-customtools":{"id":"gemini-3.1-pro-preview-customtools","name":"Gemini 3.1 Pro Preview Custom Tools","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"beta","cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview-customtools"},"gemini-3-flash-preview":{"id":"gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"beta","cost":{"input":0.5,"output":3,"cache_read":0.05,"input_audio":1},"canonical_model_id":"google/gemini-3-flash-preview"},"claude-fable-5@default":{"id":"claude-fable-5@default","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"gemini-3.8-flash":{"id":"gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"input_audio":0.75},"canonical_model_id":"google/gemini-3.8-flash"},"gemini-2.5-flash-lite":{"id":"gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":512,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":0.1,"output":0.4,"cache_read":0.01,"input_audio":0.3},"canonical_model_id":"google/gemini-2.5-flash-lite"},"claude-haiku-5-5@default":{"id":"claude-haiku-5-5@default","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"gemini-2.5-pro-tts":{"id":"gemini-2.5-pro-tts","name":"Gemini 2.5 Pro TTS","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gemini-pro","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-01","release_date":"2025-09-30","last_updated":"2025-12-10","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":32768,"input":8192,"output":16384},"cost":{"input":1,"output":20},"canonical_model_id":"google/gemini-2.5-pro-tts"},"gemini-embedding-001":{"id":"gemini-embedding-001","name":"Gemini Embedding 001","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-05","release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":2048,"output":1},"cost":{"input":0.15,"output":0},"canonical_model_id":"google/gemini-embedding-001"},"claude-sonnet-4@20250514":{"id":"claude-sonnet-4@20250514","name":"Claude Sonnet 4","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-20250514"},"gemini-nano-banana-2.1":{"id":"gemini-nano-banana-2.1","name":"Nano Banana 2.1","description":"Image model for prompt-driven generation, multi-turn editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image","video"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":1.5,"output":30,"cache_read":0.15},"canonical_model_id":"google/gemini-nano-banana-2.1"},"claude-sonnet-5@default":{"id":"claude-sonnet-5@default","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"gemini-4-argon":{"id":"gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":10,"cache_read":0.1,"input_audio":2},"canonical_model_id":"google/gemini-4-argon"},"gemini-3.1-flash-lite":{"id":"gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite"},"meta/llama-4-maverick-17b-128e-instruct-maas":{"id":"meta/llama-4-maverick-17b-128e-instruct-maas","name":"Llama 4 Maverick 17B 128E Instruct","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-29","last_updated":"2025-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":8192},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.35,"output":1.15}},"meta/llama-4-scout-17b-16e-instruct-maas":{"id":"meta/llama-4-scout-17b-16e-instruct-maas","name":"Llama 4 Scout 17B Instruct","description":"Open Llama with long-context vision for efficient multimodal agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1310720,"output":8192},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.25,"output":0.7},"canonical_model_id":"meta/llama-4-scout-17b-instruct"},"meta/llama-3.3-70b-instruct-maas":{"id":"meta/llama-3.3-70b-instruct-maas","name":"Llama 3.3 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2025-04-29","last_updated":"2025-04-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"status":"deprecated","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.72,"output":0.72}},"google/gemma-4-26b-a4b-it-maas":{"id":"google/gemma-4-26b-a4b-it-maas","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":128000},"status":"alpha","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"xai/grok-4.20-reasoning":{"id":"xai/grok-4.20-reasoning","name":"Grok 4.20 (Reasoning)","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-reasoning"},"xai/grok-4.7":{"id":"xai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":500000},"status":"beta","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"xai/grok-4.20-non-reasoning":{"id":"xai/grok-4.20-non-reasoning","name":"Grok 4.20 (Non-Reasoning)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-non-reasoning"},"xai/grok-4.1-fast-reasoning":{"id":"xai/grok-4.1-fast-reasoning","name":"Grok 4.1 Fast (Reasoning)","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":30000},"status":"deprecated","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"xai/grok-4.1-fast-reasoning"},"xai/grok-4.3":{"id":"xai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":30000},"status":"beta","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.3"},"xai/grok-4.1-fast-non-reasoning":{"id":"xai/grok-4.1-fast-non-reasoning","name":"Grok 4.1 Fast","description":"Fast Grok model for responsive chat, tool-assisted work, and low-latency responses","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":30000},"status":"deprecated","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"xai/grok-4.1-fast"},"xai/grok-4.6":{"id":"xai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":500000},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"deepseek-ai/deepseek-v3.1-maas":{"id":"deepseek-ai/deepseek-v3.1-maas","name":"DeepSeek V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-28","last_updated":"2025-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":32768},"status":"deprecated","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.6,"output":1.7,"cache_read":0.06}},"deepseek-ai/deepseek-v3.2-maas":{"id":"deepseek-ai/deepseek-v3.2-maas","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-12-17","last_updated":"2026-04-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":65536},"status":"deprecated","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.56,"output":1.68,"cache_read":0.056}},"moonshotai/kimi-k2-thinking-maas":{"id":"moonshotai/kimi-k2-thinking-maas","name":"Kimi K2 Thinking","description":"Kimi reasoning model for long-horizon research, planning, and tool use","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.6,"output":2.5,"cache_read":0.06}},"zai-org/glm-5-maas":{"id":"zai-org/glm-5-maas","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"status":"deprecated","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":1,"output":3.2,"cache_read":0.1},"canonical_model_id":"zhipuai/glm-5"},"zai-org/glm-4.7-maas":{"id":"zai-org/glm-4.7-maas","name":"GLM-4.7","description":"GLM model for coding, tool use, and complex reasoning","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-06","last_updated":"2026-01-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"status":"deprecated","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.6,"output":2.2,"cache_read":0.06}},"zai-org/glm-5.2-maas":{"id":"zai-org/glm-5.2-maas","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":64000},"status":"beta","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":1.4,"output":4.4,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.2"},"qwen/qwen3-235b-a22b-instruct-2507-maas":{"id":"qwen/qwen3-235b-a22b-instruct-2507-maas","name":"Qwen3 235B A22B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-13","last_updated":"2025-08-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"status":"deprecated","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.22,"output":0.88}},"openai/gpt-oss-20b-maas":{"id":"openai/gpt-oss-20b-maas","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"status":"deprecated","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.07,"output":0.25,"cache_read":0.007}},"openai/gpt-oss-120b-maas":{"id":"openai/gpt-oss-120b-maas","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.09,"output":0.36},"canonical_model_id":"openai/gpt-oss-120b"}}},"evroc":{"id":"evroc","env":["EVROC_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://models.think.evroc.com/v1","name":"evroc","doc":"https://docs.evroc.com/products/think/overview.html","models":{"google/gemma-4-26B-A4B-it":{"id":"google/gemma-4-26B-A4B-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.144,"output":0.575},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"intfloat/multilingual-e5-large-instruct":{"id":"intfloat/multilingual-e5-large-instruct","name":"E5 Multi-Lingual Large Embeddings 0.6B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2024-06-01","last_updated":"2024-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512,"output":512},"cost":{"input":0.114,"output":0.114}},"Qwen/Qwen3.8-27B":{"id":"Qwen/Qwen3.8-27B","name":"Qwen3.8-27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.87,"output":3.5},"canonical_model_id":"alibaba/qwen3.8-27b"},"Qwen/Qwen3-Reranker-4B":{"id":"Qwen/Qwen3-Reranker-4B","name":"Qwen3 Reranker 4B","description":"Reranking model for improving retrieval quality in search and recommendation systems","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":4096},"cost":{"input":0.0575,"output":0}},"Qwen/Qwen3.6-35B-A3B":{"id":"Qwen/Qwen3.6-35B-A3B","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.345,"output":1.38},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"Qwen/Qwen3-Embedding-8B":{"id":"Qwen/Qwen3-Embedding-8B","name":"Qwen3 Embedding 8B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":4096},"cost":{"input":0.115,"output":0.115}},"mistralai/Mistral-Medium-3.5-128B":{"id":"mistralai/Mistral-Medium-3.5-128B","name":"Mistral Medium 3.5","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.725,"output":6.9},"canonical_model_id":"mistral/mistral-medium-2604"},"mistralai/Voxtral-Small-24B-2507":{"id":"mistralai/Voxtral-Small-24B-2507","name":"Voxtral Small 24B","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"voxtral","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2025-03-01","last_updated":"2025-03-01","modalities":{"input":["audio","text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":32000},"cost":{"input":0.0023,"output":0.0023,"output_audio":2.3}},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.4375,"output":5.75},"canonical_model_id":"moonshotai/kimi-k2.6"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":131072},"cost":{"input":1.4375,"output":5.75},"canonical_model_id":"zhipuai/glm-5.2"},"nvidia/Llama-3.3-70B-Instruct-FP8":{"id":"nvidia/Llama-3.3-70B-Instruct-FP8","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":1.15,"output":1.15},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"KBLab/kb-whisper-large":{"id":"KBLab/kb-whisper-large","name":"KB Whisper","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"whisper","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2024-10-01","last_updated":"2024-10-01","modalities":{"input":["audio"],"output":["text"]},"open_weights":true,"limit":{"context":448,"output":448},"cost":{"input":0.0023,"output":0.0023,"output_audio":2.3}},"evroc/roc":{"id":"evroc/roc","name":"roc","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-01","release_date":"2026-06-06","last_updated":"2026-06-06","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":2.875,"output":11.516}},"openai/whisper-large-v3":{"id":"openai/whisper-large-v3","name":"Whisper 3 Large","description":"Open Whisper checkpoint for robust multilingual transcription and captioning","family":"whisper","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2024-10-01","last_updated":"2024-10-01","modalities":{"input":["audio"],"output":["text"]},"open_weights":true,"limit":{"context":448,"output":4096},"cost":{"input":0.0023,"output":0.0023,"output_audio":2.3},"canonical_model_id":"openai/whisper-large-v3"},"openai/whisper-large-v3-turbo":{"id":"openai/whisper-large-v3-turbo","name":"Whisper Large v3 Turbo","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"whisper","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2024-10-01","last_updated":"2024-10-01","modalities":{"input":["audio"],"output":["text"]},"open_weights":true,"limit":{"context":448,"output":448},"cost":{"input":0.0023,"output":0.0023,"output_audio":2.3},"canonical_model_id":"openai/whisper-large-v3-turbo"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.23,"output":0.92}}}},"tokengo":{"id":"tokengo","env":["TOKENGO_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.tokengo.com/v1","name":"TokenGo","doc":"https://www.tokengo.com/docs","models":{"deepseek/deepseek-v3.1":{"id":"deepseek/deepseek-v3.1","name":"DeepSeek-V3.1","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.19,"output":0.71,"cache_read":0.06},"canonical_model_id":"deepseek/deepseek-v3.1"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.435,"output":0.87},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v3.2":{"id":"deepseek/deepseek-v3.2","name":"DeepSeek V3.2","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":64000},"cost":{"input":0.2174,"output":0.326,"cache_read":0.06},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.098,"output":0.196,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.075,"output":0.025,"cache_read":0.015},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-5":{"id":"z-ai/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.89,"output":3.2647,"cache_read":0.2226},"canonical_model_id":"zhipuai/glm-5"},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/glm-5.1":{"id":"z-ai/glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5"},"qwen/qwen3.5-397b-a17b":{"id":"qwen/qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.4,"output":2.65,"cache_read":0.2},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"}}},"submodel":{"id":"submodel","env":["SUBMODEL_INSTAGEN_ACCESS_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://llm.submodel.ai/v1","name":"submodel","doc":"https://submodel.gitbook.io","models":{"Qwen/Qwen3-235B-A22B-Thinking-2507":{"id":"Qwen/Qwen3-235B-A22B-Thinking-2507","name":"Qwen3 235B A22B Thinking 2507","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-08-23","last_updated":"2025-08-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.2,"output":0.6}},"Qwen/Qwen3-235B-A22B-Instruct-2507":{"id":"Qwen/Qwen3-235B-A22B-Instruct-2507","name":"Qwen3 235B A22B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-08-23","last_updated":"2025-08-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.2,"output":0.3}},"Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8":{"id":"Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8","name":"Qwen3 Coder 480B A35B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-08-23","last_updated":"2025-08-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.2,"output":0.8}},"deepseek-ai/DeepSeek-V3.1":{"id":"deepseek-ai/DeepSeek-V3.1","name":"DeepSeek V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-08-23","last_updated":"2025-08-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":75000,"output":163840},"cost":{"input":0.2,"output":0.8}},"deepseek-ai/DeepSeek-R1-0528":{"id":"deepseek-ai/DeepSeek-R1-0528","name":"DeepSeek R1 0528","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-08-23","last_updated":"2025-08-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":75000,"output":163840},"cost":{"input":0.5,"output":2.15}},"deepseek-ai/DeepSeek-V3-0324":{"id":"deepseek-ai/DeepSeek-V3-0324","name":"DeepSeek V3 0324","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-08-23","last_updated":"2025-08-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":75000,"output":163840},"cost":{"input":0.2,"output":0.8}},"zai-org/GLM-4.5-FP8":{"id":"zai-org/GLM-4.5-FP8","name":"GLM 4.5 FP8","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.2,"output":0.8}},"zai-org/GLM-4.5-Air":{"id":"zai-org/GLM-4.5-Air","name":"GLM 4.5 Air","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-air","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.1,"output":0.5}},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-08-23","last_updated":"2025-08-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.1,"output":0.5}}}},"kosmik":{"id":"kosmik","env":["KOSMIK_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.koscompute.com/v1","name":"Kosmik Compute","doc":"https://api.koscompute.com/docs/","models":{"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.35,"output":2.2,"cache_read":0.09},"canonical_model_id":"alibaba/qwen3.8-27b"}}},"tencent-token-plan":{"id":"tencent-token-plan","env":["TENCENT_TOKEN_PLAN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.lkeap.cloud.tencent.com/plan/v3","name":"Tencent Token Plan","doc":"https://cloud.tencent.com/document/product/1823/130060","models":{"hy3":{"id":"hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":192000,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"tencent/hy3"},"hy4-preview":{"id":"hy4-preview","name":"Hy4 preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":64000},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"}}},"togetherai":{"id":"togetherai","env":["TOGETHER_API_KEY"],"npm":"@ai-sdk/togetherai","name":"Together AI","doc":"https://docs.together.ai/docs/serverless-models","models":{"meta-llama/Llama-3.3-70B-Instruct-Turbo":{"id":"meta-llama/Llama-3.3-70B-Instruct-Turbo","name":"Llama 3.3 70B","description":"Compact Llama instruction model for fast chat and local deployment","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":1.04,"output":1.04}},"thinkingmachines/Inkling":{"id":"thinkingmachines/Inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["max","xhigh","high","medium","low","none"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":131072},"cost":{"input":1,"output":4.05,"cache_read":0.17},"canonical_model_id":"thinkingmachines/inkling"},"essentialai/Rnj-1-Instruct":{"id":"essentialai/Rnj-1-Instruct","name":"Rnj-1 Instruct","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","family":"rnj","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-12-05","last_updated":"2025-12-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0.15,"output":0.15}},"Qwen/Qwen3.7-Max":{"id":"Qwen/Qwen3.7-Max","name":"Qwen3.7 Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":500000},"cost":{"input":1.25,"output":3.75,"cache_read":0.125}},"Qwen/Qwen2.5-7B-Instruct-Turbo":{"id":"Qwen/Qwen2.5-7B-Instruct-Turbo","name":"Qwen 2.5 7B Instruct Turbo","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-09-19","last_updated":"2024-09-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.3,"output":0.3}},"Qwen/Qwen3-Coder-Next-FP8":{"id":"Qwen/Qwen3-Coder-Next-FP8","name":"Qwen3 Coder Next FP8","description":"Legacy model retained for compatibility with older integrations","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2026-02-03","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.5,"output":1.2}},"Qwen/Qwen3-235B-A22B-Instruct-2507-tput":{"id":"Qwen/Qwen3-235B-A22B-Instruct-2507-tput","name":"Qwen3 235B A22B Instruct 2507 FP8","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-07","release_date":"2025-07-25","last_updated":"2025-07-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.2,"output":0.6}},"Qwen/Qwen3.5-9B":{"id":"Qwen/Qwen3.5-9B","name":"Qwen3.5 9B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.17,"output":0.25}},"Qwen/Qwen3.5-397B-A17B":{"id":"Qwen/Qwen3.5-397B-A17B","name":"Qwen3.5 397B A17B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-02-16","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":130000},"status":"deprecated","cost":{"input":0.6,"output":3.6,"cache_read":0.35}},"Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8":{"id":"Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8","name":"Qwen3 Coder 480B A35B Instruct","description":"Legacy model retained for compatibility with older integrations","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":2,"output":2}},"Qwen/Qwen3.6-Plus":{"id":"Qwen/Qwen3.6-Plus","name":"Qwen3.6 Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":500000},"cost":{"input":0.5,"output":3}},"LiquidAI/LFM2-24B-A2B":{"id":"LiquidAI/LFM2-24B-A2B","name":"LFM2-24B-A2B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","family":"liquid","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-02-25","last_updated":"2026-02-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.03,"output":0.12}},"deepseek-ai/DeepSeek-V4-Flash-0731":{"id":"deepseek-ai/DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek-ai/DeepSeek-R1":{"id":"deepseek-ai/DeepSeek-R1","name":"DeepSeek-R1","description":"Legacy model retained for compatibility with older integrations","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163839,"output":163839},"status":"deprecated","cost":{"input":3,"output":7}},"deepseek-ai/DeepSeek-V4-Pro-0813":{"id":"deepseek-ai/DeepSeek-V4-Pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":1.32,"output":3.96,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek-ai/DeepSeek-V4.1-Flash":{"id":"deepseek-ai/DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek-ai/DeepSeek-V3-1":{"id":"deepseek-ai/DeepSeek-V3-1","name":"DeepSeek V3.1","description":"Legacy model retained for compatibility with older integrations","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-08","release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"status":"deprecated","cost":{"input":0.6,"output":1.7}},"deepseek-ai/DeepSeek-V3":{"id":"deepseek-ai/DeepSeek-V3","name":"DeepSeek-V3","description":"Legacy model retained for compatibility with older integrations","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-12-26","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"status":"deprecated","cost":{"input":1.25,"output":1.25}},"MiniMaxAI/MiniMax-M3":{"id":"MiniMaxAI/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":250000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06}},"MiniMaxAI/MiniMax-M2.5":{"id":"MiniMaxAI/MiniMax-M2.5","name":"MiniMax-M2.5","description":"Legacy model retained for compatibility with older integrations","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","cost":{"input":0.3,"output":1.2,"cache_read":0.06}},"MiniMaxAI/MiniMax-M2.7":{"id":"MiniMaxAI/MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7"},"moonshotai/Kimi-K3":{"id":"moonshotai/Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"zai-org/GLM-5.1":{"id":"zai-org/GLM-5.1","name":"GLM-5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-11","release_date":"2026-04-07","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"status":"deprecated","cost":{"input":1.4,"output":4.4,"cache_read":0.26}},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-16","last_updated":"2026-06-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048575,"output":164000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-5":{"id":"zai-org/GLM-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-11","last_updated":"2026-02-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"status":"deprecated","cost":{"input":1,"output":3.2},"canonical_model_id":"zhipuai/glm-5"},"zai-org/GLM-5.3-Flash":{"id":"zai-org/GLM-5.3-Flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048575,"output":400000},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/GLM-5.3":{"id":"zai-org/GLM-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"nvidia/nemotron-3-ultra-550b-a55b":{"id":"nvidia/nemotron-3-ultra-550b-a55b","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512300,"output":512300},"cost":{"input":0.6,"output":3.6,"cache_read":0.2},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.15,"output":0.6}}}},"helicone":{"id":"helicone","env":["HELICONE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://ai-gateway.helicone.ai/v1","name":"Helicone","doc":"https://helicone.ai/models","models":{"grok-4-1-fast-reasoning":{"id":"grok-4-1-fast-reasoning","name":"xAI Grok 4.1 Fast Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-11","release_date":"2025-11-17","last_updated":"2025-11-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":0.19999999999999998,"output":0.5,"cache_read":0.049999999999999996}},"grok-3":{"id":"grok-3","name":"xAI Grok 3","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2024-06-01","last_updated":"2024-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.75}},"llama-4-scout":{"id":"llama-4-scout","name":"Meta Llama 4 Scout 17B 16E","description":"Open multimodal Llama model for long-context analysis and efficient agents","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.08,"output":0.3}},"llama-guard-4":{"id":"llama-guard-4","name":"Meta Llama Guard 4 12B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":1024},"cost":{"input":0.21,"output":0.21}},"mistral-large-2411":{"id":"mistral-large-2411","name":"Mistral-Large","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-24","last_updated":"2024-07-24","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32768},"cost":{"input":2,"output":6}},"grok-4-1-fast-non-reasoning":{"id":"grok-4-1-fast-non-reasoning","name":"xAI Grok 4.1 Fast Non-Reasoning","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"grok","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-11","release_date":"2025-11-17","last_updated":"2025-11-17","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":0.19999999999999998,"output":0.5,"cache_read":0.049999999999999996}},"qwen3-vl-235b-a22b-instruct":{"id":"qwen3-vl-235b-a22b-instruct","name":"Qwen3 VL 235B A22B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":16384},"cost":{"input":0.3,"output":1.5}},"mistral-nemo":{"id":"mistral-nemo","name":"Mistral Nemo","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16400},"cost":{"input":20,"output":40}},"gpt-5.1-codex":{"id":"gpt-5.1-codex","name":"OpenAI: GPT-5.1 Codex","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-codex","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2025-01","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.12500000000000003}},"gemini-3-pro-preview":{"id":"gemini-3-pro-preview","name":"Google Gemini 3 Pro Preview","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-11","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.19999999999999998}},"gpt-4o":{"id":"gpt-4o","name":"OpenAI GPT-4o","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-05","release_date":"2024-05-13","last_updated":"2024-05-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25}},"gpt-4.1-mini-2025-04-14":{"id":"gpt-4.1-mini-2025-04-14","name":"OpenAI GPT-4.1 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.39999999999999997,"output":1.5999999999999999,"cache_read":0.09999999999999999}},"glm-4.6":{"id":"glm-4.6","name":"Zai GLM-4.6","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":204800,"output":131072},"cost":{"input":0.44999999999999996,"output":1.5}},"claude-3.5-haiku":{"id":"claude-3.5-haiku","name":"Anthropic: Claude 3.5 Haiku","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":0.7999999999999999,"output":4,"cache_read":0.08,"cache_write":1}},"o1-mini":{"id":"o1-mini","name":"OpenAI: o1-mini","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-mini","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-01","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":65536},"cost":{"input":1.1,"output":4.4,"cache_read":0.55}},"grok-4":{"id":"grok-4","name":"xAI Grok 4","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-09","last_updated":"2024-07-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":3,"output":15,"cache_read":0.75}},"gpt-5-codex":{"id":"gpt-5-codex","name":"OpenAI: GPT-5 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2025-01","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.12500000000000003}},"llama-4-maverick":{"id":"llama-4-maverick","name":"Meta Llama 4 Maverick 17B 128E","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.15,"output":0.6}},"qwen3-coder":{"id":"qwen3-coder","name":"Qwen3 Coder 480B A35B Instruct Turbo","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-07","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":16384},"cost":{"input":0.22,"output":0.95}},"gpt-5-mini":{"id":"gpt-5-mini","name":"OpenAI GPT-5 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2025-01","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.024999999999999998}},"o4-mini":{"id":"o4-mini","name":"OpenAI o4 Mini","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-mini","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2024-06","release_date":"2024-06-01","last_updated":"2024-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.275}},"o3-mini":{"id":"o3-mini","name":"OpenAI o3 Mini","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-mini","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2023-10","release_date":"2023-10-01","last_updated":"2023-10-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55}},"kimi-k2-0711":{"id":"kimi-k2-0711","name":"Kimi K2 (07/11)","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"cost":{"input":0.5700000000000001,"output":2.3}},"gpt-4.1-nano":{"id":"gpt-4.1-nano","name":"OpenAI GPT-4.1 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.09999999999999999,"output":0.39999999999999997,"cache_read":0.024999999999999998}},"grok-4-fast-reasoning":{"id":"grok-4-fast-reasoning","name":"xAI: Grok 4 Fast Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-09-01","last_updated":"2025-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":0.19999999999999998,"output":0.5,"cache_read":0.049999999999999996}},"qwen3-32b":{"id":"qwen3-32b","name":"Qwen3 32B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":40960},"cost":{"input":0.29,"output":0.59}},"gpt-5-nano":{"id":"gpt-5-nano","name":"OpenAI GPT-5 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2025-01","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.049999999999999996,"output":0.39999999999999997,"cache_read":0.005}},"claude-3.5-sonnet-v2":{"id":"claude-3.5-sonnet-v2","name":"Anthropic: Claude 3.5 Sonnet v2","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":3,"output":15,"cache_read":0.30000000000000004,"cache_write":3.75}},"gpt-5.1-chat-latest":{"id":"gpt-5.1-chat-latest","name":"OpenAI GPT-5.1 Chat","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-codex","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2025-01","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1.25,"output":10,"cache_read":0.12500000000000003}},"claude-4.5-sonnet":{"id":"claude-4.5-sonnet","name":"Anthropic: Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.30000000000000004,"cache_write":3.75}},"deepseek-tng-r1t2-chimera":{"id":"deepseek-tng-r1t2-chimera","name":"DeepSeek TNG R1T2 Chimera","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek-thinking","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-07","release_date":"2025-07-02","last_updated":"2025-07-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":130000,"output":163840},"cost":{"input":0.3,"output":1.2}},"deepseek-v3":{"id":"deepseek-v3","name":"DeepSeek V3","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2024-12-26","last_updated":"2024-12-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.56,"output":1.68,"cache_read":0.07}},"deepseek-r1-distill-llama-70b":{"id":"deepseek-r1-distill-llama-70b","name":"DeepSeek R1 Distill Llama 70B","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-01-20","last_updated":"2025-01-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":0.03,"output":0.13}},"o1":{"id":"o1","name":"OpenAI: o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-01","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":15,"output":60,"cache_read":7.5}},"mistral-small":{"id":"mistral-small","name":"Mistral Small 3.2","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.075,"output":0.2},"canonical_model_id":"mistral/mistral-small-2506"},"chatgpt-4o-latest":{"id":"chatgpt-4o-latest","name":"OpenAI ChatGPT-4o","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2024-08-14","last_updated":"2024-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":5,"output":20,"cache_read":2.5}},"qwen3-coder-30b-a3b-instruct":{"id":"qwen3-coder-30b-a3b-instruct","name":"Qwen3 Coder 30B A3B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-07","release_date":"2025-07-31","last_updated":"2025-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.09999999999999999,"output":0.3}},"sonar-pro":{"id":"sonar-pro","name":"Perplexity Sonar Pro","description":"Advanced Sonar search model for deeper research and cited synthesis","family":"sonar-pro","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-01-27","last_updated":"2025-01-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":4096},"cost":{"input":3,"output":15}},"kimi-k2-thinking":{"id":"kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Kimi reasoning model for long-horizon research, planning, and tool use","family":"kimi-thinking","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-11","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":262144},"cost":{"input":0.48,"output":2}},"grok-4-fast-non-reasoning":{"id":"grok-4-fast-non-reasoning","name":"xAI Grok 4 Fast Non-Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-09-19","last_updated":"2025-09-19","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":0.19999999999999998,"output":0.5,"cache_read":0.049999999999999996}},"claude-opus-4-1-20250805":{"id":"claude-opus-4-1-20250805","name":"Anthropic: Claude Opus 4.1 (20250805)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":31999}],"tool_call":true,"temperature":true,"knowledge":"2025-08","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75}},"gpt-5-pro":{"id":"gpt-5-pro","name":"OpenAI: GPT-5 Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-01","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32768},"cost":{"input":15,"output":120}},"gpt-5-chat-latest":{"id":"gpt-5-chat-latest","name":"OpenAI GPT-5 Chat Latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt-codex","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2024-09","release_date":"2024-09-30","last_updated":"2024-09-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1.25,"output":10,"cache_read":0.12500000000000003}},"deepseek-v3.1-terminus":{"id":"deepseek-v3.1-terminus","name":"DeepSeek V3.1 Terminus","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-09-22","last_updated":"2025-09-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.27,"output":1,"cache_read":0.21600000000000003}},"claude-opus-4-1":{"id":"claude-opus-4-1","name":"Anthropic: Claude Opus 4.1","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":31999}],"tool_call":true,"temperature":true,"knowledge":"2025-08","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75}},"gpt-5.1":{"id":"gpt-5.1","name":"OpenAI GPT-5.1","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2025-01","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.12500000000000003}},"llama-3.3-70b-versatile":{"id":"llama-3.3-70b-versatile","name":"Meta Llama 3.3 70B Versatile","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32678},"cost":{"input":0.59,"output":0.7899999999999999}},"llama-3.3-70b-instruct":{"id":"llama-3.3-70b-instruct","name":"Meta Llama 3.3 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16400},"cost":{"input":0.13,"output":0.39}},"grok-3-mini":{"id":"grok-3-mini","name":"xAI Grok 3 Mini","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2024-06-01","last_updated":"2024-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":131072},"cost":{"input":0.3,"output":0.5,"cache_read":0.075}},"gemma-3-12b-it":{"id":"gemma-3-12b-it","name":"Google Gemma 3 12B","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-12","release_date":"2024-12-01","last_updated":"2024-12-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.049999999999999996,"output":0.09999999999999999}},"qwen2.5-coder-7b-fast":{"id":"qwen2.5-coder-7b-fast","name":"Qwen2.5 Coder 7B fast","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-09","release_date":"2024-09-15","last_updated":"2024-09-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":8192},"cost":{"input":0.03,"output":0.09}},"gpt-4o-mini":{"id":"gpt-4o-mini","name":"OpenAI GPT-4o-mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075}},"qwen3-next-80b-a3b-instruct":{"id":"qwen3-next-80b-a3b-instruct","name":"Qwen3 Next 80B A3B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":16384},"cost":{"input":0.14,"output":1.4}},"o3-pro":{"id":"o3-pro","name":"OpenAI o3 Pro","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-pro","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2024-06","release_date":"2024-06-01","last_updated":"2024-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":20,"output":80}},"gpt-oss-20b":{"id":"gpt-oss-20b","name":"OpenAI GPT-OSS 20b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2024-06-01","last_updated":"2024-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":131072},"cost":{"input":0.049999999999999996,"output":0.19999999999999998}},"gemini-2.5-pro":{"id":"gemini-2.5-pro","name":"Google Gemini 2.5 Pro","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.3125,"cache_write":1.25}},"sonar-deep-research":{"id":"sonar-deep-research","name":"Perplexity Sonar Deep Research","description":"Sonar search model for current answers, retrieval, and citation-backed chat","family":"sonar-deep-research","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-01-27","last_updated":"2025-01-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":127000,"output":4096},"cost":{"input":2,"output":8}},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"Google Gemini 2.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.3,"output":2.5,"cache_read":0.075,"cache_write":0.3}},"claude-4.5-haiku":{"id":"claude-4.5-haiku","name":"Anthropic: Claude 4.5 Haiku","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-10","release_date":"2025-10-01","last_updated":"2025-10-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":1,"output":5,"cache_read":0.09999999999999999,"cache_write":1.25}},"gemma2-9b-it":{"id":"gemma2-9b-it","name":"Google Gemma 2","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-06","release_date":"2024-06-25","last_updated":"2024-06-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8192},"cost":{"input":0.01,"output":0.03}},"claude-3.7-sonnet":{"id":"claude-3.7-sonnet","name":"Anthropic: Claude 3.7 Sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-02","release_date":"2025-02-19","last_updated":"2025-02-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.30000000000000004,"cache_write":3.75}},"hermes-2-pro-llama-3-8b":{"id":"hermes-2-pro-llama-3-8b","name":"Hermes 2 Pro Llama 3 8B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-05","release_date":"2024-05-27","last_updated":"2024-05-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":131072},"cost":{"input":0.14,"output":0.14}},"claude-sonnet-4":{"id":"claude-sonnet-4","name":"Anthropic: Claude Sonnet 4","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-05-14","last_updated":"2025-05-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.30000000000000004,"cache_write":3.75}},"qwen3-235b-a22b-thinking":{"id":"qwen3-235b-a22b-thinking","name":"Qwen3 235B A22B Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2025-07","release_date":"2025-07-25","last_updated":"2025-07-25","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":81920},"cost":{"input":0.3,"output":2.9000000000000004}},"grok-code-fast-1":{"id":"grok-code-fast-1","name":"xAI Grok Code Fast 1","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2024-08-25","last_updated":"2024-08-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":10000},"cost":{"input":0.19999999999999998,"output":1.5,"cache_read":0.02}},"claude-sonnet-4-5-20250929":{"id":"claude-sonnet-4-5-20250929","name":"Anthropic: Claude Sonnet 4.5 (20250929)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.30000000000000004,"cache_write":3.75}},"gpt-4.1":{"id":"gpt-4.1","name":"OpenAI GPT-4.1","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5}},"qwen3-30b-a3b":{"id":"qwen3-30b-a3b","name":"Qwen3 30B A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2025-06-01","last_updated":"2025-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":41000,"output":41000},"cost":{"input":0.08,"output":0.29}},"kimi-k2-0905":{"id":"kimi-k2-0905","name":"Kimi K2 (09/05)","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":16384},"cost":{"input":0.5,"output":2,"cache_read":0.39999999999999997}},"llama-3.1-8b-instruct":{"id":"llama-3.1-8b-instruct","name":"Meta Llama 3.1 8B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":16384},"cost":{"input":0.02,"output":0.049999999999999996}},"llama-3.1-8b-instruct-turbo":{"id":"llama-3.1-8b-instruct-turbo","name":"Meta Llama 3.1 8B Instruct Turbo","description":"Compact Llama instruction model for fast chat and local deployment","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000},"cost":{"input":0.02,"output":0.03}},"llama-prompt-guard-2-86m":{"id":"llama-prompt-guard-2-86m","name":"Meta Llama Prompt Guard 2 86M","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-10","release_date":"2024-10-01","last_updated":"2024-10-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":512,"output":2},"cost":{"input":0.01,"output":0.01}},"claude-haiku-4-5-20251001":{"id":"claude-haiku-4-5-20251001","name":"Anthropic: Claude 4.5 Haiku (20251001)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-10","release_date":"2025-10-01","last_updated":"2025-10-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":1,"output":5,"cache_read":0.09999999999999999,"cache_write":1.25}},"sonar":{"id":"sonar","name":"Perplexity Sonar","description":"Sonar search model for current answers, retrieval, and citation-backed chat","family":"sonar","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-01-27","last_updated":"2025-01-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":127000,"output":4096},"cost":{"input":1,"output":1}},"deepseek-reasoner":{"id":"deepseek-reasoner","name":"DeepSeek Reasoner","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-01-20","last_updated":"2025-01-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"cost":{"input":0.56,"output":1.68,"cache_read":0.07}},"gpt-4.1-mini":{"id":"gpt-4.1-mini","name":"OpenAI GPT-4.1 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.39999999999999997,"output":1.5999999999999999,"cache_read":0.09999999999999999}},"ernie-4.5-21b-a3b-thinking":{"id":"ernie-4.5-21b-a3b-thinking","name":"Baidu Ernie 4.5 21B A3B Thinking","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"ernie","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2025-03","release_date":"2025-03-16","last_updated":"2025-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8000},"cost":{"input":0.07,"output":0.28}},"claude-4.5-opus":{"id":"claude-4.5-opus","name":"Anthropic: Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-11","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"gemini-2.5-flash-lite":{"id":"gemini-2.5-flash-lite","name":"Google Gemini 2.5 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":512,"max":24576}],"tool_call":true,"temperature":true,"knowledge":"2025-07","release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.09999999999999999,"output":0.39999999999999997,"cache_read":0.024999999999999998,"cache_write":0.09999999999999999}},"claude-3-haiku-20240307":{"id":"claude-3-haiku-20240307","name":"Anthropic: Claude 3 Haiku","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-03","release_date":"2024-03-07","last_updated":"2024-03-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":4096},"cost":{"input":0.25,"output":1.25,"cache_read":0.03,"cache_write":0.3}},"sonar-reasoning-pro":{"id":"sonar-reasoning-pro","name":"Perplexity Sonar Reasoning Pro","description":"Web-grounded reasoning model for multi-step research and cited answers","family":"sonar-reasoning","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-01-27","last_updated":"2025-01-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":127000,"output":4096},"cost":{"input":2,"output":8}},"deepseek-v3.2":{"id":"deepseek-v3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-09-22","last_updated":"2025-09-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":163840,"output":65536},"cost":{"input":0.27,"output":0.41}},"llama-prompt-guard-2-22m":{"id":"llama-prompt-guard-2-22m","name":"Meta Llama Prompt Guard 2 22M","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-10","release_date":"2024-10-01","last_updated":"2024-10-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":512,"output":2},"cost":{"input":0.01,"output":0.01}},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"OpenAI GPT-OSS 120b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2024-06-01","last_updated":"2024-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":131072},"cost":{"input":0.04,"output":0.16}},"gpt-5.1-codex-mini":{"id":"gpt-5.1-codex-mini","name":"OpenAI: GPT-5.1 Codex Mini","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-codex","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2025-01","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.024999999999999998}},"o3":{"id":"o3","name":"OpenAI o3","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2024-06","release_date":"2024-06-01","last_updated":"2024-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5}},"gpt-5":{"id":"gpt-5","name":"OpenAI GPT-5","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2025-01","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.12500000000000003}},"llama-3.1-8b-instant":{"id":"llama-3.1-8b-instant","name":"Meta Llama 3.1 8B Instant","description":"Compact Llama instruction model for fast chat and local deployment","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32678},"cost":{"input":0.049999999999999996,"output":0.08}},"sonar-reasoning":{"id":"sonar-reasoning","name":"Perplexity Sonar Reasoning","description":"Web-grounded reasoning model for multi-step research and cited answers","family":"sonar-reasoning","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-01-27","last_updated":"2025-01-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":127000,"output":4096},"cost":{"input":1,"output":5}},"claude-opus-4":{"id":"claude-opus-4","name":"Anthropic: Claude Opus 4","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":31999}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-05-14","last_updated":"2025-05-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75}}}},"cortecs":{"id":"cortecs","env":["CORTECS_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.cortecs.ai/v1","name":"Cortecs","doc":"https://api.cortecs.ai/v1/models","models":{"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2.898,"output":15.453,"cache_read":0.242},"canonical_model_id":"openai/gpt-5.4"},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":0.996,"output":4.982,"cache_read":0.099,"cache_write":1.186},"canonical_model_id":"anthropic/claude-haiku-4-5"},"gpt-oss-safeguard-120b":{"id":"gpt-oss-safeguard-120b","name":"GPT OSS Safeguard 120B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0.179,"output":0.697},"canonical_model_id":"openai/gpt-oss-safeguard-120b"},"gemma-4-31b-it":{"id":"gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.223,"output":0.39},"canonical_model_id":"google/gemma-4-31b-it"},"qwen3.8-27b":{"id":"qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":500000},"cost":{"input":0.1,"output":0.4,"cache_read":0.04},"canonical_model_id":"alibaba/qwen3.8-27b"},"gemma-3-27b-it":{"id":"gemma-3-27b-it","name":"Gemma 3 27B IT","description":"Gemma 3 is a family of lightweight, multimodal models from Google, supporting text and image inputs, multilingual capabilities, and a 131K context window.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":false,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":110000},"cost":{"input":0.099,"output":0.299},"canonical_model_id":"google/gemma-3-27b-it"},"qwen3.8-2.4t-a95b":{"id":"qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":2.5,"output":6,"cache_read":0.625},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"mistral-large-2402":{"id":"mistral-large-2402","name":"mistral-large-2402","description":"Mistral Large (24.02) is Mistral AI’s most advanced language model, built for complex multilingual reasoning, code generation, and deep text understanding.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2025-05-26","last_updated":"2025-05-26","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":8192},"cost":{"input":4.284,"output":12.952}},"gpt-4o":{"id":"gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16000},"cost":{"input":2.659,"output":10.635,"cache_read":1.33},"canonical_model_id":"openai/gpt-4o"},"qwen3guard-gen-8b":{"id":"qwen3guard-gen-8b","name":"qwen3guard-gen-8b","description":"Qwen3Guard-Gen-8B is a large-scale multilingual safety moderation model designed for high-accuracy prompt and response classification.","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-02-04","last_updated":"2026-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":32000},"cost":{"input":0,"output":0}},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.1,"output":0.35,"cache_read":0.018},"canonical_model_id":"zhipuai/glm-5.3-flash"},"ministral-8b-2512":{"id":"ministral-8b-2512","name":"Ministral 3 8B 2512","description":"Ministral 3 8B is a balanced, efficient multimodal model offering strong text and vision capabilities, optimized for edge and local deployment.","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.179,"output":0.179,"cache_read":0.017},"canonical_model_id":"mistral/ministral-8b-2512"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.09,"output":0.17,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"mistral-7b-instruct-v0.2":{"id":"mistral-7b-instruct-v0.2","name":"mistral-7b-instruct-v0.2","description":"Mistral 7B Instruct is a compact, 7B parameter model optimized for fast and efficient text and code generation with a 32K token context window.","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2025-05-26","last_updated":"2025-05-26","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":8192},"cost":{"input":0.159,"output":0.219}},"qwen3-235b-a22b-instruct-2507":{"id":"qwen3-235b-a22b-instruct-2507","name":"Qwen3 235B-A22B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.199,"output":0.598,"cache_read":0.018},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":3,"output":14.999},"canonical_model_id":"moonshotai/kimi-k3"},"qwen3-coder-next":{"id":"qwen3-coder-next","name":"Qwen3 Coder Next","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.167,"output":0.891},"canonical_model_id":"alibaba/qwen3-coder-next"},"nova-lite-v1":{"id":"nova-lite-v1","name":"Nova Lite 1.0","description":"Nova Lite is a fast, low-cost multimodal foundation model capable of reasoning over text, images, and video in 200+ languages.","family":"nova-lite","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.069,"output":0.275},"canonical_model_id":"amazon/nova-lite-v1"},"claude-haiku-5.5":{"id":"claude-haiku-5.5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.113,"output":0.563,"cache_read":0.011,"cache_write":0.14},"canonical_model_id":"anthropic/claude-haiku-5-5"},"apertus-70b":{"id":"apertus-70b","name":"Apertus 70B","description":"Apertus 70B is an open, multilingual language model designed for research, long-context reasoning, and sovereignty-focused AI systems.","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-09","release_date":"2025-09-02","last_updated":"2025-09-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":16384},"cost":{"input":1.393,"output":2.228},"canonical_model_id":"swiss-ai/apertus-70b"},"gpt-5-mini":{"id":"gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.279,"output":2.192,"cache_read":0.056},"canonical_model_id":"openai/gpt-5-mini"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.201,"output":0.6,"cache_read":0.004},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"gpt-4.1-nano":{"id":"gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.111,"output":0.434,"cache_read":0.056},"canonical_model_id":"openai/gpt-4.1-nano"},"minimax-m2.5":{"id":"minimax-m2.5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196000,"output":196000},"cost":{"input":0.348,"output":1.39,"cache_read":0.075},"canonical_model_id":"minimax/MiniMax-M2.5"},"qwen3-32b":{"id":"qwen3-32b","name":"Qwen3 32B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":16384},"cost":{"input":0.179,"output":0.697},"canonical_model_id":"alibaba/qwen3-32b"},"mistral-medium-3.5":{"id":"mistral-medium-3.5","name":"mistral-medium-3.5","description":"Mistral Medium 3.5 is a frontier multimodal 128B model combining reasoning, coding, and instruction-following with strong agentic performance and efficient deployment.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1.532,"output":7.843,"cache_read":0.154}},"gpt-5-nano":{"id":"gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.06,"output":0.439,"cache_read":0.019},"canonical_model_id":"openai/gpt-5-nano"},"claude-4-6-sonnet":{"id":"claude-4-6-sonnet","name":"Claude Sonnet 4.6","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3.196,"output":15.94,"cache_read":0.32,"cache_write":3.999},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Kimi reasoning model for long-horizon research, planning, and tool use","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.475,"output":2.97,"cache_read":0.1},"canonical_model_id":"moonshotai/kimi-k2.6"},"claude-4-5-sonnet":{"id":"claude-4-5-sonnet","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":2.989,"output":14.945,"cache_read":0.326,"cache_write":4.078},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"devstral-2512":{"id":"devstral-2512","name":"Devstral 2","description":"Mistral coding agent model for repository tasks and software engineering workflows","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.478,"output":2.392,"cache_read":0.045},"canonical_model_id":"mistral/devstral-2512"},"gemini-3.6-flash":{"id":"gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.038},"canonical_model_id":"google/gemini-3.6-flash"},"mistral-7b-instruct-v0.3":{"id":"mistral-7b-instruct-v0.3","name":"mistral-7b-instruct-v0.3","description":"Mistral-7B-Instruct-v0.3 model is a fine-tuned version of the Mistral 7B base model, optimized for instruction-following tasks. Released in 2023, it is intended for demonstration purposes and does not include built-in guardrails or moderation features.","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2025-05-26","last_updated":"2025-05-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":127000,"output":127000},"cost":{"input":0.111,"output":0.111}},"qwen3-coder-30b-a3b-instruct":{"id":"qwen3-coder-30b-a3b-instruct","name":"Qwen3-Coder 30B-A3B Instruct","description":"Smaller Qwen coder for efficient local agents and repo-level fixes","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.179,"output":0.697,"cache_read":0.014},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"mixtral-8x7B-instruct-v0.1":{"id":"mixtral-8x7B-instruct-v0.1","name":"Mixtral 8x7B Instruct v0.1","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2023-12-11","last_updated":"2023-12-11","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":4096},"cost":{"input":0.488,"output":0.758}},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.4,"output":11.999,"cache_read":0.12,"cache_write":3},"canonical_model_id":"openai/gpt-6.1-sol"},"gemma-4-26b-a4b-it":{"id":"gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":81920},"cost":{"input":0.111,"output":0.557},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"gemini-3.5-flash-lite":{"id":"gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.33,"output":2.749,"cache_read":0.033,"cache_write":0.082},"canonical_model_id":"google/gemini-3.5-flash-lite"},"voxtral-small-2507":{"id":"voxtral-small-2507","name":"voxtral-small-2507","description":"Voxtral Small is a multimodal model with audio input, combining advanced speech capabilities with strong text performance for transcription, translation, and audio understanding.","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-02-02","last_updated":"2026-02-02","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":32000},"cost":{"input":0.123,"output":0.368,"cache_read":0.012}},"gpt-5.1":{"id":"gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.375,"output":10.96,"cache_read":0.156},"canonical_model_id":"openai/gpt-5.1"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.498,"cache_read":0.55,"cache_write":6.874},"canonical_model_id":"anthropic/claude-opus-5"},"llama-3.3-70b-instruct":{"id":"llama-3.3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":131000},"cost":{"input":0.724,"output":0.724},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"qwen3guard-gen-0.6b":{"id":"qwen3guard-gen-0.6b","name":"qwen3guard-gen-0.6b","description":"Qwen3Guard-Gen-0.6B is a lightweight multilingual safety moderation model that classifies prompts and responses into safe, controversial, or unsafe categories.","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-02-04","last_updated":"2026-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":32000},"cost":{"input":0,"output":0}},"gpt-4o-mini":{"id":"gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16000},"cost":{"input":0.159,"output":0.638,"cache_read":0.081},"canonical_model_id":"openai/gpt-4o-mini"},"qwen3.6-35b-a3b":{"id":"qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":32768},"cost":{"input":0.167,"output":0.557},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"pixtral-12b-2409":{"id":"pixtral-12b-2409","name":"pixtral-12b-2409","description":"Pixtral 2409 12B is a state-of-the-art multimodal model with 12B parameters and a 400M vision encoder, natively trained on interleaved text and image data. It excels in tasks spanning vision-language reasoning, instruction following, and pure text understanding, making it highly effective for real-world multimodal applications.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2024-11-09","last_updated":"2024-11-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":0.223,"output":0.223}},"claude-sonnet-5.5":{"id":"claude-sonnet-5.5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.25,"output":11.249,"cache_read":0.225,"cache_write":2.813},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"gpt-oss-20b":{"id":"gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":131000},"cost":{"input":0.045,"output":0.167},"canonical_model_id":"openai/gpt-oss-20b"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":1.649,"output":9.899,"cache_read":0.165,"cache_write":1},"canonical_model_id":"google/gemini-3.5-flash"},"gemini-2.5-pro":{"id":"gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":1.495,"output":9.964,"cache_read":0.242,"cache_write":0.434},"canonical_model_id":"google/gemini-2.5-pro"},"hermes-4-405b":{"id":"hermes-4-405b","name":"Hermes 4 405B","description":"Hermes 4 405B is a frontier hybrid-mode reasoning model built on Llama 3.1, optimized for advanced logic, math, coding, and structured output generation.","family":"hermes","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-08-31","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0.996,"output":2.989},"canonical_model_id":"nousresearch/hermes-4-405b"},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.299,"output":2.491,"cache_read":0.029,"cache_write":0.097},"canonical_model_id":"google/gemini-2.5-flash"},"qwen3-vl-235b-a22b":{"id":"qwen3-vl-235b-a22b","name":"qwen3-vl-235b-a22b","description":"Qwen3 VL 235B A22B is a 235B-parameter MoE vision-language flagship model (≈22B active) designed for frontier-level multimodal understanding across text, images, documents, and long videos.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-01-13","last_updated":"2026-01-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.617,"output":3.119,"cache_read":0.052}},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":64000},"cost":{"input":2,"output":3.999,"cache_read":0.5},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"glm-4.7-flash":{"id":"glm-4.7-flash","name":"GLM-4.7-Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":203000,"output":203000},"cost":{"input":0.08,"output":0.478},"canonical_model_id":"zhipuai/glm-4.7-flash"},"qwen3.5-9b":{"id":"qwen3.5-9b","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.111,"output":0.167},"canonical_model_id":"alibaba/qwen3.5-9b"},"claude-opus4-6":{"id":"claude-opus4-6","name":"Claude Opus 4.6","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.313,"output":26.561,"cache_read":0.531,"cache_write":6.645},"canonical_model_id":"anthropic/claude-opus-4-6"},"claude-sonnet-4":{"id":"claude-sonnet-4","name":"Claude Sonnet 4 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":65000},"cost":{"input":2.989,"output":14.945,"cache_read":0.296,"cache_write":3.707},"canonical_model_id":"anthropic/claude-sonnet-4-0"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.219,"output":1.32,"cache_read":0.022,"cache_write":0.275},"canonical_model_id":"openai/gpt-5.6-luna"},"qwen3.8-flash-next":{"id":"qwen3.8-flash-next","name":"Qwen3.8 Flash Next","description":"Open-weight experimental preview of the Qwen4 architecture: hybrid-attention MoE (125B total, 6B active) with vision encoder for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":64000},"cost":{"input":0.201,"output":0.5,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.8-flash-next"},"mistral-small-2603":{"id":"mistral-small-2603","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.156,"output":0.625,"cache_read":0.016},"canonical_model_id":"mistral/mistral-small-2603"},"nemotron-nano-v2-12b":{"id":"nemotron-nano-v2-12b","name":"nemotron-nano-v2-12b","description":"NVIDIA Nemotron Nano v2 12B is a 12-billion-parameter multimodal reasoning model designed for advanced video understanding, document intelligence, and visual reasoning, built with a hybrid Transformer-Mamba architecture for high efficiency and low latency.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2025-10-31","last_updated":"2025-10-31","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000},"cost":{"input":0.24,"output":0.707}},"mistral-small-2503":{"id":"mistral-small-2503","name":"mistral-small-2503","description":"Combines advanced text and vision capabilities with 24 billion parameters, supporting multilingual tasks and long contexts up to 131k tokens, making it versatile for various applications without sacrificing performance.","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2025-03-20","last_updated":"2025-03-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000},"cost":{"input":0.111,"output":0.334}},"gpt-4.1":{"id":"gpt-4.1","name":"GPT-4.1","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2.192,"output":8.769,"cache_read":0.546},"canonical_model_id":"openai/gpt-4.1"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.219,"cache_write":2.749},"canonical_model_id":"anthropic/claude-sonnet-5"},"qwen3.5-397b-a17b":{"id":"qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.668,"output":4.01},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"gemini-3.7-flash":{"id":"gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.038},"canonical_model_id":"google/gemini-3.7-flash"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1000000},"cost":{"input":0.9,"output":3.24,"cache_read":0.189},"canonical_model_id":"zhipuai/glm-5.2"},"pixtral-large-2502":{"id":"pixtral-large-2502","name":"Pixtral Large (25.02)","description":"Pixtral Large (25.02) is a 124B open-weight multimodal model built on Mistral Large 2, offering advanced image understanding and strong performance across text and code tasks.","family":"pixtral","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2025-04-08","last_updated":"2025-04-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000},"cost":{"input":1.993,"output":5.978},"canonical_model_id":"mistral/pixtral-large-2502"},"claude-opus4-7":{"id":"claude-opus4-7","name":"Claude Opus 4.7","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.437,"output":27.186,"cache_read":0.544,"cache_write":6.797},"canonical_model_id":"anthropic/claude-opus-4-7"},"minicpm-v-4.5":{"id":"minicpm-v-4.5","name":"minicpm-v-4.5","description":"MiniCPM-V 4.5 is a compact, high-performance vision-language model excelling in video understanding, OCR, and multimodal reasoning with efficient deployment.","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":32000},"cost":{"input":0.651,"output":1.097}},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":202752},"cost":{"input":1.384,"output":4.348,"cache_read":0.346},"canonical_model_id":"zhipuai/glm-5.1"},"qwen3-30b-a3b-instruct-2507":{"id":"qwen3-30b-a3b-instruct-2507","name":"qwen3-30b-a3b-instruct-2507","description":"Qwen3-30B-A3B-Instruct-2507 is an advanced Mixture-of-Experts model optimized for reasoning, coding, and multilingual instruction following.","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":262000},"cost":{"input":0.099,"output":0.299}},"qwen2.5-vl-72b-instruct":{"id":"qwen2.5-vl-72b-instruct","name":"qwen2.5-vl-72b-instruct","description":"Qwen2.5-VL is a powerful vision-language model with advanced capabilities in visual understanding, long video reasoning, and structured output generation.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":false,"release_date":"2025-01-27","last_updated":"2025-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":32000},"cost":{"input":1.014,"output":1.014}},"mistral-large-2512":{"id":"mistral-large-2512","name":"Mistral Large 3","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.613,"output":1.838,"cache_read":0.061},"canonical_model_id":"mistral/mistral-large-2512"},"gpt-4.1-mini":{"id":"gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.434,"output":1.704,"cache_read":0.134},"canonical_model_id":"openai/gpt-4.1-mini"},"gemini-3.8-flash":{"id":"gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.825,"output":4.125,"cache_read":0.082,"cache_write":0.084},"canonical_model_id":"google/gemini-3.8-flash"},"ministral-14b-2512":{"id":"ministral-14b-2512","name":"Ministral 3 14B 2512","description":"Ministral 3 14B is a frontier-level 14B multimodal model optimized for local deployment, delivering state-of-the-art text and vision reasoning with a 256K context window and strong agentic capabilities.","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.24,"output":0.24,"cache_read":0.022},"canonical_model_id":"mistral/ministral-14b-2512"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.12,"output":0.6,"cache_read":0.012,"cache_write":0.15},"canonical_model_id":"openai/gpt-6-luna"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.7,"output":3.4,"cache_read":0.15},"canonical_model_id":"deepseek/deepseek-v4-pro"},"mistral-large-4-0":{"id":"mistral-large-4-0","name":"Mistral Large 4","description":"Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":262144},"cost":{"input":0.765,"output":2.351,"cache_read":0.079},"canonical_model_id":"mistral/mistral-large-4"},"claude-opus-5.5":{"id":"claude-opus-5.5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4.399,"output":21.998,"cache_read":0.219,"cache_write":5.5},"canonical_model_id":"anthropic/claude-opus-5-5"},"qwen3.6-27b":{"id":"qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.446,"output":3.008},"canonical_model_id":"alibaba/qwen3.6-27b"},"claude-opus4-8":{"id":"claude-opus4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.437,"output":27.186,"cache_read":0.544,"cache_write":6.797},"canonical_model_id":"anthropic/claude-opus-4-8"},"mistral-small-3.2-24b-instruct-2506":{"id":"mistral-small-3.2-24b-instruct-2506","name":"mistral-small-3.2-24b-instruct-2506","description":"Mistral-Small-3.2-24B-Instruct-2506 is a 24B parameter instruction-tuned model with enhanced long-context support (128k) and state-of-the-art vision understanding.","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2025-05-26","last_updated":"2025-05-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":131000},"cost":{"input":0.1,"output":0.312}},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.2,"output":13.199,"cache_read":0.219,"cache_write":2.749},"canonical_model_id":"openai/gpt-5.6-terra"},"deepseek-v3.2":{"id":"deepseek-v3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":65536},"cost":{"input":0.5,"output":1.499,"cache_read":0.15},"canonical_model_id":"deepseek/deepseek-v3.2"},"nova-2-lite":{"id":"nova-2-lite","name":"Nova 2 Lite","description":"Nova 2 Lite is an advanced multimodal reasoning model that combines efficiency and performance, delivering reliable AI for agentic workflows and enterprise applications.","family":"nova","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-10","release_date":"2025-12-02","last_updated":"2025-12-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.373,"output":3.144},"canonical_model_id":"amazon/nova-2-lite"},"nova-pro-v1":{"id":"nova-pro-v1","name":"Nova Pro 1.0","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.918,"output":3.671},"canonical_model_id":"amazon/nova-pro-v1"},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":131000},"cost":{"input":0.089,"output":0.446,"cache_read":0.01},"canonical_model_id":"openai/gpt-oss-120b"},"ministral-3b-2512":{"id":"ministral-3b-2512","name":"Ministral 3 3B 2512","description":"Ministral 3 3B is a compact, efficient multimodal model with strong language, vision capabilities, and ideal for custom fine-tuning.","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.123,"output":0.123,"cache_read":0.012},"canonical_model_id":"mistral/ministral-3b-2512"},"claude-opus4-5":{"id":"claude-opus4-5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5.313,"output":26.568,"cache_read":0.531,"cache_write":6.645},"canonical_model_id":"anthropic/claude-opus-4-5"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.873,"output":3.306,"cache_read":0.221},"canonical_model_id":"zhipuai/glm-5.3"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.656,"output":3.3,"cache_read":0.18},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"gpt-5":{"id":"gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.375,"output":10.96,"cache_read":0.156},"canonical_model_id":"openai/gpt-5"},"minimax-m2.1":{"id":"minimax-m2.1","name":"MiniMax-M2.1","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196000,"output":196000},"cost":{"input":0.359,"output":1.435},"canonical_model_id":"minimax/MiniMax-M2.1"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4.399,"output":21.998,"cache_read":0.44,"cache_write":5.5},"canonical_model_id":"openai/gpt-5.6-sol"},"mistral-nemo-instruct-2407":{"id":"mistral-nemo-instruct-2407","name":"mistral-nemo-instruct-2407","description":"A 12B parameter, instruct-tuned language model by Mistral AI and NVIDIA, designed for advanced instruction following, multi-turn conversations, and generating text and code across multiple languages.","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2024-08-07","last_updated":"2024-08-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000},"cost":{"input":0.145,"output":0.145,"cache_read":0.014}},"gemini-4-argon":{"id":"gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":2.25,"output":11.249,"cache_read":0.113},"canonical_model_id":"google/gemini-4-argon"},"minimax-m2":{"id":"minimax-m2","name":"MiniMax-M2","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":400000,"output":196000},"cost":{"input":0.349,"output":1.405},"canonical_model_id":"minimax/MiniMax-M2"},"nova-micro-v1":{"id":"nova-micro-v1","name":"Nova Micro 1.0","description":"Nova Micro is a multilingual text-to-text foundation model with strong reasoning capabilities and broad language coverage across 200+ languages.","family":"nova-micro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":10000},"cost":{"input":0.04,"output":0.159},"canonical_model_id":"amazon/nova-micro-v1"},"codestral-2508":{"id":"codestral-2508","name":"Codestral 25.08","description":"Mistral coding model for code completion, generation, and developer workflows","family":"codestral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.368,"output":1.103,"cache_read":0.037},"canonical_model_id":"mistral/codestral-2508"},"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.4,"output":11.999,"cache_read":0.24,"cache_write":3},"canonical_model_id":"openai/gpt-6-sol"},"nvidia-nemotron-3-nano-30b-a3b":{"id":"nvidia-nemotron-3-nano-30b-a3b","name":"nvidia-nemotron-3-nano-30b-a3b","description":"Nemotron-Nano-3-30B-A3B is a compact Mixture-of-Experts model optimized for efficient reasoning, chat, and coding, with strong multilingual support and long-context RAG and agent workflows.","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-01-12","last_updated":"2026-01-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.06,"output":0.24}},"gemini-3.1-flash-lite":{"id":"gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.272,"output":1.631,"cache_read":0.025,"cache_write":0.082},"canonical_model_id":"google/gemini-3.1-flash-lite"}}},"agnes":{"id":"agnes","env":["AGNES_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://apihub.agnes-ai.com/v1","name":"Agnes AI","doc":"https://agnes-ai.com/doc","models":{"agnes-2.5-pro-alpha":{"id":"agnes-2.5-pro-alpha","name":"Agnes 2.5 Pro Alpha","description":"Paid reasoning model for advanced coding, scientific reasoning, long-context analysis, agentic workflows, and multimodal understanding.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":0.45,"output":0.9,"cache_read":0.0038}},"agnes-3.0-flash":{"id":"agnes-3.0-flash","name":"Agnes 3.0 Flash","description":"A new-generation Agnes AI text model with stronger Agnes Code task execution, tool orchestration, and trustworthy delivery.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09","last_updated":"2026-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":512000,"output":65536},"cost":{"input":0,"output":0}},"agnes-2.0-flash":{"id":"agnes-2.0-flash","name":"Agnes 2.0 Flash","description":"Fast and efficient model for agent workflows, tool calling, coding, and image understanding.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-05-25","last_updated":"2026-05-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":512000,"output":65536},"status":"deprecated","cost":{"input":0,"output":0}},"agnes-2.5-flash":{"id":"agnes-2.5-flash","name":"Agnes 2.5 Flash","description":"Upgraded model with improved coding, agent workflows, tool calling, and multimodal understanding.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07","last_updated":"2026-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":512000,"output":65536},"cost":{"input":0,"output":0}}}},"daoxe":{"id":"daoxe","env":["DAOXE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://daoxe.com/v1","name":"DaoXE","doc":"https://daoxe.com/pricing","models":{"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.4"},"grok-4.3":{"id":"grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2},"canonical_model_id":"xai/grok-4.3"},"gemini-3.1-pro-preview":{"id":"gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2},"canonical_model_id":"google/gemini-3.1-pro-preview"},"grok-4.5":{"id":"grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.5"},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":3,"cache_read":0.1},"canonical_model_id":"moonshotai/kimi-k2.5"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5"},"claude-haiku-4-5-20251001":{"id":"claude-haiku-4-5-20251001","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":5},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"}}},"morph":{"id":"morph","env":["MORPH_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.morphllm.com/v1","name":"Morph","doc":"https://docs.morphllm.com/api-reference/introduction","models":{"morph-v3-large":{"id":"morph-v3-large","name":"Morph v3 Large","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"morph","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-08-15","last_updated":"2024-08-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":32000},"cost":{"input":0.9,"output":1.9}},"morph-v3-fast":{"id":"morph-v3-fast","name":"Morph v3 Fast","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"morph","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-08-15","last_updated":"2024-08-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16000,"output":16000},"cost":{"input":0.8,"output":1.2}},"auto":{"id":"auto","name":"Auto","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-06-01","last_updated":"2024-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":32000},"cost":{"input":0.85,"output":1.55}}}},"openai":{"id":"openai","env":["OPENAI_API_KEY"],"npm":"@ai-sdk/openai","name":"OpenAI","doc":"https://platform.openai.com/docs/models","models":{"chatgpt-image-latest":{"id":"chatgpt-image-latest","name":"chatgpt-image-latest","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":0,"input":0,"output":0}},"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":5,"output":30,"cache_read":0.5},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}}},"gpt-5.4-pro":{"id":"gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}}},"gpt-3.5-turbo":{"id":"gpt-3.5-turbo","name":"GPT-3.5-turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"output":4096},"status":"deprecated","cost":{"input":0.5,"output":1.5,"cache_read":0}},"gpt-5.5-pro":{"id":"gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}}},"text-embedding-3-small":{"id":"text-embedding-3-small","name":"text-embedding-3-small","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2024-01","release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8191,"output":1536},"cost":{"input":0.02,"output":0}},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"flex":{"cost":{"input":0.1,"output":0.625,"cache_read":0.01},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":0.2,"output":1.25,"cache_read":0.02}},"gpt-realtime-2.1":{"id":"gpt-realtime-2.1","name":"GPT-Realtime-2.1","description":"Realtime speech-to-speech model with configurable reasoning, tool use, and robust voice-agent behavior","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2024-09-30","release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text","audio","image"],"output":["text","audio"]},"open_weights":false,"limit":{"context":128000,"input":96000,"output":32000},"cost":{"input":4,"output":24,"cache_read":0.4,"input_audio":32,"output_audio":64},"canonical_model_id":"openai/gpt-realtime-2.1"},"gpt-4o-2024-05-13":{"id":"gpt-4o-2024-05-13","name":"GPT-4o (2024-05-13)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-05-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"status":"deprecated","experimental":{"modes":{"fast":{"cost":{"input":8.75,"output":26.25},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":5,"output":15}},"gpt-4o":{"id":"gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"experimental":{"modes":{"fast":{"cost":{"input":4.25,"output":17,"cache_read":2.125},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2.5,"output":10,"cache_read":1.25}},"gpt-5-mini":{"id":"gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":0.45,"output":3.6,"cache_read":0.045},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":0.125,"output":1,"cache_read":0.0125},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":0.25,"output":2,"cache_read":0.025}},"gpt-image-2":{"id":"gpt-image-2","name":"gpt-image-2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"input":0,"output":0},"cost":{"input":5,"output":30,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-2"},"gpt-5.2-pro":{"id":"gpt-5.2-pro","name":"GPT-5.2 Pro","description":"Higher-accuracy GPT-5.2 variant for tougher reasoning and review workflows","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":21,"output":168}},"o4-mini":{"id":"o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","experimental":{"modes":{"fast":{"cost":{"input":2,"output":8,"cache_read":0.5},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":0.55,"output":2.2,"cache_read":0.138},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":1.1,"output":4.4,"cache_read":0.275}},"o3-mini":{"id":"o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":1.1,"output":4.4,"cache_read":0.55}},"text-embedding-ada-002":{"id":"text-embedding-ada-002","name":"text-embedding-ada-002","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2022-12","release_date":"2022-12-15","last_updated":"2022-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536},"cost":{"input":0.1,"output":0}},"gpt-4":{"id":"gpt-4","name":"GPT-4","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-11","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8192},"status":"deprecated","cost":{"input":30,"output":60}},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":3.5,"output":28,"cache_read":0.35},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"gpt-4.1-nano":{"id":"gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"status":"deprecated","experimental":{"modes":{"fast":{"cost":{"input":0.2,"output":0.8,"cache_read":0.05},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.1,"output":0.4,"cache_read":0.025}},"gpt-5-nano":{"id":"gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"flex":{"cost":{"input":0.025,"output":0.2,"cache_read":0.0025},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":0.05,"output":0.4,"cache_read":0.005}},"gpt-5.6":{"id":"gpt-5.6","name":"GPT-5.6","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":8,"output":40,"cache_read":0.8,"cache_write":10},"provider":{"body":{"service_tier":"priority"}}},"pro":{"provider":{"body":{"reasoning":{"mode":"pro"}}}}}},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"gpt-5.2-chat-latest":{"id":"gpt-5.2-chat-latest","name":"GPT-5.2 Chat","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"status":"deprecated","cost":{"input":1.75,"output":14,"cache_read":0.175}},"o1":{"id":"o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":15,"output":60,"cache_read":7.5}},"gpt-5-pro":{"id":"gpt-5-pro","name":"GPT-5 Pro","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":272000},"cost":{"input":15,"output":120}},"gpt-5.3-codex-spark":{"id":"gpt-5.3-codex-spark","name":"GPT-5.3 Codex Spark","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex-spark","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":100000,"output":32000},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"provider":{"body":{"service_tier":"priority"}}},"pro":{"provider":{"body":{"reasoning":{"mode":"pro"}}}},"ultrafast":{"cost":{"input":12,"output":60,"cache_read":0.6,"cache_write":15},"provider":{"body":{"service_tier":"ultrafast"}}}}},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"text-embedding-3-large":{"id":"text-embedding-3-large","name":"text-embedding-3-large","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2024-01","release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8191,"output":3072},"cost":{"input":0.13,"output":0}},"gpt-4o-2024-08-06":{"id":"gpt-4o-2024-08-06","name":"GPT-4o (2024-08-06)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-08-06","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25}},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":20,"output":100,"cache_read":2,"cache_write":25},"provider":{"body":{"service_tier":"priority"}}},"pro":{"provider":{"body":{"reasoning":{"mode":"pro"}}}},"ultrafast":{"cost":{"input":60,"output":300,"cache_read":6,"cache_write":75},"provider":{"body":{"service_tier":"ultrafast"}}}}},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"gpt-5.1":{"id":"gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":2.5,"output":20,"cache_read":0.25},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":0.625,"output":5,"cache_read":0.0625},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":1.25,"output":10,"cache_read":0.125}},"gpt-4o-mini":{"id":"gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"experimental":{"modes":{"fast":{"cost":{"input":0.25,"output":1,"cache_read":0.125},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.15,"output":0.6,"cache_read":0.075}},"o3-pro":{"id":"o3-pro","name":"o3-pro","description":"High-effort o3 tier for difficult technical reasoning and careful answers","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-06-10","last_updated":"2025-06-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":20,"output":80}},"gpt-image-1":{"id":"gpt-image-1","name":"gpt-image-1","description":"OpenAI image model for production generation, edits, and brand-safe visual workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-04-24","last_updated":"2025-04-24","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"input":0,"output":0},"status":"deprecated","canonical_model_id":"openai/gpt-image-1"},"gpt-daybreak-blue-latest":{"id":"gpt-daybreak-blue-latest","name":"Daybreak Blue","description":"Alias for flagship general-purpose models with safeguards for defensive cybersecurity work","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-08-07","last_updated":"2026-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":1.5,"output":9,"cache_read":0.15},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":0.375,"output":2.25,"cache_read":0.0375},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":0.75,"output":4.5,"cache_read":0.075}},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":0.4,"output":2.4,"cache_read":0.04,"cache_write":0.5},"provider":{"body":{"service_tier":"priority"}}},"pro":{"provider":{"body":{"reasoning":{"mode":"pro"}}}}}},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"gpt-5.2":{"id":"gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":3.5,"output":28,"cache_read":0.35},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":0.875,"output":7,"cache_read":0.0875},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":12.5,"output":75,"cache_read":1.25},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}}},"gpt-4.1":{"id":"gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"experimental":{"modes":{"fast":{"cost":{"input":3.5,"output":14,"cache_read":0.875},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2,"output":8,"cache_read":0.5}},"gpt-4o-2024-11-20":{"id":"gpt-4o-2024-11-20","name":"GPT-4o (2024-11-20)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-11-20","last_updated":"2024-11-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25}},"gpt-4.1-mini":{"id":"gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"experimental":{"modes":{"fast":{"cost":{"input":0.7,"output":2.8,"cache_read":0.175},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.4,"output":1.6,"cache_read":0.1}},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":0.2,"output":1,"cache_read":0.02,"cache_write":0.25},"provider":{"body":{"service_tier":"priority"}}},"pro":{"provider":{"body":{"reasoning":{"mode":"pro"}}}}}},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"gpt-5.3-chat-latest":{"id":"gpt-5.3-chat-latest","name":"GPT-5.3 Chat (latest)","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"status":"deprecated","cost":{"input":1.75,"output":14,"cache_read":0.175}},"gpt-image-1-mini":{"id":"gpt-image-1-mini","name":"gpt-image-1-mini","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-09-26","last_updated":"2025-09-26","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":0,"input":0,"output":0}},"gpt-image-1.5":{"id":"gpt-image-1.5","name":"gpt-image-1.5","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-11-25","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":0,"input":0,"output":0},"canonical_model_id":"openai/gpt-image-1.5"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":4,"output":24,"cache_read":0.4,"cache_write":5},"provider":{"body":{"service_tier":"priority"}}},"pro":{"provider":{"body":{"reasoning":{"mode":"pro"}}}}}},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"gpt-4-turbo":{"id":"gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":10,"output":30}},"gpt-daybreak-red-latest":{"id":"gpt-daybreak-red-latest","name":"Daybreak Red","description":"Alias for advanced cybersecurity models for authorized vulnerability research and security testing","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-08-07","last_updated":"2026-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":12.5,"output":75,"cache_read":1.25,"cache_write":15.625},"canonical_model_id":"openai/gpt-5.6-cyber"},"o3":{"id":"o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"experimental":{"modes":{"fast":{"cost":{"input":3.5,"output":14,"cache_read":0.875},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":1,"output":4,"cache_read":0.25},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":2,"output":8,"cache_read":0.5}},"gpt-5":{"id":"gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":2.5,"output":20,"cache_read":0.25},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":0.625,"output":5,"cache_read":0.0625},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":8,"output":40,"cache_read":0.8,"cache_write":10},"provider":{"body":{"service_tier":"priority"}}},"pro":{"provider":{"body":{"reasoning":{"mode":"pro"}}}}}},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5},"provider":{"body":{"service_tier":"priority"}}},"pro":{"provider":{"body":{"reasoning":{"mode":"pro"}}}}}},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"o1-pro":{"id":"o1-pro","name":"o1-pro","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2025-03-19","last_updated":"2025-03-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":150,"output":600}}}},"alibaba-coding-plan-cn":{"id":"alibaba-coding-plan-cn","env":["ALIBABA_CODING_PLAN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://coding.dashscope.aliyuncs.com/v1","name":"Alibaba Coding Plan (China)","doc":"https://help.aliyun.com/zh/model-studio/coding-plan","models":{"qwen3-coder-next":{"id":"qwen3-coder-next","name":"Qwen3 Coder Next","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3.5-plus":{"id":"qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"glm-5":{"id":"glm-5","name":"GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-11","last_updated":"2026-02-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":16384},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3-max-2026-01-23":{"id":"qwen3-max-2026-01-23","name":"Qwen3 Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-23","last_updated":"2026-01-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3-coder-plus":{"id":"qwen3-coder-plus","name":"Qwen3 Coder Plus","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"MiniMax-M2.5":{"id":"MiniMax-M2.5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":24576},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"glm-4.7":{"id":"glm-4.7","name":"GLM-4.7","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":16384},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3.6-plus":{"id":"qwen3.6-plus","name":"Qwen3.6 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.7-plus"}}},"io-net":{"id":"io-net","env":["IOINTELLIGENCE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.intelligence.io.solutions/api/v1","name":"IO.NET","doc":"https://io.net/docs/guides/intelligence/io-intelligence","models":{"meta-llama/Llama-3.2-90B-Vision-Instruct":{"id":"meta-llama/Llama-3.2-90B-Vision-Instruct","name":"Llama 3.2 90B Vision Instruct","description":"Open Llama multimodal model for image understanding and text reasoning","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":16000,"output":4096},"cost":{"input":0.35,"output":0.4,"cache_read":0.175,"cache_write":0.7}},"meta-llama/Llama-3.3-70B-Instruct":{"id":"meta-llama/Llama-3.3-70B-Instruct","name":"Llama 3.3 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.13,"output":0.38,"cache_read":0.065,"cache_write":0.26}},"meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8":{"id":"meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8","name":"Llama 4 Maverick 17B 128E Instruct","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-01-15","last_updated":"2025-01-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":430000,"output":4096},"cost":{"input":0.15,"output":0.6,"cache_read":0.075,"cache_write":0.3}},"Qwen/Qwen3-Next-80B-A3B-Instruct":{"id":"Qwen/Qwen3-Next-80B-A3B-Instruct","name":"Qwen 3 Next 80B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-01-10","last_updated":"2025-01-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":4096},"cost":{"input":0.1,"output":0.8,"cache_read":0.05,"cache_write":0.2}},"Qwen/Qwen3-235B-A22B-Thinking-2507":{"id":"Qwen/Qwen3-235B-A22B-Thinking-2507","name":"Qwen 3 235B Thinking","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-07-01","last_updated":"2025-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":4096},"cost":{"input":0.11,"output":0.6,"cache_read":0.055,"cache_write":0.22}},"Qwen/Qwen2.5-VL-32B-Instruct":{"id":"Qwen/Qwen2.5-VL-32B-Instruct","name":"Qwen 2.5 VL 32B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2024-11-01","last_updated":"2024-11-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":4096},"cost":{"input":0.05,"output":0.22,"cache_read":0.025,"cache_write":0.1}},"deepseek-ai/DeepSeek-R1-0528":{"id":"deepseek-ai/DeepSeek-R1-0528","name":"DeepSeek R1","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":2,"output":8.75,"cache_read":1,"cache_write":4}},"mistralai/Mistral-Nemo-Instruct-2407":{"id":"mistralai/Mistral-Nemo-Instruct-2407","name":"Mistral Nemo Instruct 2407","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-05","release_date":"2024-07-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.02,"output":0.04,"cache_read":0.01,"cache_write":0.04}},"mistralai/Magistral-Small-2506":{"id":"mistralai/Magistral-Small-2506","name":"Magistral Small 2506","description":"Mistral reasoning model for transparent analysis, math, and complex decisions","family":"magistral-small","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-01","last_updated":"2025-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":0.5,"output":1.5,"cache_read":0.25,"cache_write":1}},"mistralai/Devstral-Small-2505":{"id":"mistralai/Devstral-Small-2505","name":"Devstral Small 2505","description":"Mistral coding agent model for repository tasks and software engineering workflows","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-05-01","last_updated":"2025-05-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":0.05,"output":0.22,"cache_read":0.025,"cache_write":0.1}},"mistralai/Mistral-Large-Instruct-2411":{"id":"mistralai/Mistral-Large-Instruct-2411","name":"Mistral Large Instruct 2411","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-11-01","last_updated":"2024-11-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":2,"output":6,"cache_read":1,"cache_write":4}},"Intel/Qwen3-Coder-480B-A35B-Instruct-int4-mixed-ar":{"id":"Intel/Qwen3-Coder-480B-A35B-Instruct-int4-mixed-ar","name":"Qwen 3 Coder 480B","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-01-15","last_updated":"2025-01-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":106000,"output":4096},"cost":{"input":0.22,"output":0.95,"cache_read":0.11,"cache_write":0.44}},"moonshotai/Kimi-K2-Thinking":{"id":"moonshotai/Kimi-K2-Thinking","name":"Kimi K2 Thinking","description":"Kimi reasoning model for long-horizon research, planning, and tool use","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2024-11-01","last_updated":"2024-11-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":4096},"cost":{"input":0.55,"output":2.25,"cache_read":0.275,"cache_write":1.1}},"moonshotai/Kimi-K2-Instruct-0905":{"id":"moonshotai/Kimi-K2-Instruct-0905","name":"Kimi K2 Instruct","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2024-09-05","last_updated":"2024-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":4096},"cost":{"input":0.39,"output":1.9,"cache_read":0.195,"cache_write":0.78}},"zai-org/GLM-4.6":{"id":"zai-org/GLM-4.6","name":"GLM 4.6","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-11-15","last_updated":"2024-11-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":4096},"cost":{"input":0.4,"output":1.75,"cache_read":0.2,"cache_write":0.8}},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT-OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-01","last_updated":"2024-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":4096},"cost":{"input":0.03,"output":0.14,"cache_read":0.015,"cache_write":0.06}},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT-OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-01","last_updated":"2024-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":4096},"cost":{"input":0.04,"output":0.4,"cache_read":0.02,"cache_write":0.08}}}},"infomaniak":{"id":"infomaniak","env":["INFOMANIAK_API_KEY","INFOMANIAK_PRODUCT_ID"],"npm":"@ai-sdk/openai-compatible","api":"https://api.infomaniak.com/2/ai/${INFOMANIAK_PRODUCT_ID}/openai/v1","name":"Infomaniak","doc":"https://www.infomaniak.com/en/hosting/ai-services/open-source-models","models":{"mini_lm_l12_v2":{"id":"mini_lm_l12_v2","name":"All-MiniLM-L12-v2","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2021-08-30","last_updated":"2026-08-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128,"input":128,"output":384},"cost":{"input":0,"output":0}},"bge_multilingual_gemma2":{"id":"bge_multilingual_gemma2","name":"BGE Multilingual Gemma2","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-07-25","last_updated":"2026-08-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8000,"input":8000,"output":3584},"cost":{"input":0.08,"output":0}},"swiss-ai/Apertus-v1.5-70B":{"id":"swiss-ai/Apertus-v1.5-70B","name":"Apertus v1.5 70B","description":"Open, ethically-sourced Swiss AI model for multilingual, multimodal chat and instruction following","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-07-24","last_updated":"2026-08-01","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":100000,"input":100000,"output":8192},"status":"beta","cost":{"input":0.87,"output":3.1}},"google/gemma-4-31B-it":{"id":"google/gemma-4-31B-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-08-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":100000,"input":100000,"output":32768},"cost":{"input":0.25,"output":0.5},"canonical_model_id":"google/gemma-4-31b-it"},"Qwen/Qwen3.5-122B-A10B-FP8":{"id":"Qwen/Qwen3.5-122B-A10B-FP8","name":"Qwen3.5 122B-A10B FP8","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-08-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":65536},"cost":{"input":0.5,"output":3.97},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"Qwen/Qwen3.5-397B-A17B-FP8":{"id":"Qwen/Qwen3.5-397B-A17B-FP8","name":"Qwen3.5 397B-A17B FP8","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-08-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":65536},"status":"beta","cost":{"input":0.99,"output":4.46},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"mistralai/Mistral-Small-4-119B-2603":{"id":"mistralai/Mistral-Small-4-119B-2603","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-08-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.25,"output":0.93},"canonical_model_id":"mistral/mistral-small-2603"},"mistralai/Ministral-3-14B-Instruct-2512":{"id":"mistralai/Ministral-3-14B-Instruct-2512","name":"Ministral 3 14B Instruct","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2026-08-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":100000,"input":100000,"output":25600},"status":"beta","cost":{"input":0.37,"output":0.5}},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-08-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"status":"beta","cost":{"input":0.74,"output":3.72},"canonical_model_id":"moonshotai/kimi-k2.6"},"nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8":{"id":"nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8","name":"Nemotron 3 Nano 30B A3B FP8","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"temperature":true,"release_date":"2025-12-15","last_updated":"2026-08-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":262144},"status":"beta","cost":{"input":0.06,"output":0.25},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"}}},"llmtech":{"id":"llmtech","env":["LLMTECH_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.llmtech.eu/v1","name":"LLM Tech","doc":"https://llmtech.eu/models/qwen3.8-27b","models":{"nvidia/Qwen3.8-27B-NVFP4":{"id":"nvidia/Qwen3.8-27B-NVFP4","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.25,"output":2.09,"cache_read":0.04},"canonical_model_id":"alibaba/qwen3.8-27b"}}},"crossmodel":{"id":"crossmodel","env":["CROSSMODEL_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.crossmodel.ai/v1","name":"CrossModel","doc":"https://www.crossmodel.ai/docs","models":{"anthropic/claude-haiku-4-5":{"id":"anthropic/claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-opus-5-5":{"id":"anthropic/claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-fable-5-1":{"id":"anthropic/claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-opus-4-8":{"id":"anthropic/claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-haiku-5-5":{"id":"anthropic/claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-sonnet-4-6":{"id":"anthropic/claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-sonnet-5-5":{"id":"anthropic/claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-opus-4-7":{"id":"anthropic/claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.3,"output":1.2,"cache_read":0.006,"cache_write":0.3},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-flash-vision-exp":{"id":"deepseek/deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.3,"output":1.2,"cache_read":0.006,"cache_write":0.3},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.35,"output":4.05,"cache_read":0.045,"cache_write":1.35},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.3,"output":1.2,"cache_read":0.006,"cache_write":0.3},"canonical_model_id":"deepseek/deepseek-v4-flash"},"tencent/hy3":{"id":"tencent/hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":192000,"output":131072},"cost":{"input":0.16,"output":0.64,"cache_read":0.04,"cache_write":0.16},"canonical_model_id":"tencent/hy3"},"tencent/hy4-preview":{"id":"tencent/hy4-preview","name":"Hy4 preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":0.96,"output":2.88,"cache_read":0.048,"cache_write":0.96},"canonical_model_id":"tencent/hy4-preview"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.15,"output":0.5,"cache_read":0.03,"cache_write":0.15},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-5":{"id":"z-ai/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.6,"output":3,"cache_read":0.16,"cache_write":0.6,"tiers":[{"input":0.8,"output":3.4,"cache_read":0.2,"cache_write":0.8,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-5"},"z-ai/glm-4.7":{"id":"z-ai/glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.47,"output":2.16,"cache_read":0.1,"cache_write":0.47,"tiers":[{"input":0.62,"output":2.47,"cache_read":0.13,"cache_write":0.62,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.7"},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":1.2,"output":4.4,"cache_read":0.3,"cache_write":1.2},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/glm-5.1":{"id":"z-ai/glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":1,"output":3.8,"cache_read":0.2,"cache_write":1,"tiers":[{"input":1.2,"output":4.4,"cache_read":0.3,"cache_write":1.2,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-5.1"},"z-ai/glm-5-turbo":{"id":"z-ai/glm-5-turbo","name":"GLM-5-Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":0.9,"output":3.7,"cache_read":0.18,"cache_write":0.9,"tiers":[{"input":1.1,"output":4.3,"cache_read":0.27,"cache_write":1.1,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-5-turbo"},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":1.2,"output":4.4,"cache_read":0.3,"cache_write":1.2},"canonical_model_id":"zhipuai/glm-5.3"},"x-ai/grok-4.7":{"id":"x-ai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"cache_write":2,"tiers":[{"input":4,"output":12,"cache_read":1,"cache_write":4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1,"cache_write":4}},"canonical_model_id":"xai/grok-4.7"},"x-ai/grok-4.3":{"id":"x-ai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"cache_write":1.25,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"cache_write":2.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4,"cache_write":2.5}},"canonical_model_id":"xai/grok-4.3"},"x-ai/grok-4.5":{"id":"x-ai/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.3,"cache_write":2,"tiers":[{"input":4,"output":12,"cache_read":0.6,"cache_write":4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":0.6,"cache_write":4}},"canonical_model_id":"xai/grok-4.5"},"x-ai/grok-build-0.1":{"id":"x-ai/grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.2,"cache_write":1,"tiers":[{"input":2,"output":4,"cache_read":0.4,"cache_write":2,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2,"output":4,"cache_read":0.4,"cache_write":2}},"canonical_model_id":"xai/grok-build-0.1"},"x-ai/grok-4.6":{"id":"x-ai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"cache_write":2,"tiers":[{"input":4,"output":12,"cache_read":1,"cache_write":4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1,"cache_write":4}},"canonical_model_id":"xai/grok-4.6"},"xiaomi/mimo-v2.6-pro":{"id":"xiaomi/mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.47,"output":0.94,"cache_read":0.005,"cache_write":0.47},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"xiaomi/mimo-v2.5":{"id":"xiaomi/mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.16,"output":0.32,"cache_read":0.004,"cache_write":0.16},"canonical_model_id":"xiaomi/mimo-v2.5"},"xiaomi/mimo-v2.5-pro":{"id":"xiaomi/mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.47,"output":0.94,"cache_read":0.005,"cache_write":0.47},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"xiaomi/mimo-v2.6-flash":{"id":"xiaomi/mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.16,"output":0.32,"cache_read":0.004,"cache_write":0.16},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"minimax/minimax-m2.7":{"id":"minimax/minimax-m2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.33,"output":1.32,"cache_read":0.066,"cache_write":0.42},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":512000},"cost":{"input":0.33,"output":1.32,"cache_read":0.066,"cache_write":0.33,"tiers":[{"input":0.66,"output":2.63,"cache_read":0.132,"cache_write":0.66,"tier":{"type":"context","size":512000}}],"context_over_200k":{"input":0.66,"output":2.63,"cache_read":0.132,"cache_write":0.66}},"canonical_model_id":"minimax/MiniMax-M3"},"gemini/gemini-3.6-flash":{"id":"gemini/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.75},"canonical_model_id":"google/gemini-3.6-flash"},"gemini/gemini-3.5-flash-lite":{"id":"gemini/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":0.3},"canonical_model_id":"google/gemini-3.5-flash-lite"},"gemini/gemini-3.1-pro-preview":{"id":"gemini/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"gemini/gemini-3.5-flash":{"id":"gemini/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"cache_write":1.5},"canonical_model_id":"google/gemini-3.5-flash"},"gemini/gemini-2.5-pro":{"id":"gemini/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125,"cache_write":1.25,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"cache_write":2.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25,"cache_write":2.5}},"canonical_model_id":"google/gemini-2.5-pro"},"gemini/gemini-2.5-flash":{"id":"gemini/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":0.3},"canonical_model_id":"google/gemini-2.5-flash"},"gemini/gemini-3.7-flash":{"id":"gemini/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.75},"canonical_model_id":"google/gemini-3.7-flash"},"gemini/gemini-3-flash-preview":{"id":"gemini/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.5},"canonical_model_id":"google/gemini-3-flash-preview"},"gemini/gemini-3.8-flash":{"id":"gemini/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.75},"canonical_model_id":"google/gemini-3.8-flash"},"gemini/gemini-2.5-flash-lite":{"id":"gemini/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"cache_write":0.1},"canonical_model_id":"google/gemini-2.5-flash-lite"},"gemini/gemini-4-argon":{"id":"gemini/gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2},"canonical_model_id":"google/gemini-4-argon"},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":1.88,"output":5.63,"cache_read":0.375,"cache_write":2.35},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen3.8-max":{"id":"qwen/qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":1.88,"output":5.63,"cache_read":0.23,"cache_write":2.35},"canonical_model_id":"alibaba/qwen3.8-max"},"qwen/qwen3.7-flash":{"id":"qwen/qwen3.7-flash","name":"Qwen3.7 Flash","description":"Lightweight multimodal Qwen model for high-throughput text, image, and video tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":991808,"output":65536},"cost":{"input":0.04,"output":0.13,"cache_read":0.01,"cache_write":0.04,"tiers":[{"input":0.1,"output":0.37,"cache_read":0.02,"cache_write":0.12,"tier":{"type":"context","size":32000}},{"input":0.19,"output":0.74,"cache_read":0.04,"cache_write":0.24,"tier":{"type":"context","size":256000}}]},"canonical_model_id":"alibaba/qwen3.7-flash"},"qwen/qwen3.8-omni-flash":{"id":"qwen/qwen3.8-omni-flash","name":"Qwen3.8 Omni Flash","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.13,"output":0.43,"cache_read":0.016,"cache_write":0.13},"canonical_model_id":"alibaba/qwen3.8-omni-flash"},"qwen/qwen3.6-flash":{"id":"qwen/qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.19,"output":1.13,"cache_read":0.019,"cache_write":0.24,"tiers":[{"input":0.75,"output":4.5,"cache_read":0.075,"cache_write":0.94,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.75,"output":4.5,"cache_read":0.075,"cache_write":0.94}},"canonical_model_id":"alibaba/qwen3.6-flash"},"qwen/qwen3.8-flash":{"id":"qwen/qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.13,"output":0.43,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen/qwen3.6-plus":{"id":"qwen/qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.32,"output":1.88,"cache_read":0.032,"cache_write":0.4,"tiers":[{"input":1.25,"output":7.5,"cache_read":0.124,"cache_write":1.57,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1.25,"output":7.5,"cache_read":0.124,"cache_write":1.57}},"canonical_model_id":"alibaba/qwen3.6-plus"},"qwen/qwen3.7-plus":{"id":"qwen/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.32,"output":1.25,"cache_read":0.032,"cache_write":0.4,"tiers":[{"input":0.96,"output":3.75,"cache_read":0.096,"cache_write":1.2,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.96,"output":3.75,"cache_read":0.096,"cache_write":1.2}},"canonical_model_id":"alibaba/qwen3.7-plus"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"cache_write":2.5,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5,"cache_write":5}},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.5-pro":{"id":"openai/gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.5-pro"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02,"cache_write":0.2},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075,"cache_write":0.15},"canonical_model_id":"openai/gpt-4o-mini"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075,"cache_write":0.75},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":5,"tiers":[{"input":10,"output":45,"cache_read":1,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1,"cache_write":10}},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"moonshot/kimi-k3":{"id":"moonshot/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshot/kimi-k2.6":{"id":"moonshot/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":1,"output":4.16,"cache_read":0.18,"cache_write":1},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshot/kimi-k2.7-code":{"id":"moonshot/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":1,"output":4.16,"cache_read":0.18,"cache_write":1},"canonical_model_id":"moonshotai/kimi-k2.7-code"}}},"arcee":{"id":"arcee","env":["ARCEE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.arcee.ai/api/v1","name":"Arcee","doc":"https://docs.arcee.ai","models":{"trinity-large-thinking":{"id":"trinity-large-thinking","name":"Trinity Large Thinking","description":"Reasoning-optimized 398B MoE agent model with extended thinking for long-horizon and multi-turn tool use","family":"trinity","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-04-01","last_updated":"2026-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"beta","cost":{"input":0.25,"output":0.8,"cache_read":0.06},"canonical_model_id":"arcee-ai/trinity-large-thinking"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"status":"beta","cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"output":384000},"status":"beta","cost":{"input":1.74,"output":3.48,"cache_read":0.2},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v4-flash-latest":{"id":"deepseek/deepseek-v4-flash-latest","name":"DeepSeek V4 Flash Latest","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"status":"beta","cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"thinkingmachines/inkling-small":{"id":"thinkingmachines/inkling-small","name":"Inkling Small","description":"Multimodal MoE reasoning model (276B total, 12B active) for text, image, and audio","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"beta","cost":{"input":0.5,"output":1.2,"cache_read":0.1},"canonical_model_id":"thinkingmachines/inkling-small"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"beta","cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"zai-org/glm-5.2":{"id":"zai-org/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"status":"beta","cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"}}},"drun":{"id":"drun","env":["DRUN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://chat.d.run/v1","name":"D.Run (China)","doc":"https://www.d.run","models":{"public/deepseek-v3":{"id":"public/deepseek-v3","name":"DeepSeek V3","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-12-26","last_updated":"2024-12-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.28,"output":1.1}},"public/minimax-m25":{"id":"public/minimax-m25","name":"MiniMax M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"release_date":"2025-03-01","last_updated":"2025-03-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":204800,"output":131072},"cost":{"input":0.29,"output":1.16}},"public/deepseek-r1":{"id":"public/deepseek-r1","name":"DeepSeek R1","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2025-01-20","last_updated":"2025-01-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32000},"cost":{"input":0.55,"output":2.2}}}},"amd":{"id":"amd","env":["AMD_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://developer.amd.com.cn/radeon/api/v1","name":"AMD","doc":"https://developer.amd.com.cn/radeon/tokenfactory","models":{"Qwen3.8-27B":{"id":"Qwen3.8-27B","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3.8-27b"},"DeepSeek-V4.1-Flash":{"id":"DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"DeepSeek-V4-Flash":{"id":"DeepSeek-V4-Flash","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"Qwen3.8-Flash-Next":{"id":"Qwen3.8-Flash-Next","name":"Qwen3.8 Flash Next","description":"Open-weight experimental preview of the Qwen4 architecture: hybrid-attention MoE (125B total, 6B active) with vision encoder for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-flash-next"},"MiniCPM5-2B":{"id":"MiniCPM5-2B","name":"MiniCPM5-2B","description":"Dense 2B-class open-source model for on-device and resource-constrained use, with native long-context support, tool calling, and agentic tasks","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-09-06","last_updated":"2026-09-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.124,"output":0.7425,"cache_read":0.124},"canonical_model_id":"openbmb/minicpm5-2b"},"DeepSeek-V4-Flash-Vision-Exp":{"id":"DeepSeek-V4-Flash-Vision-Exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"}}},"qvac":{"id":"qvac","env":["QVAC_API_KEY"],"npm":"@qvac/ai-sdk-provider","name":"QVAC","doc":"https://www.npmjs.com/package/@qvac/ai-sdk-provider","models":{"qwen3.5-0.8b":{"id":"qwen3.5-0.8b","name":"Qwen3.5 0.8B","description":"Qwen instruction model for multilingual chat and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-11-01","last_updated":"2025-11-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0,"output":0}},"gemma4-31b":{"id":"gemma4-31b","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemma-4-31b-it"},"qwen3.6-35b-a3b":{"id":"qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"qwen3.5-2b":{"id":"qwen3.5-2b","name":"Qwen3.5 2B","description":"Qwen instruction model for multilingual chat and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-11-01","last_updated":"2025-11-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0,"output":0}},"gpt-oss-20b":{"id":"gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"openai/gpt-oss-20b"},"qwen3.5-9b":{"id":"qwen3.5-9b","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3.5-9b"},"qwen3.5-4b":{"id":"qwen3.5-4b","name":"Qwen3.5 4B","description":"Qwen instruction model for multilingual chat and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-11-01","last_updated":"2025-11-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0,"output":0}},"qwen3.6-27b":{"id":"qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3.6-27b"},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"openai/gpt-oss-120b"}}},"claudinio":{"id":"claudinio","env":["CLAUDINIO_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.claudin.io/v1","name":"Claudinio","doc":"https://claudin.io","models":{"claudinio":{"id":"claudinio","name":"Claudinio","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"knowledge":"2026-05","release_date":"2026-05-12","last_updated":"2026-06-02","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":0.5,"output":2,"cache_read":0.15}},"claudius":{"id":"claudius","name":"Claudius","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"knowledge":"2026-05","release_date":"2026-05-12","last_updated":"2026-05-12","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":3,"output":8,"cache_read":0.9}}}},"runinfra":{"id":"runinfra","env":["RUNINFRA_GATEWAY_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.runinfra.ai/v1","name":"RunInfra","doc":"https://runinfra.ai/docs","models":{"Inferact/Qwen3.8-2.4T-A95B-NVFP4":{"id":"Inferact/Qwen3.8-2.4T-A95B-NVFP4","name":"Qwen3.8 2.4T A95B (NVFP4)","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"Qwen/Qwen3.8-27B":{"id":"Qwen/Qwen3.8-27B","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.01},"canonical_model_id":"alibaba/qwen3.8-27b"},"deepseek-ai/DeepSeek-V4-Flash-0731":{"id":"deepseek-ai/DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":32768},"cost":{"input":0.13,"output":0.27,"cache_read":0.01},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek-ai/DeepSeek-V4-Pro-0813":{"id":"deepseek-ai/DeepSeek-V4-Pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":32768},"cost":{"input":0.6,"output":1.9,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"zai-org/GLM-5.3-Flash":{"id":"zai-org/GLM-5.3-Flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.01},"canonical_model_id":"zhipuai/glm-5.3-flash"},"nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16":{"id":"nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16","name":"Nemotron 3.5 Lightning 30B A3B","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.05,"output":0.15,"cache_read":0.01},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"ornith-ai/Ornith-1.5-35B-A3B":{"id":"ornith-ai/Ornith-1.5-35B-A3B","name":"Ornith 1.5 35B A3B","description":"Mixture-of-experts coding-reasoning model for agentic software tasks, tool use, and image understanding","family":"ornith","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-18","last_updated":"2026-08-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.01},"canonical_model_id":"deepreinforce/ornith-1.5-35b-a3b"}}},"hetzner":{"id":"hetzner","env":["HETZNER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://inference.hetzner.com/api/v1","name":"Hetzner","doc":"https://experiments.hetzner.com/docs/inference","models":{"Qwen3.8-27B":{"id":"Qwen3.8-27B","name":"Qwen3.8-27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"beta","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"alibaba/qwen3.8-27b"},"Qwen/Qwen3.6-35B-A3B-FP8":{"id":"Qwen/Qwen3.6-35B-A3B-FP8","name":"Qwen3.6 35B A3B FP8","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"beta","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"}}},"digitalocean":{"id":"digitalocean","env":["DIGITALOCEAN_ACCESS_TOKEN"],"npm":"@ai-sdk/openai-compatible","api":"https://inference.do-ai.run/v1","name":"DigitalOcean","doc":"https://docs.digitalocean.com/products/gradient-ai-platform/details/models/","models":{"deepseek-3.2":{"id":"deepseek-3.2","name":"Deepseek 3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2025-12-02","last_updated":"2026-04-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":163840},"cost":{"input":0.5,"output":1.6,"cache_read":0.15}},"openai-gpt-5.5":{"id":"openai-gpt-5.5","name":"OpenAI GPT-5.5","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}}},"openai-gpt-5.2-pro":{"id":"openai-gpt-5.2-pro","name":"OpenAI GPT-5.2 Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":21,"output":168}},"all-mini-lm-l6-v2":{"id":"all-mini-lm-l6-v2","name":"All-MiniLM-L6-v2","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2021-08-30","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256,"output":384},"cost":{"input":0.009,"output":0}},"multi-qa-mpnet-base-dot-v1":{"id":"multi-qa-mpnet-base-dot-v1","name":"Multi-QA-mpnet-base-dot-v1","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2021-08-30","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512,"output":768},"cost":{"input":0.009,"output":0}},"openai-gpt-image-1":{"id":"openai-gpt-image-1","name":"GPT Image 1","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-04-24","last_updated":"2025-04-24","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":40,"cache_read":1.25}},"anthropic-claude-3-opus":{"id":"anthropic-claude-3-opus","name":"Claude 3 Opus","description":"Legacy model retained for compatibility with older integrations","family":"claude-opus","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-08","release_date":"2024-02-29","last_updated":"2024-02-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":4096},"status":"deprecated","cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75}},"anthropic-claude-4.6-sonnet":{"id":"anthropic-claude-4.6-sonnet","name":"Anthropic Claude Sonnet 4.6","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}}},"anthropic-claude-haiku-4.5":{"id":"anthropic-claude-haiku-4.5","name":"Anthropic Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25}},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"openai-o1":{"id":"openai-o1","name":"OpenAI o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":15,"output":60,"cache_read":7.5}},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"anthropic-claude-opus-4.7":{"id":"anthropic-claude-opus-4.7","name":"Anthropic Claude Opus 4.7","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"stable-diffusion-3.5-large":{"id":"stable-diffusion-3.5-large","name":"Stable Diffusion 3.5 Large","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"stable-diffusion","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-10-22","last_updated":"2026-04-30","modalities":{"input":["text"],"output":["image"]},"open_weights":true,"limit":{"context":256,"output":1},"cost":{"input":0.08,"output":0}},"openai-gpt-6-luna":{"id":"openai-gpt-6-luna","name":"OpenAI GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02}},"canonical_model_id":"openai/gpt-6-luna"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8-Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":262144},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"alibaba/qwen3.8-max"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"anthropic-claude-opus-5.5":{"id":"anthropic-claude-opus-5.5","name":"Anthropic Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.4,"cache_write":10,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.4,"cache_write":10}},"canonical_model_id":"anthropic/claude-opus-5-5"},"openai-gpt-6-1-sol":{"id":"openai-gpt-6-1-sol","name":"OpenAI GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"tiers":[{"input":4,"output":15,"cache_read":0.2,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2}},"canonical_model_id":"openai/gpt-6.1-sol"},"llama-4-maverick":{"id":"llama-4-maverick","name":"Llama 4 Maverick","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2026-04-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.25,"output":0.87,"cache_read":0.05}},"openai-o3-mini":{"id":"openai-o3-mini","name":"OpenAI o3 mini","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55}},"glm-5":{"id":"glm-5","name":"GLM 5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-11","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":64000},"cost":{"input":1,"output":3.2,"cache_read":0.2}},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"minimax-m2.5":{"id":"minimax-m2.5","name":"MiniMax M2.5 (Public Preview)","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax-m2.5","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08","release_date":"2026-02-12","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.3,"output":1.2,"cache_read":0.06}},"anthropic-claude-4.1-opus":{"id":"anthropic-claude-4.1-opus","name":"Anthropic Claude 4.1 Opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75}},"anthropic-claude-sonnet-5.5":{"id":"anthropic-claude-sonnet-5.5","name":"Anthropic Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"wan2-2-t2v-a14b":{"id":"wan2-2-t2v-a14b","name":"Wan2.2-T2V-A14B","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-07-28","last_updated":"2026-04-30","modalities":{"input":["text"],"output":["video"]},"open_weights":true,"limit":{"context":100,"output":1},"cost":{"input":0.6,"output":0}},"openai-gpt-4o":{"id":"openai-gpt-4o","name":"OpenAI GPT-4o","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25}},"anthropic-claude-fable-5.1":{"id":"anthropic-claude-fable-5.1","name":"Anthropic Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19}},"nemotron-3.5-super-vl":{"id":"nemotron-3.5-super-vl","name":"NVIDIA Nemotron 3.5 Super VL","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","family":"nemotron","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.3,"output":0.65,"cache_read":0.06}},"deepseek-v3":{"id":"deepseek-v3","name":"DeepSeek V3","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-12-26","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":131072}},"deepseek-r1-distill-llama-70b":{"id":"deepseek-r1-distill-llama-70b","name":"DeepSeek R1 Distill Llama 70B","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-01-30","last_updated":"2025-01-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32678,"output":8192},"cost":{"input":0.99,"output":0.99}},"openai-gpt-5-nano":{"id":"openai-gpt-5-nano","name":"OpenAI GPT-5 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005}},"qwen3-embedding-0.6b":{"id":"qwen3-embedding-0.6b","name":"Qwen3 Embedding 0.6B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-03","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8000,"output":1024},"status":"beta","cost":{"input":0.04,"output":0}},"mistral-7b-instruct-v0.3":{"id":"mistral-7b-instruct-v0.3","name":"Mistral 7B Instruct v0.3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-05-22","last_updated":"2024-05-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768}},"anthropic-claude-5.5-haiku":{"id":"anthropic-claude-5.5-haiku","name":"Anthropic Claude 5.5 Haiku","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"anthropic/claude-haiku-5-5"},"qwen-2.5-14b-instruct":{"id":"qwen-2.5-14b-instruct","name":"Qwen 2.5 14B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2024-09-19","last_updated":"2024-09-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072}},"openai-o3":{"id":"openai-o3","name":"OpenAI o3","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5}},"openai-gpt-5":{"id":"openai-gpt-5","name":"OpenAI GPT-5","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125}},"openai-gpt-4.1":{"id":"openai-gpt-4.1","name":"OpenAI GPT-4.1","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5}},"openai-gpt-5.1-codex-max":{"id":"openai-gpt-5.1-codex-max","name":"GPT-5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125}},"anthropic-claude-3.5-haiku":{"id":"anthropic-claude-3.5-haiku","name":"Claude 3.5 Haiku","description":"Legacy model retained for compatibility with older integrations","family":"claude-haiku","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-11-05","last_updated":"2024-11-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"status":"deprecated","cost":{"input":0.8,"output":4,"cache_read":0.08,"cache_write":1}},"anthropic-claude-3.5-sonnet":{"id":"anthropic-claude-3.5-sonnet","name":"Claude 3.5 Sonnet","description":"Legacy model retained for compatibility with older integrations","family":"claude-sonnet","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-06-20","last_updated":"2024-10-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75}},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":2.7,"cache_read":0.203}},"anthropic-claude-opus-4":{"id":"anthropic-claude-opus-4","name":"Claude Opus 4","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75}},"openai-gpt-6-astra":{"id":"openai-gpt-6-astra","name":"OpenAI GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"tiers":[{"input":20,"output":75,"cache_read":2,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2}},"canonical_model_id":"openai/gpt-6-astra"},"openai-gpt-image-2":{"id":"openai-gpt-image-2","name":"OpenAI GPT Image 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-04-24","last_updated":"2025-04-24","modalities":{"input":["text","image"],"output":["image","text"]},"open_weights":false,"limit":{"context":0,"output":16384},"cost":{"input":8,"output":30}},"openai-gpt-image-1.5":{"id":"openai-gpt-image-1.5","name":"OpenAI GPT Image 1.5","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-11-25","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["image","text"]},"open_weights":false,"limit":{"context":0,"output":16384},"cost":{"input":5,"output":10,"cache_read":1}},"openai-gpt-4o-mini":{"id":"openai-gpt-4o-mini","name":"OpenAI GPT-4o mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075}},"qwen3-coder-flash":{"id":"qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2026-04-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.45,"output":1.7,"cache_read":0.09}},"deepseek-4-flash":{"id":"deepseek-4-flash","name":"Deepseek V4 Flash","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-05-27","last_updated":"2026-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.028}},"nemotron-3-ultra-550b":{"id":"nemotron-3-ultra-550b","name":"Nemotron 3 Ultra","description":"Flagship Nemotron model for high-throughput reasoning and complex agents","family":"nemotron","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-06-04","last_updated":"2026-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":131072},"cost":{"input":0.9,"output":1.7,"cache_read":0.18}},"openai-gpt-5.2":{"id":"openai-gpt-5.2","name":"OpenAI GPT-5.2","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"nvidia-nemotron-3-super-120b":{"id":"nvidia-nemotron-3-super-120b","name":"NVIDIA Nemotron 3 Super 120B (Public Preview)","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32768},"cost":{"input":0.3,"output":0.65,"cache_read":0.06},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"mimo-v2.5-pro":{"id":"mimo-v2.5-pro","name":"MiMo V2.5 Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.8,"output":3,"cache_read":0.16},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"mistral-3-14B":{"id":"mistral-3-14B","name":"Ministral 3 14B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-15","last_updated":"2026-04-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":128000},"cost":{"input":0.2,"output":0.2,"cache_read":0.04}},"anthropic-claude-opus-5":{"id":"anthropic-claude-opus-5","name":"Anthropic Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"nemotron-3-nano-omni":{"id":"nemotron-3-nano-omni","name":"Nemotron 3 Nano Omni","description":"Open Nemotron omni model combining reasoning with text, vision, and audio","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.5,"output":0.9,"cache_read":0.1},"canonical_model_id":"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning"},"nemotron-3-nano-30b":{"id":"nemotron-3-nano-30b","name":"Nemotron 3 Nano 30B A3B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"temperature":true,"release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"arcee-trinity-large-thinking":{"id":"arcee-trinity-large-thinking","name":"Arcee Trinity Large Thinking (Public Preview)","description":"Reasoning-optimized 398B MoE agent model with extended thinking for long-horizon and multi-turn tool use","family":"trinity","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"cost":{"input":0.25,"output":0.9,"cache_read":0.06},"canonical_model_id":"arcee-ai/trinity-large-thinking"},"anthropic-claude-5-sonnet":{"id":"anthropic-claude-5-sonnet","name":"Anthropic Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"openai-gpt-5.4-pro":{"id":"openai-gpt-5.4-pro","name":"OpenAI GPT-5.4 Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}}},"llama3-8b-instruct":{"id":"llama3-8b-instruct","name":"Llama 3.1 Instruct (8B)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.198,"output":0.198}},"llama3.3-70b-instruct":{"id":"llama3.3-70b-instruct","name":"Llama 3.3 Instruct (70B)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.65,"output":0.65}},"openai-gpt-oss-120b":{"id":"openai-gpt-oss-120b","name":"OpenAI GPT-oss-120b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.1,"output":0.7,"cache_read":0.02}},"alibaba-qwen3-32b":{"id":"alibaba-qwen3-32b","name":"Qwen3 32B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-30","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.25,"output":0.55}},"openai-gpt-5.3-codex":{"id":"openai-gpt-5.3-codex","name":"OpenAI GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"qwen3.5-397b-a17b":{"id":"qwen3.5-397b-a17b","name":"Qwen 3.5 397B A17B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen3.5","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-04-30","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.55,"output":3.5,"cache_read":0.111}},"anthropic-claude-3.7-sonnet":{"id":"anthropic-claude-3.7-sonnet","name":"Claude 3.7 Sonnet","description":"Legacy model retained for compatibility with older integrations","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-02-24","last_updated":"2025-02-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75}},"anthropic-claude-opus-4.8":{"id":"anthropic-claude-opus-4.8","name":"Anthropic Claude Opus 4.8","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-05-28","last_updated":"2026-05-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"openai-gpt-5.6-luna":{"id":"openai-gpt-5.6-luna","name":"OpenAI GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04}},"canonical_model_id":"openai/gpt-5.6-luna"},"qwen3-tts-voicedesign":{"id":"qwen3-tts-voicedesign","name":"Qwen3 TTS VoiceDesign","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-30","modalities":{"input":["text"],"output":["audio"]},"open_weights":true,"limit":{"context":32768,"output":1}},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.21},"canonical_model_id":"zhipuai/glm-5.2"},"openai-gpt-6-sol":{"id":"openai-gpt-6-sol","name":"OpenAI GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"tiers":[{"input":4,"output":15,"cache_read":0.4,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4}},"canonical_model_id":"openai/gpt-6-sol"},"anthropic-claude-4.5-sonnet":{"id":"anthropic-claude-4.5-sonnet","name":"Anthropic Claude 4.5 Sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}}},"bge-m3":{"id":"bge-m3","name":"BGE M3","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"bge","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-01-30","last_updated":"2026-04-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":1024},"cost":{"input":0.02,"output":0}},"ministral-3-8b-instruct-2512":{"id":"ministral-3-8b-instruct-2512","name":"Ministral 3 8B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144}},"openai-gpt-5.6-sol":{"id":"openai-gpt-5.6-sol","name":"OpenAI GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"tiers":[{"input":8,"output":30,"cache_read":0.8,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8}},"canonical_model_id":"openai/gpt-5.6-sol"},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":163840},"cost":{"input":1.3,"output":4.3,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"openai-gpt-5.4-nano":{"id":"openai-gpt-5.4-nano","name":"OpenAI GPT-5.4 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02}},"bge-reranker-v2-m3":{"id":"bge-reranker-v2-m3","name":"BGE Reranker v2 M3","description":"Reranking model for improving retrieval quality in search and recommendation systems","family":"bge","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-03-12","last_updated":"2026-04-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":1},"cost":{"input":0.01,"output":0}},"nemotron-nano-12b-v2-vl":{"id":"nemotron-nano-12b-v2-vl","name":"Nemotron-nano 12b v2-vl","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"temperature":true,"release_date":"2025-10-28","last_updated":"2025-10-28","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.2,"output":0.6,"cache_read":0.04},"canonical_model_id":"nvidia/nemotron-nano-12b-v2-vl"},"openai-gpt-5.4-mini":{"id":"openai-gpt-5.4-mini","name":"OpenAI GPT-5.4 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075}},"openai-gpt-5-mini":{"id":"openai-gpt-5-mini","name":"OpenAI GPT-5 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025}},"anthropic-claude-opus-4.6":{"id":"anthropic-claude-opus-4.6","name":"Anthropic Claude Opus 4.6","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5}}},"e5-large-v2":{"id":"e5-large-v2","name":"E5 Large v2","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2023-05-19","last_updated":"2026-04-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512,"output":1024},"cost":{"input":0.02,"output":0}},"anthropic-claude-opus-4.5":{"id":"anthropic-claude-opus-4.5","name":"Anthropic Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"Deepseek V4 Pro","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":1.74,"output":3.48,"cache_read":0.348}},"gemma-4-31B-it":{"id":"gemma-4-31B-it","name":"Gemma 4","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-30","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.18,"output":0.5,"cache_read":0.036}},"openai-gpt-5.6-terra":{"id":"openai-gpt-5.6-terra","name":"OpenAI GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"openai/gpt-5.6-terra"},"glm-5.3":{"id":"glm-5.3","name":"GLM5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":128000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"gte-large-en-v1.5":{"id":"gte-large-en-v1.5","name":"GTE Large (v1.5)","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-03-27","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":1024},"cost":{"input":0.09,"output":0}},"anthropic-claude-fable-5":{"id":"anthropic-claude-fable-5","name":"Anthropic Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"release_date":"2026-06-09","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5}},"openai-gpt-oss-20b":{"id":"openai-gpt-oss-20b","name":"OpenAI GPT-oss-20b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.05,"output":0.45,"cache_read":0.01}},"openai-gpt-5.4":{"id":"openai-gpt-5.4","name":"OpenAI GPT-5.4","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}}},"mistral-nemo-instruct-2407":{"id":"mistral-nemo-instruct-2407","name":"Mistral Nemo Instruct","description":"Legacy model retained for compatibility with older integrations","family":"mistral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"status":"deprecated","cost":{"input":0.3,"output":0.3}},"anthropic-claude-sonnet-4":{"id":"anthropic-claude-sonnet-4","name":"Claude Sonnet 4","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.3,"cache_write":3.75,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.3,"cache_write":3.75}}},"fal-ai/fast-sdxl":{"id":"fal-ai/fast-sdxl","name":"Fast SDXL","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"stable-diffusion","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2023-07-26","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["image"]},"open_weights":true,"limit":{"context":0,"output":0}},"fal-ai/elevenlabs/tts/multilingual-v2":{"id":"fal-ai/elevenlabs/tts/multilingual-v2","name":"ElevenLabs Multilingual TTS v2","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"elevenlabs","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2023-08-22","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"fal-ai/flux/schnell":{"id":"fal-ai/flux/schnell","name":"FLUX.1 [schnell]","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-08-01","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["image"]},"open_weights":true,"limit":{"context":0,"output":0}},"fal-ai/stable-audio-25/text-to-audio":{"id":"fal-ai/stable-audio-25/text-to-audio","name":"Stable Audio 2.5 (Text-to-Audio)","description":"Speech generation model for controllable voice, narration, and audio delivery","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-10-08","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}}}},"boundless":{"id":"boundless","env":["BOUNDLESS_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.inference.boundless.network/v1","name":"Boundless","doc":"https://inference.boundless.network/models","models":{"nemotron3-super":{"id":"nemotron3-super","name":"Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium"]}],"tool_call":true,"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.12,"output":0.52,"cache_read":0.06},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"mimo-v2.6-pro":{"id":"mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.12,"output":0.4,"cache_read":0.024},"canonical_model_id":"zhipuai/glm-5.3-flash"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":2.3,"output":11.4,"cache_read":0.23},"canonical_model_id":"moonshotai/kimi-k3"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.2,"output":1,"cache_read":0.01},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-5"},"qwen3.6":{"id":"qwen3.6","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.04,"output":0.35,"cache_read":0.02},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"claude-fable-5.1":{"id":"claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25},"canonical_model_id":"anthropic/claude-fable-5-1"},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":1.04,"output":2.08,"cache_read":0.0352},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"mimo-v2.6-flash":{"id":"mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.28,"output":1.1,"cache_read":0.056},"canonical_model_id":"minimax/MiniMax-M3"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.6-luna"},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-flash"},"dsv4":{"id":"dsv4","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.04,"output":0.21,"cache_read":0.02},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.34,"output":2.3,"cache_read":0.17},"canonical_model_id":"zhipuai/glm-5.2"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01},"canonical_model_id":"openai/gpt-6-luna"},"claude-opus-5.5":{"id":"claude-opus-5.5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2},"canonical_model_id":"anthropic/claude-opus-5-5"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.12,"output":3.52,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.3"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2},"canonical_model_id":"openai/gpt-5.6-sol"},"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2},"canonical_model_id":"openai/gpt-6-sol"}}},"aixy":{"id":"aixy","env":["AIXY_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.aixy-gateway.com/v1","name":"Aixy","doc":"https://docs.aixy-gateway.com/integrations/overview","models":{"anthropic/claude-opus-5-5":{"id":"anthropic/claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.aixy-gateway.com/v1"},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-fable-5-1":{"id":"anthropic/claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.aixy-gateway.com/v1"},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-haiku-5-5":{"id":"anthropic/claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.aixy-gateway.com/v1"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-sonnet-5-5":{"id":"anthropic/claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.aixy-gateway.com/v1"},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.aixy-gateway.com/v1","shape":"responses"},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.aixy-gateway.com/v1","shape":"responses"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.aixy-gateway.com/v1","shape":"responses"},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.aixy-gateway.com/v1","shape":"responses"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.aixy-gateway.com/v1","shape":"responses"},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.aixy-gateway.com/v1","shape":"responses"},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.aixy-gateway.com/v1","shape":"responses"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"}}},"alibaba-cn":{"id":"alibaba-cn","env":["DASHSCOPE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://dashscope.aliyuncs.com/compatible-mode/v1","name":"Alibaba (China)","doc":"https://www.alibabacloud.com/help/en/model-studio/models","models":{"qwen-flash":{"id":"qwen-flash","name":"Qwen Flash","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.022,"output":0.216}},"qwen3.5-flash":{"id":"qwen3.5-flash","name":"Qwen3.5 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-23","last_updated":"2026-09-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.029,"output":0.287,"reasoning":0.287,"tiers":[{"input":0.115,"output":1.147,"reasoning":1.147,"tier":{"type":"context","size":128000}},{"input":0.172,"output":1.72,"reasoning":1.72,"tier":{"type":"context","size":256000}}]}},"qwen2-5-coder-32b-instruct":{"id":"qwen2-5-coder-32b-instruct","name":"Qwen2.5-Coder 32B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-11","last_updated":"2024-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.287,"output":0.861}},"deepseek-v3-2-exp":{"id":"deepseek-v3-2-exp","name":"DeepSeek V3.2 Exp","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":65536},"cost":{"input":0.287,"output":0.431}},"deepseek-r1-distill-qwen-14b":{"id":"deepseek-r1-distill-qwen-14b","name":"DeepSeek R1 Distill Qwen 14B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":16384},"cost":{"input":0.144,"output":0.431}},"qwen-math-plus":{"id":"qwen-math-plus","name":"Qwen Math Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-08-16","last_updated":"2024-09-19","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":4096,"output":3072},"cost":{"input":0.574,"output":1.721}},"qwen-deep-research":{"id":"qwen-deep-research","name":"Qwen Deep Research","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01","last_updated":"2024-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":7.742,"output":23.367}},"qwen3.7-max":{"id":"qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":262144}],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":2.5,"output":7.5,"cache_read":0.5,"cache_write":3.125},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen2-5-32b-instruct":{"id":"qwen2-5-32b-instruct","name":"Qwen2.5 32B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.287,"output":0.861}},"qwq-plus":{"id":"qwq-plus","name":"QwQ Plus","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-03-05","last_updated":"2025-03-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.23,"output":0.574}},"qwq-32b":{"id":"qwq-32b","name":"QwQ 32B","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-12","last_updated":"2024-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.287,"output":0.861}},"qwen2-5-vl-72b-instruct":{"id":"qwen2-5-vl-72b-instruct","name":"Qwen2.5-VL 72B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":2.294,"output":6.881}},"deepseek-v3-1":{"id":"deepseek-v3-1","name":"DeepSeek V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":65536},"cost":{"input":0.574,"output":1.721}},"qwen3-vl-plus":{"id":"qwen3-vl-plus","name":"Qwen3-VL Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.143353,"output":1.433525,"reasoning":4.300576}},"qwen-plus-character":{"id":"qwen-plus-character","name":"Qwen Plus Character","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01","last_updated":"2024-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":4096},"cost":{"input":0.115,"output":0.287}},"qwen-max":{"id":"qwen-max","name":"Qwen Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-03","last_updated":"2025-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.345,"output":1.377}},"qwen3-next-80b-a3b-thinking":{"id":"qwen3-next-80b-a3b-thinking","name":"Qwen3-Next 80B-A3B (Thinking)","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.144,"output":1.434}},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":1.77744,"output":5.33231,"cache_read":0.22218,"cache_write":2.22179},"canonical_model_id":"alibaba/qwen3.8-max"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":2.827,"output":14.133,"cache_read":0.283},"canonical_model_id":"moonshotai/kimi-k3"},"qwen2-5-math-7b-instruct":{"id":"qwen2-5-math-7b-instruct","name":"Qwen2.5-Math 7B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":3072},"cost":{"input":0.144,"output":0.287}},"qwen3.5-plus":{"id":"qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-09-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.115,"output":0.688,"reasoning":0.688,"tiers":[{"input":0.287,"output":1.72,"reasoning":1.72,"tier":{"type":"context","size":128000}},{"input":0.573,"output":3.44,"reasoning":3.44,"tier":{"type":"context","size":256000}}]}},"qwen2-5-72b-instruct":{"id":"qwen2-5-72b-instruct","name":"Qwen2.5 72B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.574,"output":1.721}},"glm-5":{"id":"glm-5","name":"GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-11","last_updated":"2026-02-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":16384},"cost":{"input":0.573,"output":2.58,"tiers":[{"input":0.86,"output":3.154,"tier":{"type":"context","size":32000}}]}},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.29754,"output":1.19015,"cache_read":0.01488},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek-r1-distill-llama-8b":{"id":"deepseek-r1-distill-llama-8b","name":"DeepSeek R1 Distill Llama 8B","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":16384},"cost":{"input":0,"output":0}},"qwen3-32b":{"id":"qwen3-32b","name":"Qwen3 32B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":38912}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.287,"output":1.147,"reasoning":2.868}},"qwen2-5-coder-7b-instruct":{"id":"qwen2-5-coder-7b-instruct","name":"Qwen2.5-Coder 7B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-11","last_updated":"2024-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.144,"output":0.287}},"qwen-plus":{"id":"qwen-plus","name":"Qwen Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.115,"output":0.287,"reasoning":1.147,"cache_read":0.012,"cache_write":0.144}},"qwen3.7-flash":{"id":"qwen3.7-flash","name":"Qwen3.7 Flash","description":"Lightweight multimodal Qwen model for high-throughput text, image, and video tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":262144}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":991808,"output":131072},"cost":{"input":0.02962,"output":0.1185,"cache_read":0.002962,"cache_write":0.03703,"tiers":[{"input":0.08887,"output":0.35549,"cache_read":0.008887,"cache_write":0.11109,"tier":{"type":"context","size":32000}},{"input":0.17774,"output":0.71098,"cache_read":0.017774,"cache_write":0.22218,"tier":{"type":"context","size":256000}}]},"canonical_model_id":"alibaba/qwen3.7-flash"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Moonshot Kimi K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.929,"output":3.858}},"qwen3-max":{"id":"qwen3-max","name":"Qwen3 Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-23","last_updated":"2026-09-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.359,"output":1.434,"reasoning":1.434,"tiers":[{"input":0.574,"output":2.294,"reasoning":2.294,"tier":{"type":"context","size":32000}},{"input":1.004,"output":4.014,"reasoning":4.014,"tier":{"type":"context","size":128000}}]}},"qwen-omni-turbo-realtime":{"id":"qwen-omni-turbo-realtime","name":"Qwen-Omni Turbo Realtime","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-05-08","last_updated":"2025-05-08","modalities":{"input":["text","image","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":32768,"output":2048},"cost":{"input":0.23,"output":0.918,"input_audio":3.584,"output_audio":7.168}},"deepseek-v3":{"id":"deepseek-v3","name":"DeepSeek V3","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-12-01","last_updated":"2024-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"output":8192},"cost":{"input":0.287,"output":1.147}},"deepseek-r1-distill-llama-70b":{"id":"deepseek-r1-distill-llama-70b","name":"DeepSeek R1 Distill Llama 70B","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":16384},"cost":{"input":0.287,"output":0.861}},"qwen3-coder-480b-a35b-instruct":{"id":"qwen3-coder-480b-a35b-instruct","name":"Qwen3-Coder 480B-A35B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.861,"output":3.441,"tiers":[{"input":1.291,"output":5.161,"tier":{"type":"context","size":32000}},{"input":2.151,"output":8.602,"tier":{"type":"context","size":128000}}]}},"qwen-turbo":{"id":"qwen-turbo","name":"Qwen Turbo","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":38912}],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-11-01","last_updated":"2025-07-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":16384},"cost":{"input":0.044,"output":0.087,"reasoning":0.431}},"deepseek-r1-distill-qwen-7b":{"id":"deepseek-r1-distill-qwen-7b","name":"DeepSeek R1 Distill Qwen 7B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":16384},"cost":{"input":0.072,"output":0.144}},"qwen2-5-math-72b-instruct":{"id":"qwen2-5-math-72b-instruct","name":"Qwen2.5-Math 72B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":3072},"cost":{"input":0.574,"output":1.721}},"qwen3-coder-30b-a3b-instruct":{"id":"qwen3-coder-30b-a3b-instruct","name":"Qwen3-Coder 30B-A3B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.216,"output":0.861,"tiers":[{"input":0.323,"output":1.291,"tier":{"type":"context","size":32000}},{"input":0.538,"output":2.151,"tier":{"type":"context","size":128000}}]}},"qwen-doc-turbo":{"id":"qwen-doc-turbo","name":"Qwen Doc Turbo","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01","last_updated":"2024-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.087,"output":0.144}},"kimi-k2-thinking":{"id":"kimi-k2-thinking","name":"Moonshot Kimi K2 Thinking","description":"Kimi reasoning model for long-horizon research, planning, and tool use","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.574,"output":2.294}},"qwen3.8-omni-flash":{"id":"qwen3.8-omni-flash","name":"Qwen3.8 Omni Flash","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.113,"output":0.382,"cache_read":0.014},"canonical_model_id":"alibaba/qwen3.8-omni-flash"},"qvq-max":{"id":"qvq-max","name":"QVQ Max","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"qvq","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-03-25","last_updated":"2025-03-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":1.147,"output":4.588}},"qwen2-5-7b-instruct":{"id":"qwen2-5-7b-instruct","name":"Qwen2.5 7B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.072,"output":0.144}},"qwen3-omni-flash":{"id":"qwen3-omni-flash","name":"Qwen3-Omni Flash","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image","audio","video"],"output":["text","audio"]},"open_weights":false,"limit":{"context":65536,"output":16384},"cost":{"input":0.058,"output":0.23,"input_audio":3.584,"output_audio":7.168}},"qwen-vl-max":{"id":"qwen-vl-max","name":"Qwen-VL Max","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-08","last_updated":"2025-08-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.23,"output":0.574}},"qwen3-235b-a22b":{"id":"qwen3-235b-a22b","name":"Qwen3 235B-A22B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":38912}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.287,"output":1.147,"reasoning":2.868}},"qwen3-vl-30b-a3b":{"id":"qwen3-vl-30b-a3b","name":"Qwen3-VL 30B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.108,"output":0.431,"reasoning":1.076}},"kimi-k2.5":{"id":"kimi-k2.5","name":"Moonshot Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.574,"output":2.411}},"qwen3-next-80b-a3b-instruct":{"id":"qwen3-next-80b-a3b-instruct","name":"Qwen3-Next 80B-A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.144,"output":0.574}},"qwen-vl-plus":{"id":"qwen-vl-plus","name":"Qwen-VL Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-08-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.115,"output":0.287}},"deepseek-r1-distill-qwen-1-5b":{"id":"deepseek-r1-distill-qwen-1-5b","name":"DeepSeek R1 Distill Qwen 1.5B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":16384},"cost":{"input":0,"output":0}},"qwen3.6-flash":{"id":"qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":131072}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.1875,"output":1.125,"cache_write":0.234375},"canonical_model_id":"alibaba/qwen3.6-flash"},"qwen3-coder-flash":{"id":"qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.144,"output":0.574}},"qwen2-5-omni-7b":{"id":"qwen2-5-omni-7b","name":"Qwen2.5-Omni 7B","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-12","last_updated":"2024-12","modalities":{"input":["text","image","audio","video"],"output":["text","audio"]},"open_weights":true,"limit":{"context":32768,"output":2048},"cost":{"input":0.087,"output":0.345,"input_audio":5.448}},"qwen-mt-plus":{"id":"qwen-mt-plus","name":"Qwen-MT Plus","description":"Translation model for multilingual conversion, localization, and cross-language workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-04","release_date":"2025-01","last_updated":"2025-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":8192},"cost":{"input":0.259,"output":0.775}},"tongyi-intent-detect-v3":{"id":"tongyi-intent-detect-v3","name":"Tongyi Intent Detect V3","description":"General-purpose chat model for instruction following, writing, and analysis","family":"yi","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-04","release_date":"2024-01","last_updated":"2024-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1024},"cost":{"input":0.058,"output":0.144}},"qwen3-vl-235b-a22b":{"id":"qwen3-vl-235b-a22b","name":"Qwen3-VL 235B-A22B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.286705,"output":1.14682,"reasoning":2.867051}},"qwen3-coder-plus":{"id":"qwen3-coder-plus","name":"Qwen3 Coder Plus","description":"Hosted Qwen coder for software agents, repo edits, and long-context code","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2026-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":0.574,"output":2.296,"tiers":[{"input":0.861,"output":3.444,"tier":{"type":"context","size":32000}},{"input":1.435,"output":5.74,"tier":{"type":"context","size":128000}},{"input":2.87,"output":28.7,"tier":{"type":"context","size":256000}}]}},"moonshot-kimi-k2-instruct":{"id":"moonshot-kimi-k2-instruct","name":"Moonshot Kimi K2 Instruct","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.574,"output":2.294}},"MiniMax-M2.5":{"id":"MiniMax-M2.5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2}},"qwen2-5-14b-instruct":{"id":"qwen2-5-14b-instruct","name":"Qwen2.5 14B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.144,"output":0.431}},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.11875,"output":0.40073,"cache_read":0.01187,"cache_write":0.14844},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen2-5-vl-7b-instruct":{"id":"qwen2-5-vl-7b-instruct","name":"Qwen2.5-VL 7B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.287,"output":0.717}},"qwen-math-turbo":{"id":"qwen-math-turbo","name":"Qwen Math Turbo","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09-19","last_updated":"2024-09-19","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":4096,"output":3072},"cost":{"input":0.287,"output":0.861}},"qwen-long":{"id":"qwen-long","name":"Qwen Long","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-01-25","last_updated":"2025-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":10000000,"output":8192},"cost":{"input":0.072,"output":0.287}},"qwen3.6-max-preview":{"id":"qwen3.6-max-preview","name":"Qwen3.6 Max Preview","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":131072}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-20","last_updated":"2026-04-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":245800,"output":65536},"cost":{"input":1.32,"output":7.9,"cache_read":0.132}},"qwen-mt-turbo":{"id":"qwen-mt-turbo","name":"Qwen-MT Turbo","description":"Translation model for multilingual conversion, localization, and cross-language workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-04","release_date":"2025-01","last_updated":"2025-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":8192},"cost":{"input":0.101,"output":0.28}},"qwen3.5-397b-a17b":{"id":"qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.172,"output":1.032,"reasoning":1.032,"tiers":[{"input":0.43,"output":2.58,"reasoning":2.58,"tier":{"type":"context","size":128000}}]}},"qwen3-8b":{"id":"qwen3-8b","name":"Qwen3 8B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":38912}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.072,"output":0.287,"reasoning":0.717}},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":1.1,"output":3.851,"cache_read":0.275,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"qwen-omni-turbo":{"id":"qwen-omni-turbo","name":"Qwen-Omni Turbo","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-01-19","last_updated":"2025-03-26","modalities":{"input":["text","image","audio","video"],"output":["text","audio"]},"open_weights":false,"limit":{"context":32768,"output":2048},"cost":{"input":0.058,"output":0.23,"input_audio":3.584,"output_audio":7.168}},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":131072}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-14","last_updated":"2026-04-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":128000},"cost":{"input":0.825,"output":3.301,"cache_read":0.17,"tiers":[{"input":1.1,"output":3.851,"tier":{"type":"context","size":32000}}]}},"qwen3-omni-flash-realtime":{"id":"qwen3-omni-flash-realtime","name":"Qwen3-Omni Flash Realtime","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":65536,"output":16384},"cost":{"input":0.23,"output":0.918,"input_audio":3.584,"output_audio":7.168}},"qwen3-asr-flash":{"id":"qwen3-asr-flash","name":"Qwen3-ASR Flash","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2024-04","release_date":"2025-09-08","last_updated":"2025-09-08","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":53248,"output":4096},"cost":{"input":0.032,"output":0.032}},"deepseek-r1-distill-qwen-32b":{"id":"deepseek-r1-distill-qwen-32b","name":"DeepSeek R1 Distill Qwen 32B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":16384},"cost":{"input":0.287,"output":0.861}},"deepseek-r1":{"id":"deepseek-r1","name":"DeepSeek R1","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"cost":{"input":0.574,"output":2.294}},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.435,"output":0.87,"cache_read":0.003625},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek-r1-0528":{"id":"deepseek-r1-0528","name":"DeepSeek R1 0528","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"cost":{"input":0.574,"output":2.294}},"qwen3.6-plus":{"id":"qwen3.6-plus","name":"Qwen3.6 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625,"tiers":[{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5}}},"qwen3-14b":{"id":"qwen3-14b","name":"Qwen3 14B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":38912}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.144,"output":0.574,"reasoning":1.434}},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.1,"output":3.851,"cache_read":0.275,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":262144}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625,"tiers":[{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3.7-plus"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"qwen-vl-ocr":{"id":"qwen-vl-ocr","name":"Qwen-VL OCR","description":"OCR model for extracting structured text from documents and screenshots","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-04","release_date":"2024-10-28","last_updated":"2026-09-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":34096,"output":4096},"cost":{"input":0.043,"output":0.072}},"siliconflow/deepseek-v3-0324":{"id":"siliconflow/deepseek-v3-0324","name":"siliconflow/deepseek-v3-0324","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-12-26","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":163840,"output":163840},"cost":{"input":0.25,"output":1}},"siliconflow/deepseek-v3.1-terminus":{"id":"siliconflow/deepseek-v3.1-terminus","name":"siliconflow/deepseek-v3.1-terminus","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-29","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":163840,"output":65536},"cost":{"input":0.27,"output":1}},"siliconflow/deepseek-r1-0528":{"id":"siliconflow/deepseek-r1-0528","name":"siliconflow/deepseek-r1-0528","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":163840,"output":32768},"cost":{"input":0.5,"output":2.18}},"siliconflow/deepseek-v3.2":{"id":"siliconflow/deepseek-v3.2","name":"siliconflow/deepseek-v3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-03","last_updated":"2025-12-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":163840,"output":65536},"cost":{"input":0.27,"output":0.42}},"kimi/kimi-k2.5":{"id":"kimi/kimi-k2.5","name":"kimi/kimi-k2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":3,"cache_read":0.1}},"MiniMax/MiniMax-M2.7":{"id":"MiniMax/MiniMax-M2.7","name":"MiniMax-M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":0.375}}}}}
\ No newline at end of file
+{"sap-ai-core":{"id":"sap-ai-core","env":["AICORE_SERVICE_KEY"],"npm":"@jerome-benoit/sap-ai-provider-v2","name":"SAP AI Core","doc":"https://help.sap.com/docs/sap-ai-core","models":{"nvidia--llama-nemotron-embed-1b":{"id":"nvidia--llama-nemotron-embed-1b","type":"embedding","name":"Llama Nemotron Embed 1B v2","description":"Multilingual text embedding model for retrieval and question answering pipelines","family":"nemotron","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-10-16","last_updated":"2025-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":2048},"canonical_model_id":"nvidia/llama-nemotron-embed-1b-v2"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"canonical_model_id":"openai/gpt-6-luna"},"gemini-embedding-2":{"id":"gemini-embedding-2","type":"embedding","name":"Gemini Embedding 2","description":"Multimodal embedding model mapping text, images, video, audio, and PDFs into a unified embedding space","family":"gemini","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-11","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":3072},"canonical_model_id":"google/gemini-embedding-2"},"anthropic--claude-4.6-opus":{"id":"anthropic--claude-4.6-opus","name":"anthropic--claude-4.6-opus","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic--claude-4.8-opus":{"id":"anthropic--claude-4.8-opus","name":"anthropic--claude-4.8-opus","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"canonical_model_id":"openai/gpt-6.1-sol"},"gemini-2.5-flash-lite":{"id":"gemini-2.5-flash-lite","name":"gemini-2.5-flash-lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":512,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":0.1,"output":0.4,"cache_read":0.01,"input_audio":0.3},"canonical_model_id":"google/gemini-2.5-flash-lite"},"mistralai--mistral-small":{"id":"mistralai--mistral-small","name":"mistralai--mistral-small","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"status":"deprecated","cost":{"input":0.15,"output":0.6},"canonical_model_id":"mistral/mistral-small-2603"},"sap-abap-1":{"id":"sap-abap-1","name":"sap-abap-1","description":"SAP-hosted model for ABAP code generation and enterprise development tasks","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-11-26","last_updated":"2025-11-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":4096},"status":"deprecated"},"anthropic--claude-4.5-opus":{"id":"anthropic--claude-4.5-opus","name":"anthropic--claude-4.5-opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic--claude-3.5-sonnet":{"id":"anthropic--claude-3.5-sonnet","name":"anthropic--claude-3.5-sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04-30","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-3-5-sonnet-20241022"},"gpt-4.1":{"id":"gpt-4.1","name":"gpt-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"status":"deprecated","cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"gemini-2.5-flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":0.3,"output":2.5,"cache_read":0.03,"input_audio":1},"canonical_model_id":"google/gemini-2.5-flash"},"text-embedding-3-small":{"id":"text-embedding-3-small","type":"embedding","name":"text-embedding-3-small","description":"Small, efficient OpenAI text embedding model","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8191,"output":1536},"cost":{"input":0.02,"output":0},"canonical_model_id":"openai/text-embedding-3-small"},"mistralai--mistral-medium":{"id":"mistralai--mistral-medium","name":"Mistral Medium 3.5","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"canonical_model_id":"mistral/mistral-medium-2604"},"cohere--command-a-reasoning":{"id":"cohere--command-a-reasoning","name":"cohere--command-a-reasoning","description":"Cohere reasoning model for multilingual enterprise agents, tools, and complex workflows","family":"command-a","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]},{"type":"budget_tokens","min":1}],"tool_call":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32000},"status":"deprecated","cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-a-reasoning-08-2025"},"mistralai--mistral-medium-instruct":{"id":"mistralai--mistral-medium-instruct","name":"mistralai--mistral-medium-instruct","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000},"status":"deprecated","cost":{"input":0.4,"output":2},"canonical_model_id":"mistral/mistral-medium-2505"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"gpt-5.6-luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04}},"canonical_model_id":"openai/gpt-5.6-luna"},"amazon--nova-micro":{"id":"amazon--nova-micro","name":"amazon--nova-micro","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-micro","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.035,"output":0.14},"canonical_model_id":"amazon/nova-micro"},"anthropic--claude-3.7-sonnet":{"id":"anthropic--claude-3.7-sonnet","name":"anthropic--claude-3.7-sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2024-10-31","release_date":"2025-02-19","last_updated":"2025-02-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-3-7-sonnet-20250219"},"amazon--nova-pro":{"id":"amazon--nova-pro","name":"amazon--nova-pro","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":8192},"cost":{"input":0.8,"output":3.2},"canonical_model_id":"amazon/nova-pro"},"gemini-2.5-pro":{"id":"gemini-2.5-pro","name":"gemini-2.5-pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"google/gemini-2.5-pro"},"anthropic--claude-4.5-sonnet":{"id":"anthropic--claude-4.5-sonnet","name":"anthropic--claude-4.5-sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"gpt-5.4":{"id":"gpt-5.4","name":"gpt-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.4"},"anthropic--claude-4.7-opus":{"id":"anthropic--claude-4.7-opus","name":"anthropic--claude-4.7-opus","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic--claude-3-haiku":{"id":"anthropic--claude-3-haiku","name":"anthropic--claude-3-haiku","description":"Legacy model retained for compatibility with older integrations","family":"claude-haiku","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-08-31","release_date":"2024-03-13","last_updated":"2024-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":4096},"cost":{"input":0.25,"output":1.25,"cache_read":0.03,"cache_write":0.3},"canonical_model_id":"anthropic/claude-3-haiku-20240307"},"gemini-3.5-flash-lite":{"id":"gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"canonical_model_id":"google/gemini-3.5-flash-lite"},"anthropic--claude-4.5-haiku":{"id":"anthropic--claude-4.5-haiku","name":"anthropic--claude-4.5-haiku","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic--claude-3-sonnet":{"id":"anthropic--claude-3-sonnet","name":"anthropic--claude-3-sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-08-31","release_date":"2024-03-04","last_updated":"2024-03-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":4096},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75}},"sonar-deep-research":{"id":"sonar-deep-research","name":"sonar-deep-research","description":"Sonar search model for autonomous research and citation-backed long-form reports","family":"sonar","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":false,"temperature":false,"knowledge":"2025-01","release_date":"2025-02-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32768},"cost":{"input":2,"output":8,"reasoning":3},"canonical_model_id":"perplexity/sonar-deep-research"},"sonar":{"id":"sonar","name":"sonar","description":"Fast web-grounded Sonar for current answers, citations, and lightweight retrieval","family":"sonar","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":1,"output":1},"canonical_model_id":"perplexity/sonar"},"anthropic--claude-4-opus":{"id":"anthropic--claude-4-opus","name":"anthropic--claude-4-opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-20250514"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"gpt-5.6-sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"tiers":[{"input":8,"output":30,"cache_read":0.8,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8}},"canonical_model_id":"openai/gpt-5.6-sol"},"text-embedding-3-large":{"id":"text-embedding-3-large","type":"embedding","name":"text-embedding-3-large","description":"Most capable OpenAI embedding model for English and non-English text","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8191,"output":3072},"cost":{"input":0.13,"output":0},"canonical_model_id":"openai/text-embedding-3-large"},"gpt-4.1-mini":{"id":"gpt-4.1-mini","name":"gpt-4.1-mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"status":"deprecated","cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"anthropic--claude-4.6-sonnet":{"id":"anthropic--claude-4.6-sonnet","name":"anthropic--claude-4.6-sonnet","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic--claude-4-sonnet":{"id":"anthropic--claude-4-sonnet","name":"anthropic--claude-4-sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-20250514"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"gemini-3.5-flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.5-flash"},"gpt-5-mini":{"id":"gpt-5-mini","name":"gpt-5-mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"amazon--nova-lite":{"id":"amazon--nova-lite","name":"amazon--nova-lite","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-10","release_date":"2025-12-02","last_updated":"2025-12-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.3,"output":2.5},"canonical_model_id":"amazon/nova-2-lite"},"gpt-4.1-nano":{"id":"gpt-4.1-nano","name":"gpt-4.1-nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"status":"deprecated","cost":{"input":0.1,"output":0.4},"canonical_model_id":"openai/gpt-4.1-nano"},"gemini-3.8-flash":{"id":"gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"canonical_model_id":"google/gemini-3.8-flash"},"gemini-embedding":{"id":"gemini-embedding","type":"embedding","name":"Gemini Embedding 001","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-05","release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":2048,"output":1},"canonical_model_id":"google/gemini-embedding-001"},"nvidia--llama-3.2-nv-embedqa-1b":{"id":"nvidia--llama-3.2-nv-embedqa-1b","name":"nvidia--llama-3.2-nv-embedqa-1b","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":4096},"status":"deprecated"},"gemini-3.1-flash-lite":{"id":"gemini-3.1-flash-lite","name":"gemini-3.1-flash-lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"gpt-5.6-terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"openai/gpt-5.6-terra"},"gpt-5.5":{"id":"gpt-5.5","name":"gpt-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5"},"gpt-5":{"id":"gpt-5","name":"gpt-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"gpt-5-nano":{"id":"gpt-5-nano","name":"gpt-5-nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"amazon--titan-embed-text":{"id":"amazon--titan-embed-text","name":"amazon--titan-embed-text","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-04-30","last_updated":"2024-04-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536},"cost":{"input":0.02,"output":0}},"sonar-pro":{"id":"sonar-pro","name":"sonar-pro","description":"Deeper Sonar search model with broader retrieval and stronger synthesis","family":"sonar-pro","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":3,"output":15},"canonical_model_id":"perplexity/sonar-pro"},"gpt-5.2":{"id":"gpt-5.2","name":"gpt-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"canonical_model_id":"openai/gpt-6-astra"},"gemini-3.6-flash":{"id":"gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"canonical_model_id":"google/gemini-3.6-flash"},"anthropic--claude-3-opus":{"id":"anthropic--claude-3-opus","name":"anthropic--claude-3-opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-08-31","release_date":"2024-02-29","last_updated":"2024-02-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":4096},"status":"deprecated","cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75}}}},"llmgateway":{"id":"llmgateway","env":["LLMGATEWAY_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.llmgateway.io/v1","name":"DevPass (LLM Gateway)","doc":"https://llmgateway.io/docs","models":{"qwen3-max":{"id":"qwen3-max","name":"Qwen3 Max","description":"Flagship Qwen3 model for coding agents, complex reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.845,"output":3.38,"cache_read":0.6,"cache_write":3.75},"canonical_model_id":"alibaba/qwen3-max"},"claude-sonnet-4-5":{"id":"claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"hy-mt2-plus":{"id":"hy-mt2-plus","name":"Hy-MT2 Plus","description":"Tool-capable chat model for instruction following and agentic application workflows","family":"Hy","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8192},"cost":{"input":0.074,"output":0.295}},"mistral-large-2512":{"id":"mistral-large-2512","name":"Mistral Large 3","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"mistral/mistral-large-2512"},"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-6-sol"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"openai/gpt-6-luna"},"glm-5-turbo":{"id":"glm-5-turbo","name":"GLM-5-Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5-turbo"},"muse-spark-1.3":{"id":"muse-spark-1.3","name":"Muse Spark 1.3","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.3"},"qwen3-vl-30b-a3b-instruct":{"id":"qwen3-vl-30b-a3b-instruct","name":"Qwen3 VL 30B A3B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-04","last_updated":"2025-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"alibaba/qwen3-vl-30b-a3b-instruct"},"kimi-k3-fast":{"id":"kimi-k3-fast","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1040384,"output":131072},"cost":{"input":4.5,"output":22.5,"cache_read":0.45},"canonical_model_id":"moonshotai/kimi-k3"},"qwen-plus-latest":{"id":"qwen-plus-latest","name":"Qwen Plus Latest","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-01-25","last_updated":"2025-01-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":8192},"cost":{"input":0.4,"output":1.2,"cache_read":0.08,"cache_write":0.5}},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32766},"cost":{"input":0.032,"output":0.14,"cache_read":0.032},"canonical_model_id":"openai/gpt-oss-120b"},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"openai/gpt-6.1-sol"},"minimax-m2.1":{"id":"minimax-m2.1","name":"MiniMax-M2.1","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.27,"output":1.1},"canonical_model_id":"minimax/MiniMax-M2.1"},"fugu-max":{"id":"fugu-max","name":"Fugu Max","description":"Multi-agent model for routing expert agents across complex analytical tasks","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"sakana/fugu-max"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"gemini-3.7-flash":{"id":"gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.7-flash"},"glm-4.5v":{"id":"glm-4.5v","name":"GLM-4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.6,"output":1.8,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5v"},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"fugu-ultra":{"id":"fugu-ultra","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"sakana/fugu-ultra"},"gpt-4":{"id":"gpt-4","name":"GPT-4","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-11","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8192},"status":"deprecated","cost":{"input":30,"output":60},"canonical_model_id":"openai/gpt-4"},"qwen3.6-flash":{"id":"qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.05,"cache_write":0.3125},"canonical_model_id":"alibaba/qwen3.6-flash"},"grok-4-20-reasoning":{"id":"grok-4-20-reasoning","name":"Grok 4.20 (Reasoning)","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-reasoning"},"gpt-live-transcribe":{"id":"gpt-live-transcribe","type":"transcription","name":"GPT-Live-Transcribe","description":"Low-latency streaming speech-to-text model with keyword and language hints","family":"gpt","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-07-28","last_updated":"2026-07-28","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":0,"output":0},"canonical_model_id":"openai/gpt-live-transcribe"},"glm-4.7":{"id":"glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.45,"output":2,"cache_read":0.19,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":384000},"cost":{"input":0.076,"output":0.153,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash"},"grok-4-7":{"id":"grok-4-7","name":"Grok 4.7","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.7"},"ministral-8b-2512":{"id":"ministral-8b-2512","name":"Ministral 8B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.15,"output":0.15},"canonical_model_id":"mistral/ministral-8b-2512"},"gpt-5-pro":{"id":"gpt-5-pro","name":"GPT-5 Pro","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":272000},"cost":{"input":15,"output":120},"canonical_model_id":"openai/gpt-5-pro"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"gemini-pro-latest":{"id":"gemini-pro-latest","name":"Gemini Pro Latest","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-27","last_updated":"2026-02-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2}},"glm-4.6v":{"id":"glm-4.6v","name":"GLM-4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.3,"output":0.9,"cache_read":0.05},"canonical_model_id":"zhipuai/glm-4.6v"},"ministral-14b-2512":{"id":"ministral-14b-2512","name":"Ministral 14B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.2,"output":0.2},"canonical_model_id":"mistral/ministral-14b-2512"},"ministral-3b-2512":{"id":"ministral-3b-2512","name":"Ministral 3B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.1,"output":0.1},"canonical_model_id":"mistral/ministral-3b-2512"},"seed-2-0-code-preview-260328":{"id":"seed-2-0-code-preview-260328","name":"Seed 2.0 Code Preview (260328)","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-28","last_updated":"2026-03-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":3,"cache_read":0.1}},"minimax-m3.1-flash":{"id":"minimax-m3.1-flash","name":"MiniMax-M3.1-Flash","description":"Frontier multimodal coding model with 1M context window and tunable thinking depth","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-19","last_updated":"2026-10-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":512000},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"minimax/MiniMax-M3.1-Flash"},"qwen3.5-35b-a3b":{"id":"qwen3.5-35b-a3b","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.25,"output":2},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"gpt-5.4-pro":{"id":"gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180},"canonical_model_id":"openai/gpt-5.4-pro"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"qwen3-coder-30b-a3b-instruct":{"id":"qwen3-coder-30b-a3b-instruct","name":"Qwen3-Coder 30B-A3B Instruct","description":"Smaller Qwen coder for efficient local agents and repo-level fixes","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-31","last_updated":"2025-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":65536},"cost":{"input":0.07,"output":0.27},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"gpt-transcribe":{"id":"gpt-transcribe","type":"transcription","name":"GPT-Transcribe","description":"High-accuracy speech-to-text model for audio files and committed Realtime turns","family":"gpt","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-07-28","last_updated":"2026-07-28","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":0,"output":0},"canonical_model_id":"openai/gpt-transcribe"},"gemini-3-flash-preview":{"id":"gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05},"canonical_model_id":"google/gemini-3-flash-preview"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.605,"output":2.123,"cache_read":0.154,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"o1":{"id":"o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":15,"output":60,"cache_read":7.5},"canonical_model_id":"openai/o1"},"qwen-max":{"id":"qwen-max","name":"Qwen Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-03","last_updated":"2025-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":8192},"cost":{"input":1.6,"output":6.4},"canonical_model_id":"alibaba/qwen-max"},"glm-5v-turbo":{"id":"glm-5v-turbo","name":"GLM-5V-Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5v-turbo"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":384000},"cost":{"input":0.135,"output":0.54,"cache_read":0.0027},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"gpt-4.1":{"id":"gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"seed-1-6-flash-250715":{"id":"seed-1-6-flash-250715","name":"Seed 1.6 Flash (250715)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-26","last_updated":"2025-07-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.07,"output":0.3,"cache_read":0.015}},"glm-5":{"id":"glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":203000,"output":131072},"cost":{"input":0.573,"output":2.58,"cache_read":0.144,"cache_write":0},"canonical_model_id":"zhipuai/glm-5"},"llama-3.2-3b-instruct":{"id":"llama-3.2-3b-instruct","name":"Llama 3.2 3B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2024-09-18","last_updated":"2024-09-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32000},"cost":{"input":0.03,"output":0.05}},"qwen3.5-9b":{"id":"qwen3.5-9b","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.1,"output":0.15},"canonical_model_id":"alibaba/qwen3.5-9b"},"qwen3-14b":{"id":"qwen3-14b","name":"Qwen3 14B","description":"Tool-capable chat model for instruction following and agentic application workflows","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.076,"output":0.228}},"gpt-4o":{"id":"gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"qwen3-235b-a22b-instruct-2507":{"id":"qwen3-235b-a22b-instruct-2507","name":"Qwen3 235B A22B Instruct (2507)","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.09,"output":0.58},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"minimax-text-01":{"id":"minimax-text-01","name":"MiniMax Text 01","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-01-15","last_updated":"2025-01-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.2,"output":1.1}},"granite-4.2-8b":{"id":"granite-4.2-8b","name":"Granite 4.2 8B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"granite","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-25","last_updated":"2026-08-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.06,"output":0.25,"cache_read":0.015},"canonical_model_id":"ibm/granite-4.2-8b"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.5,"output":2,"cache_read":0.15},"canonical_model_id":"zhipuai/glm-5.3"},"qwen3.8-2.4t-a95b":{"id":"qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1010000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max Preview","description":"Preview Qwen flagship for million-token multimodal reasoning and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-19","last_updated":"2026-07-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":1.54,"output":4.631,"cache_read":0.198,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max-preview"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":384000},"cost":{"input":0.435,"output":0.87,"cache_read":0.003625},"canonical_model_id":"deepseek/deepseek-v4-pro"},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"qwen3.6-27b":{"id":"qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":65536},"cost":{"input":0.15,"output":1.35},"canonical_model_id":"alibaba/qwen3.6-27b"},"gpt-5.1":{"id":"gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"mistral-medium-3-5":{"id":"mistral-medium-3-5","name":"Mistral Medium 3.5","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":1.5,"output":7.5},"canonical_model_id":"mistral/mistral-medium-3-5"},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"grok-4-1-fast-non-reasoning":{"id":"grok-4-1-fast-non-reasoning","name":"Grok 4.1 Fast Non-Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":0.2,"output":0.5,"cache_read":0.05}},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":false,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"qwen3-235b-a22b-thinking-2507":{"id":"qwen3-235b-a22b-thinking-2507","name":"Qwen3 235B A22B Thinking (2507)","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-08","last_updated":"2025-07-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":8192},"cost":{"input":0.3,"output":3}},"qwen3-vl-plus":{"id":"qwen3-vl-plus","name":"Qwen3-VL Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.2,"output":1.6,"reasoning":4.8,"cache_read":0.04,"cache_write":0.25},"canonical_model_id":"alibaba/qwen3-vl-plus"},"muse-spark-1.2":{"id":"muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.088,"output":0.25,"cache_read":0.025},"canonical_model_id":"zhipuai/glm-5.3-flash"},"grok-4-20-non-reasoning":{"id":"grok-4-20-non-reasoning","name":"Grok 4.20 (Non-Reasoning)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-non-reasoning"},"qwen-flash":{"id":"qwen-flash","name":"Qwen Flash","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.05,"output":0.4,"cache_read":0.01,"cache_write":0.0625},"canonical_model_id":"alibaba/qwen-flash"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25},"canonical_model_id":"openai/gpt-5.6-luna"},"mistral-small-2506":{"id":"mistral-small-2506","name":"Mistral Small 3.2","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-03","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"mistral/mistral-small-2506"},"glm-4.7-flash":{"id":"glm-4.7-flash","name":"GLM-4.7-Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.06,"output":0.4,"cache_read":0.01,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7-flash"},"llama-4-maverick-17b-instruct":{"id":"llama-4-maverick-17b-instruct","name":"Llama 4 Maverick 17B Instruct","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":2048},"cost":{"input":0.27,"output":0.85},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.574,"output":3.011,"cache_read":0.225},"canonical_model_id":"moonshotai/kimi-k2.5"},"gpt-5.2-pro":{"id":"gpt-5.2-pro","name":"GPT-5.2 Pro","description":"Higher-accuracy GPT-5.2 variant for tougher reasoning and review workflows","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":21,"output":168},"canonical_model_id":"openai/gpt-5.2-pro"},"qwen3-coder-flash":{"id":"qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":997952,"output":65536},"cost":{"input":0.3,"output":1.5,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"alibaba/qwen3-coder-flash"},"mimo-v2.6-flash":{"id":"mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.12,"output":0.25,"cache_read":0.0025},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"minimax-m2.7-highspeed":{"id":"minimax-m2.7-highspeed","name":"MiniMax-M2.7-highspeed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"output":64000},"cost":{"input":0.4,"output":1.6,"cache_read":0.08,"cache_write":0.5},"canonical_model_id":"alibaba/qwen3.7-plus"},"glm-4.5-air":{"id":"glm-4.5-air","name":"GLM-4.5-Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":98304},"cost":{"input":0.2,"output":1.1,"cache_read":0.03,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5-air"},"grok-4-3":{"id":"grok-4-3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.3"},"llama-3-70b-instruct":{"id":"llama-3-70b-instruct","name":"Llama 3 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2024-04-18","last_updated":"2024-04-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8000},"cost":{"input":0.51,"output":0.74}},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"anthropic/claude-haiku-5-5"},"llama-3.3-70b-instruct":{"id":"llama-3.3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":4096},"cost":{"input":0.135,"output":0.4},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"minimax-m2.1-lightning":{"id":"minimax-m2.1-lightning","name":"MiniMax M2.1 Lightning","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":131072},"cost":{"input":0.12,"output":0.48}},"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.4"},"qwen3-coder-480b-a35b-instruct":{"id":"qwen3-coder-480b-a35b-instruct","name":"Qwen3-Coder 480B-A35B Instruct","description":"Open Qwen coding heavyweight for repository reasoning and agentic engineering","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.38,"output":1.55},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"minimax-m2.5":{"id":"minimax-m2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":228700,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5"},"reka-edge-2603":{"id":"reka-edge-2603","name":"Reka Edge 2603","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"reka","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-09","last_updated":"2026-10-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":16384},"cost":{"input":0.1,"output":0.1}},"glm-4.5-airx":{"id":"glm-4.5-airx","name":"GLM-4.5 AirX","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1.1,"output":4.5,"cache_read":0.22}},"gpt-4o-transcribe":{"id":"gpt-4o-transcribe","name":"GPT-4o Transcribe","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-03-20","last_updated":"2025-03-20","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":false,"limit":{"context":16000,"output":16000},"cost":{"input":2.5,"output":10}},"gemini-4-argon":{"id":"gemini-4-argon","name":"Gemini 4 Argon","description":"Gemini multimodal model for text, image, audio, video, and document tasks","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":0.375},"canonical_model_id":"google/gemini-4-argon"},"gemma-4-31b-it":{"id":"gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.1,"output":0.25,"cache_read":0.01},"canonical_model_id":"google/gemma-4-31b-it"},"seed-1-8-251228":{"id":"seed-1-8-251228","name":"Seed 1.8 (251228)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-18","last_updated":"2025-12-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.25,"output":2,"cache_read":0.05}},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"gemini-3.5-flash-lite":{"id":"gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.5-flash-lite"},"qwen3-next-80b-a3b-instruct":{"id":"qwen3-next-80b-a3b-instruct","name":"Qwen3-Next 80B-A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":1.5},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"nemotron-3-ultra-550b":{"id":"nemotron-3-ultra-550b","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":128000},"cost":{"input":0.5,"output":2.2,"cache_read":0.1},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"muse-spark-1.2-contributor":{"id":"muse-spark-1.2-contributor","name":"Muse Spark 1.2 Contributor","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-06","last_updated":"2026-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"muse-spark-1.1":{"id":"muse-spark-1.1","name":"Muse Spark 1.1","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.1"},"qwen3-30b-a3b":{"id":"qwen3-30b-a3b","name":"Qwen3 30B A3B","description":"Sparse MoE Qwen model with 3B active parameters for efficient chat and reasoning","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"cost":{"input":0.095,"output":0.285},"canonical_model_id":"alibaba/qwen3-30b-a3b"},"claude-fable-5-1":{"id":"claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"qwen3-32b":{"id":"qwen3-32b","name":"Qwen3 32B","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":16384},"cost":{"input":0.36,"output":0.87,"reasoning":8.4},"canonical_model_id":"alibaba/qwen3-32b"},"mistral-small-2603":{"id":"mistral-small-2603","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"mistral/mistral-small-2603"},"minimax-m2.5-highspeed":{"id":"minimax-m2.5-highspeed","name":"MiniMax-M2.5-highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-13","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5-highspeed"},"gpt-4o-mini-transcribe":{"id":"gpt-4o-mini-transcribe","name":"GPT-4o Mini Transcribe","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-03-20","last_updated":"2025-03-20","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":false,"limit":{"context":16000,"output":16000},"cost":{"input":1.25,"output":5}},"qwen35-397b-a17b":{"id":"qwen35-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.6,"output":3.6},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":3.05,"cache_read":0.13},"canonical_model_id":"moonshotai/kimi-k2.6"},"fugu-ultra-v2.0":{"id":"fugu-ultra-v2.0","name":"Fugu Ultra v2.0","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":5,"output":30,"cache_read":0.5}},"glm-4.6v-flashx":{"id":"glm-4.6v-flashx","name":"GLM-4.6V FlashX","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16000},"cost":{"input":0.04,"output":0.4,"cache_read":0.004}},"custom":{"id":"custom","name":"Custom Model","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0,"output":0}},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"sonar":{"id":"sonar","name":"Sonar","description":"Fast web-grounded Sonar for current answers, citations, and lightweight retrieval","family":"sonar","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":130000,"output":4096},"cost":{"input":0.25,"output":2.5,"cache_write":0.25},"canonical_model_id":"perplexity/sonar"},"Qwen3.8-27B":{"id":"Qwen3.8-27B","name":"Qwen3.8 27B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":32768},"cost":{"input":0.08,"output":0.35,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.8-27b"},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1.38,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.1"},"glm-4-32b-0414-128k":{"id":"glm-4-32b-0414-128k","name":"GLM-4 32B (0414-128k)","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.1,"output":0.1}},"llama-4-scout-17b-instruct":{"id":"llama-4-scout-17b-instruct","name":"Llama 4 Scout 17B Instruct","description":"Open multimodal Llama model for long-context analysis and efficient agents","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":2048},"cost":{"input":0.18,"output":0.59},"canonical_model_id":"meta/llama-4-scout-17b-instruct"},"grok-build-0-1":{"id":"grok-build-0-1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.2,"tiers":[{"input":2,"output":4,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2,"output":4,"cache_read":0.4}},"canonical_model_id":"xai/grok-build-0.1"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5},"canonical_model_id":"openai/gpt-5.6-sol"},"claude-opus-4-5-20251101":{"id":"claude-opus-4-5-20251101","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]},{"type":"budget_tokens","min":1024,"max":31999}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"qwen3.7-max":{"id":"qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":1.25,"output":3.75,"cache_read":0.25,"cache_write":3.125},"canonical_model_id":"alibaba/qwen3.7-max"},"mimo-v2.6-pro":{"id":"mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"qwen3-235b-a22b-fp8":{"id":"qwen3-235b-a22b-fp8","name":"Qwen3 235B A22B FP8","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":8192},"cost":{"input":0.2,"output":0.8}},"minimax-m2":{"id":"minimax-m2","name":"MiniMax-M2","description":"Efficient open MiniMax model built for coding agents and tool-heavy workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":131072},"cost":{"input":0.2,"output":1,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2"},"ling-3.0-flash-vl":{"id":"ling-3.0-flash-vl","name":"Ling 3.0 Flash VL","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.06,"output":0.18,"cache_read":0.012},"canonical_model_id":"inclusionai/ling-3.0-flash-vl"},"grok-4":{"id":"grok-4","name":"Grok 4","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-07-09","last_updated":"2025-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":3,"output":15,"cache_read":0.75}},"mimo-v2.5-pro":{"id":"mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.522,"output":1.044,"cache_read":0.0043,"tiers":[{"input":2,"output":6,"cache_read":0.4,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.4}},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"hy4-preview":{"id":"hy4-preview","name":"Hy4 preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":64000},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"},"mimo-v2.5":{"id":"mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.168,"output":0.336,"cache_read":0.0034,"tiers":[{"input":0.8,"output":4,"cache_read":0.16,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.8,"output":4,"cache_read":0.16}},"canonical_model_id":"xiaomi/mimo-v2.5"},"gpt-4.1-mini":{"id":"gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"gpt-oss-20b":{"id":"gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32766},"cost":{"input":0.04,"output":0.19,"cache_read":0.01},"canonical_model_id":"openai/gpt-oss-20b"},"qwen-plus":{"id":"qwen-plus","name":"Qwen Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.4,"output":1.2,"reasoning":4,"cache_read":0.08,"cache_write":0.5},"canonical_model_id":"alibaba/qwen-plus"},"gpt-5.2-codex":{"id":"gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Code-specialist GPT for repository edits, reviews, and long-running software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-codex"},"glm-4.6":{"id":"glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.55,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.6"},"glm-4.5":{"id":"glm-4.5","name":"GLM-4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":98304},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5"},"gemma-4-26b-a4b-it":{"id":"gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.07,"output":0.34},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"step-3.7-flash":{"id":"step-3.7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"grok-4-6":{"id":"grok-4-6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"gemini-3.1-pro-preview":{"id":"gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"mistral-large-4":{"id":"mistral-large-4","name":"Mistral Large 4","description":"Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":262144},"cost":{"input":1.36,"output":4.18,"cache_read":0.14},"canonical_model_id":"mistral/mistral-large-4"},"gpt-5.5-pro":{"id":"gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.5-pro"},"qwen3.5-122b-a10b":{"id":"qwen3.5-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.4,"output":3.2},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.5-flash"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"hy3":{"id":"hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":192000,"output":128000},"cost":{"input":0.132,"output":0.528,"cache_read":0.033},"canonical_model_id":"tencent/hy3"},"ling-3.0-flash":{"id":"ling-3.0-flash","name":"InclusionAI Ling 3.0 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-23","last_updated":"2026-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.06,"output":0.18,"cache_read":0.012},"canonical_model_id":"inclusionai/ling-3.0-flash"},"muse-glimmer-30b":{"id":"muse-glimmer-30b","name":"Muse Glimmer 30B","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.04},"canonical_model_id":"meta/muse-glimmer-30b"},"muse-spark-1.3-contributor":{"id":"muse-spark-1.3-contributor","name":"Muse Spark 1.3 Contributor","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"grok-4-1-fast-reasoning":{"id":"grok-4-1-fast-reasoning","name":"Grok 4.1 Fast Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"xai/grok-4.1-fast-reasoning"},"gpt-5-mini":{"id":"gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"minimax-m2.7":{"id":"minimax-m2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.08,"output":0.32,"cache_read":0.017,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7"},"glm-5.3-fast":{"id":"glm-5.3-fast","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":2.8,"output":8.8,"cache_read":0.56},"canonical_model_id":"zhipuai/glm-5.3"},"seed-2-0-pro-260328":{"id":"seed-2-0-pro-260328","name":"Seed 2.0 Pro (260328)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-28","last_updated":"2026-03-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":3,"cache_read":0.1}},"claude-sonnet-4-5-20250929":{"id":"claude-sonnet-4-5-20250929","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"gpt-4.1-nano":{"id":"gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"status":"deprecated","cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"gpt-5.1-codex":{"id":"gpt-5.1-codex","name":"GPT-5.1 Codex","description":"Codex GPT for repository edits, code review, and practical software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex"},"kimi-k2":{"id":"kimi-k2","name":"Kimi K2","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":0.57,"output":2.3,"cache_read":0.5}},"gemini-3.8-flash":{"id":"gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.8-flash"},"ernie-4.5-vl-424b-a47b":{"id":"ernie-4.5-vl-424b-a47b","name":"ERNIE 4.5 VL 424B A47B","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ernie","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-06-30","last_updated":"2025-06-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":123000,"output":123000},"cost":{"input":0.42,"output":1.25}},"qwen3.7-flash":{"id":"qwen3.7-flash","name":"Qwen3.7 Flash","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"output":1000000},"cost":{"input":0.03,"output":0.13,"cache_read":0.006,"cache_write":0.0375},"canonical_model_id":"alibaba/qwen3.7-flash"},"qwen3.6-plus":{"id":"qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625,"tiers":[{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5}},"canonical_model_id":"alibaba/qwen3.6-plus"},"qwen3-vl-235b-a22b-instruct":{"id":"qwen3-vl-235b-a22b-instruct","name":"Qwen3 VL 235B A22B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.2,"output":0.88,"cache_read":0.11},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"gpt-4-turbo":{"id":"gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":10,"output":30},"canonical_model_id":"openai/gpt-4-turbo"},"gemini-3.1-flash-lite":{"id":"gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.1-flash-lite"},"o3":{"id":"o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.6-terra"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"gpt-5":{"id":"gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"kimi-k2.7-code-highspeed":{"id":"kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code Highspeed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"muse-wonder-1.0":{"id":"muse-wonder-1.0","name":"Muse Wonder","description":"Muse Wonder is a frontier multimodal reasoning model from Meta for personal and professional agents, long-horizon coding, and computer use. It combines Active Memory, which carries relevant context across conversations, with Active Focus, which keeps it working through blockers toward a goal.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":4,"output":20,"cache_read":0.2},"canonical_model_id":"meta/muse-wonder-1.0"},"auto":{"id":"auto","name":"Auto Route","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0,"output":0}},"gpt-5-nano":{"id":"gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"qwen3.5-27b":{"id":"qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.3,"output":2.4},"canonical_model_id":"alibaba/qwen3.5-27b"},"gpt-3.5-turbo":{"id":"gpt-3.5-turbo","name":"GPT-3.5-turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"output":4096},"status":"deprecated","cost":{"input":0.5,"output":1.5,"cache_read":0},"canonical_model_id":"openai/gpt-3.5-turbo"},"deepseek-v4.1-flash-1017":{"id":"deepseek-v4.1-flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":1050000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"codestral-2508":{"id":"codestral-2508","name":"Codestral","description":"Mistral coding model for code completion, generation, and developer workflows","family":"codestral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":16384},"cost":{"input":0.3,"output":0.9},"canonical_model_id":"mistral/codestral-2508"},"o3-mini":{"id":"o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.28,"output":1.1,"cache_read":0.05},"canonical_model_id":"minimax/MiniMax-M3"},"devstral-2512":{"id":"devstral-2512","name":"Devstral 2","description":"Mistral's coding-agent model for repository work, terminal tasks, and software fixes","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.4,"output":2},"canonical_model_id":"mistral/devstral-2512"},"qwen3-vl-235b-a22b-thinking":{"id":"qwen3-vl-235b-a22b-thinking","name":"Qwen3 VL 235B A22B Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.98,"output":3.95},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-thinking"},"mistral-large-latest":{"id":"mistral-large-latest","name":"Mistral Large (latest)","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-11","release_date":"2024-11-01","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":262144},"cost":{"input":4,"output":12},"canonical_model_id":"mistral/mistral-large-latest"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.737,"output":3.08,"cache_read":0.143},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"gpt-5.1-codex-mini":{"id":"gpt-5.1-codex-mini","name":"GPT-5.1 Codex mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5.1-codex-mini"},"claude-haiku-4-5-20251001":{"id":"claude-haiku-4-5-20251001","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"gpt-4o-mini":{"id":"gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"seed-1-6-250615":{"id":"seed-1-6-250615","name":"Seed 1.6 (250615)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-06-25","last_updated":"2025-06-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.25,"output":2,"cache_read":0.05}},"glm-5.2-fast":{"id":"glm-5.2-fast","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":2.156,"output":6.776,"cache_read":0.429},"canonical_model_id":"zhipuai/glm-5.2"},"seed-2-0-lite-260428":{"id":"seed-2-0-lite-260428","name":"Seed 2.0 Lite (260428)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.25,"output":2,"cache_read":0.05}},"glm-4.7-flashx":{"id":"glm-4.7-flashx","name":"GLM-4.7-FlashX","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.07,"output":0.4,"cache_read":0.01,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7-flashx"},"deepseek-v3.2":{"id":"deepseek-v3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":16384},"cost":{"input":0.26,"output":0.38,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-v3.2"},"qwen3-coder-next":{"id":"qwen3-coder-next","name":"Qwen3 Coder Next","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.108,"output":0.675,"cache_read":0.06},"canonical_model_id":"alibaba/qwen3-coder-next"},"o4-mini":{"id":"o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":1.1,"output":4.4,"cache_read":0.275},"canonical_model_id":"openai/o4-mini"},"qwen3.6-35b-a3b":{"id":"qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.248,"output":1.485},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"glm-4.5-x":{"id":"glm-4.5-x","name":"GLM-4.5 X","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"status":"beta","cost":{"input":2.2,"output":8.9,"cache_read":0.45}},"grok-4-20-beta-0309-non-reasoning":{"id":"grok-4-20-beta-0309-non-reasoning","name":"Grok 4.20 (Non-Reasoning)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":2,"output":6,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-non-reasoning"},"llama-3.1-70b-instruct":{"id":"llama-3.1-70b-instruct","name":"Llama 3.1 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":2048},"status":"beta","cost":{"input":0.72,"output":0.72},"canonical_model_id":"meta/llama-3.1-70b-instruct"},"grok-4-20-beta-0309-reasoning":{"id":"grok-4-20-beta-0309-reasoning","name":"Grok 4.20 (Reasoning)","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":2,"output":6,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-reasoning"},"grok-4-5":{"id":"grok-4-5","name":"Grok 4.5","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.3},"canonical_model_id":"xai/grok-4.5"},"gpt-5.2":{"id":"gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":1050000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"openai/gpt-6-astra"},"gemini-3.6-flash":{"id":"gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.6-flash"},"seed-1-6-250915":{"id":"seed-1-6-250915","name":"Seed 1.6 (250915)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.25,"output":2,"cache_read":0.05}},"seed-2-0-mini-260428":{"id":"seed-2-0-mini-260428","name":"Seed 2.0 Mini (260428)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.1,"output":0.4,"cache_read":0.02}},"llama-3.2-11b-instruct":{"id":"llama-3.2-11b-instruct","name":"Llama 3.2 11B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.07,"output":0.33}}}},"aixy":{"id":"aixy","env":["AIXY_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.aixy-gateway.com/v1","name":"Aixy","doc":"https://docs.aixy-gateway.com/integrations/overview","models":{"gemini/gemini-4-argon":{"id":"gemini/gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":32768},"cost":{"input":2,"output":10,"cache_read":0.1,"input_audio":2},"canonical_model_id":"google/gemini-4-argon"},"gemini/gemini-3.8-flash":{"id":"gemini/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"input_audio":0.75},"canonical_model_id":"google/gemini-3.8-flash"},"anthropic/claude-opus-5-5":{"id":"anthropic/claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.aixy-gateway.com/v1"},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-haiku-5-5":{"id":"anthropic/claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.aixy-gateway.com/v1"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-fable-5-1":{"id":"anthropic/claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.aixy-gateway.com/v1"},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-sonnet-5-5":{"id":"anthropic/claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.aixy-gateway.com/v1"},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.aixy-gateway.com/v1","shape":"responses"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.aixy-gateway.com/v1","shape":"responses"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.aixy-gateway.com/v1","shape":"responses"},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.aixy-gateway.com/v1","shape":"responses"},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.aixy-gateway.com/v1","shape":"responses"},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.aixy-gateway.com/v1","shape":"responses"},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.aixy-gateway.com/v1","shape":"responses"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"}}},"tencent-tokenhub":{"id":"tencent-tokenhub","env":["TENCENT_TOKENHUB_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://tokenhub.tencentmaas.com/v1","name":"Tencent TokenHub","doc":"https://cloud.tencent.com/document/product/1823/130050","models":{"hy4-preview":{"id":"hy4-preview","name":"Hy4 preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":64000},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"},"hy3":{"id":"hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":192000,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"tencent/hy3"},"hy3-preview":{"id":"hy3-preview","name":"Hy3 preview","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"tencent/hy3-preview"}}},"thinkingmachines":{"id":"thinkingmachines","env":["TINKER_API_KEY"],"npm":"@ai-sdk/anthropic","api":"https://tinker.thinkingmachines.dev/services/tinker-prod/anthropic/api/v1","name":"Thinking Machines","doc":"https://tinker-docs.thinkingmachines.ai/tinker/compatible-apis/anthropic/","models":{"thinkingmachines/Inkling":{"id":"thinkingmachines/Inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":1.87,"output":4.68,"cache_read":0.374},"canonical_model_id":"thinkingmachines/inkling"},"thinkingmachines/Inkling-Small":{"id":"thinkingmachines/Inkling-Small","name":"Inkling Small","description":"Multimodal MoE reasoning model (276B total, 12B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.58,"output":1.44,"cache_read":0.116},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/Inkling-Small:peft:262144":{"id":"thinkingmachines/Inkling-Small:peft:262144","name":"Inkling Small","description":"Multimodal MoE reasoning model (276B total, 12B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.58,"output":1.44,"cache_read":0.116},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/Inkling:peft:262144":{"id":"thinkingmachines/Inkling:peft:262144","name":"Inkling (256K)","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.87,"output":4.68,"cache_read":0.374},"canonical_model_id":"thinkingmachines/inkling"},"thinkingmachines/Inkling:peft:262144:sampling-nvfp4":{"id":"thinkingmachines/Inkling:peft:262144:sampling-nvfp4","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1,"output":4.05,"cache_read":0.17},"canonical_model_id":"thinkingmachines/inkling"},"thinkingmachines/Inkling-Small:peft:262144:sampling-nvfp4":{"id":"thinkingmachines/Inkling-Small:peft:262144:sampling-nvfp4","name":"Inkling Small","description":"Multimodal MoE reasoning model (276B total, 12B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"thinkingmachines/inkling-small"},"Qwen/Qwen3-8B":{"id":"Qwen/Qwen3-8B","name":"Qwen3 8B","description":"Dense 8B Qwen3 model with switchable thinking for chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-04-29","last_updated":"2025-04-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.195,"output":0.6,"cache_read":0.039},"canonical_model_id":"alibaba/qwen3-8b"},"Qwen/Qwen3.5-397B-A17B":{"id":"Qwen/Qwen3.5-397B-A17B","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":1.65,"output":7.5,"cache_read":0.33},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"Qwen/Qwen3.5-4B":{"id":"Qwen/Qwen3.5-4B","name":"Qwen3.5 4B","description":"Small Qwen3.5 multimodal model for low-cost chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-03-02","last_updated":"2026-03-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.33,"output":1.005,"cache_read":0.066},"canonical_model_id":"alibaba/qwen3.5-4b"},"Qwen/Qwen3.5-397B-A17B:peft:262144":{"id":"Qwen/Qwen3.5-397B-A17B:peft:262144","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.65,"output":7.5,"cache_read":0.33},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"Qwen/Qwen3.8-27B:peft:262144":{"id":"Qwen/Qwen3.8-27B:peft:262144","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6975,"output":5.595,"cache_read":0.1395},"canonical_model_id":"alibaba/qwen3.8-27b"},"Qwen/Qwen3.5-9B":{"id":"Qwen/Qwen3.5-9B","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.3,"output":0.807,"cache_read":0.06},"canonical_model_id":"alibaba/qwen3.5-9b"},"Qwen/Qwen3.8-27B":{"id":"Qwen/Qwen3.8-27B","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.6975,"output":5.595,"cache_read":0.1395},"canonical_model_id":"alibaba/qwen3.8-27b"},"Qwen/Qwen3.6-27B":{"id":"Qwen/Qwen3.6-27B","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":1.86,"output":5.595,"cache_read":0.372},"canonical_model_id":"alibaba/qwen3.6-27b"},"Qwen/Qwen3.5-9B-Base":{"id":"Qwen/Qwen3.5-9B-Base","name":"Qwen3.5 9B Base","description":"Pre-trained Qwen3.5 base checkpoint for fine-tuning and research, without instruction tuning","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-02-26","last_updated":"2026-02-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.3,"output":0.807,"cache_read":0.06},"canonical_model_id":"alibaba/qwen3.5-9b-base"},"Qwen/Qwen3.6-35B-A3B":{"id":"Qwen/Qwen3.6-35B-A3B","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.45,"output":1.335,"cache_read":0.09},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"Qwen/Qwen3.5-4B:peft:262144":{"id":"Qwen/Qwen3.5-4B:peft:262144","name":"Qwen3.5 4B","description":"Small Qwen3.5 multimodal model for low-cost chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-03-02","last_updated":"2026-03-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.33,"output":1.005,"cache_read":0.066},"canonical_model_id":"alibaba/qwen3.5-4b"},"Qwen/Qwen3.5-35B-A3B-Base":{"id":"Qwen/Qwen3.5-35B-A3B-Base","name":"Qwen3.5 35B-A3B Base","description":"Pre-trained Qwen3.5 base checkpoint for fine-tuning and research, without instruction tuning","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-02-24","last_updated":"2026-02-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.54,"output":1.335,"cache_read":0.108},"canonical_model_id":"alibaba/qwen3.5-35b-a3b-base"},"Qwen/Qwen3.6-35B-A3B:peft:262144":{"id":"Qwen/Qwen3.6-35B-A3B:peft:262144","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.45,"output":1.335,"cache_read":0.09},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.33,"output":0.84,"cache_read":0.066},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-oss-120b:peft:131072":{"id":"openai/gpt-oss-120b:peft:131072","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.33,"output":0.84,"cache_read":0.066},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.18,"output":0.45,"cache_read":0.036},"canonical_model_id":"openai/gpt-oss-20b"},"zai-org/GLM-5.3-Flash:peft:262144":{"id":"zai-org/GLM-5.3-Flash:peft:262144","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.84,"output":2.11,"cache_read":0.168},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/GLM-5.3:peft:262144":{"id":"zai-org/GLM-5.3:peft:262144","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":3.78,"output":12.15,"cache_read":0.756},"canonical_model_id":"zhipuai/glm-5.3"},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":2.205,"output":5.49,"cache_read":0.441},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/Kimi-K2.6:peft:131072":{"id":"moonshotai/Kimi-K2.6:peft:131072","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":2.205,"output":5.49,"cache_read":0.441},"canonical_model_id":"moonshotai/kimi-k2.6"},"nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16:peft:262144":{"id":"nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16:peft:262144","name":"Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.57,"output":1.44,"cache_read":0.114},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-BF16":{"id":"nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-BF16","name":"Nemotron 3.5 Super VL 120B A12B","description":"NVIDIA vision-language reasoning model for text, image, and video understanding and agentic tool use","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.57,"output":1.44,"cache_read":0.114},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16":{"id":"nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16","name":"Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.57,"output":1.44,"cache_read":0.114},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16:peft:262144":{"id":"nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16:peft:262144","name":"Nemotron 3.5 Lightning 30B A3B","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.184,"output":0.495,"cache_read":0.0368},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16":{"id":"nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16","name":"Nemotron 3 Nano 30B A3B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-06-25","release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.195,"output":0.495,"cache_read":0.039},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16:peft:262144":{"id":"nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16:peft:262144","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.8,"output":6.225,"cache_read":0.36},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-BF16:peft:262144":{"id":"nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-BF16:peft:262144","name":"Nemotron 3.5 Super VL 120B A12B","description":"NVIDIA vision-language reasoning model for text, image, and video understanding and agentic tool use","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.57,"output":1.44,"cache_read":0.114},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16":{"id":"nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16","name":"Nemotron 3.5 Lightning 30B A3B","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.184,"output":0.495,"cache_read":0.0368},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16":{"id":"nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":1.8,"output":6.225,"cache_read":0.36},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"deepseek-ai/DeepSeek-V4.1-Flash:peft:262144":{"id":"deepseek-ai/DeepSeek-V4.1-Flash:peft:262144","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":3.6,"cache_read":0.12},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek-ai/DeepSeek-V4.1-Flash-1017:peft:262144":{"id":"deepseek-ai/DeepSeek-V4.1-Flash-1017:peft:262144","name":"DeepSeek V4.1 Flash 1017","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":3.6,"cache_read":0.12},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek-ai/DeepSeek-V3.1":{"id":"deepseek-ai/DeepSeek-V3.1","name":"DeepSeek-V3.1","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":1.695,"output":4.215,"cache_read":0.339},"canonical_model_id":"deepseek/deepseek-v3.1"}}},"kosmik":{"id":"kosmik","env":["KOSMIK_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.koscompute.com/v1","name":"Kosmik Compute","doc":"https://api.koscompute.com/docs/","models":{"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.35,"output":2.2,"cache_read":0.09},"canonical_model_id":"alibaba/qwen3.8-27b"}}},"umans-ai":{"id":"umans-ai","env":["UMANS_AI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.code.umans.ai/v1","name":"Umans AI","doc":"https://app.umans.ai/offers/code/docs/orgs","models":{"umans-deepseek-v4.1-flash":{"id":"umans-deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393215},"cost":{"input":0.15,"output":0.6,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"umans-kimi-k3":{"id":"umans-kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"umans-coder":{"id":"umans-coder","name":"Umans Coder","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131071},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"umans-glm-5.3":{"id":"umans-glm-5.3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131071},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"umans-deepseek-v4-flash-0731":{"id":"umans-deepseek-v4-flash-0731","name":"DeepSeek V4 Flash","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393215},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"umans-flash":{"id":"umans-flash","name":"Umans Flash","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.15,"output":1,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"umans-glm-5.3-flash":{"id":"umans-glm-5.3-flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131071},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"umans-deepseek-v4.1-flash-1017":{"id":"umans-deepseek-v4.1-flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393215},"cost":{"input":0.15,"output":0.6,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"}}},"stackit":{"id":"stackit","env":["STACKIT_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.openai-compat.model-serving.eu01.onstackit.cloud/v1","name":"STACKIT","doc":"https://docs.stackit.cloud/products/data-and-ai/ai-model-serving/basics/available-shared-models","models":{"Qwen/Qwen3-VL-235B-A22B-Instruct-FP8":{"id":"Qwen/Qwen3-VL-235B-A22B-Instruct-FP8","name":"Qwen3-VL 235B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":218000,"output":16384},"cost":{"input":1.76,"output":2.05},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"Qwen/Qwen3-VL-Embedding-8B":{"id":"Qwen/Qwen3-VL-Embedding-8B","type":"embedding","name":"Qwen3-VL Embedding 8B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":4096},"cost":{"input":0.09,"output":0}},"Qwen/Qwen3.6-27B":{"id":"Qwen/Qwen3.6-27B","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"status":"deprecated","cost":{"input":0.53,"output":0.76},"canonical_model_id":"alibaba/qwen3.6-27b"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":8192},"cost":{"input":0.53,"output":0.76},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.18,"output":0.29},"canonical_model_id":"openai/gpt-oss-20b"},"cortecs/Llama-3.3-70B-Instruct-FP8-Dynamic":{"id":"cortecs/Llama-3.3-70B-Instruct-FP8-Dynamic","name":"Llama 3.3 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.53,"output":0.76},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"intfloat/e5-mistral-7b-instruct":{"id":"intfloat/e5-mistral-7b-instruct","type":"embedding","name":"E5 Mistral 7B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"mistral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2023-12-11","last_updated":"2023-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":4096},"cost":{"input":0.02243,"output":0}},"google/gemma-3-27b-it":{"id":"google/gemma-3-27b-it","name":"Gemma 3 27B","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":37000,"output":4096},"status":"deprecated","cost":{"input":0.53,"output":0.76},"canonical_model_id":"google/gemma-3-27b-it"}}},"drun":{"id":"drun","env":["DRUN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://chat.d.run/v1","name":"D.Run (China)","doc":"https://www.d.run","models":{"public/deepseek-r1":{"id":"public/deepseek-r1","name":"DeepSeek R1","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32000},"cost":{"input":0.55,"output":2.2},"canonical_model_id":"deepseek/deepseek-r1"},"public/minimax-m25":{"id":"public/minimax-m25","name":"MiniMax M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.29,"output":1.16},"canonical_model_id":"minimax/MiniMax-M2.5"},"public/deepseek-v3":{"id":"public/deepseek-v3","name":"DeepSeek V3","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-12-26","last_updated":"2024-12-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.28,"output":1.1},"canonical_model_id":"deepseek/deepseek-v3"}}},"merge-gateway":{"id":"merge-gateway","env":["MERGE_GATEWAY_API_KEY"],"npm":"merge-gateway-ai-sdk-provider","api":"https://api-gateway.merge.dev/v1/ai-sdk","name":"Merge Gateway","doc":"https://docs.merge.dev/merge-gateway","models":{"thinkingmachines/inkling":{"id":"thinkingmachines/inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048000,"output":32000},"cost":{"input":1,"output":4.05,"cache_read":0.17},"canonical_model_id":"thinkingmachines/inkling"},"xai/grok-build-0.1":{"id":"xai/grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.2},"canonical_model_id":"xai/grok-build-0.1"},"xai/grok-4.3":{"id":"xai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.3"},"xai/grok-4.7":{"id":"xai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":2,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"xai/grok-4.6":{"id":"xai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"xai/grok-4.20-0309-non-reasoning":{"id":"xai/grok-4.20-0309-non-reasoning","name":"Grok 4.20 Non-Reasoning","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2},"canonical_model_id":"xai/grok-4.20-0309-non-reasoning"},"xai/grok-4.5":{"id":"xai/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.5"},"xai/grok-4.20-0309-reasoning":{"id":"xai/grok-4.20-0309-reasoning","name":"Grok 4.20","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-reasoning"},"anthropic/claude-opus-4-1-20250805":{"id":"anthropic/claude-opus-4-1-20250805","name":"Claude Opus 4.1 (20250805)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":31999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1-20250805"},"anthropic/claude-opus-4-7":{"id":"anthropic/claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":30,"output":150,"cache_read":3,"cache_write":37.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic/claude-opus-4-6":{"id":"anthropic/claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024,"max":127999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":30,"output":150,"cache_read":3,"cache_write":37.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-3-7-sonnet-20250219":{"id":"anthropic/claude-3-7-sonnet-20250219","name":"Claude 3.7 Sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-10-31","release_date":"2025-02-19","last_updated":"2025-02-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-3-7-sonnet-20250219"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-opus-5-5":{"id":"anthropic/claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-sonnet-4-20250514":{"id":"anthropic/claude-sonnet-4-20250514","name":"Claude Sonnet 4","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-20250514"},"anthropic/claude-opus-4-20250514":{"id":"anthropic/claude-opus-4-20250514","name":"Claude Opus 4 (20250514)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":31999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-20250514"},"anthropic/claude-haiku-5-5":{"id":"anthropic/claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-fable-5-1":{"id":"anthropic/claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-opus-4-8":{"id":"anthropic/claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":128000}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-opus-4-5-20251101":{"id":"anthropic/claude-opus-4-5-20251101","name":"Claude Opus 4.5 (20251101)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"anthropic/claude-sonnet-4-6":{"id":"anthropic/claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-sonnet-4-5-20250929":{"id":"anthropic/claude-sonnet-4-5-20250929","name":"Claude Sonnet 4.5 (20250929)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"anthropic/claude-sonnet-5-5":{"id":"anthropic/claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-haiku-4-5-20251001":{"id":"anthropic/claude-haiku-4-5-20251001","name":"Claude Haiku 4.5 (20251001)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT-OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"cost":{"input":0.05,"output":0.25},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-4":{"id":"openai/gpt-4","name":"GPT-4","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-11","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8192},"cost":{"input":30,"output":60},"canonical_model_id":"openai/gpt-4"},"openai/gpt-5.3-chat-latest":{"id":"openai/gpt-5.3-chat-latest","name":"GPT-5.3 Chat Latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-chat-latest"},"openai/gpt-5.2-chat-latest":{"id":"openai/gpt-5.2-chat-latest","name":"GPT-5.2 Chat Latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-chat-latest"},"openai/o1":{"id":"openai/o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":15,"output":60,"cache_read":7.5},"canonical_model_id":"openai/o1"},"openai/gpt-4o-2024-05-13":{"id":"openai/gpt-4o-2024-05-13","name":"GPT-4o (2024-05-13)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-05-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":5,"output":15},"canonical_model_id":"openai/gpt-4o-2024-05-13"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":5,"output":30,"cache_read":0.5},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-oss-safeguard-120b":{"id":"openai/gpt-oss-safeguard-120b","name":"GPT OSS Safeguard 120B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":4096},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-safeguard-120b"},"openai/whisper-1":{"id":"openai/whisper-1","type":"transcription","name":"Whisper","description":"General-purpose speech recognition model for transcription and translation","family":"whisper","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2023-03-01","last_updated":"2023-03-01","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":448000,"output":4096},"provider":{"npm":"@ai-sdk/openai","api":"https://api-gateway.merge.dev/v1"},"canonical_model_id":"openai/whisper-1"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 Mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":1.5,"output":9,"cache_read":0.15},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-4o-2024-08-06":{"id":"openai/gpt-4o-2024-08-06","name":"GPT-4o (2024-08-06)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-08-06","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-08-06"},"openai/gpt-oss-safeguard-20b":{"id":"openai/gpt-oss-safeguard-20b","name":"GPT OSS Safeguard 20B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":4096},"cost":{"input":0.07,"output":0.2,"cache_read":0,"cache_write":0},"canonical_model_id":"openai/gpt-oss-safeguard-20b"},"openai/gpt-audio":{"id":"openai/gpt-audio","type":"chat","name":"GPT Audio","description":"Audio model for speech input and output with the Chat Completions API","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-01","release_date":"2025-08-28","last_updated":"2025-08-28","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10},"canonical_model_id":"openai/gpt-audio"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-5-search-api":{"id":"openai/gpt-5-search-api","type":"chat","name":"GPT-5 Search API","description":"GPT-5 model trained for web search in the Chat Completions API","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2025-10-14","last_updated":"2025-10-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":272000,"output":128000},"cost":{"input":1.25,"output":10},"canonical_model_id":"openai/gpt-5-search-api"},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 Mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT-OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"cost":{"input":0.04,"output":0.15,"cache_read":0.02},"canonical_model_id":"openai/gpt-oss-20b"},"openai/gpt-4o-2024-11-20":{"id":"openai/gpt-4o-2024-11-20","name":"GPT-4o (2024-11-20)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-11-20","last_updated":"2024-11-20","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-11-20"},"openai/gpt-5.1-chat-latest":{"id":"openai/gpt-5.1-chat-latest","name":"GPT-5.1 Chat Latest","description":"Chat-tuned GPT-5.1 for polished assistants, writing, and product conversations","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-chat-latest"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1 Nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 Nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-5-chat-latest":{"id":"openai/gpt-5-chat-latest","name":"GPT-5 Chat Latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5-chat-latest"},"openai/gpt-4-turbo":{"id":"openai/gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":10,"output":30},"canonical_model_id":"openai/gpt-4-turbo"},"openai/o3":{"id":"openai/o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":12.5,"output":75,"cache_read":1.25},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"openai/gpt-audio-mini":{"id":"openai/gpt-audio-mini","type":"chat","name":"GPT Audio Mini","description":"Cost-efficient audio model for speech input and output with the Chat Completions API","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-01","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.6,"output":2.4},"canonical_model_id":"openai/gpt-audio-mini"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"openai/gpt-3.5-turbo":{"id":"openai/gpt-3.5-turbo","name":"GPT-3.5 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"output":4096},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"openai/gpt-3.5-turbo"},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3 Mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o Mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"openai/o4-mini":{"id":"openai/o4-mini","name":"o4 Mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.275},"canonical_model_id":"openai/o4-mini"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"bytedance/dola-seed-2.0-code":{"id":"bytedance/dola-seed-2.0-code","name":"Seed 2.0 Code","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","family":"seed","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.4,"output":2.4},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"bytedance/dola-seed-2.0-lite":{"id":"bytedance/dola-seed-2.0-lite","name":"Seed 2.0 Lite","description":"Cost-efficient ByteDance Seed 2.0 model for production chat, analysis, and structured generation","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.25,"output":2},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"bytedance/dola-seed-2.0-code-preview":{"id":"bytedance/dola-seed-2.0-code-preview","name":"Dola Seed 2.0 Code (preview)","description":"Preview coding model for repository understanding, refactors, and engineering tasks","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-03-28","last_updated":"2026-03-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":3}},"bytedance/dola-seed-2.0-pro":{"id":"bytedance/dola-seed-2.0-pro","name":"Seed 2.0 Pro","description":"Flagship ByteDance Seed 2.0 model for complex multimodal reasoning and long-horizon agent workflows","family":"seed","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":3},"canonical_model_id":"bytedance-seed/seed-2.0-pro"},"bytedance/dola-seed-2.0-mini":{"id":"bytedance/dola-seed-2.0-mini","name":"Seed 2.0 Mini","description":"Lightweight ByteDance Seed 2.0 model for low-latency multimodal reasoning and high-volume tasks","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.1,"output":0.4},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"zai/glm-5-turbo":{"id":"zai/glm-5-turbo","name":"GLM-5 Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24,"cache_write":0},"canonical_model_id":"zhipuai/glm-5-turbo"},"zai/glm-4.5v":{"id":"zai/glm-4.5v","name":"Glm 4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"cost":{"input":0.6,"output":1.8,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5v"},"zai/glm-4.7":{"id":"zai/glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7"},"zai/glm-5.2":{"id":"zai/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":50000}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.05,"output":3.3,"cache_read":0.195},"canonical_model_id":"zhipuai/glm-5.2"},"zai/glm-5":{"id":"zai/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2,"cache_write":0},"canonical_model_id":"zhipuai/glm-5"},"zai/glm-5.3":{"id":"zai/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.7,"output":2.2,"cache_read":0.13},"canonical_model_id":"zhipuai/glm-5.3"},"zai/glm-5.3-flash":{"id":"zai/glm-5.3-flash","name":"GLM-5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai/glm-4.7-flash":{"id":"zai/glm-4.7-flash","name":"GLM 4.7 Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.07,"output":0.4},"canonical_model_id":"zhipuai/glm-4.7-flash"},"zai/glm-4.5-air":{"id":"zai/glm-4.5-air","name":"GLM-4.5 Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":98304},"cost":{"input":0.2,"output":1.1,"cache_read":0.03,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5-air"},"zai/glm-5.1":{"id":"zai/glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.1"},"zai/glm-4.6":{"id":"zai/glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.6"},"zai/glm-4.5":{"id":"zai/glm-4.5","name":"GLM-4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":98304},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5"},"zai/glm-4.7-flashx":{"id":"zai/glm-4.7-flashx","name":"GLM-4.7 FlashX","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.07,"output":0.4,"cache_read":0.01,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7-flashx"},"moonshot/kimi-k3":{"id":"moonshot/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":2.9,"output":14,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshot/kimi-k2.5":{"id":"moonshot/kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":3,"cache_read":0.1},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshot/kimi-k2.6":{"id":"moonshot/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshot/kimi-k2.7-code-highspeed":{"id":"moonshot/kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code Highspeed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"moonshot/kimi-k2.7-code":{"id":"moonshot/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"writer/palmyra-x4":{"id":"writer/palmyra-x4","name":"Palmyra X4","description":"Enterprise language model for workflow automation, coding, data analysis, and tool use","family":"palmyra","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2024-10-09","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000},"cost":{"input":2.5,"output":10},"canonical_model_id":"writer/palmyra-x4"},"writer/palmyra-x5":{"id":"writer/palmyra-x5","name":"Palmyra X5","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"palmyra","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":250000},"cost":{"input":0.6,"output":6},"canonical_model_id":"writer/palmyra-x5"},"mistral/mistral-large-2512":{"id":"mistral/mistral-large-2512","name":"Mistral Large 3","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.5,"output":1.5,"cache_read":0.05},"canonical_model_id":"mistral/mistral-large-2512"},"mistral/devstral-medium-latest":{"id":"mistral/devstral-medium-latest","name":"Devstral 2 (latest)","description":"Mistral coding agent model for repository tasks and software engineering workflows","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.4,"output":2},"canonical_model_id":"mistral/devstral-medium-latest"},"mistral/magistral-medium-latest":{"id":"mistral/magistral-medium-latest","name":"Magistral Medium (latest)","description":"Mistral reasoning model for transparent analysis, math, and complex decisions","family":"magistral-medium","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2025-03-17","last_updated":"2025-03-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2,"output":5},"canonical_model_id":"mistral/magistral-medium-latest"},"mistral/codestral-latest":{"id":"mistral/codestral-latest","name":"Codestral (latest)","description":"Mistral code model for completions, refactors, and developer IDE workflows","family":"codestral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-05-29","last_updated":"2025-01-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":4096},"cost":{"input":0.3,"output":0.9},"canonical_model_id":"mistral/codestral-latest"},"mistral/mistral-medium-latest":{"id":"mistral/mistral-medium-latest","name":"Mistral Medium (latest)","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.4,"output":2},"canonical_model_id":"mistral/mistral-medium-latest"},"mistral/mistral-small-latest":{"id":"mistral/mistral-small-latest","name":"Mistral Small (latest)","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"mistral/mistral-small-latest"},"mistral/mistral-medium-2505":{"id":"mistral/mistral-medium-2505","name":"Mistral Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000},"cost":{"input":0.4,"output":2,"cache_read":0.04},"canonical_model_id":"mistral/mistral-medium-2505"},"mistral/devstral-small-2507":{"id":"mistral/devstral-small-2507","name":"Devstral Small","description":"Mistral coding agent model for repository tasks and software engineering workflows","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-07-10","last_updated":"2025-07-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"status":"deprecated","cost":{"input":0.1,"output":0.3},"canonical_model_id":"mistral/devstral-small-2507"},"mistral/mistral-large-2411":{"id":"mistral/mistral-large-2411","name":"Mistral Large 2.1","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2024-11-18","last_updated":"2024-11-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":2,"output":6},"canonical_model_id":"mistral/mistral-large-2411"},"mistral/devstral-medium-2507":{"id":"mistral/devstral-medium-2507","name":"Devstral Medium","description":"Mistral coding agent model for repository tasks and software engineering workflows","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-07-10","last_updated":"2025-07-10","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000},"status":"deprecated","cost":{"input":0.4,"output":2},"canonical_model_id":"mistral/devstral-medium-2507"},"mistral/devstral-2512":{"id":"mistral/devstral-2512","name":"Devstral 2","description":"Mistral's coding-agent model for repository work, terminal tasks, and software fixes","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.4,"output":2,"cache_read":0.04},"canonical_model_id":"mistral/devstral-2512"},"mistral/mistral-large-latest":{"id":"mistral/mistral-large-latest","name":"Mistral Large (latest)","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2024-11-01","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"mistral/mistral-large-latest"},"mistral/pixtral-large-latest":{"id":"mistral/pixtral-large-latest","name":"Pixtral Large (latest)","description":"Mistral's larger vision model for document-heavy image understanding and chat","family":"pixtral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2024-11-01","last_updated":"2024-11-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":2,"output":6},"canonical_model_id":"mistral/pixtral-large-latest"},"qwen/qwen3-max":{"id":"qwen/qwen3-max","name":"Qwen3 Max","description":"Flagship Qwen3 model for coding agents, complex reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.359,"output":1.434,"cache_read":0.0718,"cache_write":0.44875},"canonical_model_id":"alibaba/qwen3-max"},"qwen/qwen3-vl-30b-a3b-instruct":{"id":"qwen/qwen3-vl-30b-a3b-instruct","name":"Qwen3-VL 30B-A3B Instruct","description":"Open vision-language MoE model for image and video understanding, documents, and visual agents","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-04","last_updated":"2025-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6,"cache_read":0.0216},"canonical_model_id":"alibaba/qwen3-vl-30b-a3b-instruct"},"qwen/qwen3-235b-a22b":{"id":"qwen/qwen3-235b-a22b","name":"Qwen3 235B A22B","description":"Large open Qwen MoE for multilingual reasoning, coding, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.287,"output":1.147,"cache_read":0.0574},"canonical_model_id":"alibaba/qwen3-235b-a22b"},"qwen/qwen3.8-flash":{"id":"qwen/qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":977000,"output":128000},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen/qwen3.6-flash":{"id":"qwen/qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":250000},"cost":{"input":0.165,"output":0.99,"cache_read":0.0165,"cache_write":0.20625},"canonical_model_id":"alibaba/qwen3.6-flash"},"qwen/qwen3.5-4b":{"id":"qwen/qwen3.5-4b","name":"Qwen3.5 4B","description":"Small Qwen3.5 multimodal model for low-cost chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-02","last_updated":"2026-03-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.04,"output":0.07},"canonical_model_id":"alibaba/qwen3.5-4b"},"qwen/qwen3.5-35b-a3b":{"id":"qwen/qwen3.5-35b-a3b","name":"Qwen3.5 35B A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.057,"output":0.459,"cache_read":0.020357},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"qwen/qwen3-max-preview":{"id":"qwen/qwen3-max-preview","name":"Qwen3 Max Preview","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-05","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":65536},"cost":{"input":1.08,"output":4.8},"canonical_model_id":"alibaba/qwen3-max-preview"},"qwen/qwen3-coder-plus":{"id":"qwen/qwen3-coder-plus","name":"Qwen3 Coder Plus","description":"Hosted Qwen coder for software agents, repo edits, and long-context code","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":250000},"cost":{"input":0.574,"output":2.294,"cache_read":0.1148,"cache_write":0.7175},"canonical_model_id":"alibaba/qwen3-coder-plus"},"qwen/qwen3.5-9b":{"id":"qwen/qwen3.5-9b","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.09,"output":0.13},"canonical_model_id":"alibaba/qwen3.5-9b"},"qwen/qwen3-235b-a22b-instruct-2507":{"id":"qwen/qwen3-235b-a22b-instruct-2507","name":"Qwen3 235B A22B Instruct 2507","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.1,"output":0.6,"cache_read":0.0574},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"qwen/qwen3.8-2.4t-a95b":{"id":"qwen/qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":1010000},"cost":{"input":2.5,"output":6.25,"cache_read":0.5},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"qwen/qwen3.8-max":{"id":"qwen/qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"qwen/qwen3.6-27b":{"id":"qwen/qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.4126,"output":2.4754},"canonical_model_id":"alibaba/qwen3.6-27b"},"qwen/qwen3-vl-plus":{"id":"qwen/qwen3-vl-plus","name":"Qwen3-VL Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.143,"output":1.434,"cache_read":0.0286,"cache_write":0.17875},"canonical_model_id":"alibaba/qwen3-vl-plus"},"qwen/qwen-flash":{"id":"qwen/qwen-flash","name":"Qwen Flash","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":250000},"cost":{"input":0.022,"output":0.216,"cache_read":0.0044,"cache_write":0.0275},"canonical_model_id":"alibaba/qwen-flash"},"qwen/qwen3-coder-flash":{"id":"qwen/qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":250000},"cost":{"input":0.144,"output":0.574,"cache_read":0.0288,"cache_write":0.18},"canonical_model_id":"alibaba/qwen3-coder-flash"},"qwen/qwen3.7-plus":{"id":"qwen/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.4,"output":1.6},"canonical_model_id":"alibaba/qwen3.7-plus"},"qwen/qwen3-vl-flash":{"id":"qwen/qwen3-vl-flash","name":"Qwen3-VL Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.022,"output":0.215,"cache_read":0.0044,"cache_write":0.0275},"canonical_model_id":"alibaba/qwen3-vl-flash"},"qwen/qwen3-coder-480b-a35b-instruct":{"id":"qwen/qwen3-coder-480b-a35b-instruct","name":"Qwen3 Coder 480B A35B Instruct","description":"Open Qwen coding heavyweight for repository reasoning and agentic engineering","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.22,"output":1.8},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"qwen/qwen3.5-397b-a17b":{"id":"qwen/qwen3.5-397b-a17b","name":"Qwen3.5 397B A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.172,"output":1.032,"cache_read":0.0344},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"qwen/qwen3-next-80b-a3b-instruct":{"id":"qwen/qwen3-next-80b-a3b-instruct","name":"Qwen3-Next 80B-A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.1,"output":1.1,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"qwen/qwen3-30b-a3b":{"id":"qwen/qwen3-30b-a3b","name":"Qwen3 30B A3B","description":"Sparse MoE Qwen model with 3B active parameters for efficient chat and reasoning","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.108,"output":1.076,"cache_read":0.0216},"canonical_model_id":"alibaba/qwen3-30b-a3b"},"qwen/qwen3.5-flash":{"id":"qwen/qwen3.5-flash","name":"Qwen3.5 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":250000},"cost":{"input":0.029,"output":0.287,"cache_read":0.0029,"cache_write":0.03625},"canonical_model_id":"alibaba/qwen3.5-flash"},"qwen/qwen3-32b":{"id":"qwen/qwen3-32b","name":"Qwen3 32B","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"alibaba/qwen3-32b"},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":250000},"cost":{"input":0.825,"output":2.4755,"cache_read":0.165,"cache_write":1.03125},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen-plus":{"id":"qwen/qwen-plus","name":"Qwen Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":250000},"cost":{"input":0.115,"output":0.287,"cache_read":0.023,"cache_write":0.14375},"canonical_model_id":"alibaba/qwen-plus"},"qwen/qwen3.5-122b-a10b":{"id":"qwen/qwen3.5-122b-a10b","name":"Qwen3.5 122B A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.115,"output":0.917,"cache_read":0.023},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"qwen/qwen3.6-plus":{"id":"qwen/qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":250000},"cost":{"input":0.276,"output":1.651,"cache_read":0.0276,"cache_write":0.345},"canonical_model_id":"alibaba/qwen3.6-plus"},"qwen/qwen3-vl-235b-a22b-instruct":{"id":"qwen/qwen3-vl-235b-a22b-instruct","name":"Qwen3-VL 235B A22B Instruct","description":"Qwen vision-language instruct model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.21,"output":1.9,"cache_read":0.105},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"qwen/qwen3.5-27b":{"id":"qwen/qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.086,"output":0.688,"cache_read":0.0172},"canonical_model_id":"alibaba/qwen3.5-27b"},"qwen/qwen3.6-max-preview":{"id":"qwen/qwen3.6-max-preview","name":"Qwen3.6 Max Preview","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":65536},"cost":{"input":1.31,"output":7.88},"canonical_model_id":"alibaba/qwen3.6-max-preview"},"qwen/qwen3-vl-235b-a22b-thinking":{"id":"qwen/qwen3-vl-235b-a22b-thinking","name":"Qwen3-VL 235B A22B Thinking","description":"Qwen vision-language thinking model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.287,"output":2.867,"cache_read":0.0574},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-thinking"},"qwen/qwen3-coder-next":{"id":"qwen/qwen3-coder-next","name":"Qwen3 Coder Next","description":"Open-weight Qwen coding model for agents, repository edits, and multi-turn tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.15,"output":0.8,"cache_read":0.075},"canonical_model_id":"alibaba/qwen3-coder-next"},"qwen/qwen3.6-35b-a3b":{"id":"qwen/qwen3.6-35b-a3b","name":"Qwen3.6 35B A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.248,"output":1.485,"cache_read":0.0496},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"qwen/qwen3.5-plus":{"id":"qwen/qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":250000},"cost":{"input":0.115,"output":0.688,"cache_read":0.0115,"cache_write":0.14375},"canonical_model_id":"alibaba/qwen3.5-plus"},"qwen/qwen3-next-80b-a3b-thinking":{"id":"qwen/qwen3-next-80b-a3b-thinking","name":"Qwen3-Next 80B-A3B (Thinking)","description":"Efficient Qwen thinking model for local reasoning, math, and coding agents","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":1.2},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-thinking"},"sakana/fugu-max":{"id":"sakana/fugu-max","name":"Fugu Max","description":"Multi-agent model for routing expert agents across complex analytical tasks","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"sakana/fugu-max"},"sakana/fugu-ultra":{"id":"sakana/fugu-ultra","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"sakana/fugu-ultra"},"sakana/sakana-namazu":{"id":"sakana/sakana-namazu","name":"Sakana Namazu","description":"Japanese-specialized reasoning model based on Kimi K2.6 and tuned for Japanese language, culture, and business workflows","family":"sakana-namazu","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.95,"output":4,"cache_read":0.15},"canonical_model_id":"sakana/sakana-namazu"},"minimax/minimax-m2.1":{"id":"minimax/minimax-m2.1","name":"MiniMax M2.1","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":8192},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.1"},"minimax/minimax-m3.1-flash":{"id":"minimax/minimax-m3.1-flash","name":"MiniMax M3.1 Flash","description":"Frontier multimodal coding model with 1M context window and tunable thinking depth","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-19","last_updated":"2026-10-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"minimax/MiniMax-M3.1-Flash"},"minimax/minimax-m2.7-highspeed":{"id":"minimax/minimax-m2.7-highspeed","name":"MiniMax M2.7 Highspeed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":8192},"cost":{"input":0.6,"output":2.4,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":8192},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5"},"minimax/minimax-m2.5-highspeed":{"id":"minimax/minimax-m2.5-highspeed","name":"MiniMax M2.5 Highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-13","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":8192},"cost":{"input":0.6,"output":2.4,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5-highspeed"},"minimax/minimax-m2":{"id":"minimax/minimax-m2","name":"MiniMax M2","description":"Efficient open MiniMax model built for coding agents and tool-heavy workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":8192},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2"},"minimax/minimax-m2.7":{"id":"minimax/minimax-m2.7","name":"MiniMax M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":8192},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":128000}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"moonshotai/kimi-k2-thinking":{"id":"moonshotai/kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Thinking Kimi model for slower research passes, planning, and hard technical questions","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.6,"output":2.5},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"deepseek/deepseek-v4-flash-0423":{"id":"deepseek/deepseek-v4-flash-0423","name":"DeepSeek V4 Flash 0423","description":"Initial DeepSeek V4 Flash snapshot for economical reasoning, coding, and million-token agent workloads","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.139,"output":0.278},"canonical_model_id":"deepseek/deepseek-v4-flash-0423"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.3,"output":1.2,"cache_read":0.006,"cache_write":0.1125},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v3.1":{"id":"deepseek/deepseek-v3.1","name":"DeepSeek V3.1","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.56,"output":1.68,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-v3.1"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-flash-0731-fast":{"id":"deepseek/deepseek-v4-flash-0731-fast","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.28,"output":0.56,"cache_read":0.07},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-r1":{"id":"deepseek/deepseek-r1","name":"DeepSeek R1","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":40960},"cost":{"input":1.35,"output":5.4},"canonical_model_id":"deepseek/deepseek-r1"},"deepseek/deepseek-v4-pro-0423":{"id":"deepseek/deepseek-v4-pro-0423","name":"DeepSeek V4 Pro 0423","description":"DeepSeek V4 Pro initial snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":1.65,"output":3.3},"canonical_model_id":"deepseek/deepseek-v4-pro-0423"},"deepseek/deepseek-v3":{"id":"deepseek/deepseek-v3","name":"DeepSeek V3","description":"Open DeepSeek MoE chat model for coding, math, and general reasoning","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2024-12-26","last_updated":"2024-12-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":81920},"cost":{"input":0.27,"output":1.1},"canonical_model_id":"deepseek/deepseek-v3"},"deepseek/deepseek-r1-0528":{"id":"deepseek/deepseek-r1-0528","name":"DeepSeek R1 (0528)","description":"May 2025 DeepSeek R1 update with improved mathematics, coding, and reasoning","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":32768},"cost":{"input":1.35,"output":5.4,"cache_read":0.945},"canonical_model_id":"deepseek/deepseek-r1-0528"},"deepseek/deepseek-v4.1-flash-1017":{"id":"deepseek/deepseek-v4.1-flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.035,"output":0.07,"cache_read":0.007},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v3.2":{"id":"deepseek/deepseek-v3.2","name":"DeepSeek V3.2","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.28,"output":0.4,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.74,"output":3.48,"cache_read":0.003625},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"nvidia/nemotron-nano-9b-v2":{"id":"nvidia/nemotron-nano-9b-v2","name":"Nemotron Nano 9B","description":"Compact Nemotron model for efficient reasoning and deployable AI agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-09","release_date":"2025-08-18","last_updated":"2025-08-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.06,"output":0.23},"canonical_model_id":"nvidia/nemotron-nano-9b-v2"},"nvidia/nemotron-3.5-lightning-30b-a3b":{"id":"nvidia/nemotron-3.5-lightning-30b-a3b","name":"Nemotron 3.5 Lightning 30B A3B","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/nemotron-3-nano-30b-a3b":{"id":"nvidia/nemotron-3-nano-30b-a3b","name":"Nemotron 3 Nano 30B A3B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-06-25","release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32000},"cost":{"input":0.05,"output":0.2},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"cohere/command-r7b-12-2024":{"id":"cohere/command-r7b-12-2024","name":"Command R7B 12-2024","description":"Cohere retrieval model for long-context chat and enterprise RAG workflows","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-12-13","last_updated":"2024-12-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.0375,"output":0.15},"canonical_model_id":"cohere/command-r7b-12-2024"},"cohere/command-r-08-2024":{"id":"cohere/command-r-08-2024","name":"Command R 08-2024","description":"Cohere retrieval model for long-context chat and enterprise RAG workflows","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"cohere/command-r-08-2024"},"cohere/command-a-03-2025":{"id":"cohere/command-a-03-2025","name":"Command A 03-2025","description":"Cohere command model for multilingual enterprise agents, tools, and chat","family":"command-a","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2025-03-13","last_updated":"2025-03-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8000},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-a-03-2025"},"cohere/command-r-plus-08-2024":{"id":"cohere/command-r-plus-08-2024","name":"Command R+ 08-2024","description":"Cohere's RAG workhorse for long-context enterprise search and tool use","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-r-plus-08-2024"},"meta/muse-spark-open":{"id":"meta/muse-spark-open","name":"Muse Spark Open","description":"Muse Spark Open is an 816B total / 42B active open-weight multimodal reasoning model from Meta for coding and long-horizon agentic work, with 1M-token context.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-open"},"meta/muse-spark-1.2":{"id":"meta/muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":262144},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"meta/llama-3.3-70b-instruct":{"id":"meta/llama-3.3-70b-instruct","name":"Llama 3.3 70B Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.22,"output":0.5,"cache_read":0.11},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"meta/muse-spark-1.1":{"id":"meta/muse-spark-1.1","name":"Muse Spark 1.1","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":262144},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.1"},"meta/llama-3.1-8b-instruct":{"id":"meta/llama-3.1-8b-instruct","name":"Llama 3.1 8B","description":"Compact open Llama model for lightweight chat, drafting, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":2048},"cost":{"input":0.22,"output":0.22},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"meta/llama-3.1-70b-instruct":{"id":"meta/llama-3.1-70b-instruct","name":"Llama 3.1 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":2048},"cost":{"input":0.99,"output":0.99},"canonical_model_id":"meta/llama-3.1-70b-instruct"},"google/gemini-embedding-2":{"id":"google/gemini-embedding-2","type":"embedding","name":"Gemini Embedding 2","description":"Multimodal embedding model mapping text, images, video, audio, and PDFs into a unified embedding space","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2025-11","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8192},"cost":{"input":0.2,"output":0},"canonical_model_id":"google/gemini-embedding-2"},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":512,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"input_audio":0.3},"canonical_model_id":"google/gemini-2.5-flash-lite"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.7-flash"},"google/gemini-3-pro-image":{"id":"google/gemini-3-pro-image","type":"image","name":"Gemini 3 Pro Image","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":65536},"cost":{"input":2,"output":12},"canonical_model_id":"google/gemini-3-pro-image"},"google/gemini-2.5-computer-use-preview-10-2025":{"id":"google/gemini-2.5-computer-use-preview-10-2025","name":"Gemini 2.5 Computer Use Preview (10-2025)","description":"Specialized Gemini 2.5 model for browser-control agents that automate UI tasks","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-10-07","last_updated":"2025-10-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"cost":{"input":1.25,"output":10},"canonical_model_id":"google/gemini-2.5-computer-use-preview-10-2025"},"google/gemini-3.1-flash-lite-preview":{"id":"google/gemini-3.1-flash-lite-preview","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite-preview"},"google/gemini-3.1-flash-image":{"id":"google/gemini-3.1-flash-image","type":"image","name":"Gemini 3.1 Flash Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3.1-flash-image"},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"input_audio":1},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"input_audio":1},"canonical_model_id":"google/gemini-2.5-flash"},"google/gemini-flash-lite-latest":{"id":"google/gemini-flash-lite-latest","name":"Gemini Flash-Lite Latest","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-flash-lite-latest"},"google/gemini-3-pro-preview":{"id":"google/gemini-3-pro-preview","name":"Gemini 3 Pro Preview","description":"Preview Gemini flagship for complex reasoning, coding, and rich multimodal prompts","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3-pro-preview"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro"},"google/gemini-2.5-flash-image":{"id":"google/gemini-2.5-flash-image","type":"image","name":"Gemini 2.5 Flash Image","description":"Nano Banana image model for fast generation, edits, and character-consistent assets","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.3,"output":2.5},"canonical_model_id":"google/gemini-2.5-flash-image"},"google/gemma-3-4b-it":{"id":"google/gemma-3-4b-it","name":"Gemma 3 4B","description":"Open multimodal Gemma instruction model for efficient text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.04,"output":0.08},"canonical_model_id":"google/gemma-3-4b-it"},"google/gemini-4-argon":{"id":"google/gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":10,"cache_read":0.1},"canonical_model_id":"google/gemini-4-argon"},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B It","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.14,"output":0.4},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash-Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemma-4-26b-a4b-it":{"id":"google/gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.13,"output":0.4},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-embedding-001":{"id":"google/gemini-embedding-001","type":"embedding","name":"Gemini Embedding 001","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2025-05","release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":2048,"output":4096},"cost":{"input":0.15,"output":0},"canonical_model_id":"google/gemini-embedding-001"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash-Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite"},"google/gemma-3-27b-it":{"id":"google/gemma-3-27b-it","name":"Gemma 3 27B IT","description":"Largest open Gemma 3 instruction model for multilingual text generation and visual understanding","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.08,"output":0.45,"cache_read":0.04},"canonical_model_id":"google/gemma-3-27b-it"},"google/gemma-3-12b-it":{"id":"google/gemma-3-12b-it","name":"Gemma 3 12B","description":"Open multimodal Gemma instruction model for multilingual text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.09,"output":0.29},"canonical_model_id":"google/gemma-3-12b-it"},"google/gemini-3.1-pro-preview-customtools":{"id":"google/gemini-3.1-pro-preview-customtools","name":"Gemini 3.1 Pro Preview Custom Tools","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview-customtools"},"google/gemini-flash-latest":{"id":"google/gemini-flash-latest","name":"Gemini Flash Latest","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-flash-latest"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"google/gemini-3.6-flash"}}},"ovhcloud":{"id":"ovhcloud","env":["OVHCLOUD_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://oai.endpoints.kepler.ai.cloud.ovh.net/v1","name":"OVHcloud AI Endpoints","doc":"https://www.ovhcloud.com/en/public-cloud/ai-endpoints/catalog//","models":{"gpt-oss-120b":{"id":"gpt-oss-120b","name":"gpt-oss-120b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.09,"output":0.47},"canonical_model_id":"openai/gpt-oss-120b"},"mistral-nemo-instruct-2407":{"id":"mistral-nemo-instruct-2407","name":"Mistral-Nemo-Instruct-2407","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.14,"output":0.14},"canonical_model_id":"mistral/mistral-nemo"},"qwen3.5-9b":{"id":"qwen3.5-9b","name":"Qwen3.5-9B","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.12,"output":0.18},"canonical_model_id":"alibaba/qwen3.5-9b"},"qwen2.5-vl-72b-instruct":{"id":"qwen2.5-vl-72b-instruct","name":"Qwen2.5-VL-72B-Instruct","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-01-26","last_updated":"2025-01-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":1.01,"output":1.01},"canonical_model_id":"alibaba/qwen2-5-vl-72b-instruct"},"qwen3.6-27b":{"id":"qwen3.6-27b","name":"Qwen3.6-27B","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.47,"output":3.19},"canonical_model_id":"alibaba/qwen3.6-27b"},"qwen3.5-397b-a17b":{"id":"qwen3.5-397b-a17b","name":"Qwen3.5-397B-A17B","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.71,"output":4.25},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"mistral-small-3.2-24b-instruct-2506":{"id":"mistral-small-3.2-24b-instruct-2506","name":"Mistral-Small-3.2-24B-Instruct-2506","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["image","text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.1,"output":0.31},"canonical_model_id":"mistral/mistral-small-3.2-24b-instruct"},"gpt-oss-20b":{"id":"gpt-oss-20b","name":"gpt-oss-20b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.05,"output":0.18},"canonical_model_id":"openai/gpt-oss-20b"},"qwen3guard-gen-8b":{"id":"qwen3guard-gen-8b","name":"Qwen3Guard-Gen-8B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-01-22","last_updated":"2026-01-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"cost":{"input":0,"output":0}},"qwen3.8-27b":{"id":"qwen3.8-27b","name":"Qwen3.8-27B","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.47,"output":3.19},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen3guard-gen-0.6b":{"id":"qwen3guard-gen-0.6b","name":"Qwen3Guard-Gen-0.6B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-01-22","last_updated":"2026-01-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"cost":{"input":0,"output":0}},"meta-llama-3_3-70b-instruct":{"id":"meta-llama-3_3-70b-instruct","name":"Meta-Llama-3_3-70B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.74,"output":0.74},"canonical_model_id":"meta/llama-3.3-70b-instruct"}}},"iteracompute":{"id":"iteracompute","env":["ITERACOMPUTE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.iteracompute.com/v1","name":"IteraCompute","doc":"https://iteracompute.com/docs.html","models":{"qwen/qwen3.8-2.4t-a95b":{"id":"qwen/qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.95,"output":5.7,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"alibaba/qwen3.8-27b"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":524288},"cost":{"input":0.3,"output":1.19,"cache_read":0.05},"canonical_model_id":"minimax/MiniMax-M3"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":999999},"cost":{"input":2.35,"output":11.76,"cache_read":0.23},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.69,"output":3.29,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.17,"output":0.7,"cache_read":0.005},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731 (legacy alias)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.17,"output":0.7,"cache_read":0.005},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.79,"output":2.38,"cache_read":0.026},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.82,"output":2.88,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5.3"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.08,"output":0.28,"cache_read":0.023},"canonical_model_id":"zhipuai/glm-5.3-flash"}}},"azure":{"id":"azure","env":["AZURE_RESOURCE_NAME","AZURE_API_KEY"],"npm":"@ai-sdk/azure","name":"Azure","doc":"https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models","models":{"claude-sonnet-4-5":{"id":"claude-sonnet-4-5","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75}},"gpt-image-2":{"id":"gpt-image-2","type":"image","name":"GPT-Image-2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":30,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-2"},"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"phi-4-mini":{"id":"phi-4-mini","name":"Phi-4-mini","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"phi","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-10","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.075,"output":0.3}},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"gpt-image-2.5-flare":{"id":"gpt-image-2.5-flare","type":"image","name":"GPT Image 2.5 Flare","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":30,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-2.5-flare"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-24","last_updated":"2026-02-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-07-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5}}},"gpt-5-codex":{"id":"gpt-5-codex","name":"GPT-5-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125}},"grok-4-20-reasoning":{"id":"grok-4-20-reasoning","name":"Grok 4.20 (Reasoning)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-04-08","last_updated":"2026-04-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":8192},"status":"beta","cost":{"input":2,"output":6}},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek-V4-Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/models"},"cost":{"input":0.19,"output":0.51},"canonical_model_id":"deepseek/deepseek-v4-flash"},"gpt-5-pro":{"id":"gpt-5-pro","name":"GPT-5 Pro","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":15,"output":120},"canonical_model_id":"openai/gpt-5-pro"},"gpt-image-1.5":{"id":"gpt-image-1.5","type":"image","name":"GPT-Image-1.5","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-11-25","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":32,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-1.5"},"gpt-image-1":{"id":"gpt-image-1","type":"image","name":"GPT-Image-1","description":"OpenAI image model for production generation, edits, and brand-safe visual workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-04-24","last_updated":"2025-04-24","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":40,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-1"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"status":"beta","provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"mistral-small-2503":{"id":"mistral-small-2503","name":"Mistral Small 3.1","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2025-03-01","last_updated":"2025-03-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32768},"cost":{"input":0.1,"output":0.3}},"gpt-5.4-pro":{"id":"gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.4-pro"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"gpt-3.5-turbo-0125":{"id":"gpt-3.5-turbo-0125","name":"GPT-3.5 Turbo 0125","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2021-08","release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":4096},"status":"deprecated","cost":{"input":0.5,"output":1.5}},"o1":{"id":"o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":15,"output":60,"cache_read":7.5}},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek-V4.1-Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"status":"beta","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/models"},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"gpt-4.1":{"id":"gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"status":"deprecated","cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"phi-4-reasoning-plus":{"id":"phi-4-reasoning-plus","name":"Phi-4-reasoning-plus","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"phi","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2023-10","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":4096},"cost":{"input":0.125,"output":0.5}},"gpt-4o":{"id":"gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"status":"deprecated","cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"phi-4-mini-reasoning":{"id":"phi-4-mini-reasoning","name":"Phi-4-mini-reasoning","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"phi","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2023-10","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.075,"output":0.3}},"llama-4-maverick-17b-128e-instruct-fp8":{"id":"llama-4-maverick-17b-128e-instruct-fp8","name":"Llama 4 Maverick 17B 128E Instruct FP8","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":16384},"cost":{"input":0.25,"output":1}},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek-V4-Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/models"},"cost":{"input":1.74,"output":3.48},"canonical_model_id":"deepseek/deepseek-v4-pro"},"text-embedding-3-small":{"id":"text-embedding-3-small","name":"text-embedding-3-small","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536},"cost":{"input":0.02,"output":0}},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"phi-4":{"id":"phi-4","name":"Phi-4","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","family":"phi","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2023-10","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.125,"output":0.5}},"gpt-5.1":{"id":"gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-14","last_updated":"2025-11-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":2.5,"output":20,"cache_read":0.25},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":1.25,"output":10,"cache_read":0.125}},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25}},"grok-4-1-fast-non-reasoning":{"id":"grok-4-1-fast-non-reasoning","name":"Grok 4.1 Fast (Non-Reasoning)","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-06-27","last_updated":"2025-06-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.2,"output":0.5,"cache_read":0.05}},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"ministral-3b":{"id":"ministral-3b","name":"Ministral 3B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-03","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.04,"output":0.04}},"deepseek-r1":{"id":"deepseek-r1","name":"DeepSeek-R1","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-01-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":163840},"status":"deprecated","cost":{"input":1.35,"output":5.4}},"cohere-embed-v3-multilingual":{"id":"cohere-embed-v3-multilingual","name":"Embed v3 Multilingual","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"cohere-embed","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2023-11-07","last_updated":"2023-11-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512,"output":1024},"cost":{"input":0.1,"output":0}},"gpt-chat-latest":{"id":"gpt-chat-latest","name":"GPT Chat Latest","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-05-05","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"beta","cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5-instant"},"cohere-embed-v-4-0":{"id":"cohere-embed-v-4-0","name":"Embed v4","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"cohere-embed","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-04-15","last_updated":"2025-04-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":1536},"cost":{"input":0.12,"output":0}},"grok-4-20-non-reasoning":{"id":"grok-4-20-non-reasoning","name":"Grok 4.20 (Non-Reasoning)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-04-08","last_updated":"2026-04-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262000,"output":8192},"status":"beta","cost":{"input":2,"output":6}},"grok-4.7":{"id":"grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"status":"beta","canonical_model_id":"xai/grok-4.7"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"cohere-command-a":{"id":"cohere-command-a","name":"Command A","description":"Cohere command model for multilingual enterprise agents, tools, and chat","family":"command-a","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2025-03-13","last_updated":"2025-03-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":2.5,"output":10}},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/models"},"cost":{"input":0.6,"output":3},"canonical_model_id":"moonshotai/kimi-k2.5"},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"llama-3.3-70b-instruct":{"id":"llama-3.3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.71,"output":0.71}},"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":5,"output":30,"cache_read":0.5},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 Mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":1.5,"output":9,"cache_read":0.15},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"text-embedding-ada-002":{"id":"text-embedding-ada-002","name":"text-embedding-ada-002","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2022-12-15","last_updated":"2022-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536},"cost":{"input":0.1,"output":0}},"gpt-image-2.5-sunburst":{"id":"gpt-image-2.5-sunburst","type":"image","name":"GPT Image 2.5 Sunburst","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":30,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-2.5-sunburst"},"claude-fable-5-1":{"id":"claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"gpt-5.1-codex-max":{"id":"gpt-5.1-codex-max","name":"GPT-5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex-max"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/models"},"cost":{"input":0.95,"output":4},"canonical_model_id":"moonshotai/kimi-k2.6"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-31","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5}},"canonical_model_id":"anthropic/claude-opus-4-8"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":8,"output":40,"cache_read":0.8,"cache_write":10},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"gpt-3.5-turbo-instruct":{"id":"gpt-3.5-turbo-instruct","name":"GPT-3.5 Turbo Instruct","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2021-08","release_date":"2023-09-21","last_updated":"2023-09-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":4096,"output":4096},"status":"deprecated","cost":{"input":1.5,"output":2}},"text-embedding-3-large":{"id":"text-embedding-3-large","name":"text-embedding-3-large","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":3072},"cost":{"input":0.13,"output":0}},"codex-mini":{"id":"codex-mini","name":"Codex Mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-04","release_date":"2025-05-16","last_updated":"2025-05-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":1.5,"output":6,"cache_read":0.375}},"cohere-embed-v3-english":{"id":"cohere-embed-v3-english","name":"Embed v3 English","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"cohere-embed","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2023-11-07","last_updated":"2023-11-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512,"output":1024},"cost":{"input":0.1,"output":0}},"gpt-4.1-mini":{"id":"gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"status":"deprecated","cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"gpt-5.2-codex":{"id":"gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-01-14","last_updated":"2026-01-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"codestral-2501":{"id":"codestral-2501","name":"Codestral 25.01","description":"Mistral coding model for code completion, generation, and developer workflows","family":"codestral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-03","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.3,"output":0.9}},"grok-4.6":{"id":"grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"status":"beta","cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"mistral-medium-2505":{"id":"mistral-medium-2505","name":"Mistral Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000},"cost":{"input":0.4,"output":2}},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"llama-4-scout-17b-16e-instruct":{"id":"llama-4-scout-17b-16e-instruct","name":"Llama 4 Scout 17B 16E Instruct","description":"Open multimodal Llama model for long-context analysis and efficient agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.2,"output":0.78}},"claude-mythos-5":{"id":"claude-mythos-5","name":"Claude Mythos 5","description":"Restricted Claude model for advanced cybersecurity and biology research workflows","family":"claude-mythos","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"status":"beta","provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-mythos-5"},"grok-4-1-fast-reasoning":{"id":"grok-4-1-fast-reasoning","name":"Grok 4.1 Fast (Reasoning)","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-06-27","last_updated":"2025-06-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.2,"output":0.5,"cache_read":0.05}},"gpt-5-mini":{"id":"gpt-5-mini","name":"GPT-5 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025}},"gpt-4.1-nano":{"id":"gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"status":"deprecated","cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"deepseek-v3.2-speciale":{"id":"deepseek-v3.2-speciale","name":"DeepSeek-V3.2-Speciale","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0.58,"output":1.68}},"gpt-4-turbo-vision":{"id":"gpt-4-turbo-vision","name":"GPT-4 Turbo Vision","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-11","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":10,"output":30}},"phi-4-reasoning":{"id":"phi-4-reasoning","name":"Phi-4-reasoning","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"phi","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2023-10","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":4096},"cost":{"input":0.125,"output":0.5}},"gpt-5.1-codex":{"id":"gpt-5.1-codex","name":"GPT-5.1 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-14","last_updated":"2025-11-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125}},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 Nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"gpt-4-turbo":{"id":"gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":10,"output":30},"canonical_model_id":"openai/gpt-4-turbo"},"o3":{"id":"o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":4,"output":24,"cache_read":0.4,"cache_write":5},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":12.5,"output":75,"cache_read":1.25},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"gpt-5":{"id":"gpt-5","name":"GPT-5","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125}},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"gpt-5-nano":{"id":"gpt-5-nano","name":"GPT-5 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005}},"phi-4-multimodal":{"id":"phi-4-multimodal","name":"Phi-4-multimodal","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"phi","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2023-10","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.08,"output":0.32,"input_audio":4}},"o3-mini":{"id":"o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"model-router":{"id":"model-router","name":"Model Router","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"model-router","attachment":true,"reasoning":false,"tool_call":true,"release_date":"2025-05-19","last_updated":"2025-11-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":16384},"provider":{"npm":"@ai-sdk/azure","shape":"completions"},"cost":{"input":0.14,"output":0}},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/models"},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"gpt-5.1-codex-mini":{"id":"gpt-5.1-codex-mini","name":"GPT-5.1 Codex Mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-14","last_updated":"2025-11-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025}},"gpt-4o-mini":{"id":"gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"status":"deprecated","cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"claude-opus-4-1":{"id":"claude-opus-4-1","name":"Claude Opus 4.1","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75}},"claude-opus-4-5":{"id":"claude-opus-4-5","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-11-24","last_updated":"2025-08-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://${AZURE_RESOURCE_NAME}.services.ai.azure.com/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"deepseek-v3.2":{"id":"deepseek-v3.2","name":"DeepSeek-V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0.58,"output":1.68}},"o4-mini":{"id":"o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":1.1,"output":4.4,"cache_read":0.275},"canonical_model_id":"openai/o4-mini"},"gpt-5.2":{"id":"gpt-5.2","name":"GPT-5.2","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":3.5,"output":28,"cache_read":0.35},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"gpt-3.5-turbo-1106":{"id":"gpt-3.5-turbo-1106","name":"GPT-3.5 Turbo 1106","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2021-08","release_date":"2023-11-06","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":4096},"status":"deprecated","cost":{"input":1,"output":2}}}},"alibaba-coding-plan-cn":{"id":"alibaba-coding-plan-cn","env":["ALIBABA_CODING_PLAN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://coding.dashscope.aliyuncs.com/v1","name":"Alibaba Coding Plan (China)","doc":"https://help.aliyun.com/zh/model-studio/coding-plan","models":{"glm-4.7":{"id":"glm-4.7","name":"GLM-4.7","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":16384},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3-coder-plus":{"id":"qwen3-coder-plus","name":"Qwen3 Coder Plus","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"glm-5":{"id":"glm-5","name":"GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-11","last_updated":"2026-02-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":16384},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.7-plus"},"MiniMax-M2.5":{"id":"MiniMax-M2.5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":24576},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3-max-2026-01-23":{"id":"qwen3-max-2026-01-23","name":"Qwen3 Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-23","last_updated":"2026-01-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3.6-plus":{"id":"qwen3.6-plus","name":"Qwen3.6 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3-coder-next":{"id":"qwen3-coder-next","name":"Qwen3 Coder Next","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3.5-plus":{"id":"qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}}}},"tencent-coding-plan":{"id":"tencent-coding-plan","env":["TENCENT_CODING_PLAN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.lkeap.cloud.tencent.com/coding/v3","name":"Tencent Coding Plan (China)","doc":"https://cloud.tencent.com/document/product/1772/128947","models":{"hunyuan-2.0-thinking":{"id":"hunyuan-2.0-thinking","name":"Tencent HY 2.0 Think","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"hunyuan","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-03-08","last_updated":"2026-03-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"glm-5":{"id":"glm-5","name":"GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":16384},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5"},"hunyuan-t1":{"id":"hunyuan-t1","name":"Hunyuan-T1","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"hunyuan","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-03-08","last_updated":"2026-03-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi-K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.5"},"minimax-m2.5":{"id":"minimax-m2.5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":32768},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"minimax/MiniMax-M2.5"},"hunyuan-turbos":{"id":"hunyuan-turbos","name":"Hunyuan-TurboS","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"hunyuan","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-03-08","last_updated":"2026-03-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"tc-code-latest":{"id":"tc-code-latest","name":"Auto","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-03-08","last_updated":"2026-03-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"hunyuan-2.0-instruct":{"id":"hunyuan-2.0-instruct","name":"Tencent HY 2.0 Instruct","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"hunyuan","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-03-08","last_updated":"2026-03-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}}}},"agnes":{"id":"agnes","env":["AGNES_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://apihub.agnes-ai.com/v1","name":"Agnes AI","doc":"https://agnes-ai.com/doc","models":{"agnes-2.5-pro-alpha":{"id":"agnes-2.5-pro-alpha","name":"Agnes 2.5 Pro Alpha","description":"Paid reasoning model for advanced coding, scientific reasoning, long-context analysis, agentic workflows, and multimodal understanding.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":0.45,"output":0.9,"cache_read":0.0038}},"agnes-3.0-flash":{"id":"agnes-3.0-flash","name":"Agnes 3.0 Flash","description":"A new-generation Agnes AI text model with stronger Agnes Code task execution, tool orchestration, and trustworthy delivery.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09","last_updated":"2026-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":512000,"output":65536},"cost":{"input":0,"output":0}},"agnes-2.5-flash":{"id":"agnes-2.5-flash","name":"Agnes 2.5 Flash","description":"Upgraded model with improved coding, agent workflows, tool calling, and multimodal understanding.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07","last_updated":"2026-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":512000,"output":65536},"cost":{"input":0,"output":0}},"agnes-2.0-flash":{"id":"agnes-2.0-flash","name":"Agnes 2.0 Flash","description":"Fast and efficient model for agent workflows, tool calling, coding, and image understanding.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-05-25","last_updated":"2026-05-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":512000,"output":65536},"status":"deprecated","cost":{"input":0,"output":0}}}},"jalapeno":{"id":"jalapeno","env":["JALAPENO_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.jalapeno-cloud.ai/v1","name":"Jalapeno Cloud","doc":"https://www.jalapeno-cloud.ai/docs/","models":{"Qwen3-Next-80B-A3B-Thinking":{"id":"Qwen3-Next-80B-A3B-Thinking","name":"Qwen3-Next 80B-A3B (Thinking)","description":"Efficient Qwen thinking model for local reasoning, math, and coding agents","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"status":"deprecated","cost":{"input":0.15,"output":1.5},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-thinking"},"Qwen3.5-122B-A10B":{"id":"Qwen3.5-122B-A10B","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.4,"output":3.2},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"Kimi-K2.5":{"id":"Kimi-K2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":180224},"cost":{"input":0.6,"output":3,"cache_read":0.1},"canonical_model_id":"moonshotai/kimi-k2.5"},"Qwen3.5-397B-A17B":{"id":"Qwen3.5-397B-A17B","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.6,"output":3.6},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"Qwen3-VL-235B-A22B-Thinking":{"id":"Qwen3-VL-235B-A22B-Thinking","name":"Qwen3 VL 235B A22B Thinking","description":"Qwen vision-language thinking model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"status":"deprecated","cost":{"input":0.98,"output":3.95},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-thinking"},"Qwen3.5-27B":{"id":"Qwen3.5-27B","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.3,"output":2.4},"canonical_model_id":"alibaba/qwen3.5-27b"},"Qwen3.5-35B-A3B":{"id":"Qwen3.5-35B-A3B","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.25,"output":2},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"Kimi-K2.7-Code":{"id":"Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":271360,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"Hy3":{"id":"Hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"input":192000,"output":128000},"status":"deprecated","cost":{"input":0.14,"output":0.58},"canonical_model_id":"tencent/hy3"},"Kimi-K3":{"id":"Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"Qwen3-VL-235B-A22B-Instruct":{"id":"Qwen3-VL-235B-A22B-Instruct","name":"Qwen3 VL 235B A22B Instruct","description":"Qwen vision-language instruct model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":129024,"output":32768},"status":"deprecated","cost":{"input":0.3,"output":1.5},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"DeepSeek-V4-Pro":{"id":"DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":1.6,"output":3.38,"cache_read":0.14},"canonical_model_id":"deepseek/deepseek-v4-pro"},"Qwen3-Next-80B-A3B-Instruct":{"id":"Qwen3-Next-80B-A3B-Instruct","name":"Qwen3-Next 80B-A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":129024,"output":32768},"status":"deprecated","cost":{"input":0.15,"output":1.5},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"DeepSeek-V4-Flash":{"id":"DeepSeek-V4-Flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"GLM-5.1":{"id":"GLM-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":1.38,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"MiniMax-M3":{"id":"MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":512000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"GLM-5.2":{"id":"GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"}}},"alibaba-cn":{"id":"alibaba-cn","env":["DASHSCOPE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://dashscope.aliyuncs.com/compatible-mode/v1","name":"Alibaba (China)","doc":"https://www.alibabacloud.com/help/en/model-studio/models","models":{"qwen3-max":{"id":"qwen3-max","name":"Qwen3 Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-23","last_updated":"2026-09-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"status":"deprecated","cost":{"input":0.359,"output":1.434,"reasoning":1.434,"tiers":[{"input":0.574,"output":2.294,"reasoning":2.294,"tier":{"type":"context","size":32000}},{"input":1.004,"output":4.014,"reasoning":4.014,"tier":{"type":"context","size":128000}}]}},"qwen3-235b-a22b":{"id":"qwen3-235b-a22b","name":"Qwen3 235B-A22B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":38912}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"status":"deprecated","cost":{"input":0.287,"output":1.147,"reasoning":2.868}},"kimi-k2-thinking":{"id":"kimi-k2-thinking","name":"Moonshot Kimi K2 Thinking","description":"Kimi reasoning model for long-horizon research, planning, and tool use","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"status":"deprecated","cost":{"input":0.574,"output":2.294}},"deepseek-r1-distill-qwen-14b":{"id":"deepseek-r1-distill-qwen-14b","name":"DeepSeek R1 Distill Qwen 14B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":16384},"status":"deprecated","cost":{"input":0.144,"output":0.431}},"qwq-32b":{"id":"qwq-32b","name":"QwQ 32B","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-12","last_updated":"2024-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.287,"output":0.861}},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.11875,"output":0.40073,"cache_read":0.01187,"cache_write":0.14844},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen3.6-flash":{"id":"qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":131072}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.165,"output":0.99,"cache_read":0.0165,"cache_write":0.20625,"tiers":[{"input":0.66,"output":3.961,"cache_read":0.066,"cache_write":0.825,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.66,"output":3.961,"cache_read":0.066,"cache_write":0.825}},"canonical_model_id":"alibaba/qwen3.6-flash"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"status":"deprecated","cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":2.827,"output":14.133,"cache_read":0.283},"canonical_model_id":"moonshotai/kimi-k3"},"moonshot-kimi-k2-instruct":{"id":"moonshot-kimi-k2-instruct","name":"Moonshot Kimi K2 Instruct","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.574,"output":2.294}},"qwen-plus-character":{"id":"qwen-plus-character","name":"Qwen Plus Character","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-04","release_date":"2024-01","last_updated":"2024-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":4096},"cost":{"input":0.115,"output":0.287}},"qwen3-omni-flash-realtime":{"id":"qwen3-omni-flash-realtime","type":"realtime","name":"Qwen3-Omni Flash Realtime","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":65536,"output":16384},"status":"deprecated","provider":{"api":"wss://dashscope.aliyuncs.com/api-ws/v1/realtime"},"cost":{"input":0.23,"output":0.918,"input_audio":3.584,"output_audio":7.168}},"qwen2-5-coder-7b-instruct":{"id":"qwen2-5-coder-7b-instruct","name":"Qwen2.5-Coder 7B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-11","last_updated":"2024-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.144,"output":0.287}},"qwen3-omni-flash":{"id":"qwen3-omni-flash","name":"Qwen3-Omni Flash","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image","audio","video"],"output":["text","audio"]},"open_weights":false,"limit":{"context":65536,"output":16384},"cost":{"input":0.258,"output":0.989,"input_audio":2.265,"output_audio":8.974}},"qwen3-coder-30b-a3b-instruct":{"id":"qwen3-coder-30b-a3b-instruct","name":"Qwen3-Coder 30B-A3B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","cost":{"input":0.216,"output":0.861,"tiers":[{"input":0.323,"output":1.291,"tier":{"type":"context","size":32000}},{"input":0.538,"output":2.151,"tier":{"type":"context","size":128000}}]}},"qwen-mt-turbo":{"id":"qwen-mt-turbo","name":"Qwen-MT Turbo","description":"Translation model for multilingual conversion, localization, and cross-language workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-04","release_date":"2025-01","last_updated":"2025-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":8192},"status":"deprecated","cost":{"input":0.101,"output":0.28}},"deepseek-r1-distill-qwen-32b":{"id":"deepseek-r1-distill-qwen-32b","name":"DeepSeek R1 Distill Qwen 32B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":16384},"status":"deprecated","cost":{"input":0.287,"output":0.861}},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":1.1,"output":3.851,"cache_read":0.275,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"qwen-max":{"id":"qwen-max","name":"Qwen Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-03","last_updated":"2025-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.345,"output":1.377}},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.29754,"output":1.19015,"cache_read":0.01488},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"qwen3-coder-plus":{"id":"qwen3-coder-plus","name":"Qwen3 Coder Plus","description":"Hosted Qwen coder for software agents, repo edits, and long-context code","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2026-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":0.574,"output":2.296,"tiers":[{"input":0.861,"output":3.444,"tier":{"type":"context","size":32000}},{"input":1.435,"output":5.74,"tier":{"type":"context","size":128000}},{"input":2.87,"output":28.7,"tier":{"type":"context","size":256000}}]}},"glm-5":{"id":"glm-5","name":"GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-11","last_updated":"2026-02-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":16384},"cost":{"input":0.573,"output":2.58,"tiers":[{"input":0.86,"output":3.154,"tier":{"type":"context","size":32000}}]}},"qwen3-8b":{"id":"qwen3-8b","name":"Qwen3 8B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":38912}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.072,"output":0.287,"reasoning":0.717}},"qwen3-14b":{"id":"qwen3-14b","name":"Qwen3 14B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":38912}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.144,"output":0.574,"reasoning":1.434}},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.1,"output":3.851,"cache_read":0.275,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":1.77744,"output":5.33231,"cache_read":0.22218,"cache_write":2.22179},"canonical_model_id":"alibaba/qwen3.8-max"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.65,"output":3.301},"canonical_model_id":"deepseek/deepseek-v4-pro"},"qwen2-5-32b-instruct":{"id":"qwen2-5-32b-instruct","name":"Qwen2.5 32B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.287,"output":0.861}},"qwen3.8-omni-flash":{"id":"qwen3.8-omni-flash","name":"Qwen3.8 Omni Flash","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.113,"output":0.382,"cache_read":0.014},"canonical_model_id":"alibaba/qwen3.8-omni-flash"},"tongyi-intent-detect-v3":{"id":"tongyi-intent-detect-v3","name":"Tongyi Intent Detect V3","description":"General-purpose chat model for instruction following, writing, and analysis","family":"yi","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-04","release_date":"2024-01","last_updated":"2024-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1024},"cost":{"input":0.058,"output":0.144}},"qwen-vl-max":{"id":"qwen-vl-max","name":"Qwen-VL Max","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-08","last_updated":"2025-08-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.23,"output":0.574}},"qwen3-vl-plus":{"id":"qwen3-vl-plus","name":"Qwen3-VL Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.143353,"output":1.433525,"tiers":[{"input":0.215,"output":2.15,"tier":{"type":"context","size":32000}},{"input":0.43,"output":4.301,"tier":{"type":"context","size":128000}}]}},"qwen2-5-vl-7b-instruct":{"id":"qwen2-5-vl-7b-instruct","name":"Qwen2.5-VL 7B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.287,"output":0.717}},"deepseek-r1-distill-llama-70b":{"id":"deepseek-r1-distill-llama-70b","name":"DeepSeek R1 Distill Llama 70B","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":16384},"cost":{"input":0.287,"output":0.861}},"deepseek-r1":{"id":"deepseek-r1","name":"DeepSeek R1","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"status":"deprecated","cost":{"input":0.574,"output":2.294}},"qwen2-5-vl-72b-instruct":{"id":"qwen2-5-vl-72b-instruct","name":"Qwen2.5-VL 72B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":2.294,"output":6.881}},"qwen-flash":{"id":"qwen-flash","name":"Qwen Flash","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.022,"output":0.216,"tiers":[{"input":0.087,"output":0.861,"tier":{"type":"context","size":128000}},{"input":0.173,"output":1.721,"tier":{"type":"context","size":256000}}]}},"kimi-k2.5":{"id":"kimi-k2.5","name":"Moonshot Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.574,"output":3.011}},"qwen3-coder-flash":{"id":"qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.144,"output":0.574,"tiers":[{"input":0.216,"output":0.861,"tier":{"type":"context","size":32000}},{"input":0.359,"output":1.434,"tier":{"type":"context","size":128000}},{"input":0.717,"output":3.584,"tier":{"type":"context","size":256000}}]}},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":262144}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.276,"output":1.101,"cache_read":0.0276,"cache_write":0.345,"tiers":[{"input":0.826,"output":3.301,"cache_read":0.0826,"cache_write":1.0325,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.826,"output":3.301,"cache_read":0.0826,"cache_write":1.0325}},"canonical_model_id":"alibaba/qwen3.7-plus"},"deepseek-r1-distill-qwen-7b":{"id":"deepseek-r1-distill-qwen-7b","name":"DeepSeek R1 Distill Qwen 7B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":16384},"status":"deprecated","cost":{"input":0.072,"output":0.144}},"MiniMax-M2.5":{"id":"MiniMax-M2.5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2}},"qwen-omni-turbo":{"id":"qwen-omni-turbo","name":"Qwen-Omni Turbo","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-01-19","last_updated":"2025-03-26","modalities":{"input":["text","image","audio","video"],"output":["text","audio"]},"open_weights":false,"limit":{"context":32768,"output":2048},"status":"deprecated","cost":{"input":0.058,"output":0.23,"input_audio":3.584,"output_audio":7.168}},"qwen3-coder-480b-a35b-instruct":{"id":"qwen3-coder-480b-a35b-instruct","name":"Qwen3-Coder 480B-A35B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","cost":{"input":0.861,"output":3.441,"tiers":[{"input":1.291,"output":5.161,"tier":{"type":"context","size":32000}},{"input":2.151,"output":8.602,"tier":{"type":"context","size":128000}}]}},"qwen3.5-397b-a17b":{"id":"qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.172,"output":1.032,"reasoning":1.032,"tiers":[{"input":0.43,"output":2.58,"reasoning":2.58,"tier":{"type":"context","size":128000}}]}},"qwen3-vl-235b-a22b":{"id":"qwen3-vl-235b-a22b","name":"Qwen3-VL 235B-A22B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"status":"deprecated","cost":{"input":0.286705,"output":1.14682,"reasoning":2.867051}},"qwen3-next-80b-a3b-instruct":{"id":"qwen3-next-80b-a3b-instruct","name":"Qwen3-Next 80B-A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"status":"deprecated","cost":{"input":0.144,"output":0.574}},"qwen3.5-flash":{"id":"qwen3.5-flash","name":"Qwen3.5 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-23","last_updated":"2026-09-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.029,"output":0.287,"reasoning":0.287,"tiers":[{"input":0.115,"output":1.147,"reasoning":1.147,"tier":{"type":"context","size":128000}},{"input":0.172,"output":1.72,"reasoning":1.72,"tier":{"type":"context","size":256000}}]}},"qwen3-32b":{"id":"qwen3-32b","name":"Qwen3 32B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":38912}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"status":"deprecated","cost":{"input":0.287,"output":1.147,"reasoning":2.868}},"kimi-k2.6":{"id":"kimi-k2.6","name":"Moonshot Kimi K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.929,"output":3.858}},"qwen-turbo":{"id":"qwen-turbo","name":"Qwen Turbo","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":38912}],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-11-01","last_updated":"2025-07-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":16384},"status":"deprecated","cost":{"input":0.044,"output":0.087,"reasoning":0.431}},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":131072}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-14","last_updated":"2026-04-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":128000},"cost":{"input":0.825,"output":3.301,"cache_read":0.17,"tiers":[{"input":1.1,"output":3.851,"tier":{"type":"context","size":32000}}]}},"qwen3.7-max":{"id":"qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":262144}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":1.65,"output":4.951,"cache_read":0.33,"cache_write":2.0625},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen-deep-research":{"id":"qwen-deep-research","name":"Qwen Deep Research","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01","last_updated":"2024-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":7.742,"output":23.367}},"qwen-doc-turbo":{"id":"qwen-doc-turbo","name":"Qwen Doc Turbo","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01","last_updated":"2024-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.087,"output":0.144}},"qwq-plus":{"id":"qwq-plus","name":"QwQ Plus","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-03-05","last_updated":"2025-03-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.23,"output":0.574}},"qwen-mt-plus":{"id":"qwen-mt-plus","name":"Qwen-MT Plus","description":"Translation model for multilingual conversion, localization, and cross-language workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-04","release_date":"2025-01","last_updated":"2025-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":8192},"cost":{"input":0.259,"output":0.775}},"deepseek-r1-distill-qwen-1-5b":{"id":"deepseek-r1-distill-qwen-1-5b","name":"DeepSeek R1 Distill Qwen 1.5B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":16384},"cost":{"input":0,"output":0}},"deepseek-v3-2-exp":{"id":"deepseek-v3-2-exp","name":"DeepSeek V3.2 Exp","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":65536},"status":"deprecated","cost":{"input":0.287,"output":0.431}},"qwen-plus":{"id":"qwen-plus","name":"Qwen Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.115,"output":0.287,"reasoning":1.147,"cache_read":0.012,"cache_write":0.144,"tiers":[{"input":0.345,"output":2.868,"reasoning":3.441,"tier":{"type":"context","size":128000}},{"input":0.689,"output":6.881,"reasoning":9.175,"tier":{"type":"context","size":256000}}]}},"qwen-omni-turbo-realtime":{"id":"qwen-omni-turbo-realtime","type":"realtime","name":"Qwen-Omni Turbo Realtime","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-05-08","last_updated":"2025-05-08","modalities":{"input":["text","image","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":32768,"output":2048},"status":"deprecated","provider":{"api":"wss://dashscope.aliyuncs.com/api-ws/v1/realtime"},"cost":{"input":0.23,"output":0.918,"input_audio":3.584,"output_audio":7.168}},"qwen-math-plus":{"id":"qwen-math-plus","name":"Qwen Math Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-08-16","last_updated":"2024-09-19","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":4096,"output":3072},"status":"deprecated","cost":{"input":0.574,"output":1.721}},"deepseek-r1-distill-llama-8b":{"id":"deepseek-r1-distill-llama-8b","name":"DeepSeek R1 Distill Llama 8B","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":16384},"status":"deprecated","cost":{"input":0,"output":0}},"qwen3.7-flash":{"id":"qwen3.7-flash","name":"Qwen3.7 Flash","description":"Lightweight multimodal Qwen model for high-throughput text, image, and video tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":262144}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":991808,"output":131072},"cost":{"input":0.02962,"output":0.1185,"cache_read":0.002962,"cache_write":0.03703,"tiers":[{"input":0.08887,"output":0.35549,"cache_read":0.008887,"cache_write":0.11109,"tier":{"type":"context","size":32000}},{"input":0.17774,"output":0.71098,"cache_read":0.017774,"cache_write":0.22218,"tier":{"type":"context","size":256000}}]},"canonical_model_id":"alibaba/qwen3.7-flash"},"qwen3.6-plus":{"id":"qwen3.6-plus","name":"Qwen3.6 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.276,"output":1.651,"cache_read":0.0276,"cache_write":0.345,"tiers":[{"input":1.101,"output":6.602,"cache_read":0.1101,"cache_write":1.37625,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1.101,"output":6.602,"cache_read":0.1101,"cache_write":1.37625}}},"deepseek-v3":{"id":"deepseek-v3","name":"DeepSeek V3","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-12-01","last_updated":"2024-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"output":8192},"status":"deprecated","cost":{"input":0.287,"output":1.147}},"qwen2-5-7b-instruct":{"id":"qwen2-5-7b-instruct","name":"Qwen2.5 7B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.072,"output":0.144}},"deepseek-v3-1":{"id":"deepseek-v3-1","name":"DeepSeek V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":65536},"status":"deprecated","cost":{"input":0.574,"output":1.721}},"deepseek-r1-0528":{"id":"deepseek-r1-0528","name":"DeepSeek R1 0528","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"status":"deprecated","cost":{"input":0.574,"output":2.294}},"qwen2-5-math-7b-instruct":{"id":"qwen2-5-math-7b-instruct","name":"Qwen2.5-Math 7B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":3072},"status":"deprecated","cost":{"input":0.144,"output":0.287}},"qwen2-5-14b-instruct":{"id":"qwen2-5-14b-instruct","name":"Qwen2.5 14B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.144,"output":0.431}},"qwen3.6-max-preview":{"id":"qwen3.6-max-preview","name":"Qwen3.6 Max Preview","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":131072}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-20","last_updated":"2026-04-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":245800,"output":65536},"status":"deprecated","cost":{"input":1.32,"output":7.9,"cache_read":0.132}},"qwen2-5-omni-7b":{"id":"qwen2-5-omni-7b","name":"Qwen2.5-Omni 7B","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-12","last_updated":"2024-12","modalities":{"input":["text","image","audio","video"],"output":["text","audio"]},"open_weights":true,"limit":{"context":32768,"output":2048},"status":"deprecated","cost":{"input":0.087,"output":0.345,"input_audio":5.448}},"qwen-math-turbo":{"id":"qwen-math-turbo","name":"Qwen Math Turbo","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09-19","last_updated":"2024-09-19","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":4096,"output":3072},"status":"deprecated","cost":{"input":0.287,"output":0.861}},"qwen2-5-math-72b-instruct":{"id":"qwen2-5-math-72b-instruct","name":"Qwen2.5-Math 72B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":3072},"status":"deprecated","cost":{"input":0.574,"output":1.721}},"qwen3-vl-30b-a3b":{"id":"qwen3-vl-30b-a3b","name":"Qwen3-VL 30B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04","last_updated":"2025-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"status":"deprecated","cost":{"input":0.108,"output":0.431,"reasoning":1.076}},"qwen-long":{"id":"qwen-long","name":"Qwen Long","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-01-25","last_updated":"2025-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":10000000,"output":8192},"cost":{"input":0.072,"output":0.287}},"qvq-max":{"id":"qvq-max","name":"QVQ Max","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"qvq","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-03-25","last_updated":"2025-03-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":1.147,"output":4.588}},"qwen-vl-plus":{"id":"qwen-vl-plus","name":"Qwen-VL Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-08-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.115,"output":0.287}},"qwen3-asr-flash":{"id":"qwen3-asr-flash","type":"transcription","name":"Qwen3-ASR Flash","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2024-04","release_date":"2025-09-08","last_updated":"2025-09-08","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":53248,"output":4096}},"qwen3.5-plus":{"id":"qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":81920}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-09-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.115,"output":0.688,"reasoning":0.688,"tiers":[{"input":0.287,"output":1.72,"reasoning":1.72,"tier":{"type":"context","size":128000}},{"input":0.573,"output":3.44,"reasoning":3.44,"tier":{"type":"context","size":256000}}]}},"qwen2-5-coder-32b-instruct":{"id":"qwen2-5-coder-32b-instruct","name":"Qwen2.5-Coder 32B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-11","last_updated":"2024-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.287,"output":0.861}},"qwen2-5-72b-instruct":{"id":"qwen2-5-72b-instruct","name":"Qwen2.5 72B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-09","last_updated":"2024-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.574,"output":1.721}},"qwen-vl-ocr":{"id":"qwen-vl-ocr","name":"Qwen-VL OCR","description":"OCR model for extracting structured text from documents and screenshots","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-04","release_date":"2024-10-28","last_updated":"2026-09-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":34096,"output":4096},"cost":{"input":0.043,"output":0.072}},"qwen3-next-80b-a3b-thinking":{"id":"qwen3-next-80b-a3b-thinking","name":"Qwen3-Next 80B-A3B (Thinking)","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"status":"deprecated","cost":{"input":0.144,"output":1.434}},"MiniMax/MiniMax-M2.7":{"id":"MiniMax/MiniMax-M2.7","name":"MiniMax-M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":0.375}},"siliconflow/deepseek-v3.1-terminus":{"id":"siliconflow/deepseek-v3.1-terminus","name":"siliconflow/deepseek-v3.1-terminus","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-29","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":163840,"output":65536},"cost":{"input":0.27,"output":1}},"siliconflow/deepseek-r1-0528":{"id":"siliconflow/deepseek-r1-0528","name":"siliconflow/deepseek-r1-0528","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":163840,"output":32768},"cost":{"input":0.5,"output":2.18}},"siliconflow/deepseek-v3.2":{"id":"siliconflow/deepseek-v3.2","name":"siliconflow/deepseek-v3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-03","last_updated":"2025-12-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":163840,"output":65536},"cost":{"input":0.27,"output":0.42}},"siliconflow/deepseek-v3-0324":{"id":"siliconflow/deepseek-v3-0324","name":"siliconflow/deepseek-v3-0324","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-12-26","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":163840,"output":163840},"cost":{"input":0.25,"output":1}},"kimi/kimi-k2.5":{"id":"kimi/kimi-k2.5","name":"kimi/kimi-k2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":3,"cache_read":0.1}}}},"xiaomi":{"id":"xiaomi","env":["XIAOMI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.xiaomimimo.com/v1","name":"Xiaomi","doc":"https://platform.xiaomimimo.com/#/docs","models":{"mimo-v2.6-pro-ultraspeed":{"id":"mimo-v2.6-pro-ultraspeed","name":"MiMo-V2.6-Pro-UltraSpeed","description":"MiMo pro model for strong multimodal reasoning and agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":4.35,"output":8.7,"cache_read":0.036},"canonical_model_id":"xiaomi/mimo-v2.6-pro-ultraspeed"},"mimo-v2-flash":{"id":"mimo-v2-flash","name":"MiMo-V2-Flash","description":"Legacy model retained for compatibility with older integrations","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12-01","release_date":"2025-12-16","last_updated":"2026-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2-flash"},"mimo-v2.6-flash":{"id":"mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"mimo-v2-omni":{"id":"mimo-v2-omni","name":"MiMo-V2-Omni","description":"Legacy model retained for compatibility with older integrations","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"status":"deprecated","cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2-omni"},"mimo-v2-pro":{"id":"mimo-v2-pro","name":"MiMo-V2-Pro","description":"Earlier MiMo Pro model for multimodal agents, reasoning, and code tasks","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2-pro"},"mimo-v2.5-pro-ultraspeed":{"id":"mimo-v2.5-pro-ultraspeed","name":"MiMo-V2.5-Pro-UltraSpeed","description":"MiMo pro model for strong multimodal reasoning and agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-06-08","last_updated":"2026-06-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":1.305,"output":2.61,"cache_read":0.0108},"canonical_model_id":"xiaomi/mimo-v2.5-pro-ultraspeed"},"mimo-v2.6-pro":{"id":"mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"MiMo Pro model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"mimo-v2.5-pro":{"id":"mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"mimo-v2.5":{"id":"mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.5"}}},"meganova":{"id":"meganova","env":["MEGANOVA_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.meganova.ai/v1","name":"Meganova","doc":"https://docs.meganova.ai","models":{"Qwen/Qwen3.5-Plus":{"id":"Qwen/Qwen3.5-Plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.4,"output":2.4,"reasoning":2.4},"canonical_model_id":"alibaba/qwen3.5-plus"},"Qwen/Qwen3-235B-A22B-Instruct-2507":{"id":"Qwen/Qwen3-235B-A22B-Instruct-2507","name":"Qwen3 235B A22B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.09,"output":0.1},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"Qwen/Qwen2.5-VL-32B-Instruct":{"id":"Qwen/Qwen2.5-VL-32B-Instruct","name":"Qwen2.5 VL 32B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-03-24","last_updated":"2025-03-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":16384},"cost":{"input":0.2,"output":0.6}},"zai-org/GLM-4.7":{"id":"zai-org/GLM-4.7","name":"GLM-4.7","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.4,"output":1.75,"cache_read":0.08},"canonical_model_id":"zhipuai/glm-4.7"},"zai-org/GLM-5":{"id":"zai-org/GLM-5","name":"GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.8,"output":2.56,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"zai-org/GLM-4.6":{"id":"zai-org/GLM-4.6","name":"GLM-4.6","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.45,"output":1.9},"canonical_model_id":"zhipuai/glm-4.6"},"mistralai/Mistral-Small-3.2-24B-Instruct-2506":{"id":"mistralai/Mistral-Small-3.2-24B-Instruct-2506","name":"Mistral Small 3.2 24B Instruct","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"mistral/mistral-small-2506"},"mistralai/Mistral-Nemo-Instruct-2407":{"id":"mistralai/Mistral-Nemo-Instruct-2407","name":"Mistral Nemo Instruct 2407","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.02,"output":0.04},"canonical_model_id":"mistral/mistral-nemo"},"XiaomiMiMo/MiMo-V2-Flash":{"id":"XiaomiMiMo/MiMo-V2-Flash","name":"MiMo V2 Flash","description":"MiMo flash model for fast multimodal assistance and agent workflows","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12-01","release_date":"2025-12-16","last_updated":"2026-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32000},"status":"deprecated","cost":{"input":0.1,"output":0.3},"canonical_model_id":"xiaomi/mimo-v2-flash"},"moonshotai/Kimi-K2.5":{"id":"moonshotai/Kimi-K2.5","name":"Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2026-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.45,"output":2.25,"cache_read":0.07},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/Kimi-K2-Thinking":{"id":"moonshotai/Kimi-K2-Thinking","name":"Kimi K2 Thinking","description":"Kimi reasoning model for long-horizon research, planning, and tool use","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":2.6},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"meta-llama/Llama-3.3-70B-Instruct":{"id":"meta-llama/Llama-3.3-70B-Instruct","name":"Llama 3.3 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"MiniMaxAI/MiniMax-M2.5":{"id":"MiniMaxAI/MiniMax-M2.5","name":"MiniMax M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.15},"canonical_model_id":"minimax/MiniMax-M2.5"},"MiniMaxAI/MiniMax-M2.1":{"id":"MiniMaxAI/MiniMax-M2.1","name":"MiniMax M2.1","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":131072},"cost":{"input":0.28,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2.1"},"deepseek-ai/DeepSeek-R1-0528":{"id":"deepseek-ai/DeepSeek-R1-0528","name":"DeepSeek R1 0528","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-07","release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":64000},"cost":{"input":0.5,"output":2.15,"cache_read":0.4},"canonical_model_id":"deepseek/deepseek-r1-0528"},"deepseek-ai/DeepSeek-V3.2-Exp":{"id":"deepseek-ai/DeepSeek-V3.2-Exp","name":"DeepSeek V3.2 Exp","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-10","last_updated":"2025-10-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":164000},"cost":{"input":0.26,"output":0.38,"cache_read":0.13}},"deepseek-ai/DeepSeek-V3.2":{"id":"deepseek-ai/DeepSeek-V3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":164000},"cost":{"input":0.26,"output":0.38,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepseek-ai/DeepSeek-V3-0324":{"id":"deepseek-ai/DeepSeek-V3-0324","name":"DeepSeek V3 0324","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-03-24","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":163840},"cost":{"input":0.275,"output":1.1},"canonical_model_id":"deepseek/deepseek-v3-0324"},"deepseek-ai/DeepSeek-V3.1":{"id":"deepseek-ai/DeepSeek-V3.1","name":"DeepSeek V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":164000},"cost":{"input":0.19,"output":0.79},"canonical_model_id":"deepseek/deepseek-v3.1"}}},"coralbricks":{"id":"coralbricks","env":["CORAL_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://inference.coralbricks.ai/v1","name":"CoralBricks","doc":"https://www.coralbricks.ai/docs","models":{"deepseek-v4.1-flash-fast":{"id":"deepseek-v4.1-flash-fast","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.25,"output":1.2,"cache_read":0.005,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4.1-flash"}}},"qihang-ai":{"id":"qihang-ai","env":["QIHANG_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.qhaigc.net/v1","name":"QiHang","doc":"https://www.qhaigc.net/docs","models":{"gemini-3-flash-preview":{"id":"gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.07,"output":0.43,"tiers":[{"input":0.07,"output":0.43,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":0.07,"output":0.43}},"canonical_model_id":"google/gemini-3-flash-preview"},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.09,"output":0.71,"tiers":[{"input":0.09,"output":0.71,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":0.09,"output":0.71}},"canonical_model_id":"google/gemini-2.5-flash"},"gemini-3-pro-preview":{"id":"gemini-3-pro-preview","name":"Gemini 3 Pro Preview","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-11","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65000},"cost":{"input":0.57,"output":3.43},"canonical_model_id":"google/gemini-3-pro-preview"},"claude-opus-4-5-20251101":{"id":"claude-opus-4-5-20251101","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","cost":{"input":0.71,"output":3.57},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"gpt-5.2-codex":{"id":"gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":0.14,"output":1.14},"canonical_model_id":"openai/gpt-5.2-codex"},"gpt-5-mini":{"id":"gpt-5-mini","name":"GPT-5-Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":0.04,"output":0.29},"canonical_model_id":"openai/gpt-5-mini"},"claude-sonnet-4-5-20250929":{"id":"claude-sonnet-4-5-20250929","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":0.43,"output":2.14},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"claude-haiku-4-5-20251001":{"id":"claude-haiku-4-5-20251001","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":0.14,"output":0.71},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"gpt-5.2":{"id":"gpt-5.2","name":"GPT-5.2","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":0.25,"output":2},"canonical_model_id":"openai/gpt-5.2"}}},"dinference":{"id":"dinference","env":["DINFERENCE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.dinference.com/v1","name":"DInference","doc":"https://dinference.com","models":{"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.0675,"output":0.27},"canonical_model_id":"openai/gpt-oss-120b"},"glm-4.7":{"id":"glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.45,"output":1.65},"canonical_model_id":"zhipuai/glm-4.7"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"status":"deprecated","cost":{"input":1.25,"output":3.89},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5":{"id":"glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.75,"output":2.4},"canonical_model_id":"zhipuai/glm-5"},"minimax-m2.5":{"id":"minimax-m2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"status":"deprecated","cost":{"input":0.22,"output":0.88},"canonical_model_id":"minimax/MiniMax-M2.5"},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"status":"deprecated","cost":{"input":1.25,"output":3.89},"canonical_model_id":"zhipuai/glm-5.1"}}},"bothub":{"id":"bothub","env":["BOTHUB_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://openai.bothub.ru/v1","name":"Bothub","doc":"https://bothub.ru/models","models":{"nemotron-3-ultra-550b-a55b:free":{"id":"nemotron-3-ultra-550b-a55b:free","name":"Nemotron 3 Ultra (free)","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"gemma-4-31b-it:free":{"id":"gemma-4-31b-it:free","name":"Gemma 4 31B IT (free)","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemma-4-31b-it"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4243,"output":4.4765},"canonical_model_id":"zhipuai/glm-5.3"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.1566,"output":0.522},"canonical_model_id":"zhipuai/glm-5.3-flash"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2677,"output":1.6064},"canonical_model_id":"openai/gpt-5.6-luna"},"muse-spark-1.3-contributor":{"id":"muse-spark-1.3-contributor","name":"Muse Spark 1.3 Contributor","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.1,"output":0.2},"canonical_model_id":"meta/muse-spark-1.3"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.589,"output":1.7671},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.7671,"output":5.3011},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"}}},"requesty":{"id":"requesty","env":["REQUESTY_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://router.requesty.ai/v1","name":"Requesty","doc":"https://requesty.ai/solution/llm-routing/models","models":{"claude-sonnet-4-5":{"id":"claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"nemotron-3-nano-omni-30b-a3b-reasoning":{"id":"nemotron-3-nano-omni-30b-a3b-reasoning","name":"Nemotron 3 Nano Omni 30B A3B Reasoning","description":"Open Nemotron omni model combining reasoning with text, vision, and audio","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":20480},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning"},"gemini-2.5-flash@eu":{"id":"gemini-2.5-flash@eu","name":"Gemini 2.5 Flash (EU)","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.3,"output":2.5,"cache_read":0.075,"cache_write":0.55},"canonical_model_id":"google/gemini-2.5-flash"},"qwen3.8-flash-next":{"id":"qwen3.8-flash-next","name":"Qwen3.8 Flash Next","description":"Open-weight experimental preview of the Qwen4 architecture: hybrid-attention MoE (125B total, 6B active) with vision encoder for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.8-flash-next"},"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"muse-spark-1.3":{"id":"muse-spark-1.3","name":"Muse Spark 1.3","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.3"},"kimi-k2.6@eu":{"id":"kimi-k2.6@eu","name":"Kimi K2.6 (EU)","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":128000},"cost":{"input":0.95,"output":4,"cache_read":0.95},"canonical_model_id":"moonshotai/kimi-k2.6"},"gpt-5.4@eu":{"id":"gpt-5.4@eu","name":"GPT-5.4 (EU)","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.75,"output":16.5,"cache_read":0.275,"tiers":[{"input":5.5,"output":24.75,"cache_read":0.55,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5.5,"output":24.75,"cache_read":0.55}},"canonical_model_id":"openai/gpt-5.4"},"leanstral-1-5@eu":{"id":"leanstral-1-5@eu","name":"leanstral-1-5@eu","description":"Leanstral 1.5 is an updated Lean 4 formal proof engineering model from Mistral AI, optimized for automated theorem proving and autoformalization. It has 119B total parameters with 6.5B active and supports a 256K token context window. It supports native function calling and structured output.","family":"leanstral","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-27","last_updated":"2026-05-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0}},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"o4-mini@eu":{"id":"o4-mini@eu","name":"o4-mini (EU)","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.21,"output":4.84,"cache_read":0.3025},"canonical_model_id":"openai/o4-mini"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"claude-fable-5@eu":{"id":"claude-fable-5@eu","name":"Claude Fable 5 (EU)","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":11,"output":55,"cache_read":1.1,"cache_write":13.75},"canonical_model_id":"anthropic/claude-fable-5"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"deepseek-v4.1-flash@eu":{"id":"deepseek-v4.1-flash@eu","name":"DeepSeek V4.1 Flash (EU)","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.5,"output":1.5,"cache_read":0.05},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"gemini-3.7-flash":{"id":"gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.7-flash"},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.16,"output":0.47,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"fugu-ultra":{"id":"fugu-ultra","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"sakana/fugu-ultra"},"gemini-3-pro-image":{"id":"gemini-3-pro-image","type":"image","name":"Nano Banana Pro","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":1048576,"output":32768},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":4.5},"canonical_model_id":"google/gemini-3-pro-image"},"qwen3.8-2.4T-A95B@eu":{"id":"qwen3.8-2.4T-A95B@eu","name":"Qwen3.8 2.4T A95B (EU)","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":262144},"cost":{"input":2.5,"output":6,"cache_read":0.63},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"grok-build-0.1":{"id":"grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.1},"canonical_model_id":"xai/grok-build-0.1"},"claude-sonnet-4-5@eu":{"id":"claude-sonnet-4-5@eu","name":"Claude Sonnet 4.5 (latest) (EU)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3.3,"output":16.5,"cache_read":0.3,"cache_write":4.125,"tiers":[{"input":6.6,"output":24.75,"cache_read":0.6,"cache_write":8.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6.6,"output":24.75,"cache_read":0.6,"cache_write":8.25}},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"gpt-5.6-sol@eu":{"id":"gpt-5.6-sol@eu","name":"GPT-5.6 Sol (EU)","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4.4,"output":22,"cache_read":0.44,"cache_write":5.5,"tiers":[{"input":8.8,"output":33,"cache_read":0.88,"cache_write":11,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8.8,"output":33,"cache_read":0.88,"cache_write":11}},"canonical_model_id":"openai/gpt-5.6-sol"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.28,"output":0.56,"cache_read":0.07},"canonical_model_id":"deepseek/deepseek-v4-flash"},"grok-4.3":{"id":"grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"cache_write":1.25,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"cache_write":2.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4,"cache_write":2.5}},"canonical_model_id":"xai/grok-4.3"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":3,"output":15,"cache_read":0.45},"canonical_model_id":"moonshotai/kimi-k3"},"minimax-m3@eu":{"id":"minimax-m3@eu","name":"MiniMax-M3 (EU)","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.4,"output":2,"cache_read":0.1},"canonical_model_id":"minimax/MiniMax-M3"},"ling-3.0-tiny":{"id":"ling-3.0-tiny","name":"ling-3.0-tiny","description":"Ling-3.0-tiny is an efficient 7.9B parameter MoE model from inclusionAI with only 1.3B active parameters per token. Built for responsive agents, reliable instruction following and multi turn conversation, with a 256K context window, native function calling, prompt caching and switchable Thinking and Instant modes.","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0}},"claude-opus-4-6@eu":{"id":"claude-opus-4-6@eu","name":"Claude Opus 4.6 (EU)","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-6"},"minimax-m3.1-flash":{"id":"minimax-m3.1-flash","name":"MiniMax-M3.1-Flash","description":"Frontier multimodal coding model with 1M context window and tunable thinking depth","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-19","last_updated":"2026-10-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"minimax/MiniMax-M3.1-Flash"},"qwen3.5-35b-a3b":{"id":"qwen3.5-35b-a3b","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.14,"output":1,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"qwen3.8-flash-next@eu":{"id":"qwen3.8-flash-next@eu","name":"Qwen3.8 Flash Next (EU)","description":"Open-weight experimental preview of the Qwen4 architecture: hybrid-attention MoE (125B total, 6B active) with vision encoder for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.8-flash-next"},"gemini-3.1-flash-image":{"id":"gemini-3.1-flash-image","type":"image","name":"Nano Banana 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","video","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":2},"canonical_model_id":"google/gemini-3.1-flash-image"},"nemotron-lightning-3.5-30b-a3b":{"id":"nemotron-lightning-3.5-30b-a3b","name":"nemotron-lightning-3.5-30b-a3b","description":"Nemotron-Lightning-3.5-30B-A3B is a 30B-parameter Mixture-of-Experts language model (3B active) from NVIDIA's Nemotron-H family, built on a hybrid Mamba-Transformer architecture for efficient long-context inference. Like other models in the family, it responds to queries by first generating a reasoning trace and then concluding with a final response, with reasoning behavior configurable through a flag in the chat template. It includes a multi-token prediction (MTP) speculative decoding head for low-latency serving.","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-15","last_updated":"2026-08-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.05,"output":0.2,"cache_read":0.01}},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":11,"output":55,"cache_read":1.1,"cache_write":13.75},"canonical_model_id":"anthropic/claude-fable-5"},"gpt-5.4-pro":{"id":"gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"cache_read":30},"canonical_model_id":"openai/gpt-5.4-pro"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"glm-5.3-flash@eu":{"id":"glm-5.3-flash@eu","name":"GLM-5.3-Flash (EU)","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":262144},"cost":{"input":0.2,"output":0.6,"cache_read":0.07},"canonical_model_id":"zhipuai/glm-5.3-flash"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.8,"output":2.55,"cache_read":0.16},"canonical_model_id":"zhipuai/glm-5.2"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.5,"output":1.5,"cache_read":0.05},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"mistral-small-2603@eu":{"id":"mistral-small-2603@eu","name":"Mistral Small 4 (EU)","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.165,"output":0.66,"cache_read":0.165},"canonical_model_id":"mistral/mistral-small-2603"},"claude-sonnet-4-6@eu":{"id":"claude-sonnet-4-6@eu","name":"Claude Sonnet 4.6 (EU)","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3.3,"output":16.5,"cache_read":0.3,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"kimi-k2.7-code@eu":{"id":"kimi-k2.7-code@eu","name":"Kimi K2.7 Code (EU)","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.25,"output":4.5,"cache_read":0.31},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"kimi-k2.5@eu":{"id":"kimi-k2.5@eu","name":"Kimi K2.5 (EU)","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16000},"cost":{"input":0.72,"output":3.6,"cache_read":0.72,"cache_write":0.72},"canonical_model_id":"moonshotai/kimi-k2.5"},"gpt-4.1-nano@eu":{"id":"gpt-4.1-nano@eu","name":"GPT-4.1 nano (EU)","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.11,"output":0.44,"cache_read":0.0275},"canonical_model_id":"openai/gpt-4.1-nano"},"muse-spark-open":{"id":"muse-spark-open","name":"Muse Spark Open","description":"Muse Spark Open is an 816B total / 42B active open-weight multimodal reasoning model from Meta for coding and long-horizon agentic work, with 1M-token context.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-open"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.2,"output":4.2,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro"},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"glm-5.3@eu":{"id":"glm-5.3@eu","name":"GLM-5.3 (EU)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.2,"output":4.2,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"gemini-3.7-flash@eu":{"id":"gemini-3.7-flash@eu","name":"Gemini 3.7 Flash (EU)","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.825,"output":4.125,"cache_read":0.0825},"canonical_model_id":"google/gemini-3.7-flash"},"mistral-medium-3-5":{"id":"mistral-medium-3-5","name":"Mistral Medium 3.5","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":209715},"cost":{"input":1.65,"output":8.25,"cache_read":1.65},"canonical_model_id":"mistral/mistral-medium-3-5"},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"ring-2.6-1t":{"id":"ring-2.6-1t","name":"ring-2.6-1t","description":"Inclusion AI ring-2.6-1t","family":"ring","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-05-08","last_updated":"2026-05-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.3,"output":2.5}},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"claude-sonnet-5-5@eu":{"id":"claude-sonnet-5-5@eu","name":"Claude Sonnet 5.5 (EU)","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.22,"cache_write":2.75},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"laguna-m.1":{"id":"laguna-m.1","name":"Laguna M.1","description":"Poolside's open-weight model for agentic coding and long-horizon work","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"poolside/laguna-m.1"},"kat-coder-pro":{"id":"kat-coder-pro","name":"kat-coder-pro","description":"KAT-Coder-Pro V2 by KwaiKAT is a non-reasoning model optimized for agentic coding. It delivers strong performance on reasoning-style tasks while requiring significantly fewer output tokens than peer models. With the 1210 release, it achieved a score of 64 on the Artificial Analysis Intelligence Index, placing it in the global Top 10 and ranking first among all non-reasoning models.","family":"kat-coder","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2026-03-27","last_updated":"2026-03-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.3,"output":1.2}},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":262144},"cost":{"input":0.2,"output":0.6,"cache_read":0.07},"canonical_model_id":"zhipuai/glm-5.3-flash"},"gemini-3.8-flash@eu":{"id":"gemini-3.8-flash@eu","name":"Gemini 3.8 Flash (EU)","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.825,"output":4.125,"cache_read":0.0825},"canonical_model_id":"google/gemini-3.8-flash"},"leanstral-1-5":{"id":"leanstral-1-5","name":"leanstral-1-5","description":"Leanstral 1.5 is an updated Lean 4 formal proof engineering model from Mistral AI, optimized for automated theorem proving and autoformalization. It has 119B total parameters with 6.5B active and supports a 256K token context window. It supports native function calling and structured output.","family":"leanstral","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-27","last_updated":"2026-05-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0}},"grok-4.2-beta":{"id":"grok-4.2-beta","name":"Grok 4.20 (Reasoning)","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":2,"output":6,"cache_read":0.2,"cache_write":2,"tiers":[{"input":4,"output":12,"cache_read":0.4,"cache_write":4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":0.4,"cache_write":4}},"canonical_model_id":"xai/grok-4.20-0309-reasoning"},"glm-5.2@eu":{"id":"glm-5.2@eu","name":"GLM-5.2 (EU)","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":1.2,"output":4.2,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"step-5-preview":{"id":"step-5-preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":1,"output":2.7,"cache_read":0.05},"canonical_model_id":"stepfun/step-5-preview"},"nemotron-3.5-content-safety":{"id":"nemotron-3.5-content-safety","name":"Nemotron 3.5 Content Safety","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-content-safety"},"seed-2.0-mini":{"id":"seed-2.0-mini","name":"Seed 2.0 Mini","description":"Lightweight ByteDance Seed 2.0 model for low-latency multimodal reasoning and high-volume tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.1,"output":0.4,"cache_read":0.02},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"grok-4.7":{"id":"grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"cache_write":2},"canonical_model_id":"xai/grok-4.7"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"qwen3.8-2.4T-A95B":{"id":"qwen3.8-2.4T-A95B","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"nemotron-3-nano-omni@eu":{"id":"nemotron-3-nano-omni@eu","name":"nemotron-3-nano-omni@eu","description":"The most open, efficient, and accurate omni modal reasoning model for agentic AI.","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-20","last_updated":"2026-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":300000},"cost":{"input":0.06,"output":0.24,"cache_read":0.06}},"nemotron-3-nano-omni":{"id":"nemotron-3-nano-omni","name":"nemotron-3-nano-omni","description":"The most open, efficient, and accurate omni modal reasoning model for agentic AI.","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-20","last_updated":"2026-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":300000},"cost":{"input":0.06,"output":0.24,"cache_read":0.06}},"deepseek-v4-flash-0731@eu":{"id":"deepseek-v4-flash-0731@eu","name":"DeepSeek V4 Flash 0731 (EU)","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.28,"output":0.56,"cache_read":0.07},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"mimo-v2.6-flash":{"id":"mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0027},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"minimax-m2.7-highspeed":{"id":"minimax-m2.7-highspeed","name":"MiniMax-M2.7-highspeed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.6,"output":2.4,"cache_read":0.06,"cache_write":1.2},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.32,"output":1.28,"cache_read":0.032,"cache_write":0.4},"canonical_model_id":"alibaba/qwen3.7-plus"},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.13,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.63,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"claude-sonnet-4@eu":{"id":"claude-sonnet-4@eu","name":"Claude Sonnet 4 (latest) (EU)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}},"canonical_model_id":"anthropic/claude-sonnet-4-0"},"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.75,"output":16.5,"cache_read":0.275},"canonical_model_id":"openai/gpt-5.4"},"claude-opus-4-8@eu":{"id":"claude-opus-4-8@eu","name":"Claude Opus 4.8 (EU)","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-8"},"claude-sonnet-5@eu":{"id":"claude-sonnet-5@eu","name":"Claude Sonnet 5 (EU)","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.22,"cache_write":2.75},"canonical_model_id":"anthropic/claude-sonnet-5"},"gpt-5-nano@eu":{"id":"gpt-5-nano@eu","name":"GPT-5 Nano (EU)","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":0.055,"output":0.44,"cache_read":0.0055},"canonical_model_id":"openai/gpt-5-nano"},"gemini-4-argon":{"id":"gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":10,"cache_read":0.1},"canonical_model_id":"google/gemini-4-argon"},"gemma-4-31b-it":{"id":"gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemma-4-31b-it"},"devstral-latest@eu":{"id":"devstral-latest@eu","name":"devstral-latest@eu","description":"An enterprise grade text model, that excels at using tools to explore codebases, editing multiple files and power software engineering agents.","family":"devstral","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-27","last_updated":"2026-05-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.44,"output":2.2,"cache_read":0.44}},"mistral-large-4@eu":{"id":"mistral-large-4@eu","name":"Mistral Large 4 (EU)","description":"Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":262144},"cost":{"input":0.68,"output":2.09,"cache_read":0.07},"canonical_model_id":"mistral/mistral-large-4"},"nemotron-3-super-120b-a12b":{"id":"nemotron-3-super-120b-a12b","name":"Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"claude-haiku-5-5@eu":{"id":"claude-haiku-5-5@eu","name":"Claude Haiku 5.5 (EU)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.11,"output":0.55,"cache_read":0.02,"cache_write":0.14,"tiers":[{"input":0.55,"output":2.75,"cache_read":0.06,"cache_write":0.69,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"gemini-3.5-flash-lite":{"id":"gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"gpt-5.1@eu":{"id":"gpt-5.1@eu","name":"GPT-5.1 (EU)","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.375,"output":11,"cache_read":0.1375},"canonical_model_id":"openai/gpt-5.1"},"nemotron-3-ultra-550b-a55b":{"id":"nemotron-3-ultra-550b-a55b","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"mistral-medium-3-5@eu":{"id":"mistral-medium-3-5@eu","name":"Mistral Medium 3.5 (EU)","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":209715},"cost":{"input":1.65,"output":8.25,"cache_read":1.65},"canonical_model_id":"mistral/mistral-medium-3-5"},"gpt-4.1-mini@eu":{"id":"gpt-4.1-mini@eu","name":"GPT-4.1 mini (EU)","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.44,"output":1.76,"cache_read":0.11},"canonical_model_id":"openai/gpt-4.1-mini"},"gpt-5.5@eu":{"id":"gpt-5.5@eu","name":"GPT-5.5 (EU)","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5.5,"output":33,"cache_read":0.55,"tiers":[{"input":11,"output":49.5,"cache_read":1.1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":11,"output":49.5,"cache_read":1.1}},"canonical_model_id":"openai/gpt-5.5"},"gpt-5.6-luna@eu":{"id":"gpt-5.6-luna@eu","name":"GPT-5.6 Luna (EU)","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.22,"output":1.32,"cache_read":0.022,"cache_write":0.275,"tiers":[{"input":0.44,"output":1.98,"cache_read":0.044,"cache_write":0.55,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.44,"output":1.98,"cache_read":0.044,"cache_write":0.55}},"canonical_model_id":"openai/gpt-5.6-luna"},"mistral-small-2603":{"id":"mistral-small-2603","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.165,"output":0.66,"cache_read":0.165},"canonical_model_id":"mistral/mistral-small-2603"},"gpt-5-mini@eu":{"id":"gpt-5-mini@eu","name":"GPT-5 Mini (EU)","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":0.275,"output":2.2,"cache_read":0.0275},"canonical_model_id":"openai/gpt-5-mini"},"nemotron-3-ultra-nvfp4":{"id":"nemotron-3-ultra-nvfp4","name":"nemotron-3-ultra-nvfp4","description":"Nemotron-3-Ultra-550B-A55B-NVFP4 is a frontier-scale large language model (LLM) trained by NVIDIA, designed to deliver strong agentic, reasoning, and conversational capabilities. It is optimized for the most demanding workloads, including complex multi-step agents, long-context analysis, and high-accuracy reasoning over code, math, and science. The model employs a hybrid Latent Mixture-of-Experts (LatentMoE) architecture, utilizing interleaved Mamba-2 and MoE layers, along with select Attention layers. Like the Super model, the Ultra model incorporates Multi-Token Prediction (MTP) layers for faster text generation and improved quality, and it is trained using an NVFP4 pre-training recipe to maximize compute efficiency. The model has 55B active parameters and 550B parameters in total.","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":2.4,"cache_read":0.12}},"claude-opus-5-5@eu":{"id":"claude-opus-5-5@eu","name":"Claude Opus 5.5 (EU)","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4.4,"output":22,"cache_read":0.22,"cache_write":5.5},"canonical_model_id":"anthropic/claude-opus-5-5"},"mistral-medium-latest@eu":{"id":"mistral-medium-latest@eu","name":"Mistral Medium (latest) (EU)","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.44,"output":2.2,"cache_read":0.44},"canonical_model_id":"mistral/mistral-medium-latest"},"gemini-3.5-flash@eu":{"id":"gemini-3.5-flash@eu","name":"Gemini 3.5 Flash (EU)","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":1.65,"output":9.9,"cache_read":0.165,"cache_write":1.7413},"canonical_model_id":"google/gemini-3.5-flash"},"gpt-4o-mini@eu":{"id":"gpt-4o-mini@eu","name":"GPT-4o mini (EU)","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16000},"cost":{"input":0.165,"output":0.66,"cache_read":0.0825},"canonical_model_id":"openai/gpt-4o-mini"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"nemotron-3.5-lightning-30b-a3b":{"id":"nemotron-3.5-lightning-30b-a3b","name":"Nemotron 3.5 Lightning 30B A3B","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-09","release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"claude-opus-4-5@eu":{"id":"claude-opus-4-5@eu","name":"Claude Opus 4.5 (latest) (EU)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-5"},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"gpt-6-luna@eu":{"id":"gpt-6-luna@eu","name":"GPT-6 Luna (EU)","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.12,"output":0.6,"cache_read":0.012,"cache_write":0.15,"tiers":[{"input":0.24,"output":0.9,"cache_read":0.024,"cache_write":0.3,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.24,"output":0.9,"cache_read":0.024,"cache_write":0.3}},"canonical_model_id":"openai/gpt-6-luna"},"gpt-6-sol@eu":{"id":"gpt-6-sol@eu","name":"GPT-6 Sol (EU)","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.4,"output":12,"cache_read":0.24,"cache_write":3,"tiers":[{"input":4.8,"output":18,"cache_read":0.48,"cache_write":6,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4.8,"output":18,"cache_read":0.48,"cache_write":6}},"canonical_model_id":"openai/gpt-6-sol"},"ling-2.6-flash":{"id":"ling-2.6-flash","name":"ling-2.6-flash","description":"Inclusion AI ling-2.6-flash","family":"ling","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.1,"output":0.3}},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"seed-1.8":{"id":"seed-1.8","name":"Seed 1.8","description":"ByteDance Seed model for multimodal reasoning, long-context analysis, and agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-28","last_updated":"2025-12-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":0.25,"output":2,"cache_read":0.05},"canonical_model_id":"bytedance-seed/seed-1-8"},"qwen3.7-max":{"id":"qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":2.5,"output":7.5,"cache_read":0.25,"cache_write":3.125},"canonical_model_id":"alibaba/qwen3.7-max"},"deepseek-v4-pro@eu":{"id":"deepseek-v4-pro@eu","name":"DeepSeek V4 Pro (EU)","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.75,"output":3.5,"cache_read":0.44},"canonical_model_id":"deepseek/deepseek-v4-pro"},"mimo-v2.6-pro":{"id":"mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.43,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"inkling-256k":{"id":"inkling-256k","name":"Inkling 256K","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":1.87,"output":4.68,"cache_read":0.374},"canonical_model_id":"thinkingmachines/inkling"},"devstral-latest":{"id":"devstral-latest","name":"devstral-latest","description":"An enterprise grade text model, that excels at using tools to explore codebases, editing multiple files and power software engineering agents.","family":"devstral","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-27","last_updated":"2026-05-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.44,"output":2.2,"cache_read":0.44}},"kimi-k3@eu":{"id":"kimi-k3@eu","name":"Kimi K3 (EU)","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":3,"output":15,"cache_read":0.45},"canonical_model_id":"moonshotai/kimi-k3"},"gemini-3.1-flash-lite@eu":{"id":"gemini-3.1-flash-lite@eu","name":"Gemini 3.1 Flash Lite (EU)","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.275,"output":1.65,"cache_read":0.0275,"cache_write":0.091663},"canonical_model_id":"google/gemini-3.1-flash-lite"},"mimo-v2.5-pro":{"id":"mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"deepseek-v4-pro-0813@eu":{"id":"deepseek-v4-pro-0813@eu","name":"DeepSeek V4 Pro 0813 (EU)","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":1.75,"output":3.5,"cache_read":0.44},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"gpt-4.1@eu":{"id":"gpt-4.1@eu","name":"GPT-4.1 (EU)","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2.2,"output":8.8,"cache_read":0.55},"canonical_model_id":"openai/gpt-4.1"},"claude-opus-4-7@eu":{"id":"claude-opus-4-7@eu","name":"Claude Opus 4.7 (EU)","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-7"},"mimo-v2.5":{"id":"mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.5"},"mistral-medium-latest":{"id":"mistral-medium-latest","name":"Mistral Medium (latest)","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.44,"output":2.2,"cache_read":0.44},"canonical_model_id":"mistral/mistral-medium-latest"},"gemma-4-26b-a4b-it":{"id":"gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.07,"output":0.34,"cache_read":0.07},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"step-3.7-flash":{"id":"step-3.7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"gemini-3.1-pro-preview":{"id":"gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":4.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":9,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":9}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"mistral-large-4":{"id":"mistral-large-4","name":"Mistral Large 4","description":"Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":262144},"cost":{"input":0.68,"output":2.09,"cache_read":0.07},"canonical_model_id":"mistral/mistral-large-4"},"gpt-5.5-pro":{"id":"gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180},"canonical_model_id":"openai/gpt-5.5-pro"},"gemini-3.5-flash-lite@eu":{"id":"gemini-3.5-flash-lite@eu","name":"Gemini 3.5 Flash Lite (EU)","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.33,"output":2.75,"cache_read":0.033},"canonical_model_id":"google/gemini-3.5-flash-lite"},"grok-4.6":{"id":"grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"cache_write":2,"tiers":[{"input":4,"output":12,"cache_read":1,"cache_write":4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1,"cache_write":4}},"canonical_model_id":"xai/grok-4.6"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":1.5,"output":9,"cache_read":0.15,"cache_write":1.583},"canonical_model_id":"google/gemini-3.5-flash"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"hy3":{"id":"hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.14,"output":0.58,"cache_read":0.035},"canonical_model_id":"tencent/hy3"},"muse-glimmer-30b":{"id":"muse-glimmer-30b","name":"Muse Glimmer 30B","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":20480},"cost":{"input":0,"output":0},"canonical_model_id":"meta/muse-glimmer-30b"},"minimax-m2.7":{"id":"minimax-m2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":1.2},"canonical_model_id":"minimax/MiniMax-M2.7"},"inkling":{"id":"inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":32768},"cost":{"input":1.87,"output":4.68,"cache_read":0.374},"canonical_model_id":"thinkingmachines/inkling"},"gemini-2.5-flash-lite@eu":{"id":"gemini-2.5-flash-lite@eu","name":"Gemini 2.5 Flash-Lite (EU)","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"cache_write":0.18333},"canonical_model_id":"google/gemini-2.5-flash-lite"},"nvidia-nemotron-3-super-120b-a12b":{"id":"nvidia-nemotron-3-super-120b-a12b","name":"Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.1,"output":0.5},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"claude-fable-5.1":{"id":"claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"gemini-3.8-flash":{"id":"gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.8-flash"},"grok-4.5":{"id":"grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"cache_write":2,"tiers":[{"input":4,"output":12,"cache_read":1,"cache_write":4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1,"cache_write":4}},"canonical_model_id":"xai/grok-4.5"},"claude-opus-5@eu":{"id":"claude-opus-5@eu","name":"Claude Opus 5 (EU)","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-5"},"qwen3.6-plus":{"id":"qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625},"canonical_model_id":"alibaba/qwen3.6-plus"},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"laguna-xs.2":{"id":"laguna-xs.2","name":"Laguna XS.2","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"poolside/laguna-xs.2"},"gemini-3.1-flash-lite":{"id":"gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.1-flash-lite"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"seed-2.0-code":{"id":"seed-2.0-code","name":"Seed 2.0 Code","description":"ByteDance Seed coding model for multimodal software engineering and long-running agents","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":131072},"cost":{"input":0.5,"output":3,"cache_read":0.1},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"gpt-5.6-terra@eu":{"id":"gpt-5.6-terra@eu","name":"GPT-5.6 Terra (EU)","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.2,"output":13.2,"cache_read":0.22,"cache_write":2.75,"tiers":[{"input":4.4,"output":19.8,"cache_read":0.44,"cache_write":5.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4.4,"output":19.8,"cache_read":0.44,"cache_write":5.5}},"canonical_model_id":"openai/gpt-5.6-terra"},"gemini-4-argon@eu":{"id":"gemini-4-argon@eu","name":"Gemini 4 Argon (EU)","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2.2,"output":11,"cache_read":0.11},"canonical_model_id":"google/gemini-4-argon"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5.5,"output":33,"cache_read":0.55},"canonical_model_id":"openai/gpt-5.5"},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"ling-2.6-1t":{"id":"ling-2.6-1t","name":"ling-2.6-1t","description":"Inclusion AI ling-2.6-1t","family":"ling","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.3,"output":2.5}},"muse-wonder-1.0":{"id":"muse-wonder-1.0","name":"Muse Wonder","description":"Muse Wonder is a frontier multimodal reasoning model from Meta for personal and professional agents, long-horizon coding, and computer use. It combines Active Memory, which carries relevant context across conversations, with Active Focus, which keeps it working through blockers toward a goal.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":4,"output":20,"cache_read":0.2},"canonical_model_id":"meta/muse-wonder-1.0"},"claude-haiku-4-5@eu":{"id":"claude-haiku-4-5@eu","name":"Claude Haiku 4.5 (latest) (EU)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1.1,"output":5.5,"cache_read":0.11,"cache_write":1.375},"canonical_model_id":"anthropic/claude-haiku-4-5"},"nvidia-nemotron-3-ultra":{"id":"nvidia-nemotron-3-ultra","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.5,"output":2.5},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"qwen3.5-27b":{"id":"qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.26,"output":2.6},"canonical_model_id":"alibaba/qwen3.5-27b"},"gemini-2.5-pro@eu":{"id":"gemini-2.5-pro@eu","name":"Gemini 2.5 Pro (EU)","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":1.25,"output":10,"cache_read":0.31,"cache_write":2.375,"tiers":[{"input":2.5,"output":15,"cache_read":0.62,"cache_write":4.75,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.62,"cache_write":4.75}},"canonical_model_id":"google/gemini-2.5-pro"},"deepseek-v4.1-flash-1017":{"id":"deepseek-v4.1-flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.5,"output":1.5,"cache_read":0.05},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.28,"output":0.56,"cache_read":0.07},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"seed-2.0-pro":{"id":"seed-2.0-pro","name":"Seed 2.0 Pro","description":"Flagship ByteDance Seed 2.0 model for complex multimodal reasoning and long-horizon agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.5,"output":3,"cache_read":0.1},"canonical_model_id":"bytedance-seed/seed-2.0-pro"},"glm-5.2-fast":{"id":"glm-5.2-fast","name":"glm-5.2-fast","description":"GLM-5.2 introduces a robust 1M-token context and advanced, multi-effort coding capabilities to significantly enhance performance on long-horizon tasks. Its new IndexShare architecture and improved MTP layer simultaneously boost efficiency by reducing per-token FLOPs and increasing speculative decoding lengths. A 743B-parameter model in Zhipu AI's GLM series, designed to plan, execute, and iterate autonomously on extended, engineering-grade tasks.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-07-13","last_updated":"2026-07-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2.1,"output":6.6,"cache_read":0.21}},"claude-opus-4-1":{"id":"claude-opus-4-1","name":"Claude Opus 4.1 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1"},"claude-opus-4-5":{"id":"claude-opus-4-5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"qwen3.5-2b":{"id":"qwen3.5-2b","name":"Qwen3.5 2B","description":"Compact Qwen3.5 multimodal model for fast chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-02","last_updated":"2026-03-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":81920},"cost":{"input":0.02,"output":0.1},"canonical_model_id":"alibaba/qwen3.5-2b"},"deepseek-v4.1-flash-1017@eu":{"id":"deepseek-v4.1-flash-1017@eu","name":"DeepSeek V4.1 Flash 1017 (EU)","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.5,"output":1.5,"cache_read":0.05},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"glm-5.1@eu":{"id":"glm-5.1@eu","name":"GLM-5.1 (EU)","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":1.4},"canonical_model_id":"zhipuai/glm-5.1"},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"gemini-3.6-flash":{"id":"gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":1.5,"output":7,"cache_read":0.15},"canonical_model_id":"google/gemini-3.6-flash"},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"gpt-5@eu":{"id":"gpt-5@eu","name":"GPT-5 (EU)","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.375,"output":11,"cache_read":0.1375},"canonical_model_id":"openai/gpt-5"},"claude-fable-5.1@eu":{"id":"claude-fable-5.1@eu","name":"Claude Fable 5.1 (EU)","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":11,"output":55,"cache_read":0.275,"cache_write":13.75},"canonical_model_id":"anthropic/claude-fable-5-1"},"gpt-6.1-sol@eu":{"id":"gpt-6.1-sol@eu","name":"GPT-6.1 Sol (EU)","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.4,"output":12,"cache_read":0.12,"cache_write":3,"tiers":[{"input":4.8,"output":18,"cache_read":0.24,"cache_write":6,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4.8,"output":18,"cache_read":0.24,"cache_write":6}},"canonical_model_id":"openai/gpt-6.1-sol"}}},"fireworks-ai":{"id":"fireworks-ai","env":["FIREWORKS_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.fireworks.ai/inference/v1/","name":"Fireworks AI","doc":"https://fireworks.ai/docs/","models":{"accounts/fireworks/routers/kimi-k3-fast":{"id":"accounts/fireworks/routers/kimi-k3-fast","name":"Kimi K3 Fast","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":4.5,"output":22.5,"cache_read":0.45},"canonical_model_id":"moonshotai/kimi-k3"},"accounts/fireworks/routers/glm-latest":{"id":"accounts/fireworks/routers/glm-latest","name":"GLM Latest","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048573,"output":262144},"experimental":{"modes":{"priority":{"cost":{"input":1.75,"output":5.5,"cache_read":0.325},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"accounts/fireworks/routers/glm-fast-latest":{"id":"accounts/fireworks/routers/glm-fast-latest","name":"GLM 5.3 Fast (Latest)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048572,"output":262144},"cost":{"input":2.1,"output":6.6,"cache_read":0.39},"canonical_model_id":"zhipuai/glm-5.3"},"accounts/fireworks/routers/kimi-latest":{"id":"accounts/fireworks/routers/kimi-latest","name":"Kimi Latest","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"experimental":{"modes":{"priority":{"cost":{"input":3.75,"output":18.75,"cache_read":0.375},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"accounts/fireworks/routers/glm-flash-latest":{"id":"accounts/fireworks/routers/glm-flash-latest","name":"GLM Flash Latest (GLM 5.3 Flash)","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048573,"output":131072},"experimental":{"modes":{"priority":{"cost":{"input":0.1875,"output":0.625,"cache_read":0.0375},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"accounts/fireworks/routers/kimi-fast-latest":{"id":"accounts/fireworks/routers/kimi-fast-latest","name":"Kimi Fast Latest","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":4.5,"output":22.5,"cache_read":0.45},"canonical_model_id":"moonshotai/kimi-k3"},"accounts/fireworks/routers/glm-5p3-fast":{"id":"accounts/fireworks/routers/glm-5p3-fast","name":"GLM 5.3 Fast","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048572,"output":262144},"cost":{"input":2.1,"output":6.6,"cache_read":0.39},"canonical_model_id":"zhipuai/glm-5.3"},"accounts/fireworks/routers/qwen-max-latest":{"id":"accounts/fireworks/routers/qwen-max-latest","name":"Qwen Max Latest (Qwen3.8 Max)","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"experimental":{"modes":{"priority":{"cost":{"input":3,"output":9,"cache_read":0.375},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-max"},"accounts/fireworks/routers/minimax-latest":{"id":"accounts/fireworks/routers/minimax-latest","name":"MiniMax Latest","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"output":512000},"experimental":{"modes":{"priority":{"cost":{"input":0.45,"output":1.8,"cache_read":0.09},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"accounts/fireworks/routers/deepseek-flash-latest":{"id":"accounts/fireworks/routers/deepseek-flash-latest","name":"DeepSeek Flash Latest","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"experimental":{"modes":{"priority":{"cost":{"input":0.375,"output":1.5,"cache_read":0.0075},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"accounts/fireworks/models/gpt-oss-120b":{"id":"accounts/fireworks/models/gpt-oss-120b","name":"GPT OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"status":"deprecated","experimental":{"modes":{"priority":{"cost":{"input":0.18,"output":0.72,"cache_read":0.018},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"openai/gpt-oss-120b"},"accounts/fireworks/models/kimi-k3":{"id":"accounts/fireworks/models/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"experimental":{"modes":{"priority":{"cost":{"input":3.75,"output":18.75,"cache_read":0.375},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"accounts/fireworks/models/deepseek-v4p1-flash-1017":{"id":"accounts/fireworks/models/deepseek-v4p1-flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"experimental":{"modes":{"priority":{"cost":{"input":0.375,"output":1.5,"cache_read":0.0075},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"accounts/fireworks/models/muse-spark-open":{"id":"accounts/fireworks/models/muse-spark-open","name":"Muse Spark Open","description":"Muse Spark Open is an 816B total / 42B active open-weight multimodal reasoning model from Meta for coding and long-horizon agentic work, with 1M-token context.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-open"},"accounts/fireworks/models/nemotron-lightning-3p5-30b-a3b":{"id":"accounts/fireworks/models/nemotron-lightning-3p5-30b-a3b","name":"Nemotron 3.5 Lightning 30B A3B","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","experimental":{"modes":{"priority":{"cost":{"input":0.0625,"output":0.25,"cache_read":0.0125},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.05,"output":0.2,"cache_read":0.01},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"accounts/fireworks/models/qwen3p8-2p4t-a95b":{"id":"accounts/fireworks/models/qwen3p8-2p4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"accounts/fireworks/models/nemotron-3-ultra-nvfp4":{"id":"accounts/fireworks/models/nemotron-3-ultra-nvfp4","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":128000},"status":"deprecated","cost":{"input":0.6,"output":2.4,"cache_read":0.12},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"accounts/fireworks/models/ember-1":{"id":"accounts/fireworks/models/ember-1","name":"Ember-1","description":"Specialized model from Fireworks built on Kimi K3, producing shorter reasoning traces with approximately 40% fewer tokens while maintaining comparable quality","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"fireworks/ember-1"},"accounts/fireworks/models/deepseek-v4p1-flash":{"id":"accounts/fireworks/models/deepseek-v4p1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"experimental":{"modes":{"priority":{"cost":{"input":0.375,"output":1.5,"cache_read":0.0075},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"accounts/fireworks/models/glm-5p3-flash":{"id":"accounts/fireworks/models/glm-5p3-flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048573,"output":131072},"experimental":{"modes":{"priority":{"cost":{"input":0.1875,"output":0.625,"cache_read":0.0375},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"accounts/fireworks/models/inkling":{"id":"accounts/fireworks/models/inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"status":"deprecated","cost":{"input":1,"output":4.05,"cache_read":0.17},"canonical_model_id":"thinkingmachines/inkling"},"accounts/fireworks/models/qwen3p8-max":{"id":"accounts/fireworks/models/qwen3p8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"experimental":{"modes":{"priority":{"cost":{"input":3,"output":9,"cache_read":0.375},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-max"},"accounts/fireworks/models/minimax-m3":{"id":"accounts/fireworks/models/minimax-m3","name":"MiniMax-M3","description":"Fireworks text-only MiniMax coding model for long-context reasoning and agent tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"output":512000},"experimental":{"modes":{"priority":{"cost":{"input":0.45,"output":1.8,"cache_read":0.09},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"accounts/fireworks/models/glm-5p3":{"id":"accounts/fireworks/models/glm-5p3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048573,"output":262144},"experimental":{"modes":{"priority":{"cost":{"input":1.75,"output":5.5,"cache_read":0.325},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"}}},"io-net":{"id":"io-net","env":["IOINTELLIGENCE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.intelligence.io.solutions/api/v1","name":"IO.NET","doc":"https://io.net/docs/guides/intelligence/io-intelligence","models":{"Qwen/Qwen3-235B-A22B-Thinking-2507":{"id":"Qwen/Qwen3-235B-A22B-Thinking-2507","name":"Qwen 3 235B Thinking","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-07-25","last_updated":"2025-07-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":4096},"status":"deprecated","cost":{"input":0.11,"output":0.6,"cache_read":0.055,"cache_write":0.22},"canonical_model_id":"alibaba/qwen3-235b-a22b-thinking-2507"},"Qwen/Qwen3-Next-80B-A3B-Instruct":{"id":"Qwen/Qwen3-Next-80B-A3B-Instruct","name":"Qwen 3 Next 80B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":4096},"cost":{"input":0.11875,"output":1.2625,"cache_read":0.059375},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"Qwen/Qwen2.5-VL-32B-Instruct":{"id":"Qwen/Qwen2.5-VL-32B-Instruct","name":"Qwen 2.5 VL 32B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2024-11-01","last_updated":"2024-11-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":4096},"status":"deprecated","cost":{"input":0.05,"output":0.22,"cache_read":0.025,"cache_write":0.1}},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT-OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":4096},"cost":{"input":0.188,"output":0.7,"cache_read":0.094},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT-OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":4096},"cost":{"input":0.055,"output":0.194,"cache_read":0.0275},"canonical_model_id":"openai/gpt-oss-20b"},"Intel/Qwen3-Coder-480B-A35B-Instruct-int4-mixed-ar":{"id":"Intel/Qwen3-Coder-480B-A35B-Instruct-int4-mixed-ar","name":"Qwen 3 Coder 480B","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":106000,"output":4096},"cost":{"input":0.46125,"output":2.29375,"cache_read":0.230625},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"zai-org/GLM-4.6":{"id":"zai-org/GLM-4.6","name":"GLM 4.6","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":4096},"cost":{"input":0.52,"output":2.0375,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-4.6"},"mistralai/Mistral-Large-Instruct-2411":{"id":"mistralai/Mistral-Large-Instruct-2411","name":"Mistral Large Instruct 2411","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-11-18","last_updated":"2024-11-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":2,"output":6,"cache_read":1,"cache_write":4},"canonical_model_id":"mistral/mistral-large-2411"},"mistralai/Magistral-Small-2506":{"id":"mistralai/Magistral-Small-2506","name":"Magistral Small 2506","description":"Mistral reasoning model for transparent analysis, math, and complex decisions","family":"magistral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-10","last_updated":"2025-06-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0.5,"output":1.5,"cache_read":0.25,"cache_write":1},"canonical_model_id":"mistral/magistral-small-2506"},"mistralai/Mistral-Nemo-Instruct-2407":{"id":"mistralai/Mistral-Nemo-Instruct-2407","name":"Mistral Nemo Instruct 2407","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-05","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.0514,"output":0.082,"cache_read":0.0257},"canonical_model_id":"mistral/mistral-nemo"},"mistralai/Devstral-Small-2505":{"id":"mistralai/Devstral-Small-2505","name":"Devstral Small 2505","description":"Mistral coding agent model for repository tasks and software engineering workflows","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-05-01","last_updated":"2025-05-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0.05,"output":0.22,"cache_read":0.025,"cache_write":0.1}},"moonshotai/Kimi-K2-Instruct-0905":{"id":"moonshotai/Kimi-K2-Instruct-0905","name":"Kimi K2 Instruct","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":4096},"cost":{"input":0.57,"output":2.3,"cache_read":0.285},"canonical_model_id":"moonshotai/kimi-k2-0905"},"moonshotai/Kimi-K2-Thinking":{"id":"moonshotai/Kimi-K2-Thinking","name":"Kimi K2 Thinking","description":"Kimi reasoning model for long-horizon research, planning, and tool use","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":4096},"cost":{"input":0.6,"output":2.5,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8":{"id":"meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8","name":"Llama 4 Maverick 17B 128E Instruct","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":430000,"output":4096},"cost":{"input":0.26875,"output":0.82625,"cache_read":0.134375},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"meta-llama/Llama-3.3-70B-Instruct":{"id":"meta-llama/Llama-3.3-70B-Instruct","name":"Llama 3.3 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.5466,"output":1.0226,"cache_read":0.2733},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"meta-llama/Llama-3.2-90B-Vision-Instruct":{"id":"meta-llama/Llama-3.2-90B-Vision-Instruct","name":"Llama 3.2 90B Vision Instruct","description":"Open Llama multimodal model for image understanding and text reasoning","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":16000,"output":4096},"status":"deprecated","cost":{"input":0.35,"output":0.4,"cache_read":0.175,"cache_write":0.7}},"deepseek-ai/DeepSeek-R1-0528":{"id":"deepseek-ai/DeepSeek-R1-0528","name":"DeepSeek R1","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.523667,"output":2.205333,"cache_read":0.261834},"canonical_model_id":"deepseek/deepseek-r1-0528"}}},"aki-io":{"id":"aki-io","env":["AKI_IO_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://aki.io/v1","name":"AKI.IO","doc":"https://aki.io/docs/","models":{"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.168225,"output":0.616825},"canonical_model_id":"openai/gpt-oss-120b"},"deepseek-v4.1-flash-552b":{"id":"deepseek-v4.1-flash-552b","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":81920},"cost":{"input":0.280375,"output":1.1215,"cache_read":0.11215},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"qwen3.6-35b":{"id":"qwen3.6-35b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32768},"status":"deprecated","cost":{"input":0.168225,"output":0.56075},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"glm5.3-754b":{"id":"glm5.3-754b","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":81920},"cost":{"input":1.1215,"output":3.92525,"cache_read":0.280375},"canonical_model_id":"zhipuai/glm-5.3"},"mistral4-119b":{"id":"mistral4-119b","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":81920},"cost":{"input":0.2243,"output":0.6729},"canonical_model_id":"mistral/mistral-small-2603"},"gemma4-26b":{"id":"gemma4-26b","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32768},"cost":{"input":0.11215,"output":0.56075},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"qwen3.8-27b":{"id":"qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.33645,"output":2.4673,"cache_read":0.11215},"canonical_model_id":"alibaba/qwen3.8-27b"}}},"digitalocean":{"id":"digitalocean","env":["DIGITALOCEAN_ACCESS_TOKEN"],"npm":"@ai-sdk/openai-compatible","api":"https://inference.do-ai.run/v1","name":"DigitalOcean","doc":"https://docs.digitalocean.com/products/gradient-ai-platform/details/models/","models":{"openai-gpt-5.5":{"id":"openai-gpt-5.5","name":"OpenAI GPT-5.5","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"openai-o1":{"id":"openai-o1","name":"OpenAI o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":15,"output":60,"cache_read":7.5},"canonical_model_id":"openai/o1"},"openai-gpt-image-1.5":{"id":"openai-gpt-image-1.5","type":"image","name":"OpenAI GPT Image 1.5","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-11-25","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":0,"output":16384},"cost":{"input":5,"output":10,"cache_read":1},"canonical_model_id":"openai/gpt-image-1.5"},"anthropic-claude-5-sonnet":{"id":"anthropic-claude-5-sonnet","name":"Anthropic Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"openai-gpt-image-1":{"id":"openai-gpt-image-1","type":"image","name":"GPT Image 1","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-04-24","last_updated":"2025-04-24","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5,"output":40,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-1"},"wan2-2-t2v-a14b":{"id":"wan2-2-t2v-a14b","type":"video","name":"Wan2.2-T2V-A14B","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-07-28","last_updated":"2026-04-30","modalities":{"input":["text"],"output":["video"]},"open_weights":true,"limit":{"context":100,"output":1}},"qwen3-embedding-0.6b":{"id":"qwen3-embedding-0.6b","type":"embedding","name":"Qwen3 Embedding 0.6B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-03","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8000,"output":1024},"status":"beta","cost":{"input":0.04,"output":0}},"mistral-nemo-instruct-2407":{"id":"mistral-nemo-instruct-2407","name":"Mistral Nemo Instruct","description":"Legacy model retained for compatibility with older integrations","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"status":"deprecated","cost":{"input":0.3,"output":0.3},"canonical_model_id":"mistral/mistral-nemo"},"qwen-2.5-14b-instruct":{"id":"qwen-2.5-14b-instruct","name":"Qwen 2.5 14B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2024-09-19","last_updated":"2024-09-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072}},"nemotron-3-nano-30b":{"id":"nemotron-3-nano-30b","name":"Nemotron 3 Nano 30B A3B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-06-25","release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"openai-gpt-5.3-codex":{"id":"openai-gpt-5.3-codex","name":"OpenAI GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"anthropic-claude-haiku-4.5":{"id":"anthropic-claude-haiku-4.5","name":"Anthropic Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"qwen3-tts-voicedesign":{"id":"qwen3-tts-voicedesign","type":"speech","name":"Qwen3 TTS VoiceDesign","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-30","modalities":{"input":["text"],"output":["audio"]},"open_weights":true,"limit":{"context":32768,"output":1},"provider":{"npm":"@ai-sdk/openai"}},"all-mini-lm-l6-v2":{"id":"all-mini-lm-l6-v2","type":"embedding","name":"All-MiniLM-L6-v2","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2021-08-30","last_updated":"2021-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256,"output":384},"cost":{"input":0.009,"output":0},"canonical_model_id":"sentence-transformers/all-minilm-l6-v2"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.21},"canonical_model_id":"zhipuai/glm-5.2"},"openai-gpt-4.1":{"id":"openai-gpt-4.1","name":"OpenAI GPT-4.1","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"openai-gpt-5.6-luna":{"id":"openai-gpt-5.6-luna","name":"OpenAI GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04}},"canonical_model_id":"openai/gpt-5.6-luna"},"anthropic-claude-3-opus":{"id":"anthropic-claude-3-opus","name":"Claude 3 Opus","description":"Legacy model retained for compatibility with older integrations","family":"claude-opus","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-08","release_date":"2024-02-29","last_updated":"2024-02-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":4096},"status":"deprecated","cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75}},"nvidia-nemotron-3-super-120b":{"id":"nvidia-nemotron-3-super-120b","name":"NVIDIA Nemotron 3 Super 120B (Public Preview)","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32768},"status":"deprecated","cost":{"input":0.3,"output":0.65,"cache_read":0.06},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"glm-5":{"id":"glm-5","name":"GLM 5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":64000},"status":"deprecated","cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"anthropic-claude-opus-4.7":{"id":"anthropic-claude-opus-4.7","name":"Anthropic Claude Opus 4.7","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"glm-5.3":{"id":"glm-5.3","name":"GLM5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":128000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"gemma-4-31B-it":{"id":"gemma-4-31B-it","name":"Gemma 4","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.18,"output":0.5,"cache_read":0.036},"canonical_model_id":"google/gemma-4-31b-it"},"openai-gpt-5.6-terra":{"id":"openai-gpt-5.6-terra","name":"OpenAI GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"openai/gpt-5.6-terra"},"anthropic-claude-opus-5":{"id":"anthropic-claude-opus-5","name":"Anthropic Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8-Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":262144},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"alibaba/qwen3.8-max"},"openai-gpt-5.4-pro":{"id":"openai-gpt-5.4-pro","name":"OpenAI GPT-5.4 Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.4-pro"},"anthropic-claude-5.5-haiku":{"id":"anthropic-claude-5.5-haiku","name":"Anthropic Claude 5.5 Haiku","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"anthropic/claude-haiku-5-5"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"Deepseek V4 Pro","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":1.74,"output":3.48,"cache_read":0.348},"canonical_model_id":"deepseek/deepseek-v4-pro"},"openai-gpt-oss-120b":{"id":"openai-gpt-oss-120b","name":"OpenAI GPT-oss-120b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.1,"output":0.7,"cache_read":0.02},"canonical_model_id":"openai/gpt-oss-120b"},"openai-gpt-5.4-nano":{"id":"openai-gpt-5.4-nano","name":"OpenAI GPT-5.4 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"multi-qa-mpnet-base-dot-v1":{"id":"multi-qa-mpnet-base-dot-v1","type":"embedding","name":"Multi-QA-mpnet-base-dot-v1","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2021-08-23","last_updated":"2021-08-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512,"output":768},"cost":{"input":0.009,"output":0},"canonical_model_id":"sentence-transformers/multi-qa-mpnet-base-dot-v1"},"deepseek-r1-distill-llama-70b":{"id":"deepseek-r1-distill-llama-70b","name":"DeepSeek R1 Distill Llama 70B","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-01-30","last_updated":"2025-01-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32678,"output":8192},"status":"deprecated","cost":{"input":0.99,"output":0.99}},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"openai-o3-mini":{"id":"openai-o3-mini","name":"OpenAI o3 mini","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"arcee-trinity-large-thinking":{"id":"arcee-trinity-large-thinking","name":"Arcee Trinity Large Thinking (Public Preview)","description":"Reasoning-optimized 398B MoE agent model with extended thinking for long-horizon and multi-turn tool use","family":"trinity","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"cost":{"input":0.25,"output":0.9,"cache_read":0.06},"canonical_model_id":"arcee-ai/trinity-large-thinking"},"nemotron-3-nano-omni":{"id":"nemotron-3-nano-omni","name":"Nemotron 3 Nano Omni","description":"Open Nemotron omni model combining reasoning with text, vision, and audio","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.5,"output":0.9,"cache_read":0.1},"canonical_model_id":"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning"},"openai-gpt-5.1-codex-max":{"id":"openai-gpt-5.1-codex-max","name":"GPT-5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex-max"},"nemotron-3.5-super-vl":{"id":"nemotron-3.5-super-vl","name":"NVIDIA Nemotron 3.5 Super VL","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.3,"output":0.65,"cache_read":0.06},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.5,"output":2.7,"cache_read":0.203},"canonical_model_id":"moonshotai/kimi-k2.5"},"anthropic-claude-4.1-opus":{"id":"anthropic-claude-4.1-opus","name":"Anthropic Claude 4.1 Opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"status":"deprecated","cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1"},"qwen3-coder-flash":{"id":"qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.45,"output":1.7,"cache_read":0.09},"canonical_model_id":"alibaba/qwen3-coder-flash"},"anthropic-claude-3.5-sonnet":{"id":"anthropic-claude-3.5-sonnet","name":"Claude 3.5 Sonnet","description":"Legacy model retained for compatibility with older integrations","family":"claude-sonnet","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-06-20","last_updated":"2024-10-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75}},"gte-large-en-v1.5":{"id":"gte-large-en-v1.5","type":"embedding","name":"GTE Large (v1.5)","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-03-27","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":1024},"cost":{"input":0.09,"output":0}},"llama3.3-70b-instruct":{"id":"llama3.3-70b-instruct","name":"Llama 3.3 Instruct (70B)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0.65,"output":0.65},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"anthropic-claude-fable-5.1":{"id":"anthropic-claude-fable-5.1","name":"Anthropic Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"minimax-m2.5":{"id":"minimax-m2.5","name":"MiniMax M2.5 (Public Preview)","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax-m2.5","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08","release_date":"2026-02-12","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.3,"output":1.2,"cache_read":0.06}},"qwen3.5-397b-a17b":{"id":"qwen3.5-397b-a17b","name":"Qwen 3.5 397B A17B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.55,"output":3.5,"cache_read":0.111},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"e5-large-v2":{"id":"e5-large-v2","type":"embedding","name":"E5 Large v2","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2023-05","last_updated":"2023-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512,"output":1024},"cost":{"input":0.02,"output":0},"canonical_model_id":"intfloat/e5-large-v2"},"openai-gpt-oss-20b":{"id":"openai-gpt-oss-20b","name":"OpenAI GPT-oss-20b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.05,"output":0.45,"cache_read":0.01},"canonical_model_id":"openai/gpt-oss-20b"},"nemotron-3-ultra-550b":{"id":"nemotron-3-ultra-550b","name":"Nemotron 3 Ultra","description":"Flagship Nemotron model for high-throughput reasoning and complex agents","family":"nemotron","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.9,"output":1.7,"cache_read":0.18},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"deepseek-4-flash":{"id":"deepseek-4-flash","name":"Deepseek V4 Flash","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"anthropic-claude-opus-5.5":{"id":"anthropic-claude-opus-5.5","name":"Anthropic Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.4,"cache_write":10,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.4,"cache_write":10}},"canonical_model_id":"anthropic/claude-opus-5-5"},"ministral-3-8b-instruct-2512":{"id":"ministral-3-8b-instruct-2512","name":"Ministral 3 8B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"canonical_model_id":"mistral/ministral-3-8b-instruct-2512"},"anthropic-claude-sonnet-5.5":{"id":"anthropic-claude-sonnet-5.5","name":"Anthropic Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.6"},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":163840},"status":"deprecated","cost":{"input":1.3,"output":4.3,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"mistral-7b-instruct-v0.3":{"id":"mistral-7b-instruct-v0.3","name":"Mistral 7B Instruct v0.3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-05-22","last_updated":"2024-05-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768}},"openai-gpt-6-luna":{"id":"openai-gpt-6-luna","name":"OpenAI GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02}},"canonical_model_id":"openai/gpt-6-luna"},"anthropic-claude-sonnet-4":{"id":"anthropic-claude-sonnet-4","name":"Claude Sonnet 4","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.3,"cache_write":3.75,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.3,"cache_write":3.75}},"canonical_model_id":"anthropic/claude-sonnet-4-0"},"bge-reranker-v2-m3":{"id":"bge-reranker-v2-m3","type":"reranking","name":"BGE Reranker v2 M3","description":"Reranking model for improving retrieval quality in search and recommendation systems","family":"bge","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-03-15","last_updated":"2024-03-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":1},"cost":{"input":0.01,"output":0},"canonical_model_id":"baai/bge-reranker-v2-m3"},"llama3-8b-instruct":{"id":"llama3-8b-instruct","name":"Llama 3.1 Instruct (8B)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.198,"output":0.198},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"mimo-v2.5-pro":{"id":"mimo-v2.5-pro","name":"MiMo V2.5 Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.8,"output":3,"cache_read":0.16},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"anthropic-claude-opus-4.5":{"id":"anthropic-claude-opus-4.5","name":"Anthropic Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"openai-gpt-5.6-sol":{"id":"openai-gpt-5.6-sol","name":"OpenAI GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"tiers":[{"input":8,"output":30,"cache_read":0.8,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8}},"canonical_model_id":"openai/gpt-5.6-sol"},"openai-gpt-6-astra":{"id":"openai-gpt-6-astra","name":"OpenAI GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"tiers":[{"input":20,"output":75,"cache_read":2,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2}},"canonical_model_id":"openai/gpt-6-astra"},"openai-gpt-6-1-sol":{"id":"openai-gpt-6-1-sol","name":"OpenAI GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"tiers":[{"input":4,"output":15,"cache_read":0.2,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2}},"canonical_model_id":"openai/gpt-6.1-sol"},"openai-gpt-4o":{"id":"openai-gpt-4o","name":"OpenAI GPT-4o","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"anthropic-claude-3.5-haiku":{"id":"anthropic-claude-3.5-haiku","name":"Claude 3.5 Haiku","description":"Legacy model retained for compatibility with older integrations","family":"claude-haiku","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07-31","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"status":"deprecated","cost":{"input":0.8,"output":4,"cache_read":0.08,"cache_write":1},"canonical_model_id":"anthropic/claude-3-5-haiku-20241022"},"reflection-beam":{"id":"reflection-beam","name":"Beam","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-10-21","last_updated":"2026-10-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.4,"output":1.2,"cache_read":0.04}},"openai-gpt-image-2":{"id":"openai-gpt-image-2","type":"image","name":"OpenAI GPT Image 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["image","text"]},"open_weights":false,"limit":{"context":0,"output":16384},"cost":{"input":8,"output":30},"canonical_model_id":"openai/gpt-image-2"},"mistral-3-14B":{"id":"mistral-3-14B","name":"Ministral 3 14B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":128000},"cost":{"input":0.2,"output":0.2,"cache_read":0.04},"canonical_model_id":"mistral/ministral-3-14b-instruct-2512"},"deepseek-v3":{"id":"deepseek-v3","name":"DeepSeek V3","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-12-26","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":131072}},"openai-gpt-5":{"id":"openai-gpt-5","name":"OpenAI GPT-5","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"anthropic-claude-4.5-sonnet":{"id":"anthropic-claude-4.5-sonnet","name":"Anthropic Claude 4.5 Sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"openai-gpt-5.2":{"id":"openai-gpt-5.2","name":"OpenAI GPT-5.2","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"anthropic-claude-opus-4.6":{"id":"anthropic-claude-opus-4.6","name":"Anthropic Claude Opus 4.6","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5}},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic-claude-opus-4.8":{"id":"anthropic-claude-opus-4.8","name":"Anthropic Claude Opus 4.8","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"openai-gpt-4o-mini":{"id":"openai-gpt-4o-mini","name":"OpenAI GPT-4o mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"llama-4-maverick":{"id":"llama-4-maverick","name":"Llama 4 Maverick","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.25,"output":0.87,"cache_read":0.05},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"anthropic-claude-fable-5":{"id":"anthropic-claude-fable-5","name":"Anthropic Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"openai-gpt-5.4":{"id":"openai-gpt-5.4","name":"OpenAI GPT-5.4","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"alibaba-qwen3-32b":{"id":"alibaba-qwen3-32b","name":"Qwen3 32B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0.25,"output":0.55},"canonical_model_id":"alibaba/qwen3-32b"},"anthropic-claude-4.6-sonnet":{"id":"anthropic-claude-4.6-sonnet","name":"Anthropic Claude Sonnet 4.6","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic-claude-opus-4":{"id":"anthropic-claude-opus-4","name":"Claude Opus 4","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-0"},"anthropic-claude-3.7-sonnet":{"id":"anthropic-claude-3.7-sonnet","name":"Claude 3.7 Sonnet","description":"Legacy model retained for compatibility with older integrations","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-10-31","release_date":"2025-02-19","last_updated":"2025-02-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-3-7-sonnet-20250219"},"stable-diffusion-3.5-large":{"id":"stable-diffusion-3.5-large","type":"image","name":"Stable Diffusion 3.5 Large","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"stable-diffusion","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-10-22","last_updated":"2026-04-30","modalities":{"input":["text"],"output":["image"]},"open_weights":true,"limit":{"context":256,"output":1}},"openai-gpt-5-nano":{"id":"openai-gpt-5-nano","name":"OpenAI GPT-5 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"bge-m3":{"id":"bge-m3","type":"embedding","name":"BGE M3","description":"Multilingual embedding model combining dense, sparse, and multi-vector retrieval","family":"bge","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-01-30","last_updated":"2024-01-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":1024},"cost":{"input":0.02,"output":0},"canonical_model_id":"baai/bge-m3"},"openai-gpt-5.2-pro":{"id":"openai-gpt-5.2-pro","name":"OpenAI GPT-5.2 Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":21,"output":168},"canonical_model_id":"openai/gpt-5.2-pro"},"nemotron-nano-12b-v2-vl":{"id":"nemotron-nano-12b-v2-vl","name":"Nemotron-nano 12b v2-vl","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"temperature":true,"release_date":"2025-10-28","last_updated":"2025-10-28","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.2,"output":0.6,"cache_read":0.04},"canonical_model_id":"nvidia/nemotron-nano-12b-v2-vl"},"openai-gpt-5-mini":{"id":"openai-gpt-5-mini","name":"OpenAI GPT-5 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"openai-gpt-5.4-mini":{"id":"openai-gpt-5.4-mini","name":"OpenAI GPT-5.4 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"deepseek-3.2":{"id":"deepseek-3.2","name":"Deepseek 3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":163840},"cost":{"input":0.5,"output":1.6,"cache_read":0.15},"canonical_model_id":"deepseek/deepseek-v3.2"},"openai-o3":{"id":"openai-o3","name":"OpenAI o3","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"openai-gpt-6-sol":{"id":"openai-gpt-6-sol","name":"OpenAI GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"tiers":[{"input":4,"output":15,"cache_read":0.4,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4}},"canonical_model_id":"openai/gpt-6-sol"},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"fal-ai/fast-sdxl":{"id":"fal-ai/fast-sdxl","type":"image","name":"Fast SDXL","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"stable-diffusion","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2023-07-26","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["image"]},"open_weights":true,"limit":{"context":0,"output":0}},"fal-ai/elevenlabs/tts/multilingual-v2":{"id":"fal-ai/elevenlabs/tts/multilingual-v2","type":"speech","name":"ElevenLabs Multilingual TTS v2","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"elevenlabs","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2023-08-22","last_updated":"2023-08-22","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0},"canonical_model_id":"elevenlabs/eleven_multilingual_v2"},"fal-ai/flux/schnell":{"id":"fal-ai/flux/schnell","type":"image","name":"FLUX.1 [schnell]","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-08-01","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["image"]},"open_weights":true,"limit":{"context":0,"output":0}},"fal-ai/stable-audio-25/text-to-audio":{"id":"fal-ai/stable-audio-25/text-to-audio","name":"Stable Audio 2.5 (Text-to-Audio)","description":"Speech generation model for controllable voice, narration, and audio delivery","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-10-08","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}}}},"xai":{"id":"xai","env":["XAI_API_KEY"],"npm":"@ai-sdk/xai","name":"xAI","doc":"https://docs.x.ai/docs/models","models":{"grok-build-0.1":{"id":"grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.2,"tiers":[{"input":2,"output":4,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2,"output":4,"cache_read":0.4}}},"grok-4.3":{"id":"grok-4.3","name":"Grok 4.3","description":"xAI's Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"grok-imagine-video-1.5-lite":{"id":"grok-imagine-video-1.5-lite","type":"video","name":"Grok Imagine Video 1.5 Lite","description":"Cost-efficient video model for text-to-video and image-to-video generation","family":"grok","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-01","last_updated":"2026-10-01","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":1024,"output":0},"canonical_model_id":"xai/grok-imagine-video-1.5-lite"},"grok-imagine-image-quality":{"id":"grok-imagine-image-quality","type":"image","name":"Grok Imagine Image Quality","description":"Higher-fidelity Grok Imagine image model for prompt-driven generation, editing, and visual design workflows","family":"grok","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-03","last_updated":"2026-04-03","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":16000,"output":0},"status":"deprecated","canonical_model_id":"xai/grok-imagine-image-quality"},"grok-4.7":{"id":"grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"grok-imagine-image":{"id":"grok-imagine-image","type":"image","name":"Grok Imagine Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"grok","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-01-28","last_updated":"2026-01-28","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":16000,"output":0},"canonical_model_id":"xai/grok-imagine-image"},"grok-imagine-video":{"id":"grok-imagine-video","type":"video","name":"Grok Imagine Video","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"grok","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-01-28","last_updated":"2026-01-28","modalities":{"input":["text","image","video"],"output":["video"]},"open_weights":false,"limit":{"context":1024,"output":0}},"grok-imagine-video-1.5":{"id":"grok-imagine-video-1.5","type":"video","name":"Grok Imagine Video 1.5","description":"Video model for text-to-video, image-to-video, and reference-to-video generation with optional voice references","family":"grok","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-05-30","last_updated":"2026-05-30","modalities":{"input":["text","image","audio"],"output":["video"]},"open_weights":false,"limit":{"context":1024,"output":0},"canonical_model_id":"xai/grok-imagine-video-1.5"},"grok-4.6":{"id":"grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"grok-4.20-0309-non-reasoning":{"id":"grok-4.20-0309-non-reasoning","name":"Grok 4.20 (Non-Reasoning)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"grok-4.5":{"id":"grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.3,"tiers":[{"input":4,"output":12,"cache_read":0.6,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":0.6}},"canonical_model_id":"xai/grok-4.5"},"grok-4.20-0309-reasoning":{"id":"grok-4.20-0309-reasoning","name":"Grok 4.20 (Reasoning)","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"grok-4.20-multi-agent-0309":{"id":"grok-4.20-multi-agent-0309","name":"Grok 4.20 Multi-Agent","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}}}},"qiniu-ai":{"id":"qiniu-ai","env":["QINIU_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.qnaigc.com/v1","name":"Qiniu","doc":"https://developer.qiniu.com/aitokenapi","models":{"qwen3-max":{"id":"qwen3-max","name":"Qwen3 Max","description":"Flagship Qwen3 model for coding agents, complex reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"status":"deprecated","cost":{"input":0.86956522,"output":3.47826087,"tiers":[{"input":1.44927536,"output":5.79710145,"tier":{"type":"context","size":32000}},{"input":2.17391304,"output":8.69565217,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3-max"},"gemini-3.0-flash-preview":{"id":"gemini-3.0-flash-preview","name":"Gemini 3.0 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"status":"deprecated","canonical_model_id":"google/gemini-3-flash-preview"},"qwen3-235b-a22b":{"id":"qwen3-235b-a22b","name":"Qwen 3 235B A22B","description":"Large open Qwen MoE for multilingual reasoning, coding, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"status":"deprecated","cost":{"input":0.28985507,"output":1.15942029},"canonical_model_id":"alibaba/qwen3-235b-a22b"},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"gpt-oss-120b","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","canonical_model_id":"openai/gpt-oss-120b"},"qwen3-vl-30b-a3b-thinking":{"id":"qwen3-vl-30b-a3b-thinking","name":"Qwen3-Vl 30b A3b Thinking","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-09","last_updated":"2026-02-09","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000},"status":"deprecated","cost":{"input":0.10869565,"output":1.08695652}},"claude-4.5-opus":{"id":"claude-4.5-opus","name":"Claude 4.5 Opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":200000},"status":"deprecated","canonical_model_id":"anthropic/claude-opus-4-5"},"gemini-2.5-flash-lite":{"id":"gemini-2.5-flash-lite","name":"Gemini 2.5 Flash Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":64000},"status":"deprecated","canonical_model_id":"google/gemini-2.5-flash-lite"},"qwen3-30b-a3b-instruct-2507":{"id":"qwen3-30b-a3b-instruct-2507","name":"Qwen3 30b A3b Instruct 2507","description":"Updated compact Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"status":"deprecated","cost":{"input":0.10869565,"output":0.43478261},"canonical_model_id":"alibaba/qwen3-30b-a3b-instruct-2507"},"doubao-seed-1.6-flash":{"id":"doubao-seed-1.6-flash","name":"Doubao-Seed 1.6 Flash","description":"Low-latency ByteDance Seed model for high-throughput chat, extraction, and lightweight tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-28","last_updated":"2025-08-28","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"status":"deprecated","cost":{"input":0.02173913,"output":0.2173913,"tiers":[{"input":0.04347826,"output":0.43478261,"tier":{"type":"context","size":32000}},{"input":0.08695652,"output":0.86956522,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-1-6-flash"},"qwen3-30b-a3b-thinking-2507":{"id":"qwen3-30b-a3b-thinking-2507","name":"Qwen3 30b A3b Thinking 2507","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-04","last_updated":"2026-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":126000,"output":32000},"status":"deprecated","cost":{"input":0.10869565,"output":1.08695652}},"gemini-2.0-flash":{"id":"gemini-2.0-flash","name":"Gemini 2.0 Flash","description":"Earlier Gemini Flash workhorse for responsive multimodal apps and tool use","family":"gemini-flash","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-06","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":8192},"status":"deprecated","canonical_model_id":"google/gemini-2.0-flash"},"deepseek-v3.1":{"id":"deepseek-v3.1","name":"DeepSeek-V3.1","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"status":"deprecated","cost":{"input":0.57971014,"output":1.73913043},"canonical_model_id":"deepseek/deepseek-v3.1"},"qwen3-max-preview":{"id":"qwen3-max-preview","name":"Qwen3 Max Preview","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-05","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"status":"deprecated","cost":{"input":0.86956522,"output":3.47826087,"tiers":[{"input":1.44927536,"output":5.79710145,"tier":{"type":"context","size":32000}},{"input":2.17391304,"output":8.69565217,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3-max-preview"},"claude-3.5-sonnet":{"id":"claude-3.5-sonnet","name":"Claude 3.5 Sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-04-30","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"status":"deprecated","canonical_model_id":"anthropic/claude-3-5-sonnet-20241022"},"mimo-v2-flash":{"id":"mimo-v2-flash","name":"Mimo-V2-Flash","description":"MiMo flash model for fast multimodal assistance and agent workflows","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12-01","release_date":"2025-12-16","last_updated":"2026-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"status":"deprecated","cost":{"input":0.1,"output":0.3,"cache_read":0.01},"canonical_model_id":"xiaomi/mimo-v2-flash"},"MiniMax-M1":{"id":"MiniMax-M1","name":"MiniMax M1","description":"Open hybrid-attention MoE reasoning model with a million-token context and an 80K thinking budget","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":80000},"status":"deprecated","cost":{"input":0.57971014,"output":2.31884058},"canonical_model_id":"minimax/minimax-m1-80k"},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":64000},"status":"deprecated","canonical_model_id":"google/gemini-2.5-flash"},"qwen3-235b-a22b-instruct-2507":{"id":"qwen3-235b-a22b-instruct-2507","name":"Qwen3 235b A22B Instruct 2507","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":64000},"status":"deprecated","cost":{"input":0.28985507,"output":1.15942029},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"qwen2.5-vl-72b-instruct":{"id":"qwen2.5-vl-72b-instruct","name":"Qwen 2.5 VL 72B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-01-26","last_updated":"2025-01-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"status":"deprecated","cost":{"input":2.31884058,"output":6.95652174},"canonical_model_id":"alibaba/qwen2-5-vl-72b-instruct"},"claude-4.5-sonnet":{"id":"claude-4.5-sonnet","name":"Claude 4.5 Sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","canonical_model_id":"anthropic/claude-sonnet-4-5"},"qwen3-235b-a22b-thinking-2507":{"id":"qwen3-235b-a22b-thinking-2507","name":"Qwen3 235B A22B Thinking 2507","description":"Updated large open Qwen3 MoE thinking model for reasoning, math, coding, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-25","last_updated":"2025-07-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":4096},"status":"deprecated","cost":{"input":0.28985507,"output":2.89855072},"canonical_model_id":"alibaba/qwen3-235b-a22b-thinking-2507"},"gemini-2.0-flash-lite":{"id":"gemini-2.0-flash-lite","name":"Gemini 2.0 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-06","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":8192},"status":"deprecated","canonical_model_id":"google/gemini-2.0-flash-lite"},"deepseek-r1":{"id":"deepseek-r1","name":"DeepSeek-R1","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"status":"deprecated","cost":{"input":0.57971014,"output":2.31884058},"canonical_model_id":"deepseek/deepseek-r1"},"claude-4.0-opus":{"id":"claude-4.0-opus","name":"Claude 4.0 Opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","canonical_model_id":"anthropic/claude-opus-4-0"},"claude-4.1-opus":{"id":"claude-4.1-opus","name":"Claude 4.1 Opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","canonical_model_id":"anthropic/claude-opus-4-1"},"gemini-2.5-pro":{"id":"gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","canonical_model_id":"google/gemini-2.5-pro"},"glm-4.5-air":{"id":"glm-4.5-air","name":"GLM 4.5 Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":4096},"status":"deprecated","canonical_model_id":"zhipuai/glm-4.5-air"},"gemini-2.5-flash-image":{"id":"gemini-2.5-flash-image","type":"image","name":"Gemini 2.5 Flash Image","description":"Nano Banana image model for fast generation, edits, and character-consistent assets","family":"gemini-flash","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":32768,"output":8192},"status":"deprecated","canonical_model_id":"google/gemini-2.5-flash-image"},"doubao-seed-2.0-code":{"id":"doubao-seed-2.0-code","name":"Doubao Seed 2.0 Code","description":"ByteDance Seed coding model for multimodal software engineering and long-running agents","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"status":"deprecated","cost":{"input":0.46376812,"output":2.31884058,"cache_read":0.09275362,"tiers":[{"input":0.69565217,"output":3.47826087,"cache_read":0.13913043,"tier":{"type":"context","size":32000}},{"input":1.39130435,"output":6.95652174,"cache_read":0.27826087,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"qwen3-coder-480b-a35b-instruct":{"id":"qwen3-coder-480b-a35b-instruct","name":"Qwen3 Coder 480B A35B Instruct","description":"Open Qwen coding heavyweight for repository reasoning and agentic engineering","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":4096},"status":"deprecated","cost":{"input":0.86956522,"output":3.47826087,"tiers":[{"input":1.30434783,"output":5.2173913,"tier":{"type":"context","size":32000}},{"input":2.17391304,"output":8.69565217,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"qwen3.5-397b-a17b":{"id":"qwen3.5-397b-a17b","name":"Qwen3.5 397B A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.17391304,"output":1.04347826,"tiers":[{"input":0.43478261,"output":2.60869565,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"qwen3-next-80b-a3b-instruct":{"id":"qwen3-next-80b-a3b-instruct","name":"Qwen3 Next 80B A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"status":"deprecated","cost":{"input":0.14492754,"output":0.57971014},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"qwen3-30b-a3b":{"id":"qwen3-30b-a3b","name":"Qwen3 30B A3B","description":"Sparse MoE Qwen model with 3B active parameters for efficient chat and reasoning","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40000,"output":4096},"status":"deprecated","cost":{"input":0.10869565,"output":0.43478261},"canonical_model_id":"alibaba/qwen3-30b-a3b"},"qwen3-32b":{"id":"qwen3-32b","name":"Qwen3 32B","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40000,"output":4096},"status":"deprecated","cost":{"input":0.28985507,"output":1.15942029},"canonical_model_id":"alibaba/qwen3-32b"},"qwen-turbo":{"id":"qwen-turbo","name":"Qwen-Turbo","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-11-01","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":4096},"status":"deprecated","cost":{"input":0.04347826,"output":0.08695652},"canonical_model_id":"alibaba/qwen-turbo"},"doubao-seed-2.0-mini":{"id":"doubao-seed-2.0-mini","name":"Doubao Seed 2.0 Mini","description":"Lightweight ByteDance Seed 2.0 model for low-latency multimodal reasoning and high-volume tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.02898551,"output":0.28985507,"cache_read":0.0057971,"tiers":[{"input":0.05797101,"output":0.57971014,"cache_read":0.0115942,"tier":{"type":"context","size":32000}},{"input":0.11594203,"output":1.15942029,"cache_read":0.02318841,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"claude-3.5-haiku":{"id":"claude-3.5-haiku","name":"Claude 3.5 Haiku","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-07-31","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"status":"deprecated","canonical_model_id":"anthropic/claude-3-5-haiku-20241022"},"gpt-oss-20b":{"id":"gpt-oss-20b","name":"gpt-oss-20b","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","canonical_model_id":"openai/gpt-oss-20b"},"glm-4.5":{"id":"glm-4.5","name":"GLM 4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"status":"deprecated","cost":{"input":0.57971014,"output":2.31884058},"canonical_model_id":"zhipuai/glm-4.5"},"gemini-3.0-pro-image-preview":{"id":"gemini-3.0-pro-image-preview","type":"image","name":"Gemini 3.0 Pro Image Preview","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-20","last_updated":"2025-11-20","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":32768,"output":8192},"status":"deprecated","canonical_model_id":"google/gemini-3-pro-image-preview"},"doubao-seed-1.6-thinking":{"id":"doubao-seed-1.6-thinking","name":"Doubao-Seed 1.6 Thinking","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-15","last_updated":"2025-08-15","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"status":"deprecated","cost":{"input":0.11594203,"output":1.15942029,"tiers":[{"input":0.17391304,"output":2.31884058,"tier":{"type":"context","size":32000}},{"input":0.34782609,"output":3.47826087,"tier":{"type":"context","size":128000}}]}},"doubao-seed-2.0-lite":{"id":"doubao-seed-2.0-lite","name":"Doubao Seed 2.0 Lite","description":"Cost-efficient ByteDance Seed 2.0 model for production chat, analysis, and structured generation","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.08695652,"output":0.52173913,"cache_read":0.0173913,"tiers":[{"input":0.13043478,"output":0.7826087,"cache_read":0.02608696,"tier":{"type":"context","size":32000}},{"input":0.26086957,"output":1.56521739,"cache_read":0.05217391,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"doubao-1.5-thinking-pro":{"id":"doubao-1.5-thinking-pro","name":"Doubao 1.5 Thinking Pro","description":"Flagship model for demanding analysis, coding, and production agent workflows","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16000},"status":"deprecated","cost":{"input":0.57971014,"output":2.31884058}},"doubao-1.5-pro-32k":{"id":"doubao-1.5-pro-32k","name":"Doubao 1.5 Pro 32k","description":"Flagship model for demanding analysis, coding, and production agent workflows","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":12000},"status":"deprecated","cost":{"input":0.11594203,"output":0.28985507}},"gemini-3.0-pro-preview":{"id":"gemini-3.0-pro-preview","name":"Gemini 3.0 Pro Preview","description":"Preview Gemini flagship for complex reasoning, coding, and rich multimodal prompts","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"status":"deprecated","canonical_model_id":"google/gemini-3-pro-preview"},"kimi-k2":{"id":"kimi-k2","name":"Kimi K2","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12-31","release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"status":"deprecated","cost":{"input":0.57971014,"output":2.31884058},"canonical_model_id":"moonshotai/kimi-k2"},"claude-3.7-sonnet":{"id":"claude-3.7-sonnet","name":"Claude 3.7 Sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10-31","release_date":"2025-02-19","last_updated":"2025-02-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"status":"deprecated","canonical_model_id":"anthropic/claude-3-7-sonnet-20250219"},"deepseek-v3":{"id":"deepseek-v3","name":"DeepSeek-V3","description":"Open DeepSeek MoE chat model for coding, math, and general reasoning","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2024-12-26","last_updated":"2024-12-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16000},"status":"deprecated","cost":{"input":0.28985507,"output":1.15942029},"canonical_model_id":"deepseek/deepseek-v3"},"doubao-seed-2.0-pro":{"id":"doubao-seed-2.0-pro","name":"Doubao Seed 2.0 Pro","description":"Flagship ByteDance Seed 2.0 model for complex multimodal reasoning and long-horizon agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"status":"deprecated","cost":{"input":0.46376812,"output":2.31884058,"cache_read":0.09275362,"tiers":[{"input":0.69565217,"output":3.47826087,"cache_read":0.13913043,"tier":{"type":"context","size":32000}},{"input":1.39130435,"output":6.95652174,"cache_read":0.27826087,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-pro"},"deepseek-r1-0528":{"id":"deepseek-r1-0528","name":"DeepSeek-R1-0528","description":"May 2025 DeepSeek R1 update with improved mathematics, coding, and reasoning","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"status":"deprecated","cost":{"input":0.57971014,"output":2.31884058},"canonical_model_id":"deepseek/deepseek-r1-0528"},"qwen-vl-max-2025-01-25":{"id":"qwen-vl-max-2025-01-25","name":"Qwen VL-MAX-2025-01-25","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0.43478261,"output":1.30434783}},"doubao-1.5-vision-pro":{"id":"doubao-1.5-vision-pro","name":"Doubao 1.5 Vision Pro","description":"Flagship model for demanding analysis, coding, and production agent workflows","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16000},"status":"deprecated","cost":{"input":0.43478261,"output":1.30434783}},"qwen-max-2025-01-25":{"id":"qwen-max-2025-01-25","name":"Qwen2.5-Max-2025-01-25","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-03","last_updated":"2025-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0.34782609,"output":1.39130435},"canonical_model_id":"alibaba/qwen-max"},"qwen2.5-vl-7b-instruct":{"id":"qwen2.5-vl-7b-instruct","name":"Qwen 2.5 VL 7B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"status":"deprecated"},"kling-v2-6":{"id":"kling-v2-6","type":"video","name":"Kling-V2 6","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-01-13","last_updated":"2026-01-13","modalities":{"input":["text","image","video"],"output":["video"]},"open_weights":false,"limit":{"context":99999999,"output":99999999}},"doubao-seed-1.6":{"id":"doubao-seed-1.6","name":"Doubao-Seed 1.6","description":"ByteDance Seed model for long-context reasoning, instruction following, and tool-assisted tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"status":"deprecated","cost":{"input":0.11594203,"output":1.15942029,"tiers":[{"input":0.17391304,"output":2.31884058,"tier":{"type":"context","size":32000}},{"input":0.34782609,"output":3.47826087,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-1-6"},"claude-4.0-sonnet":{"id":"claude-4.0-sonnet","name":"Claude 4.0 Sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","canonical_model_id":"anthropic/claude-sonnet-4-0"},"deepseek-v3-0324":{"id":"deepseek-v3-0324","name":"DeepSeek-V3-0324","description":"March 2025 checkpoint of DeepSeek-V3 with improved reasoning and coding","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-03-24","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16000},"status":"deprecated","canonical_model_id":"deepseek/deepseek-v3-0324"},"claude-4.5-haiku":{"id":"claude-4.5-haiku","name":"Claude 4.5 Haiku","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","canonical_model_id":"anthropic/claude-haiku-4-5"},"qwen3-next-80b-a3b-thinking":{"id":"qwen3-next-80b-a3b-thinking","name":"Qwen3 Next 80B A3B Thinking","description":"Efficient Qwen thinking model for local reasoning, math, and coding agents","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"status":"deprecated","cost":{"input":0.14492754,"output":1.44927536},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-thinking"},"xiaomi/mimo-v2-flash":{"id":"xiaomi/mimo-v2-flash","name":"Xiaomi/Mimo-V2-Flash","description":"MiMo flash model for fast multimodal assistance and agent workflows","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12-01","release_date":"2025-12-16","last_updated":"2026-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"status":"deprecated","cost":{"input":0.1,"output":0.3,"cache_read":0.01},"canonical_model_id":"xiaomi/mimo-v2-flash"},"meituan/longcat-flash-chat":{"id":"meituan/longcat-flash-chat","name":"Meituan/Longcat-Flash-Chat","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-11-05","last_updated":"2025-11-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":131072},"status":"deprecated"},"meituan/longcat-flash-lite":{"id":"meituan/longcat-flash-lite","name":"Meituan/Longcat-Flash-Lite","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-06","last_updated":"2026-02-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":320000},"status":"deprecated","cost":{"input":0,"output":0}},"x-ai/grok-code-fast-1":{"id":"x-ai/grok-code-fast-1","name":"x-AI/Grok-Code-Fast 1","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-02","last_updated":"2025-09-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":10000},"status":"deprecated","canonical_model_id":"xai/grok-code-fast-1"},"x-ai/grok-4-fast-non-reasoning":{"id":"x-ai/grok-4-fast-non-reasoning","name":"X-Ai/Grok-4-Fast-Non-Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-18","last_updated":"2025-12-18","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"status":"deprecated","canonical_model_id":"xai/grok-4-fast-non-reasoning"},"x-ai/grok-4.1-fast-reasoning":{"id":"x-ai/grok-4.1-fast-reasoning","name":"X-Ai/Grok 4.1 Fast Reasoning","description":"xAI's fast agentic tool-calling model with a 2M context window and built-in reasoning","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":20000000,"output":2000000},"status":"deprecated","canonical_model_id":"xai/grok-4.1-fast-reasoning"},"x-ai/grok-4-fast-reasoning":{"id":"x-ai/grok-4-fast-reasoning","name":"X-Ai/Grok-4-Fast-Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-18","last_updated":"2025-12-18","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"status":"deprecated","canonical_model_id":"xai/grok-4-fast-reasoning"},"x-ai/grok-4.1-fast":{"id":"x-ai/grok-4.1-fast","name":"x-AI/Grok-4.1-Fast","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-11-20","last_updated":"2025-11-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"status":"deprecated"},"x-ai/grok-4.1-fast-non-reasoning":{"id":"x-ai/grok-4.1-fast-non-reasoning","name":"X-Ai/Grok 4.1 Fast Non Reasoning","description":"xAI's fast agentic tool-calling model with a 2M context window; non-reasoning variant for low-latency responses","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"status":"deprecated","canonical_model_id":"xai/grok-4.1-fast"},"x-ai/grok-4-fast":{"id":"x-ai/grok-4-fast","name":"x-AI/Grok-4-Fast","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-20","last_updated":"2025-09-20","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"status":"deprecated"},"openai/gpt-5":{"id":"openai/gpt-5","name":"OpenAI/GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","canonical_model_id":"openai/gpt-5"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"OpenAI/GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","canonical_model_id":"openai/gpt-5.2"},"stepfun-ai/gelab-zero-4b-preview":{"id":"stepfun-ai/gelab-zero-4b-preview","name":"Stepfun-Ai/Gelab Zero 4b Preview","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":4096},"status":"deprecated"},"minimax/minimax-m2.1":{"id":"minimax/minimax-m2.1","name":"Minimax/Minimax-M2.1","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":128000},"status":"deprecated","cost":{"input":0.30434783,"output":1.2173913},"canonical_model_id":"minimax/MiniMax-M2.1"},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"Minimax/Minimax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":128000},"cost":{"input":0.30434783,"output":1.2173913},"canonical_model_id":"minimax/MiniMax-M2.5"},"minimax/minimax-m2.5-highspeed":{"id":"minimax/minimax-m2.5-highspeed","name":"Minimax/Minimax-M2.5 Highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-13","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":128000},"status":"deprecated","cost":{"input":0.60869565,"output":2.43478261},"canonical_model_id":"minimax/MiniMax-M2.5-highspeed"},"minimax/minimax-m2":{"id":"minimax/minimax-m2","name":"Minimax/Minimax-M2","description":"Efficient open MiniMax model built for coding agents and tool-heavy workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"status":"deprecated","cost":{"input":0.30434783,"output":1.2173913},"canonical_model_id":"minimax/MiniMax-M2"},"moonshotai/kimi-k2-0905":{"id":"moonshotai/kimi-k2-0905","name":"Kimi K2 0905","description":"September 2025 Kimi K2 instruction update with a 256K context and improved agentic coding","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":100000},"status":"deprecated","canonical_model_id":"moonshotai/kimi-k2-0905"},"moonshotai/kimi-k2-thinking":{"id":"moonshotai/kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Thinking Kimi model for slower research passes, planning, and hard technical questions","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":100000},"status":"deprecated","cost":{"input":0.57971014,"output":2.31884058},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"moonshotai/kimi-k2.5":{"id":"moonshotai/kimi-k2.5","name":"Moonshotai/Kimi-K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"status":"deprecated","cost":{"input":0.57971014,"output":3.04347826},"canonical_model_id":"moonshotai/kimi-k2.5"},"deepseek/deepseek-v3.2-exp-thinking":{"id":"deepseek/deepseek-v3.2-exp-thinking","name":"DeepSeek/DeepSeek-V3.2-Exp-Thinking","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000},"status":"deprecated","cost":{"input":0.28985507,"output":0.43478261}},"deepseek/deepseek-v3.1-terminus-thinking":{"id":"deepseek/deepseek-v3.1-terminus-thinking","name":"DeepSeek/DeepSeek-V3.1-Terminus-Thinking","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-22","last_updated":"2025-09-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000},"status":"deprecated","cost":{"input":0.57971014,"output":1.73913043}},"deepseek/deepseek-math-v2":{"id":"deepseek/deepseek-math-v2","name":"Deepseek/Deepseek-Math-V2","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-12-04","last_updated":"2025-12-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":160000,"output":160000},"status":"deprecated"},"deepseek/deepseek-v3.1-terminus":{"id":"deepseek/deepseek-v3.1-terminus","name":"DeepSeek/DeepSeek-V3.1-Terminus","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-22","last_updated":"2025-09-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000},"status":"deprecated","cost":{"input":0.57971014,"output":1.73913043}},"deepseek/deepseek-v3.2-exp":{"id":"deepseek/deepseek-v3.2-exp","name":"DeepSeek/DeepSeek-V3.2-Exp","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000},"status":"deprecated","cost":{"input":0.28985507,"output":0.43478261}},"deepseek/deepseek-v3.2-251201":{"id":"deepseek/deepseek-v3.2-251201","name":"Deepseek/DeepSeek-V3.2","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"status":"deprecated","cost":{"input":0.28985507,"output":0.43478261,"cache_read":0.02898551},"canonical_model_id":"deepseek/deepseek-v3.2"},"stepfun/step-3.5-flash":{"id":"stepfun/step-3.5-flash","name":"Stepfun/Step-3.5 Flash","description":"StepFun flash lane for quick multimodal reasoning and coding assistance","family":"step","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"input":256000,"output":4096},"status":"deprecated","canonical_model_id":"stepfun/step-3.5-flash"},"z-ai/glm-4.7":{"id":"z-ai/glm-4.7","name":"Z-Ai/GLM 4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":200000},"status":"deprecated","cost":{"input":0.45913043,"output":1.81565217},"canonical_model_id":"zhipuai/glm-4.7"},"z-ai/glm-5":{"id":"z-ai/glm-5","name":"Z-Ai/GLM 5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.57971014,"output":2.60869565,"tiers":[{"input":0.86956522,"output":3.1884058,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-5"},"z-ai/glm-4.6":{"id":"z-ai/glm-4.6","name":"Z-AI/GLM 4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":200000},"status":"deprecated","cost":{"input":1.04347826,"output":1.82608696},"canonical_model_id":"zhipuai/glm-4.6"},"z-ai/autoglm-phone-9b":{"id":"z-ai/autoglm-phone-9b","name":"Z-Ai/Autoglm Phone 9b","description":"GLM vision model for visual reasoning, documents, and multimodal agents","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":12800,"output":4096},"status":"deprecated"}}},"alibaba-token-plan":{"id":"alibaba-token-plan","env":["ALIBABA_TOKEN_PLAN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://token-plan.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1","name":"Alibaba Token Plan","doc":"https://www.alibabacloud.com/help/en/model-studio/token-plan-overview","models":{"qwen-image-2.0":{"id":"qwen-image-2.0","type":"image","name":"Qwen Image 2.0","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":8192,"output":0},"provider":{"api":"https://token-plan.ap-southeast-1.maas.aliyuncs.com/api/v1"},"cost":{"input":0,"output":0}},"happyhorse-1.1-r2v":{"id":"happyhorse-1.1-r2v","type":"video","name":"HappyHorse 1.1 Reference-to-Video","description":"Video model for reference-guided video generation","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-07-17","last_updated":"2026-07-17","modalities":{"input":["image","text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"npm":"@ai-sdk/alibaba","api":"https://token-plan.ap-southeast-1.maas.aliyuncs.com"},"cost":{"input":0,"output":0}},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen3.8-max-preview":{"id":"qwen3.8-max-preview","name":"Qwen3.8 Max Preview","description":"Preview Qwen flagship for million-token multimodal reasoning and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-19","last_updated":"2026-07-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.8-max-preview"},"qwen3.6-flash":{"id":"qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":131072}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.6-flash"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4-flash"},"wan2.7-image":{"id":"wan2.7-image","type":"image","name":"Wan2.7 Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":8192,"output":0},"provider":{"api":"https://token-plan.ap-southeast-1.maas.aliyuncs.com/api/v1"},"cost":{"input":0,"output":0}},"happyhorse-1.1-i2v":{"id":"happyhorse-1.1-i2v","type":"video","name":"HappyHorse 1.1 Image-to-Video","description":"Video model for image-to-video generation","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-07-17","last_updated":"2026-07-17","modalities":{"input":["image","text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"npm":"@ai-sdk/alibaba","api":"https://token-plan.ap-southeast-1.maas.aliyuncs.com"},"cost":{"input":0,"output":0}},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"glm-5":{"id":"glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":16384},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.8-max"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4-pro"},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.5"},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.7-plus"},"MiniMax-M2.5":{"id":"MiniMax-M2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"input":196601,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"minimax/MiniMax-M2.5"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.6"},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.1"},"qwen3.7-max":{"id":"qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.7-max"},"happyhorse-1.1-t2v":{"id":"happyhorse-1.1-t2v","type":"video","name":"HappyHorse 1.1 Text-to-Video","description":"Video model for prompt-driven text-to-video generation","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-07-17","last_updated":"2026-07-17","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"npm":"@ai-sdk/alibaba","api":"https://token-plan.ap-southeast-1.maas.aliyuncs.com"},"cost":{"input":0,"output":0}},"qwen3.6-plus":{"id":"qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":131072}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.6-plus"},"wan2.7-image-pro":{"id":"wan2.7-image-pro","type":"image","name":"Wan2.7 Image Pro","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":8192,"output":0},"provider":{"api":"https://token-plan.ap-southeast-1.maas.aliyuncs.com/api/v1"},"cost":{"input":0,"output":0}},"deepseek-v4.1-flash-1017":{"id":"deepseek-v4.1-flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"qwen-image-2.0-pro":{"id":"qwen-image-2.0-pro","type":"image","name":"Qwen Image 2.0 Pro","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":8192,"output":0},"provider":{"api":"https://token-plan.ap-southeast-1.maas.aliyuncs.com/api/v1"},"cost":{"input":0,"output":0}},"deepseek-v3.2":{"id":"deepseek-v3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-03","last_updated":"2025-12-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"status":"deprecated","cost":{"input":0,"output":0}},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"}}},"zhipuai":{"id":"zhipuai","env":["ZHIPU_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://open.bigmodel.cn/api/paas/v4","name":"Zhipu AI","doc":"https://docs.bigmodel.cn/cn/guide/start/pricing","models":{"glm-4.5v":{"id":"glm-4.5v","name":"GLM-4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":16384},"cost":{"input":0.29879,"output":0.89637,"cache_read":0.05976,"cache_write":0,"tiers":[{"input":0.59758,"output":1.79274,"cache_read":0.11952,"cache_write":0,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.5v"},"glm-4.7":{"id":"glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.44819,"output":2.09153,"cache_read":0.08964,"cache_write":0,"tiers":[{"input":0.59758,"output":2.39032,"cache_read":0.11952,"cache_write":0,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.7"},"glm-4.6v":{"id":"glm-4.6v","name":"GLM-4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.1494,"output":0.44819,"cache_read":0.02988,"cache_write":0,"tiers":[{"input":0.29879,"output":0.89637,"cache_read":0.05976,"cache_write":0,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.6v"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.19516,"output":4.18306,"cache_read":0.29879,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5v-turbo":{"id":"glm-5v-turbo","name":"GLM-5V-Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":0.74698,"output":3.28669,"cache_read":0.17927,"cache_write":0,"tiers":[{"input":1.04577,"output":3.88427,"cache_read":0.26891,"cache_write":0,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-5v-turbo"},"glm-5":{"id":"glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.59758,"output":2.68911,"cache_read":0.1494,"cache_write":0,"tiers":[{"input":0.89637,"output":3.28669,"cache_read":0.22409,"cache_write":0,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-5"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.19516,"output":4.18306,"cache_read":0.29879,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.11952,"output":0.41831,"cache_read":0.03436,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"glm-4.7-flash":{"id":"glm-4.7-flash","name":"GLM-4.7-Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7-flash"},"glm-4.5-air":{"id":"glm-4.5-air","name":"GLM-4.5-Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.11952,"output":0.89637,"cache_read":0.0239,"cache_write":0,"tiers":[{"input":0.17927,"output":1.19516,"cache_read":0.03585,"cache_write":0,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.5-air"},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.89637,"output":3.58548,"cache_read":0.19421,"cache_write":0,"tiers":[{"input":1.19516,"output":4.18306,"cache_read":0.29879,"cache_write":0,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-5.1"},"glm-4.6":{"id":"glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.6"},"glm-4.5":{"id":"glm-4.5","name":"GLM-4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5"},"glm-4.6v-flash":{"id":"glm-4.6v-flash","name":"GLM-4.6V-Flash","description":"Lightweight GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.6v-flash"},"glm-4.5-flash":{"id":"glm-4.5-flash","name":"GLM-4.5-Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":98304},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5-flash"},"glm-5.3-flashx":{"id":"glm-5.3-flashx","name":"GLM-5.3-FlashX","description":"High-speed GLM-5.3-Flash serving option for coding and agent workflows","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-18","last_updated":"2026-09-18","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.29879,"output":1.04577,"cache_read":0.08516,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"glm-4.7-flashx":{"id":"glm-4.7-flashx","name":"GLM-4.7-FlashX","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.0747,"output":0.44819,"cache_read":0.01494,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7-flashx"}}},"prime":{"id":"prime","env":["PRIME_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.pinference.ai/api/v1","name":"Prime Inference","doc":"https://docs.primeintellect.ai/inference/overview","models":{"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3,"output":15},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-4.6":{"id":"anthropic/claude-opus-4.6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-opus-5.5":{"id":"anthropic/claude-opus-5.5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-sonnet-5.5":{"id":"anthropic/claude-sonnet-5.5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-fable-5.1":{"id":"anthropic/claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-4-7"},"x-ai/grok-4.7":{"id":"x-ai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":450000},"cost":{"input":1.6,"output":4.8},"canonical_model_id":"xai/grok-4.7"},"x-ai/grok-4.6":{"id":"x-ai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":450000},"cost":{"input":2,"output":6},"canonical_model_id":"xai/grok-4.6"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2,"output":10},"canonical_model_id":"openai/gpt-6-sol"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":0.1,"output":0.5},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"gpt-oss-120b","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.35,"output":0.75},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2,"output":10},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT-5.3-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.75,"output":14},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":30,"output":180},"canonical_model_id":"openai/gpt-5.4-pro"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.25,"output":10},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":0.2,"output":1.2},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2.5,"output":15},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 Mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.75,"output":4.5},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":5,"output":30},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 Mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"gpt-oss-20b","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.07,"output":0.3},"canonical_model_id":"openai/gpt-oss-20b"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.25,"output":2},"canonical_model_id":"openai/gpt-5-mini"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1 Nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.1,"output":0.4},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 Nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.2,"output":1.25},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2.5,"output":15},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":5,"output":30},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.25,"output":10},"canonical_model_id":"openai/gpt-5"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.05,"output":0.4},"canonical_model_id":"openai/gpt-5-nano"},"openai/gpt-5.6-luna-pro":{"id":"openai/gpt-5.6-luna-pro","name":"GPT-5.6 Luna Pro","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":1,"output":6},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o-mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-4o-mini"},"openai/gpt-5.6-terra-pro":{"id":"openai/gpt-5.6-terra-pro","name":"GPT-5.6 Terra Pro","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2.5,"output":15},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":1.75,"output":14},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-5.6-sol-pro":{"id":"openai/gpt-5.6-sol-pro","name":"GPT-5.6 Sol Pro","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":5,"output":30},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":10,"output":50},"canonical_model_id":"openai/gpt-6-astra"},"mistralai/mistral-large-2512":{"id":"mistralai/mistral-large-2512","name":"Mistral Large 3 2512","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"mistral/mistral-large-2512"},"mistralai/mistral-nemo":{"id":"mistralai/mistral-nemo","name":"Mistral Nemo","description":"Efficient Mistral-NVIDIA open model for multilingual chat and local deployment","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.165,"output":0.17},"canonical_model_id":"mistral/mistral-nemo"},"mistralai/mistral-small-2603":{"id":"mistralai/mistral-small-2603","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.165,"output":0.66},"canonical_model_id":"mistral/mistral-small-2603"},"mistralai/mixtral-8x22b-instruct":{"id":"mistralai/mixtral-8x22b-instruct","name":"Mixtral 8x22B Instruct","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-01-31","release_date":"2024-04-17","last_updated":"2024-04-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":52428},"cost":{"input":2.2,"output":6.6},"canonical_model_id":"mistral/mixtral-8x22b-instruct"},"qwen/qwen3-vl-30b-a3b-instruct":{"id":"qwen/qwen3-vl-30b-a3b-instruct","name":"Qwen3 VL 30B A3B Instruct","description":"Open vision-language MoE model for image and video understanding, documents, and visual agents","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-04","last_updated":"2025-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.2,"output":0.7},"canonical_model_id":"alibaba/qwen3-vl-30b-a3b-instruct"},"qwen/qwen3-30b-a3b-instruct-2507":{"id":"qwen/qwen3-30b-a3b-instruct-2507","name":"Qwen3 30B A3B Instruct 2507","description":"Updated compact Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.13,"output":0.52},"canonical_model_id":"alibaba/qwen3-30b-a3b-instruct-2507"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":0.99,"output":3.2},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3-vl-235b-a22b-instruct":{"id":"qwen/qwen3-vl-235b-a22b-instruct","name":"Qwen3 VL 235B A22B Instruct","description":"Qwen vision-language instruct model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.3,"output":1.5},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"qwen/qwen3-coder-next":{"id":"qwen/qwen3-coder-next","name":"Qwen3 Coder Next","description":"Open-weight Qwen coding model for agents, repository edits, and multi-turn tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.3,"output":1.5},"canonical_model_id":"alibaba/qwen3-coder-next"},"moonshotai/kimi-k2-0905":{"id":"moonshotai/kimi-k2-0905","name":"Kimi K2 0905","description":"September 2025 Kimi K2 instruction update with a 256K context and improved agentic coding","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":0.6,"output":2.5},"canonical_model_id":"moonshotai/kimi-k2-0905"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":3.45,"output":17.25},"canonical_model_id":"moonshotai/kimi-k3"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash 0423","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943717},"cost":{"input":0.44,"output":1.32},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.3},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro 0423","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":1.91,"output":3.83},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v4.1-flash-1017":{"id":"deepseek/deepseek-v4.1-flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.006,"cache_write":0.3},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.44,"output":1.32},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"meta-llama/llama-3.3-70b-instruct":{"id":"meta-llama/llama-3.3-70b-instruct","name":"Llama 3.3 70B Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":1.04,"output":2.253},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"meta/muse-spark-open":{"id":"meta/muse-spark-open","name":"Muse Spark Open","description":"Muse Spark Open is an 816B total / 42B active open-weight multimodal reasoning model from Meta for coding and long-horizon agentic work, with 1M-token context.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":1.25,"output":4.25},"canonical_model_id":"meta/muse-spark-open"},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":1.54,"output":4.84},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":1.4},"canonical_model_id":"zhipuai/glm-5.3"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03,"cache_write":0.15},"canonical_model_id":"zhipuai/glm-5.3-flash"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.35,"output":6.75},"canonical_model_id":"google/gemini-3.7-flash"},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-4-argon":{"id":"google/gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["audio","image","text","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":2,"output":10},"canonical_model_id":"google/gemini-4-argon"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["audio","image","text","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemma-3-27b-it":{"id":"google/gemma-3-27b-it","name":"Gemma 3 27B","description":"Largest open Gemma 3 instruction model for multilingual text generation and visual understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.119,"output":0.3},"canonical_model_id":"google/gemma-3-27b-it"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5},"canonical_model_id":"google/gemini-3.6-flash"}}},"perplexity-agent":{"id":"perplexity-agent","env":["PERPLEXITY_API_KEY"],"npm":"@ai-sdk/openai","api":"https://api.perplexity.ai/v1","name":"Perplexity Agent","doc":"https://docs.perplexity.ai/docs/agent-api/models","models":{"xai/grok-4-1-fast-non-reasoning":{"id":"xai/grok-4-1-fast-non-reasoning","name":"Grok 4.1 Fast (Non-Reasoning)","description":"xAI's fast agentic tool-calling model with a 2M context window; non-reasoning variant for low-latency responses","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-07","release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"status":"deprecated","cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"xai/grok-4.1-fast"},"xai/grok-4.7":{"id":"xai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"cache_write":2,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"xai/grok-4.6":{"id":"xai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"xai/grok-4.5":{"id":"xai/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.3,"tiers":[{"input":4,"output":12,"cache_read":0.6,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":0.6}},"canonical_model_id":"xai/grok-4.5"},"anthropic/claude-sonnet-4-5":{"id":"anthropic/claude-sonnet-4-5","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-opus-4-7":{"id":"anthropic/claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic/claude-opus-4-6":{"id":"anthropic/claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-opus-5-5":{"id":"anthropic/claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-haiku-4-5":{"id":"anthropic/claude-haiku-4-5","name":"Claude Haiku 4.5","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-haiku-5-5":{"id":"anthropic/claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-fable-5-1":{"id":"anthropic/claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-sonnet-4-6":{"id":"anthropic/claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-sonnet-5-5":{"id":"anthropic/claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-opus-4-5":{"id":"anthropic/claude-opus-4-5","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4}},"canonical_model_id":"openai/gpt-6-sol"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02}},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2}},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"status":"deprecated","cost":{"input":2.5,"output":15,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8}},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2}},"canonical_model_id":"openai/gpt-6-astra"},"perplexity/kimi-k3":{"id":"perplexity/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"perplexity/nemotron-3.5-super-120b-a12b":{"id":"perplexity/nemotron-3.5-super-120b-a12b","name":"Nemotron 3.5 Super 120B A12B","description":"NVIDIA Nemotron 3.5 Super reasoning model (120B total, 12B active) served with text-only input","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.2,"output":0.5,"cache_read":0.04},"canonical_model_id":"nvidia/nemotron-3.5-super-120b-a12b"},"perplexity/glm-5.3":{"id":"perplexity/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"perplexity/glm-5.3-flash":{"id":"perplexity/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"perplexity/sonar":{"id":"perplexity/sonar","name":"Sonar","description":"Fast web-grounded Sonar for current answers, citations, and lightweight retrieval","family":"sonar","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.25,"output":2.5,"cache_read":0.0625},"canonical_model_id":"perplexity/sonar"},"perplexity/deepseek-v4-pro-0813":{"id":"perplexity/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"moonshot-ai/kimi-k3":{"id":"moonshot-ai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshot-ai/kimi-k2.7-code":{"id":"moonshot-ai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"status":"deprecated","cost":{"input":0.13,"output":0.26,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"nvidia/nemotron-3-super-120b-a12b":{"id":"nvidia/nemotron-3-super-120b-a12b","name":"Nemotron 3 Super 120B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2026-02","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32000},"status":"deprecated","cost":{"input":0.25,"output":2.5},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.7-flash"},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"tiers":[{"input":0.5,"output":3,"cache_read":0.05,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":0.5,"output":3,"cache_read":0.05}},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-2.5-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":1.25,"output":10,"cache_read":0.125,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro"},"google/gemini-4-argon":{"id":"google/gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":10,"cache_read":0.1},"canonical_model_id":"google/gemini-4-argon"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"google/gemini-3.6-flash"}}},"ollama-cloud":{"id":"ollama-cloud","env":["OLLAMA_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://ollama.com/v1","name":"Ollama Cloud","doc":"https://docs.ollama.com/cloud","models":{"beam":{"id":"beam","name":"Beam 1.0 501B A23B","description":"Sparse mixture-of-experts reasoning model with 23B active parameters for coding and agentic workflows","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2026-06-30","release_date":"2026-10-05","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"canonical_model_id":"reflection/beam-1.0-501b-a23b"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"deepseek-v4-flash","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"status":"deprecated","cost":{"input":0.22,"output":0.66,"cache_read":0.007},"canonical_model_id":"deepseek/deepseek-v4-flash"},"kimi-k3":{"id":"kimi-k3","name":"kimi-k3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"minimax-m3.1-flash":{"id":"minimax-m3.1-flash","name":"MiniMax-M3.1-Flash","description":"Frontier multimodal coding model with 1M context window and tunable thinking depth","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-19","last_updated":"2026-10-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":512000},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"minimax/MiniMax-M3.1-Flash"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":976000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"nemotron-3-ultra":{"id":"nemotron-3-ultra","name":"nemotron-3-ultra","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":128000},"cost":{"input":0.1,"output":3,"cache_read":0.1},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"muse-spark-open":{"id":"muse-spark-open","name":"Muse Spark Open","description":"Muse Spark Open is an 816B total / 42B active open-weight multimodal reasoning model from Meta for coding and long-horizon agentic work, with 1M-token context.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-open"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"deepseek-v4-pro","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.66,"output":1.98,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-pro"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"kimi-k2.5":{"id":"kimi-k2.5","name":"kimi-k2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","canonical_model_id":"moonshotai/kimi-k2.5"},"deepseek-v4.1-flash:1017":{"id":"deepseek-v4.1-flash:1017","name":"DeepSeek V4.1 Flash 1017","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"mistral-large-3:675b":{"id":"mistral-large-3:675b","name":"mistral-large-3:675b","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"mistral/mistral-large-2512"},"minimax-m2.5":{"id":"minimax-m2.5","name":"minimax-m2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","canonical_model_id":"minimax/MiniMax-M2.5"},"gpt-oss:20b":{"id":"gpt-oss:20b","name":"gpt-oss:20b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.07,"output":0.3,"cache_read":0.035},"canonical_model_id":"openai/gpt-oss-20b"},"deepseek-v4-pro:0813":{"id":"deepseek-v4-pro:0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.66,"output":1.98,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"kimi-k2.6":{"id":"kimi-k2.6","name":"kimi-k2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"gpt-oss:120b":{"id":"gpt-oss:120b","name":"gpt-oss:120b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6,"cache_read":0.014},"canonical_model_id":"openai/gpt-oss-120b"},"glm-5.1":{"id":"glm-5.1","name":"glm-5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"status":"deprecated","cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5.1"},"nemotron-3-super":{"id":"nemotron-3-super","name":"nemotron-3-super","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.015,"output":0.6,"cache_read":0.015},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"gemma4:31b":{"id":"gemma4:31b","name":"gemma4:31b","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.14,"output":0.4,"cache_read":0.05},"canonical_model_id":"google/gemma-4-31b-it"},"mistral-large-4":{"id":"mistral-large-4","name":"Mistral Large 4","description":"Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":262144},"cost":{"input":0.68,"output":2.09,"cache_read":0.07},"canonical_model_id":"mistral/mistral-large-4"},"minimax-m2.7":{"id":"minimax-m2.7","name":"minimax-m2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":196608},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7"},"nemotron-3-nano:30b":{"id":"nemotron-3-nano:30b","name":"nemotron-3-nano:30b","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-06-25","release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.06,"output":0.24},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"qwen3.5:397b":{"id":"qwen3.5:397b","name":"qwen3.5:397b","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":false,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","cost":{"input":0.6,"output":3.6},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"minimax-m3":{"id":"minimax-m3","name":"minimax-m3","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.12},"canonical_model_id":"minimax/MiniMax-M3"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"kimi-k2.7-code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"deepseek-v4-flash:0731":{"id":"deepseek-v4-flash:0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"status":"deprecated","cost":{"input":0.22,"output":0.66,"cache_read":0.007},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"}}},"iflowcn":{"id":"iflowcn","env":["IFLOW_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://apis.iflow.cn/v1","name":"iFlow","doc":"https://platform.iflow.cn/en/docs","models":{"qwen3-max":{"id":"qwen3-max","name":"Qwen3-Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3-max"},"kimi-k2-0905":{"id":"kimi-k2-0905","name":"Kimi-K2-0905","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"moonshotai/kimi-k2-0905"},"qwen3-max-preview":{"id":"qwen3-max-preview","name":"Qwen3-Max-Preview","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-09-05","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3-max-preview"},"qwen3-coder-plus":{"id":"qwen3-coder-plus","name":"Qwen3-Coder-Plus","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3-coder-plus"},"qwen3-235b-a22b-thinking-2507":{"id":"qwen3-235b-a22b-thinking-2507","name":"Qwen3-235B-A22B-Thinking","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-25","last_updated":"2025-07-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3-235b-a22b-thinking-2507"},"qwen3-vl-plus":{"id":"qwen3-vl-plus","name":"Qwen3-VL-Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3-vl-plus"},"deepseek-r1":{"id":"deepseek-r1","name":"DeepSeek-R1","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-r1"},"qwen3-32b":{"id":"qwen3-32b","name":"Qwen3-32B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3-32b"},"qwen3-235b-a22b-instruct":{"id":"qwen3-235b-a22b-instruct","name":"Qwen3-235B-A22B-Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"glm-4.6":{"id":"glm-4.6","name":"GLM-4.6","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-4.6"},"kimi-k2":{"id":"kimi-k2","name":"Kimi-K2","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":64000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"moonshotai/kimi-k2"},"deepseek-v3":{"id":"deepseek-v3","name":"DeepSeek-V3","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-26","last_updated":"2024-12-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-v3"},"deepseek-v3.2":{"id":"deepseek-v3.2","name":"DeepSeek-V3.2-Exp","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":64000},"status":"deprecated","cost":{"input":0,"output":0}},"qwen3-235b":{"id":"qwen3-235b","name":"Qwen3-235B-A22B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3-235b-a22b"}}},"anyapi":{"id":"anyapi","env":["ANYAPI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.anyapi.ai/v1","name":"AnyAPI","doc":"https://docs.anyapi.ai","models":{"xai/grok-4.3":{"id":"xai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"canonical_model_id":"xai/grok-4.3"},"anthropic/claude-sonnet-4-5":{"id":"anthropic/claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-opus-4-7":{"id":"anthropic/claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":30,"output":150,"cache_read":3,"cache_write":37.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic/claude-opus-4-6":{"id":"anthropic/claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024,"max":127999}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":30,"output":150,"cache_read":3,"cache_write":37.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-haiku-4-5":{"id":"anthropic/claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-sonnet-4-6":{"id":"anthropic/claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":5,"output":30,"cache_read":0.5},"provider":{"body":{"service_tier":"priority"}}}}},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"canonical_model_id":"openai/gpt-5-mini"},"openai/o3":{"id":"openai/o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"canonical_model_id":"openai/o3"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"canonical_model_id":"openai/gpt-5"},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"canonical_model_id":"openai/o3-mini"},"openai/o4-mini":{"id":"openai/o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"canonical_model_id":"openai/o4-mini"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"canonical_model_id":"openai/gpt-5.2"},"perplexity/sonar-reasoning-pro":{"id":"perplexity/sonar-reasoning-pro","name":"Sonar Reasoning Pro","description":"Web-grounded Sonar for multi-step research questions that need cited reasoning","family":"sonar-reasoning","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"canonical_model_id":"perplexity/sonar-reasoning-pro"},"perplexity/sonar-pro":{"id":"perplexity/sonar-pro","name":"Sonar Pro","description":"Deeper Sonar search model with broader retrieval and stronger synthesis","family":"sonar-pro","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"canonical_model_id":"perplexity/sonar-pro"},"mistralai/mistral-large-2512":{"id":"mistralai/mistral-large-2512","name":"Mistral Large 3","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"canonical_model_id":"mistral/mistral-large-2512"},"mistralai/devstral-2512":{"id":"mistralai/devstral-2512","name":"Devstral 2","description":"Mistral's coding-agent model for repository work, terminal tasks, and software fixes","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","canonical_model_id":"mistral/devstral-2512"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-r1":{"id":"deepseek/deepseek-r1","name":"DeepSeek Reasoner","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-09","release_date":"2025-12-01","last_updated":"2026-02-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"canonical_model_id":"deepseek/deepseek-reasoner"},"deepseek/deepseek-chat":{"id":"deepseek/deepseek-chat","name":"DeepSeek Chat","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-12-01","last_updated":"2026-02-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"canonical_model_id":"deepseek/deepseek-chat"},"cohere/command-r-plus-08-2024":{"id":"cohere/command-r-plus-08-2024","name":"Command R+","description":"Cohere's RAG workhorse for long-context enterprise search and tool use","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"canonical_model_id":"cohere/command-r-plus-08-2024"},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"canonical_model_id":"google/gemini-2.5-flash-lite"},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"canonical_model_id":"google/gemini-2.5-flash"},"google/gemini-3-pro-preview":{"id":"google/gemini-3-pro-preview","name":"Gemini 3 Pro Preview","description":"Preview Gemini flagship for complex reasoning, coding, and rich multimodal prompts","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"canonical_model_id":"google/gemini-3-pro-preview"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"canonical_model_id":"google/gemini-2.5-pro"}}},"vercel":{"id":"vercel","env":["AI_GATEWAY_API_KEY"],"npm":"@ai-sdk/gateway","name":"Vercel AI Gateway","doc":"https://github.com/vercel/ai/tree/5eb85cc45a259553501f535b8ac79a77d0e79223/packages/gateway","models":{"thinkingmachines/inkling-small":{"id":"thinkingmachines/inkling-small","name":"Inkling Small","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":1000000},"cost":{"input":0.45,"output":1.2,"cache_read":0.1},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/inkling":{"id":"thinkingmachines/inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":4.05,"cache_read":0.17},"canonical_model_id":"thinkingmachines/inkling"},"xiaomi/mimo-v2.6-pro-ultraspeed":{"id":"xiaomi/mimo-v2.6-pro-ultraspeed","name":"MiMo V2.6 Pro UltraSpeed","description":"MiMo pro model for strong multimodal reasoning and agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":4.35,"output":8.7,"cache_read":0.036},"canonical_model_id":"xiaomi/mimo-v2.6-pro-ultraspeed"},"xiaomi/mimo-v2.6-flash":{"id":"xiaomi/mimo-v2.6-flash","name":"MiMo V2.6 Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"xiaomi/mimo-v2.6-pro":{"id":"xiaomi/mimo-v2.6-pro","name":"MiMo V2.6 Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"xiaomi/mimo-v2.5-pro":{"id":"xiaomi/mimo-v2.5-pro","name":"MiMo V2.5 Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":131000},"cost":{"input":0.3045,"output":0.609,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"xiaomi/mimo-v2.5":{"id":"xiaomi/mimo-v2.5","name":"MiMo M2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":131100},"cost":{"input":0.119,"output":0.238,"cache_read":0.0025},"canonical_model_id":"xiaomi/mimo-v2.5"},"meituan/longcat-2.5-preview":{"id":"meituan/longcat-2.5-preview","name":"LongCat 2.5 Preview","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"longcat","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":false,"release_date":"2026-09-25","last_updated":"2026-09-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"meituan/longcat-2.5-preview"},"elorian/glimpse":{"id":"elorian/glimpse","name":"Glimpse","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":false,"release_date":"2026-10-16","last_updated":"2026-10-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":220000,"output":4096},"cost":{"input":0.6,"output":3,"cache_read":0.06}},"heygen/heygen-video-1":{"id":"heygen/heygen-video-1","type":"video","name":"HeyGen Video","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-09","last_updated":"2026-10-09","modalities":{"input":["text","image","video","audio"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"prodia/flux-fast-schnell":{"id":"prodia/flux-fast-schnell","type":"image","name":"Flux Schnell","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-08-02","last_updated":"2026-06-08","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":512,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"reflection/beam":{"id":"reflection/beam","name":"Beam 1.0","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-06-30","release_date":"2026-10-05","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"reflection/beam-1.0-501b-a23b"},"reflection/beam-free":{"id":"reflection/beam-free","name":"Beam 1.0 (Free)","description":"Free provider route for experiments, demos, and cost-sensitive chat workloads","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-06-30","release_date":"2026-10-05","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"reflection/beam-1.0-501b-a23b"},"anthropic/claude-opus-4.8-fast":{"id":"anthropic/claude-opus-4.8-fast","name":"Claude Opus 4.8 (Fast)","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]},{"type":"budget_tokens"}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-haiku-5.5":{"id":"anthropic/claude-haiku-5.5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100001}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-4.6":{"id":"anthropic/claude-opus-4.6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]},{"type":"budget_tokens"}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-opus-5.5":{"id":"anthropic/claude-opus-5.5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-haiku-4.5":{"id":"anthropic/claude-haiku-4.5","name":"Claude Haiku 4.5","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-opus-5-fast":{"id":"anthropic/claude-opus-5-fast","name":"Claude Opus 5 (Fast)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]},{"type":"budget_tokens"}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-sonnet-5.5":{"id":"anthropic/claude-sonnet-5.5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-fable-5.1":{"id":"anthropic/claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-opus-4.5":{"id":"anthropic/claude-opus-4.5","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic/claude-opus-5.5-fast":{"id":"anthropic/claude-opus-5.5-fast","name":"Claude Opus 5.5 (Fast)","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":8,"output":40,"cache_read":0.4,"cache_write":10},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-sonnet-4.5":{"id":"anthropic/claude-sonnet-4.5","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75}},"morph/morph-v3-fast":{"id":"morph/morph-v3-fast","name":"Morph v3 Fast","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"morph","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-08-15","last_updated":"2024-08-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16000,"output":16000},"cost":{"input":0.8,"output":1.2}},"morph/morph-v3-large":{"id":"morph/morph-v3-large","name":"Morph v3 Large","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"morph","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-08-15","last_updated":"2024-08-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":32000},"cost":{"input":0.9,"output":1.9}},"quiverai/arrow-2-telos":{"id":"quiverai/arrow-2-telos","name":"Arrow 2 Telos","description":"High-fidelity SVG generation model for complex vector work and long-context refinement","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"temperature":false,"release_date":"2026-09-16","last_updated":"2026-09-16","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":65536},"cost":{"input":6,"output":30,"cache_read":0.6,"cache_write":7.5},"canonical_model_id":"quiverai/arrow-2-telos"},"quiverai/arrow-2":{"id":"quiverai/arrow-2","name":"Arrow 2","description":"Fast SVG generation model for creation, vectorization, editing, and animation","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"temperature":false,"release_date":"2026-09-16","last_updated":"2026-09-16","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":65536},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5},"canonical_model_id":"quiverai/arrow-2"},"poolside/laguna-s-2.1-free":{"id":"poolside/laguna-s-2.1-free","name":"Laguna S 2.1 Free","description":"Free provider route for experiments, demos, and cost-sensitive chat workloads","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"poolside/laguna-s-2.1"},"poolside/laguna-s-2.1":{"id":"poolside/laguna-s-2.1","name":"Laguna S 2.1","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.09,"output":0.18,"cache_read":0.009},"canonical_model_id":"poolside/laguna-s-2.1"},"topaz/proteus":{"id":"topaz/proteus","type":"video","name":"Proteus","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"topaz/starlight-precise-2.6":{"id":"topaz/starlight-precise-2.6","type":"video","name":"Starlight Precise 2.6","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"topaz/wonder-3.5":{"id":"topaz/wonder-3.5","type":"image","name":"Wonder 3.5","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"openai/gpt-5.6-sol-fast":{"id":"openai/gpt-5.6-sol-fast","name":"GPT 5.6 Sol (Fast)","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":8,"output":40,"cache_read":0.8,"cache_write":10,"tiers":[{"input":16,"output":60,"cache_read":1.6,"cache_write":20,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":16,"output":60,"cache_read":1.6,"cache_write":20}},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-image-2":{"id":"openai/gpt-image-2","type":"image","name":"GPT Image 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"cost":{"input":5,"output":30,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-2"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272001}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272001}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-realtime-1.5":{"id":"openai/gpt-realtime-1.5","type":"realtime","name":"GPT-Realtime-1.5","description":"Realtime speech-to-speech model for voice agents and customer support","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":32000,"output":4096},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"cost":{"input":4,"output":16,"cache_read":0.4,"input_audio":32,"output_audio":64},"canonical_model_id":"openai/gpt-realtime-1.5"},"openai/gpt-4.1-nano-fast":{"id":"openai/gpt-4.1-nano-fast","name":"GPT-4.1 nano (Fast)","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"input":1014808,"output":32768},"cost":{"input":0.2,"output":0.8,"cache_read":0.05},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.1,"output":0.5,"cache_read":0.1},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-realtime-mini":{"id":"openai/gpt-realtime-mini","type":"realtime","name":"GPT-Realtime mini","description":"Cost-efficient realtime speech-to-speech model for voice agents","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-10-01","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":32000,"output":4096},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"cost":{"input":0.6,"output":2.4,"cache_read":0.06,"input_audio":10,"output_audio":20},"canonical_model_id":"openai/gpt-realtime-mini"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272001}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-image-2.5-flare":{"id":"openai/gpt-image-2.5-flare","type":"image","name":"GPT Image 2.5 Flare","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"cost":{"input":5,"output":30,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-2.5-flare"},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT 5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-6-luna-fast":{"id":"openai/gpt-6-luna-fast","name":"GPT-6 Luna (Fast)","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.5,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272001}}],"context_over_200k":{"input":0.4,"output":1.5,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-5-codex":{"id":"openai/gpt-5-codex","name":"GPT-5-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.13},"canonical_model_id":"openai/gpt-5-codex"},"openai/gpt-5-pro":{"id":"openai/gpt-5-pro","name":"GPT-5 pro","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":128000,"output":272000},"cost":{"input":15,"output":120},"canonical_model_id":"openai/gpt-5-pro"},"openai/o4-mini-fast":{"id":"openai/o4-mini-fast","name":"o4-mini (Fast)","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":100000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o4-mini"},"openai/gpt-image-1.5":{"id":"openai/gpt-image-1.5","type":"image","name":"GPT Image 1.5","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-11-25","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"cost":{"input":5,"output":32,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-1.5"},"openai/gpt-4o-fast":{"id":"openai/gpt-4o-fast","name":"GPT-4o (Fast)","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":111616,"output":16384},"cost":{"input":4.25,"output":17,"cache_read":2.125},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-image-1":{"id":"openai/gpt-image-1","type":"image","name":"GPT Image 1","description":"OpenAI image model for production generation, edits, and brand-safe visual workflows","family":"gpt-image","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-04-24","last_updated":"2025-04-24","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"cost":{"input":5,"output":40,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-1"},"openai/gpt-realtime-2":{"id":"openai/gpt-realtime-2","type":"realtime","name":"gpt-realtime-2","description":"Realtime speech-to-speech model with configurable reasoning and reliable tool use for voice agents","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":128000,"output":32000},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"cost":{"input":4,"output":24,"cache_read":0.4,"input_audio":32,"output_audio":64},"canonical_model_id":"openai/gpt-realtime-2"},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT 5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.4-pro"},"openai/gpt-realtime-2.1":{"id":"openai/gpt-realtime-2.1","type":"realtime","name":"gpt-realtime-2.1","description":"Realtime speech-to-speech model with configurable reasoning, tool use, and robust voice-agent behavior","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":128000,"input":96000,"output":32000},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"cost":{"input":4,"output":24,"cache_read":0.4,"input_audio":32,"output_audio":64},"canonical_model_id":"openai/gpt-realtime-2.1"},"openai/gpt-6-astra-fast":{"id":"openai/gpt-6-astra-fast","name":"GPT-6 Astra (Fast)","description":"Fast variant of GPT-6 Astra for low-latency assistance and high-volume workloads.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":20,"output":100,"cache_read":2,"cache_write":25,"tiers":[{"input":40,"output":150,"cache_read":4,"cache_write":50,"tier":{"type":"context","size":272001}}],"context_over_200k":{"input":40,"output":150,"cache_read":4,"cache_write":50}},"canonical_model_id":"openai/gpt-6-astra-fast"},"openai/gpt-realtime-whisper":{"id":"openai/gpt-realtime-whisper","type":"transcription","name":"gpt-realtime-whisper","description":"Streaming speech-to-text model for low-latency transcript deltas from live audio","family":"whisper","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":16000,"output":2000},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"openai/gpt-realtime-whisper"},"openai/text-embedding-3-small":{"id":"openai/text-embedding-3-small","type":"embedding","name":"text-embedding-3-small","description":"Small, efficient OpenAI text embedding model","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"openai/text-embedding-3-small"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT 5.6 Luna","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.1-thinking":{"id":"openai/gpt-5.1-thinking","name":"GPT 5.1 Thinking","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-11-12","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125}},"openai/gpt-5.2-pro":{"id":"openai/gpt-5.2-pro","name":"GPT 5.2 ","description":"Higher-accuracy GPT-5.2 variant for tougher reasoning and review workflows","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":21,"output":168},"canonical_model_id":"openai/gpt-5.2-pro"},"openai/gpt-5.2-fast":{"id":"openai/gpt-5.2-fast","name":"GPT 5.2 (Fast)","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":3.5,"output":28,"cache_read":0.35},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT 5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-oss-safeguard-120b":{"id":"openai/gpt-oss-safeguard-120b","name":"GPT OSS Safeguard 120B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":112000,"output":16000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-safeguard-120b"},"openai/gpt-4o-transcribe":{"id":"openai/gpt-4o-transcribe","type":"transcription","name":"GPT-4o Transcribe","description":"Speech-to-text model powered by GPT-4o for accurate transcription","family":"gpt","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2024-06-01","release_date":"2025-03-20","last_updated":"2025-03-20","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":16000,"output":2000},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"cost":{"input":2.5,"output":10,"input_audio":2.5},"canonical_model_id":"openai/gpt-4o-transcribe"},"openai/gpt-5.4-fast":{"id":"openai/gpt-5.4-fast","name":"GPT 5.4 (Fast)","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.4"},"openai/whisper-1":{"id":"openai/whisper-1","type":"transcription","name":"Whisper","description":"General-purpose speech recognition model for transcription and translation","family":"whisper","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2023-03-01","last_updated":"2023-03-01","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"openai/whisper-1"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT 5.4 Mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/text-embedding-ada-002":{"id":"openai/text-embedding-ada-002","type":"embedding","name":"text-embedding-ada-002","description":"Legacy OpenAI text embedding model","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2022-12-15","last_updated":"2022-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"openai/text-embedding-ada-002"},"openai/gpt-image-2.5-sunburst":{"id":"openai/gpt-image-2.5-sunburst","type":"image","name":"GPT Image 2.5 Sunburst","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"cost":{"input":5,"output":30,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-2.5-sunburst"},"openai/gpt-5.1-codex-max":{"id":"openai/gpt-5.1-codex-max","name":"GPT 5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex-max"},"openai/gpt-oss-safeguard-20b":{"id":"openai/gpt-oss-safeguard-20b","name":"gpt-oss-safeguard-20b","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":112000,"output":16000},"cost":{"input":0.07,"output":0.2},"canonical_model_id":"openai/gpt-oss-safeguard-20b"},"openai/tts-1":{"id":"openai/tts-1","type":"speech","name":"TTS-1","description":"Text-to-speech model optimized for low latency","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2023-11-06","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"openai/tts-1"},"openai/gpt-5-fast":{"id":"openai/gpt-5-fast","name":"GPT-5 (Fast)","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":2.5,"output":20,"cache_read":0.25},"canonical_model_id":"openai/gpt-5"},"openai/gpt-4o-mini-transcribe":{"id":"openai/gpt-4o-mini-transcribe","type":"transcription","name":"GPT-4o mini Transcribe","description":"Speech-to-text model powered by GPT-4o Mini for fast, accurate transcription","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2024-06-01","release_date":"2025-03-20","last_updated":"2025-03-20","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":16000,"output":2000},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"cost":{"input":1.25,"output":5,"input_audio":1.25},"canonical_model_id":"openai/gpt-4o-mini-transcribe"},"openai/gpt-6.1-sol-fast":{"id":"openai/gpt-6.1-sol-fast","name":"GPT-6.1 Sol (Fast)","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.4,"cache_write":10,"tier":{"type":"context","size":272001}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.4,"cache_write":10}},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-5.6-luna-fast":{"id":"openai/gpt-5.6-luna-fast","name":"GPT 5.6 Luna (Fast)","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.4,"output":2.4,"cache_read":0.04,"cache_write":0.5,"tiers":[{"input":0.8,"output":3.6,"cache_read":0.08,"cache_write":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.8,"output":3.6,"cache_read":0.08,"cache_write":1}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-6-sol-fast":{"id":"openai/gpt-6-sol-fast","name":"GPT-6 Sol (Fast)","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272001}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-6-sol"},"openai/gpt-4o-mini-fast":{"id":"openai/gpt-4o-mini-fast","name":"GPT-4o mini (Fast)","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":111616,"output":16384},"cost":{"input":0.25,"output":1,"cache_read":0.125},"canonical_model_id":"openai/gpt-4o-mini"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT 5.6 Sol","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/text-embedding-3-large":{"id":"openai/text-embedding-3-large","type":"embedding","name":"text-embedding-3-large","description":"Most capable OpenAI embedding model for English and non-English text","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"openai/text-embedding-3-large"},"openai/gpt-4.1-fast":{"id":"openai/gpt-4.1-fast","name":"GPT-4.1 (Fast)","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"input":1014808,"output":32768},"cost":{"input":3.5,"output":14,"cache_read":0.875},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-5.5-fast":{"id":"openai/gpt-5.5-fast","name":"GPT 5.5 (Fast)","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":872000,"output":128000},"cost":{"input":12.5,"output":75,"cache_read":1.25},"canonical_model_id":"openai/gpt-5.5"},"openai/o3-fast":{"id":"openai/o3-fast","name":"o3 (Fast)","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":100000,"output":100000},"cost":{"input":3.5,"output":14,"cache_read":0.875},"canonical_model_id":"openai/o3"},"openai/gpt-live-1":{"id":"openai/gpt-live-1","type":"realtime","name":"GPT-Live 1","description":"Full-duplex voice model for natural conversations that delegates reasoning and tools to a backend agent","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"openai/gpt-live-1"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":122880,"output":8192},"cost":{"input":0.03,"output":0.14},"canonical_model_id":"openai/gpt-oss-20b"},"openai/gpt-5.2-codex":{"id":"openai/gpt-5.2-codex","name":"GPT-5.2-Codex","description":"Code-specialist GPT for repository edits, reviews, and long-running software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-codex"},"openai/gpt-5.1-thinking-fast":{"id":"openai/gpt-5.1-thinking-fast","name":"GPT 5.1 Thinking (Fast)","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"release_date":"2025-11-12","last_updated":"2025-11-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":2.5,"output":20,"cache_read":0.25}},"openai/gpt-5.5-pro":{"id":"openai/gpt-5.5-pro","name":"GPT 5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":872000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.5-pro"},"openai/gpt-5.1-codex":{"id":"openai/gpt-5.1-codex","name":"GPT-5.1-Codex","description":"Codex GPT for repository edits, code review, and practical software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.13},"canonical_model_id":"openai/gpt-5.1-codex"},"openai/gpt-5-mini-fast":{"id":"openai/gpt-5-mini-fast","name":"GPT-5 mini (Fast)","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.45,"output":3.6,"cache_read":0.045},"canonical_model_id":"openai/gpt-5-mini"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT 5.4 Nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/o3-pro":{"id":"openai/o3-pro","name":"o3 Pro","description":"High-effort o3 tier for difficult technical reasoning and careful answers","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-05","release_date":"2025-06-10","last_updated":"2025-06-10","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":100000,"output":100000},"cost":{"input":20,"output":80},"canonical_model_id":"openai/o3-pro"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT 5.6 Terra","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-5.4-mini-fast":{"id":"openai/gpt-5.4-mini-fast","name":"GPT 5.4 Mini (Fast)","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.5,"output":9,"cache_read":0.15},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.6-terra-fast":{"id":"openai/gpt-5.6-terra-fast","name":"GPT 5.6 Terra (Fast)","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":24,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":36,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":36,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT 5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":872000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"openai/tts-1-hd":{"id":"openai/tts-1-hd","type":"speech","name":"TTS-1 HD","description":"Text-to-speech model optimized for audio quality","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2023-11-06","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"openai/tts-1-hd"},"openai/gpt-3.5-turbo":{"id":"openai/gpt-3.5-turbo","name":"GPT-3.5 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"input":12289,"output":4096},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"openai/gpt-3.5-turbo"},"openai/gpt-5.1-codex-mini":{"id":"openai/gpt-5.1-codex-mini","name":"GPT-5.1 Codex mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.03},"canonical_model_id":"openai/gpt-5.1-codex-mini"},"openai/gpt-4.1-mini-fast":{"id":"openai/gpt-4.1-mini-fast","name":"GPT-4.1 mini (Fast)","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"input":1014808,"output":32768},"cost":{"input":0.7,"output":2.8,"cache_read":0.175},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-image-1-mini":{"id":"openai/gpt-image-1-mini","type":"image","name":"GPT Image 1 Mini","description":"Cost-efficient GPT Image 1 variant for image generation and editing","family":"gpt-image","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"cost":{"input":2,"output":8,"cache_read":0.2},"canonical_model_id":"openai/gpt-image-1-mini"},"openai/gpt-5.3-codex-fast":{"id":"openai/gpt-5.3-codex-fast","name":"GPT 5.3 Codex (Fast)","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":3.5,"output":28,"cache_read":0.35},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272001}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"openai/o4-mini":{"id":"openai/o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","experimental":{"modes":{"fast":{"cost":{"input":2,"output":8,"cache_read":0.5},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":0.55,"output":2.2,"cache_read":0.1375},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":1.1,"output":4.4,"cache_read":0.275}},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"experimental":{"modes":{"fast":{"cost":{"input":0.25,"output":1,"cache_read":0.125},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.15,"output":0.6,"cache_read":0.075}},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":1.1,"output":4.4,"cache_read":0.55}},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"flex":{"cost":{"input":0.025,"output":0.2,"cache_read":0.0025},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":0.05,"output":0.4,"cache_read":0.005}},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":2.5,"output":20,"cache_read":0.25},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":0.625,"output":5,"cache_read":0.0625},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"openai/o3":{"id":"openai/o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"experimental":{"modes":{"fast":{"cost":{"input":3.5,"output":14,"cache_read":0.875},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":1,"output":4,"cache_read":0.25},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":2,"output":8,"cache_read":0.5}},"openai/gpt-4-turbo":{"id":"openai/gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":10,"output":30}},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"status":"deprecated","experimental":{"modes":{"fast":{"cost":{"input":0.2,"output":0.8,"cache_read":0.05},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.1,"output":0.4,"cache_read":0.025}},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":0.45,"output":3.6,"cache_read":0.045},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":0.125,"output":1,"cache_read":0.0125},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":0.25,"output":2,"cache_read":0.025}},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"experimental":{"modes":{"fast":{"cost":{"input":0.7,"output":2.8,"cache_read":0.175},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.4,"output":1.6,"cache_read":0.1}},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"experimental":{"modes":{"fast":{"cost":{"input":4.25,"output":17,"cache_read":2.125},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2.5,"output":10,"cache_read":1.25}},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"experimental":{"modes":{"fast":{"cost":{"input":3.5,"output":14,"cache_read":0.875},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2,"output":8,"cache_read":0.5}},"openai/o1":{"id":"openai/o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":15,"output":60,"cache_read":7.5}},"inception/mercury-2":{"id":"inception/mercury-2","name":"Mercury 2","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-24","last_updated":"2026-02-24","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":50000},"cost":{"input":0.25,"output":0.75,"cache_read":0.025},"canonical_model_id":"inception/mercury-2"},"inception/mercury-3":{"id":"inception/mercury-3","name":"Mercury 3","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"release_date":"2026-10-19","last_updated":"2026-10-19","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.1,"output":0.35,"cache_read":0.01}},"inception/mercury-coder-small":{"id":"inception/mercury-coder-small","name":"Mercury Coder Small Beta","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","family":"mercury","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-02-26","last_updated":"2025-02-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":16384},"cost":{"input":0.25,"output":1}},"inception/mercury-2.5":{"id":"inception/mercury-2.5","name":"Mercury 2.5","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":260000,"output":65536},"cost":{"input":0.04,"output":0.15,"cache_read":0.004},"canonical_model_id":"inception/mercury-2.5"},"bytedance/seedance-2.0-mini":{"id":"bytedance/seedance-2.0-mini","type":"video","name":"Seedance 2.0 Mini","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"seed","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-06-22","last_updated":"2026-06-22","modalities":{"input":["text","image","video","audio"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"bytedance/seedance-2.0-fast":{"id":"bytedance/seedance-2.0-fast","type":"video","name":"Seedance 2.0 Fast","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"seed","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-14","last_updated":"2026-04-14","modalities":{"input":["text","image","video","audio"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"bytedance/seedream-4.5":{"id":"bytedance/seedream-4.5","type":"image","name":"Seedream 4.5","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-03","last_updated":"2025-11-28","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"bytedance/seedance-2.5":{"id":"bytedance/seedance-2.5","type":"video","name":"Seedance 2.5","description":"ByteDance multimodal audio-video model with up to 30-second single-pass generation, multi-round extension, reference inputs and timestamp-level editing.","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-07-31","last_updated":"2026-10-04","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"bytedance-seed/seedance-2.5"},"bytedance/seed-1.6":{"id":"bytedance/seed-1.6","name":"Seed 1.6","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.25,"output":2,"cache_read":0.05,"tiers":[{"input":0.5,"output":4,"cache_read":0.05,"tier":{"type":"context","size":128001}}]},"canonical_model_id":"bytedance-seed/seed-1-6"},"bytedance/seedream-4.0":{"id":"bytedance/seedream-4.0","type":"image","name":"Seedream 4.0","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-09-09","last_updated":"2025-08-28","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"bytedance/seedance-v1.5-pro":{"id":"bytedance/seedance-v1.5-pro","type":"video","name":"Seedance v1.5 Pro","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"seed","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"bytedance/seed-1.8":{"id":"bytedance/seed-1.8","name":"Seed 1.8","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-28","last_updated":"2025-12-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32768},"cost":{"input":0.25,"output":2,"cache_read":0.05,"tiers":[{"input":0.5,"output":4,"cache_read":0.05,"tier":{"type":"context","size":128001}}]},"canonical_model_id":"bytedance-seed/seed-1-8"},"bytedance/seedance-v1.0-pro-fast":{"id":"bytedance/seedance-v1.0-pro-fast","type":"video","name":"Seedance v1.0 Pro Fast","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"seed","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-10-24","last_updated":"2025-10-31","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"bytedance/seedance-v1.0-pro":{"id":"bytedance/seedance-v1.0-pro","type":"video","name":"Seedance v1.0 Pro","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"seed","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-11","last_updated":"2025-06-11","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"bytedance/seed-2.1-turbo":{"id":"bytedance/seed-2.1-turbo","name":"Seed 2.1 Turbo","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":2.5,"cache_read":0.1},"canonical_model_id":"bytedance-seed/seed-2.1-turbo"},"bytedance/seedance-2.0":{"id":"bytedance/seedance-2.0","type":"video","name":"Seedance 2.0","description":"ByteDance unified multimodal audio-video model supporting text, image, video and audio references, editing, extension and synchronized stereo sound.","family":"seed","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-02-12","last_updated":"2026-10-04","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"bytedance-seed/seedance-2.0"},"bytedance/seedream-5.0-lite":{"id":"bytedance/seedream-5.0-lite","type":"image","name":"Seedream 5.0 Lite","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-02-13","last_updated":"2026-01-28","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"bytedance/seedream-5.0-pro":{"id":"bytedance/seedream-5.0-pro","type":"image","name":"Seedream 5.0 Pro","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-07-11","last_updated":"2026-07-11","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"perplexity/pplx-embed-v1-0.6b":{"id":"perplexity/pplx-embed-v1-0.6b","type":"embedding","name":"Embed v1 0.6b","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"v0","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-02-26","last_updated":"2026-02-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"perplexity/pplx-embed-v1-4b":{"id":"perplexity/pplx-embed-v1-4b","type":"embedding","name":"Embed v1 4b","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-02-26","last_updated":"2026-02-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"perplexity/sonar":{"id":"perplexity/sonar","name":"Sonar","description":"Sonar search model for current answers, retrieval, and citation-backed chat","family":"sonar","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-02","release_date":"2025-02-19","last_updated":"2025-02-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":127000,"output":8000},"cost":{"input":0.25,"output":2.5,"cache_write":0.0625}},"zai/glm-5-turbo":{"id":"zai/glm-5-turbo","name":"GLM 5 Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":202800,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5-turbo"},"zai/glm-4.5v":{"id":"zai/glm-4.5v","name":"GLM 4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":66000,"output":16000},"cost":{"input":0.6,"output":1.8,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5v"},"zai/glm-4.7":{"id":"zai/glm-4.7","name":"GLM 4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":120000},"cost":{"input":0.6,"output":2.2},"canonical_model_id":"zhipuai/glm-4.7"},"zai/glm-5.2":{"id":"zai/glm-5.2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.8,"output":2.55,"cache_read":0.16},"canonical_model_id":"zhipuai/glm-5.2"},"zai/glm-5v-turbo":{"id":"zai/glm-5v-turbo","name":"GLM 5V Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5v-turbo"},"zai/glm-5":{"id":"zai/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202800,"output":131100},"cost":{"input":1,"output":3.2},"canonical_model_id":"zhipuai/glm-5"},"zai/glm-5.3":{"id":"zai/glm-5.3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":1000000},"cost":{"input":1.4,"output":4.4,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.3"},"zai/glm-5.3-flash":{"id":"zai/glm-5.3-flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131000},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai/glm-4.7-flash":{"id":"zai/glm-4.7-flash","name":"GLM 4.7 Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131000},"cost":{"input":0.07,"output":0.4},"canonical_model_id":"zhipuai/glm-4.7-flash"},"zai/glm-4.5-air":{"id":"zai/glm-4.5-air","name":"GLM 4.5 Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":96000},"cost":{"input":0.2,"output":1.1,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-4.5-air"},"zai/glm-5.1":{"id":"zai/glm-5.1","name":"GLM 5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202800,"output":64000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"zai/glm-4.6":{"id":"zai/glm-4.6","name":"GLM 4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":96000},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.6"},"zai/glm-4.5":{"id":"zai/glm-4.5","name":"GLM 4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":96000},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5"},"zai/glm-5.3-fast":{"id":"zai/glm-5.3-fast","name":"GLM 5.3 Fast","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":2.1,"output":6.6,"cache_read":0.21},"canonical_model_id":"zhipuai/glm-5.3"},"zai/glm-5.2-fast":{"id":"zai/glm-5.2-fast","name":"GLM 5.2 Fast","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":2.8,"output":8.8,"cache_read":0.56},"canonical_model_id":"zhipuai/glm-5.2"},"zai/glm-5.3-flashx":{"id":"zai/glm-5.3-flashx","name":"GLM 5.3 FlashX","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.37,"output":1.25,"cache_read":0.075},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai/glm-4.7-flashx":{"id":"zai/glm-4.7-flashx","name":"GLM 4.7 FlashX","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.06,"output":0.4,"cache_read":0.01},"canonical_model_id":"zhipuai/glm-4.7-flashx"},"stealth/glyph-cluster":{"id":"stealth/glyph-cluster","name":"Glyph Cluster","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0,"output":0}},"callstack/apex":{"id":"callstack/apex","name":"Apex","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"release_date":"2026-10-08","last_updated":"2026-10-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.5,"output":3,"cache_read":0.2}},"recraft/recraft-v4-pro":{"id":"recraft/recraft-v4-pro","type":"image","name":"Recraft V4 Pro","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"recraft","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-02-17","last_updated":"2026-02-17","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"recraft/recraft-v4.1-utility-pro":{"id":"recraft/recraft-v4.1-utility-pro","type":"image","name":"Recraft V4.1 Utility Pro","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"recraft","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-05-14","last_updated":"2026-05-14","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"recraft/recraft-v4.1-pro":{"id":"recraft/recraft-v4.1-pro","type":"image","name":"Recraft V4.1 Pro","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"recraft","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-05-14","last_updated":"2026-05-14","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"recraft/recraft-v4.1":{"id":"recraft/recraft-v4.1","type":"image","name":"Recraft V4.1","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"recraft","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-05-14","last_updated":"2026-05-14","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"recraft/recraft-v4":{"id":"recraft/recraft-v4","type":"image","name":"Recraft V4","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"recraft","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-02-17","last_updated":"2026-02-17","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"recraft/recraft-v2":{"id":"recraft/recraft-v2","type":"image","name":"Recraft V2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"recraft","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-03-13","last_updated":"2024-03","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":512,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"recraft/recraft-v3":{"id":"recraft/recraft-v3","type":"image","name":"Recraft V3","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"recraft","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-10-30","last_updated":"2024-10","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":512,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"recraft/recraft-v4.1-flash":{"id":"recraft/recraft-v4.1-flash","type":"image","name":"Recraft V4.1 Flash","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"recraft","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"recraft/recraft-v4.1-utility":{"id":"recraft/recraft-v4.1-utility","type":"image","name":"Recraft V4.1 Utility","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"recraft","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-05-14","last_updated":"2026-05-14","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"inclusionai/ling-3.0-flash-fin":{"id":"inclusionai/ling-3.0-flash-fin","name":"Ling 3.0 Flash Fin","description":"Finance-enhanced model for financial research, multi-step investment workflows, and long-horizon planning and execution","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-08-27","last_updated":"2026-09-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32000},"cost":{"input":0.075,"output":0.22,"cache_read":0.015},"canonical_model_id":"inclusionai/ling-3.0-flash-fin"},"inclusionai/ling-3.1-flash":{"id":"inclusionai/ling-3.1-flash","name":"Ling 3.1 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.3,"output":0.9,"cache_read":0.06},"canonical_model_id":"inclusionai/ling-3.1-flash"},"inclusionai/ling-3.0-flash-sante":{"id":"inclusionai/ling-3.0-flash-sante","name":"Ling 3.0 Flash Sante","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.075,"output":0.22,"cache_read":0.015},"canonical_model_id":"inclusionai/ling-3.0-flash-sante"},"inclusionai/ling-3.0-flash-vl":{"id":"inclusionai/ling-3.0-flash-vl","name":"Ling 3.0 Flash VL","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32000},"cost":{"input":0.075,"output":0.22,"cache_read":0.015},"canonical_model_id":"inclusionai/ling-3.0-flash-vl"},"inclusionai/ling-3.0-flash":{"id":"inclusionai/ling-3.0-flash","name":"Ling 3.0 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-07-23","last_updated":"2026-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32000},"cost":{"input":0.021,"output":0.063,"cache_read":0.0042},"canonical_model_id":"inclusionai/ling-3.0-flash"},"spacexai/grok-4.20-non-reasoning-beta":{"id":"spacexai/grok-4.20-non-reasoning-beta","name":"Grok 4.20 Beta Non-Reasoning","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.4,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"spacexai/grok-build-0.1":{"id":"spacexai/grok-build-0.1","name":"Grok Build 0.1","description":"Grok coding model for agentic engineering, edits, and codebase workflows","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.2,"tiers":[{"input":2,"output":4,"cache_read":0.4,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":2,"output":4,"cache_read":0.4}},"canonical_model_id":"xai/grok-build-0.1"},"spacexai/grok-4.3":{"id":"spacexai/grok-4.3","name":"Grok 4.3","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.3"},"spacexai/grok-imagine-video-1.5-lite":{"id":"spacexai/grok-imagine-video-1.5-lite","type":"video","name":"Grok Imagine Video 1.5 Lite","description":"Cost-efficient video model for text-to-video and image-to-video generation","family":"grok","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-01","last_updated":"2026-10-01","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":1024,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"xai/grok-imagine-video-1.5-lite"},"spacexai/grok-4.1-fast-reasoning":{"id":"spacexai/grok-4.1-fast-reasoning","name":"Grok 4.1 Fast Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"xai/grok-4.1-fast-reasoning"},"spacexai/grok-4.7":{"id":"spacexai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"spacexai/grok-imagine-image":{"id":"spacexai/grok-imagine-image","type":"image","name":"Grok Imagine Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"grok","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-01-28","last_updated":"2026-01-28","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":16000,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"xai/grok-imagine-image"},"spacexai/grok-imagine-image-2.0":{"id":"spacexai/grok-imagine-image-2.0","type":"image","name":"Grok Imagine Image 2.0","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"grok","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-08-07","last_updated":"2026-08-07","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":64000,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"xai/grok-imagine-image-2.0"},"spacexai/grok-imagine-video":{"id":"spacexai/grok-imagine-video","type":"video","name":"Grok Imagine","description":"Video model for text-to-video, image-to-video, video editing and extension with native synchronized audio","family":"grok","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-01-28","last_updated":"2026-01-28","modalities":{"input":["text","image","video"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"xai/grok-imagine-video"},"spacexai/grok-stt":{"id":"spacexai/grok-stt","type":"transcription","name":"Grok STT","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"grok","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"spacexai/grok-tts":{"id":"spacexai/grok-tts","type":"speech","name":"Grok TTS","description":"Convert text into spoken audio with a single API call. The API supports a rich set of expressive voices, inline speech tags for fine-grained delivery control, and output formats from high-fidelity MP3 to telephony-optimized μ-law.","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":15000,"output":15000},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"xai/grok-tts"},"spacexai/grok-voice-think-fast-2.0":{"id":"spacexai/grok-voice-think-fast-2.0","type":"realtime","name":"Grok Voice Think Fast 2.0","description":"Realtime voice model for low-latency spoken conversations","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"spacexai/grok-4.20-non-reasoning":{"id":"spacexai/grok-4.20-non-reasoning","name":"Grok 4.20 Non-Reasoning","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-non-reasoning"},"spacexai/grok-imagine-video-1.5":{"id":"spacexai/grok-imagine-video-1.5","type":"video","name":"Grok Imagine Video 1.5","description":"Video model for text-to-video, image-to-video, and reference-to-video generation with optional voice references","family":"grok","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-05-30","last_updated":"2026-05-30","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":1024,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"xai/grok-imagine-video-1.5"},"spacexai/grok-4.6":{"id":"spacexai/grok-4.6","name":"Grok 4.6","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"spacexai/grok-4.20-multi-agent":{"id":"spacexai/grok-4.20-multi-agent","name":"Grok 4.20 Multi-Agent","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"release_date":"2026-03-10","last_updated":"2026-03-10","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"spacexai/grok-4.1-fast-non-reasoning":{"id":"spacexai/grok-4.1-fast-non-reasoning","name":"Grok 4.1 Fast Non-Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"xai/grok-4.1-fast"},"spacexai/grok-4.5":{"id":"spacexai/grok-4.5","name":"Grok 4.5","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.3,"tiers":[{"input":4,"output":12,"cache_read":0.6,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":4,"output":12,"cache_read":0.6}},"canonical_model_id":"xai/grok-4.5"},"spacexai/grok-4.20-reasoning":{"id":"spacexai/grok-4.20-reasoning","name":"Grok 4.20 Reasoning","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-reasoning"},"spacexai/grok-4.20-multi-agent-beta":{"id":"spacexai/grok-4.20-multi-agent-beta","name":"Grok 4.20 Multi Agent Beta","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"spacexai/grok-4.20-reasoning-beta":{"id":"spacexai/grok-4.20-reasoning-beta","name":"Grok 4.20 Beta Reasoning","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":2000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"alibaba/wan-v2.6-i2v-flash":{"id":"alibaba/wan-v2.6-i2v-flash","type":"video","name":"Wan v2.6 Image-to-Video Flash","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text","image","audio"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"alibaba/qwen-3-30b":{"id":"alibaba/qwen-3-30b","name":"Qwen3-30B-A3B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":16384},"cost":{"input":0.12,"output":0.5},"canonical_model_id":"alibaba/qwen3-30b-a3b"},"alibaba/qwen3-embedding-4b":{"id":"alibaba/qwen3-embedding-4b","type":"embedding","name":"Qwen3 Embedding 4B","description":"Multilingual text embedding model for retrieval, code search, classification, and clustering","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"alibaba/qwen3-embedding-4b"},"alibaba/qwen3-coder-30b-a3b":{"id":"alibaba/qwen3-coder-30b-a3b","name":"Qwen 3 Coder 30B A3B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-31","last_updated":"2025-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"alibaba/wan-v2.5-t2v-preview":{"id":"alibaba/wan-v2.5-t2v-preview","type":"video","name":"Wan v2.5 Text-to-Video Preview","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-09-24","last_updated":"2025-09-24","modalities":{"input":["text","audio"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"alibaba/qwen3.8-flash":{"id":"alibaba/qwen3.8-flash","name":"Qwen 3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":991000,"output":128000},"cost":{"input":0.15,"output":0.47,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"alibaba/wan-v2.6-r2v":{"id":"alibaba/wan-v2.6-r2v","type":"video","name":"Wan v2.6 Reference-to-Video","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text","image","video"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"alibaba/wan-v2.6-r2v-flash":{"id":"alibaba/wan-v2.6-r2v-flash","type":"video","name":"Wan v2.6 Reference-to-Video Flash","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text","image","video"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"alibaba/qwen3-vl-instruct":{"id":"alibaba/qwen3-vl-instruct","name":"Qwen3 VL Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.2,"output":0.88,"cache_read":0.11}},"alibaba/wan-v3.0-video-prime":{"id":"alibaba/wan-v3.0-video-prime","type":"video","name":"Wan v3.0 Video Prime","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text","image","video","audio"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"alibaba/qwen3-embedding-0.6b":{"id":"alibaba/qwen3-embedding-0.6b","type":"embedding","name":"Qwen3 Embedding 0.6B","description":"Compact multilingual text embedding model for retrieval, code search, classification, and clustering","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"alibaba/qwen3-embedding-0.6b"},"alibaba/wan-v2.7-r2v":{"id":"alibaba/wan-v2.7-r2v","type":"video","name":"Wan v2.7 Reference-to-Video","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text","image","video","audio"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"alibaba/qwen-3-235b":{"id":"alibaba/qwen-3-235b","name":"Qwen3 235B A22B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.22,"output":0.88},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"alibaba/qwen3.8-2.4t-a95b":{"id":"alibaba/qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":128000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"alibaba/qwen3.8-max":{"id":"alibaba/qwen3.8-max","name":"Qwen 3.8 Max","description":"Preview Qwen flagship for million-token multimodal reasoning and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"temperature":true,"release_date":"2026-07-19","last_updated":"2026-07-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":128000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-max-preview"},"alibaba/qwen3-embedding-8b":{"id":"alibaba/qwen3-embedding-8b","type":"embedding","name":"Qwen3 Embedding 8B","description":"Multilingual text embedding model for retrieval, code search, classification, and clustering","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"alibaba/qwen3-embedding-8b"},"alibaba/qwen3.6-27b":{"id":"alibaba/qwen3.6-27b","name":"Qwen 3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":131072}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0.6,"output":3.6},"canonical_model_id":"alibaba/qwen3.6-27b"},"alibaba/qwen3.8-omni-flash":{"id":"alibaba/qwen3.8-omni-flash","name":"Qwen 3.8 Omni Flash","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-omni-flash"},"alibaba/qwen-3-32b":{"id":"alibaba/qwen-3-32b","name":"Qwen 3.32B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"alibaba/qwen3-32b"},"alibaba/qwen3.8-max-0902":{"id":"alibaba/qwen3.8-max-0902","name":"Qwen3.8 Max 0902","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":991000,"output":128000},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max-0902"},"alibaba/qwen3.7-plus":{"id":"alibaba/qwen3.7-plus","name":"Qwen 3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]},{"type":"budget_tokens","min":1,"max":262144}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.4,"output":1.6,"cache_read":0.08,"cache_write":0.5,"tiers":[{"input":1.2,"output":4.8,"cache_read":0.24,"cache_write":1.5,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1.2,"output":4.8,"cache_read":0.24,"cache_write":1.5}},"canonical_model_id":"alibaba/qwen3.7-plus"},"alibaba/qwen3.8-max-prime":{"id":"alibaba/qwen3.8-max-prime","name":"Qwen 3.8 Max Prime","description":"High-throughput edition of Qwen3.8 Max for coding, professional work, multimodal understanding, and long-running agent workflows","family":"qwen3.8-max","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":4,"output":12,"cache_read":0.5,"cache_write":5},"canonical_model_id":"alibaba/qwen3.8-max-prime"},"alibaba/qwen3-next-80b-a3b-instruct":{"id":"alibaba/qwen3-next-80b-a3b-instruct","name":"Qwen3 Next 80B A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262114,"output":262114},"cost":{"input":0.15,"output":1.2},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"alibaba/wan-v2.6-i2v":{"id":"alibaba/wan-v2.6-i2v","type":"video","name":"Wan v2.6 Image-to-Video","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text","image","audio"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"alibaba/qwen3.5-flash":{"id":"alibaba/qwen3.5-flash","name":"Qwen 3.5 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]},{"type":"budget_tokens","min":1,"max":81920}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"alibaba/qwen3.5-flash"},"alibaba/wan-v3.0-video":{"id":"alibaba/wan-v3.0-video","type":"video","name":"Wan v3.0 Video","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-08-23","last_updated":"2026-08-23","modalities":{"input":["text","image","video","audio"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"alibaba/qwen3.7-max":{"id":"alibaba/qwen3.7-max","name":"Qwen 3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]},{"type":"budget_tokens","min":1,"max":262144}],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":991000,"output":64000},"cost":{"input":2.5,"output":7.5,"cache_read":0.5,"cache_write":3.125},"canonical_model_id":"alibaba/qwen3.7-max"},"alibaba/wan-v2.7-t2v":{"id":"alibaba/wan-v2.7-t2v","type":"video","name":"Wan v2.7 Text-to-Video","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text","audio"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"alibaba/wan-v2.6-t2v":{"id":"alibaba/wan-v2.6-t2v","type":"video","name":"Wan v2.6 Text-to-Video","description":"Video model for prompt-guided generation, editing, and motion workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text","audio"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"alibaba/qwen3-max-thinking":{"id":"alibaba/qwen3-max-thinking","name":"Qwen 3 Max Thinking","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1,"max":81920}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-23","last_updated":"2025-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":1.2,"output":6,"cache_read":0.24,"tiers":[{"input":2.4,"output":12,"cache_read":0.48,"tier":{"type":"context","size":32001}},{"input":3,"output":15,"cache_read":0.6,"tier":{"type":"context","size":128001}}]}},"alibaba/qwen3.7-flash":{"id":"alibaba/qwen3.7-flash","name":"Qwen 3.7 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":991000,"output":64000},"cost":{"input":0.03,"output":0.13,"cache_read":0.006,"cache_write":0.038,"tiers":[{"input":0.1,"output":0.4,"cache_read":0.02,"cache_write":0.125,"tier":{"type":"context","size":32000}},{"input":0.2,"output":0.8,"cache_read":0.04,"cache_write":0.25,"tier":{"type":"context","size":256000}}]},"canonical_model_id":"alibaba/qwen3.7-flash"},"alibaba/qwen3.8-27b":{"id":"alibaba/qwen3.8-27b","name":"Qwen3.8 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.5,"output":3,"cache_read":0.1,"cache_write":0.625},"canonical_model_id":"alibaba/qwen3.8-27b"},"alibaba/qwen3.6-plus":{"id":"alibaba/qwen3.6-plus","name":"Qwen 3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]},{"type":"budget_tokens","min":1,"max":131072}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625,"tiers":[{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.2,"cache_write":2.5}},"canonical_model_id":"alibaba/qwen3.6-plus"},"alibaba/qwen3-coder":{"id":"alibaba/qwen3-coder","name":"Qwen3 Coder 480B A35B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.22,"output":1.8,"cache_read":0.022,"tiers":[{"input":2.7,"output":13.5,"cache_read":0.54,"tier":{"type":"context","size":32001}},{"input":4.5,"output":22.5,"cache_read":0.9,"tier":{"type":"context","size":128001}}]},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"alibaba/qwen3-coder-next":{"id":"alibaba/qwen3-coder-next","name":"Qwen3 Coder Next","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.5,"output":1.2},"canonical_model_id":"alibaba/qwen3-coder-next"},"alibaba/qwen3.5-plus":{"id":"alibaba/qwen3.5-plus","name":"Qwen 3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]},{"type":"budget_tokens","min":1,"max":81920}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.4,"output":2.4,"cache_read":0.04,"cache_write":0.5,"tiers":[{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":256001}}],"context_over_200k":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625}},"canonical_model_id":"alibaba/qwen3.5-plus"},"alibaba/qwen-3-14b":{"id":"alibaba/qwen-3-14b","name":"Qwen3-14B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":40960,"output":16384},"cost":{"input":0.12,"output":0.24}},"alibaba/qwen3-next-80b-a3b-thinking":{"id":"alibaba/qwen3-next-80b-a3b-thinking","name":"Qwen3 Next 80B A3B Thinking","description":"Efficient Qwen thinking model for local reasoning, math, and coding agents","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.15,"output":1.2},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-thinking"},"mistral/ministral-8b":{"id":"mistral/ministral-8b","name":"Ministral 8B (latest)","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-10-16","last_updated":"2024-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":4000},"cost":{"input":0.15,"output":0.15,"cache_read":0.015}},"mistral/mistral-nemo":{"id":"mistral/mistral-nemo","name":"Mistral Nemo","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.029,"output":0.03},"canonical_model_id":"mistral/mistral-nemo"},"mistral/ministral-3b":{"id":"mistral/ministral-3b","name":"Ministral 3B (latest)","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-10-16","last_updated":"2024-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":4000},"cost":{"input":0.1,"output":0.1,"cache_read":0.01}},"mistral/mistral-embed":{"id":"mistral/mistral-embed","type":"embedding","name":"Mistral Embed","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"mistral-embed","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2023-12-11","last_updated":"2023-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8000,"output":3072},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"mistral/mistral-embed"},"mistral/voxtral-mini-transcribe-3":{"id":"mistral/voxtral-mini-transcribe-3","type":"transcription","name":"Voxtral Mini Transcribe 3","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"mistral","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-20","last_updated":"2026-10-20","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"mistral/mistral-medium-3.5":{"id":"mistral/mistral-medium-3.5","name":"Mistral Medium Latest","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":256000},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"mistral/mistral-medium-3-5"},"mistral/codestral-embed":{"id":"mistral/codestral-embed","type":"embedding","name":"Codestral Embed","description":"Embedding model for code search, retrieval, and code-aware RAG pipelines","family":"codestral-embed","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":3072},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"mistral/codestral-embed-2505"},"mistral/mistral-large-3":{"id":"mistral/mistral-large-3","name":"Mistral Large 3","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.5,"output":1.5,"cache_read":0.05},"canonical_model_id":"mistral/mistral-large-2512"},"mistral/mistral-large-4":{"id":"mistral/mistral-large-4","name":"Mistral Large 4","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":262144},"cost":{"input":1.36,"output":4.18,"cache_read":0.14},"canonical_model_id":"mistral/mistral-large-4"},"mistral/voxtral-mini-tts-3":{"id":"mistral/voxtral-mini-tts-3","type":"speech","name":"Voxtral TTS 3","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mistral","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-20","last_updated":"2026-10-20","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"mistral/voxtral-small-transcribe-3":{"id":"mistral/voxtral-small-transcribe-3","type":"transcription","name":"Voxtral Small Transcribe 3","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"mistral","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-20","last_updated":"2026-10-20","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"mistral/ministral-14b":{"id":"mistral/ministral-14b","name":"Ministral 14B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.2,"output":0.2,"cache_read":0.02},"canonical_model_id":"mistral/ministral-14b"},"mistral/codestral":{"id":"mistral/codestral","name":"Codestral (latest)","description":"Mistral code model for completions, refactors, and developer IDE workflows","family":"codestral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-05-29","last_updated":"2025-01-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.3,"output":0.9,"cache_read":0.03},"canonical_model_id":"mistral/codestral-latest"},"mistral/mistral-small":{"id":"mistral/mistral-small","name":"Mistral Small (latest)","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":4000},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"mistral/mistral-small-latest"},"amazon/nova-2-lite":{"id":"amazon/nova-2-lite","name":"Nova 2 Lite","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-10","release_date":"2025-12-02","last_updated":"2025-12-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.3,"output":2.5,"cache_read":0.075},"canonical_model_id":"amazon/nova-2-lite"},"amazon/titan-embed-text-v2":{"id":"amazon/titan-embed-text-v2","type":"embedding","name":"Titan Text Embeddings V2","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"titan-embed","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-04-30","last_updated":"2024-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"amazon/nova-lite":{"id":"amazon/nova-lite","name":"Nova Lite","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.06,"output":0.24,"cache_read":0.015,"cache_write":0.06},"canonical_model_id":"amazon/nova-lite"},"amazon/nova-micro":{"id":"amazon/nova-micro","name":"Nova Micro","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-micro","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":10000},"cost":{"input":0.035,"output":0.14,"cache_read":0.00875,"cache_write":0.035},"canonical_model_id":"amazon/nova-micro"},"amazon/nova-pro":{"id":"amazon/nova-pro","name":"Nova Pro","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.8,"output":3.2,"cache_read":0.2,"cache_write":0.8},"canonical_model_id":"amazon/nova-pro"},"mixedbread/toast-1":{"id":"mixedbread/toast-1","name":"Toast 1","description":"Specialized search model for knowledge-intensive questions, multi-step retrieval, and evidence synthesis","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":4000},"cost":{"input":0.3,"output":0.72,"cache_read":0.036},"canonical_model_id":"mixedbread/toast-1"},"sakana/fugu-max":{"id":"sakana/fugu-max","name":"Fugu Max","description":"Multi-agent model for routing expert agents across complex analytical tasks","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"sakana/fugu-max"},"sakana/fugu-ultra":{"id":"sakana/fugu-ultra","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272001}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"sakana/fugu-ultra"},"sakana/namazu":{"id":"sakana/namazu","name":"Sakana Namazu","description":"Multi-agent model for routing expert agents across complex analytical tasks","family":"sakana-namazu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.95,"output":4,"cache_read":0.15},"canonical_model_id":"sakana/sakana-namazu"},"sakana/fugu-ultra-v2":{"id":"sakana/fugu-ultra-v2","name":"Fugu Ultra v2","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-08-28","release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272001}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"sakana/fugu-ultra-v2"},"minimax/minimax-m2.1":{"id":"minimax/minimax-m2.1","name":"MiniMax M2.1","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.1"},"minimax/minimax-m3.1-flash":{"id":"minimax/minimax-m3.1-flash","name":"MiniMax-M3.1-Flash","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-10-19","last_updated":"2026-10-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":524288},"cost":{"input":0,"output":0},"canonical_model_id":"minimax/MiniMax-M3.1-Flash"},"minimax/minimax-h3":{"id":"minimax/minimax-h3","type":"video","name":"MiniMax H3","description":"MiniMax general-purpose video model with multimodal references and synchronized stereo audio. Open H3-Base checkpoints; Context-IR and 2K regeneration are not included in the initial weights release.","family":"minimax","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-07-31","last_updated":"2026-10-04","modalities":{"input":["text","image"],"output":["video"]},"open_weights":true,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"minimax/MiniMax-H3"},"minimax/minimax-m2.7-highspeed":{"id":"minimax/minimax-m2.7-highspeed","name":"MiniMax M2.7 High Speed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131100},"cost":{"input":0.6,"output":2.4,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"minimax/minimax-m2.1-lightning":{"id":"minimax/minimax-m2.1-lightning","name":"MiniMax M2.1 Lightning","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-12-23","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":2.4,"cache_read":0.03,"cache_write":0.375}},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131000},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5"},"minimax/minimax-m2.5-highspeed":{"id":"minimax/minimax-m2.5-highspeed","name":"MiniMax M2.5 High Speed","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"release_date":"2026-02-13","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131000},"cost":{"input":0.6,"output":2.4,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5-highspeed"},"minimax/minimax-m2":{"id":"minimax/minimax-m2","name":"MiniMax M2","description":"Efficient open MiniMax model built for coding agents and tool-heavy workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":205000,"output":196608},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2"},"minimax/minimax-m2.7":{"id":"minimax/minimax-m2.7","name":"Minimax M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"output":512000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"minimax/minimax-h3-max":{"id":"minimax/minimax-h3-max","type":"video","name":"MiniMax H3 Max","description":"Fast video model post-trained by fal.ai on MiniMax H3, with synchronized audio at 480p and 768p","family":"minimax","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"minimax/MiniMax-H3-Max"},"liquid/lfm2.5-24b-a2b":{"id":"liquid/lfm2.5-24b-a2b","name":"LFM2.5-24B-A2B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"liquid","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8200},"cost":{"input":0.05,"output":0.7,"cache_read":0.025}},"moonshotai/kimi-k3-fast":{"id":"moonshotai/kimi-k3-fast","name":"Kimi K3 Fast","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":4.5,"output":22.5,"cache_read":0.45},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.5":{"id":"moonshotai/kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.6,"output":3},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2":{"id":"moonshotai/kimi-k2","name":"Kimi K2 Instruct","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-12-31","release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.57,"output":2.3},"canonical_model_id":"moonshotai/kimi-k2"},"moonshotai/kimi-k2.7-code-highspeed":{"id":"moonshotai/kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code High Speed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32768},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"fish-audio/s1":{"id":"fish-audio/s1","type":"speech","name":"S1","description":"Speech generation model for controllable voice, narration, and audio delivery","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-10-20","last_updated":"2025-10-20","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"fish-audio/transcribe-1":{"id":"fish-audio/transcribe-1","type":"transcription","name":"Transcribe-1","description":"Speech transcription model for accurate audio-to-text and captioning workflows","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-03-01","last_updated":"2026-03-01","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"fish-audio/drama-3":{"id":"fish-audio/drama-3","type":"speech","name":"Drama 3","description":"Speech generation model for controllable voice, narration, and audio delivery","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"fish-audio/s2-pro":{"id":"fish-audio/s2-pro","type":"speech","name":"S2 Pro","description":"Speech generation model for controllable voice, narration, and audio delivery","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"fish-audio/s2.1-pro":{"id":"fish-audio/s2.1-pro","type":"speech","name":"S2.1 Pro","description":"Speech generation model for controllable voice, narration, and audio delivery","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-07-28","last_updated":"2026-07-28","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.13,"output":0.26,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v3.1":{"id":"deepseek/deepseek-v3.1","name":"DeepSeek-V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":128000},"cost":{"input":0.25,"output":0.95,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-v3.1"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":32768},"cost":{"input":0.075,"output":0.3,"cache_read":0.0015},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.66,"output":1.98,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v4.1-flash-fast":{"id":"deepseek/deepseek-v4.1-flash-fast","name":"DeepSeek V4.1 Flash Fast","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":32768},"cost":{"input":0.6,"output":2.4,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v3.2-thinking":{"id":"deepseek/deepseek-v3.2-thinking","name":"DeepSeek V3.2 Thinking","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8000},"cost":{"input":0.62,"output":1.85},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepseek/deepseek-v4-flash-vision-exp":{"id":"deepseek/deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.2156,"output":0.6468,"cache_read":0.0068},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"deepseek/deepseek-v4.1-flash-1017":{"id":"deepseek/deepseek-v4.1-flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.075,"output":0.3,"cache_read":0.0015},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.076,"output":0.153,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v4.1-flash-1017-fast":{"id":"deepseek/deepseek-v4.1-flash-1017-fast","name":"DeepSeek V4.1 Flash 1017 Fast","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":0.6,"output":2.4,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek/deepseek-v3.2":{"id":"deepseek/deepseek-v3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8000},"cost":{"input":0.62,"output":1.85},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.66,"output":1.98,"cache_read":0.066},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek/deepseek-r1":{"id":"deepseek/deepseek-r1","name":"DeepSeek-R1","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"status":"deprecated","cost":{"input":1.35,"output":5.4},"canonical_model_id":"deepseek/deepseek-r1"},"nvidia/nemotron-3.5-super-vl":{"id":"nvidia/nemotron-3.5-super-vl","name":"NVIDIA Nemotron 3.5 Super VL","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.2,"output":0.5,"cache_read":0.04},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"nvidia/nemotron-nano-9b-v2":{"id":"nvidia/nemotron-nano-9b-v2","name":"Nvidia Nemotron Nano 9B V2","description":"Compact Nemotron model for efficient reasoning and deployable AI agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2025-08-18","last_updated":"2025-08-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.06,"output":0.23},"canonical_model_id":"nvidia/nemotron-nano-9b-v2"},"nvidia/nemotron-3-super-120b-a12b":{"id":"nvidia/nemotron-3-super-120b-a12b","name":"NVIDIA Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32000},"cost":{"input":0.15,"output":0.65},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"nvidia/nemotron-3-ultra-550b-a55b":{"id":"nvidia/nemotron-3-ultra-550b-a55b","name":"Nemotron 3 Ultra","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65000},"cost":{"input":0.6,"output":2.4,"cache_read":0.12},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/nemotron-3.5-lightning-free":{"id":"nvidia/nemotron-3.5-lightning-free","name":"Nemotron 3.5 Lightning Free","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65000},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/nemotron-3.5-lightning":{"id":"nvidia/nemotron-3.5-lightning","name":"Nemotron 3.5 Lightning 30B","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.05,"output":0.2,"cache_read":0.01},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/nemotron-nano-12b-v2-vl":{"id":"nvidia/nemotron-nano-12b-v2-vl","name":"Nvidia Nemotron Nano 12B V2 VL","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2025-10-28","last_updated":"2025-10-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.2,"output":0.6},"canonical_model_id":"nvidia/nemotron-nano-12b-v2-vl"},"nvidia/nemotron-3-nano-30b-a3b":{"id":"nvidia/nemotron-3-nano-30b-a3b","name":"Nemotron 3 Nano 30B A3B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-06-25","release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.05,"output":0.2,"cache_read":0.025},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"arcee-ai/trinity-large-thinking":{"id":"arcee-ai/trinity-large-thinking","name":"Trinity Large Thinking","description":"Reasoning-optimized 398B MoE agent model with extended thinking for long-horizon and multi-turn tool use","family":"trinity","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262100,"output":80000},"cost":{"input":0.25,"output":0.8,"cache_read":0.06},"canonical_model_id":"arcee-ai/trinity-large-thinking"},"microsoft/mai-voice-2-flash":{"id":"microsoft/mai-voice-2-flash","type":"speech","name":"MAI-Voice-2-Flash","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mai","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-07-23","last_updated":"2026-07-23","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"microsoft/mai-voice-2":{"id":"microsoft/mai-voice-2","type":"speech","name":"MAI-Voice-2","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mai","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"microsoft/mai-transcribe-2-streaming":{"id":"microsoft/mai-transcribe-2-streaming","type":"transcription","name":"MAI-Transcribe-2-Streaming","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"mai","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-01","last_updated":"2026-10-01","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"microsoft/mai-image-2.6":{"id":"microsoft/mai-image-2.6","type":"image","name":"MAI-Image-2.6","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"mai","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"cost":{"input":5,"output":38}},"microsoft/mai-image-2.6-flash":{"id":"microsoft/mai-image-2.6-flash","type":"image","name":"MAI-Image-2.6-Flash","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"mai","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"cost":{"input":1.75,"output":19}},"microsoft/mai-voice-2.1-flash":{"id":"microsoft/mai-voice-2.1-flash","type":"speech","name":"MAI-Voice-2.1-Flash","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mai","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-01","last_updated":"2026-10-01","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"microsoft/mai-transcribe-2":{"id":"microsoft/mai-transcribe-2","type":"transcription","name":"MAI-Transcribe 2","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"mai","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-03","last_updated":"2026-09-03","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"microsoft/mai-voice-2.1":{"id":"microsoft/mai-voice-2.1","type":"speech","name":"MAI-Voice-2.1","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mai","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-01","last_updated":"2026-10-01","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"cohere/rerank-v4-pro":{"id":"cohere/rerank-v4-pro","type":"reranking","name":"Cohere Rerank 4 Pro","description":"Multilingual reranker for maximum relevance on documents and semi-structured data","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"cohere/rerank-v4.0-pro"},"cohere/command-a":{"id":"cohere/command-a","name":"Command A","description":"Cohere command model for multilingual enterprise agents, tools, and chat","family":"command-a","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-03-13","last_updated":"2025-03-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8000},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-a"},"cohere/embed-v4.0":{"id":"cohere/embed-v4.0","type":"embedding","name":"Embed v4.0","description":"Multimodal embedding model for text, images, and mixed text-and-image documents","family":"cohere-embed","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-04-15","last_updated":"2025-04-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":1536},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"cohere/embed-v4.0"},"cohere/embed-v5.0-fast":{"id":"cohere/embed-v5.0-fast","type":"embedding","name":"Embed 5 Fast","description":"Faster, lighter Embed 5 model sharing Embed 5 Pro's embedding space","family":"cohere-embed","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-30","last_updated":"2026-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":2048},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"cohere/embed-v5.0-fast"},"cohere/rerank-v3.5":{"id":"cohere/rerank-v3.5","type":"reranking","name":"Cohere Rerank 3.5","description":"Multilingual reranker for documents and semi-structured data","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-12-02","last_updated":"2024-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":4096,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"cohere/rerank-v3.5"},"cohere/embed-v5.0-pro":{"id":"cohere/embed-v5.0-pro","type":"embedding","name":"Embed 5 Pro","description":"Cohere's most capable multimodal embedding model for text, images, and mixed documents","family":"cohere-embed","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-30","last_updated":"2026-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":2048},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"cohere/embed-v5.0-pro"},"cohere/rerank-v5-pro":{"id":"cohere/rerank-v5-pro","type":"reranking","name":"Cohere Rerank 5 Pro","description":"Reranking model for improving retrieval quality in search and recommendation systems","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-21","last_updated":"2026-10-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"cohere/rerank-v5-fast":{"id":"cohere/rerank-v5-fast","type":"reranking","name":"Cohere Rerank 5 Fast","description":"Reranking model for improving retrieval quality in search and recommendation systems","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-21","last_updated":"2026-10-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"cohere/rerank-v4-fast":{"id":"cohere/rerank-v4-fast","type":"reranking","name":"Cohere Rerank 4 Fast","description":"Low-latency multilingual reranker for high-throughput retrieval","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"cohere/rerank-v4.0-fast"},"inference-net/schematron-v2-turbo":{"id":"inference-net/schematron-v2-turbo","name":"Schematron V2 Turbo","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.03,"output":0.15,"cache_read":0.03},"canonical_model_id":"inference-net/schematron-v2-turbo"},"inference-net/schematron-v2-small":{"id":"inference-net/schematron-v2-small","name":"Schematron V2 Small","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":0.05,"output":0.23,"cache_read":0.05},"canonical_model_id":"inference-net/schematron-v2-small"},"interfaze/interfaze-beta":{"id":"interfaze/interfaze-beta","name":"Interfaze Beta","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"temperature":true,"release_date":"2025-10-07","last_updated":"2026-04-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32000},"cost":{"input":1.5,"output":3.5}},"scaledown/scaledown-summarize-1":{"id":"scaledown/scaledown-summarize-1","name":"Summarize-1","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-10-20","last_updated":"2026-10-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000},"cost":{"input":0.05,"output":0}},"scaledown/scaledown-extract-1":{"id":"scaledown/scaledown-extract-1","name":"Extract-1","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-10-20","last_updated":"2026-10-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":0.05,"output":0}},"tencent/hy-mt2-plus":{"id":"tencent/hy-mt2-plus","name":"Tencent Hy-MT2-Plus","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8000,"output":4000},"cost":{"input":0.074,"output":0.295}},"tencent/hy4-preview":{"id":"tencent/hy4-preview","name":"Tencent Hy4 Preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":64000},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"},"tencent/hy3":{"id":"tencent/hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.14,"output":0.58,"cache_read":0.035},"canonical_model_id":"tencent/hy3"},"tencent/hy-mt2-lite":{"id":"tencent/hy-mt2-lite","name":"Tencent Hy-MT2-Lite","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8000,"output":4000},"cost":{"input":0.044,"output":0.177}},"tencent/hy-mt2-pro":{"id":"tencent/hy-mt2-pro","name":"Tencent Hy-MT2-Pro","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8000,"output":4000},"cost":{"input":0.074,"output":0.295}},"meta/muse-spark-1.3":{"id":"meta/muse-spark-1.3","name":"Muse Spark 1.3","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.3"},"meta/muse-spark-open":{"id":"meta/muse-spark-open","name":"Muse Spark Open","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-open"},"meta/muse-image-1.0":{"id":"meta/muse-image-1.0","type":"image","name":"Muse Image 1.0","description":"Agentic image generation and editing model that plans, searches and refines before rendering","family":"muse","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-07-07","last_updated":"2026-07-07","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"meta/muse-image-1.0"},"meta/muse-spark-1.2":{"id":"meta/muse-spark-1.2","name":"Muse Spark 1.2","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"meta/llama-3.1-8b":{"id":"meta/llama-3.1-8b","name":"Llama 3.1 8B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.22,"output":0.22},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"meta/llama-3.1-70b":{"id":"meta/llama-3.1-70b","name":"Llama 3.1 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.72,"output":0.72},"canonical_model_id":"meta/llama-3.1-70b-instruct"},"meta/muse-spark-1.2-contributor":{"id":"meta/muse-spark-1.2-contributor","name":"Muse Spark 1.2 Contributor","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"meta/muse-spark-1.1":{"id":"meta/muse-spark-1.1","name":"Muse Spark 1.1","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.1"},"meta/llama-4-scout":{"id":"meta/llama-4-scout","name":"Llama-4-Scout-17B-16E-Instruct-FP8","description":"Open multimodal Llama model for long-context analysis and efficient agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.17,"output":0.66},"canonical_model_id":"meta/llama-4-scout-17b-instruct"},"meta/muse-glimmer-30b":{"id":"meta/muse-glimmer-30b","name":"Muse Glimmer 30B","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.35,"output":1.5,"cache_read":0.04},"canonical_model_id":"meta/muse-glimmer-30b"},"meta/muse-spark-1.3-contributor":{"id":"meta/muse-spark-1.3-contributor","name":"Muse Spark 1.3 Contributor","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"meta/llama-4-maverick":{"id":"meta/llama-4-maverick","name":"Llama-4-Maverick-17B-128E-Instruct-FP8","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.24,"output":0.97},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"meta/muse-wonder-1.0":{"id":"meta/muse-wonder-1.0","name":"Muse Wonder","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":4,"output":20,"cache_read":0.2},"canonical_model_id":"meta/muse-wonder-1.0"},"meta/llama-3.3-70b":{"id":"meta/llama-3.3-70b","name":"Llama-3.3-70B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.72,"output":0.72},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"stepfun/step-5-preview":{"id":"stepfun/step-5-preview","name":"Step 5 Preview","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1,"output":2.7,"cache_read":0.1},"canonical_model_id":"stepfun/step-5-preview"},"stepfun/step-3.7-flash":{"id":"stepfun/step-3.7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"voyage/rerank-2.5-lite":{"id":"voyage/rerank-2.5-lite","type":"reranking","name":"Voyage Rerank 2.5 Lite","description":"Instruction-following reranker optimized for latency and quality","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"voyageai/rerank-2.5-lite"},"voyage/voyage-code-2":{"id":"voyage/voyage-code-2","type":"embedding","name":"voyage-code-2","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-01-01","last_updated":"2024-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16000,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"voyage/rerank-2.5":{"id":"voyage/rerank-2.5","type":"reranking","name":"Voyage Rerank 2.5","description":"Instruction-following reranker optimized for retrieval quality","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"voyageai/rerank-2.5"},"voyage/rerank-3-lite":{"id":"voyage/rerank-3-lite","type":"reranking","name":"Voyage Rerank 3 Lite","description":"Reranker optimized for latency and cost, successor to rerank-2.5-lite","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-30","last_updated":"2026-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"voyageai/rerank-3-lite"},"voyage/voyage-3.5":{"id":"voyage/voyage-3.5","type":"embedding","name":"voyage-3.5","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"voyage/voyage-finance-2":{"id":"voyage/voyage-finance-2","type":"embedding","name":"voyage-finance-2","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-06-03","last_updated":"2024-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"voyage/voyage-4-large":{"id":"voyage/voyage-4-large","type":"embedding","name":"voyage-4-large","description":"General-purpose and multilingual embedding model optimized for retrieval quality","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-01-15","last_updated":"2026-01-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"voyageai/voyage-4-large"},"voyage/voyage-3.5-lite":{"id":"voyage/voyage-3.5-lite","type":"embedding","name":"voyage-3.5-lite","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"voyage/voyage-3-large":{"id":"voyage/voyage-3-large","type":"embedding","name":"voyage-3-large","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-01-07","last_updated":"2024-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"voyage/rerank-3":{"id":"voyage/rerank-3","type":"reranking","name":"Voyage Rerank 3","description":"Reranker optimized for retrieval quality, successor to rerank-2.5","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-30","last_updated":"2026-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"voyageai/rerank-3"},"voyage/voyage-4":{"id":"voyage/voyage-4","type":"embedding","name":"voyage-4","description":"General-purpose and multilingual embedding model balancing retrieval quality and cost","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-01-15","last_updated":"2026-01-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"voyageai/voyage-4"},"voyage/voyage-4-lite":{"id":"voyage/voyage-4-lite","type":"embedding","name":"voyage-4-lite","description":"Lightweight general-purpose embedding model optimized for latency and cost","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-01-15","last_updated":"2026-01-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"voyageai/voyage-4-lite"},"voyage/voyage-law-2":{"id":"voyage/voyage-law-2","type":"embedding","name":"voyage-law-2","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-04-15","last_updated":"2024-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16000,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"voyage/voyage-code-3":{"id":"voyage/voyage-code-3","type":"embedding","name":"voyage-code-3","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"voyage","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-12-04","last_updated":"2024-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"fireworks/ember-1":{"id":"fireworks/ember-1","name":"Ember-1","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":1048576},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"fireworks/ember-1"},"bfl/flux-2-pro":{"id":"bfl/flux-2-pro","type":"image","name":"FLUX.2 [pro]","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-11-25","last_updated":"2026-06-08","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":67300,"output":67300},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"bfl/flux-2-flex":{"id":"bfl/flux-2-flex","type":"image","name":"FLUX.2 [flex]","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-11-25","last_updated":"2026-06-08","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"bfl/flux-3-image-klein":{"id":"bfl/flux-3-image-klein","type":"image","name":"FLUX 3 Image Klein","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"bfl/flux-pro-1.0-fill":{"id":"bfl/flux-pro-1.0-fill","type":"image","name":"FLUX.1 Fill [pro]","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-10-01","last_updated":"2024-10","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":512,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"bfl/flux-2-klein-4b":{"id":"bfl/flux-2-klein-4b","type":"image","name":"FLUX.2 [klein] 4B","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-01-15","last_updated":"2026-06-08","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"bfl/flux-kontext-pro":{"id":"bfl/flux-kontext-pro","type":"image","name":"FLUX.1 Kontext Pro","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-05-29","last_updated":"2025-06","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":512,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"bfl/flux-2-max":{"id":"bfl/flux-2-max","type":"image","name":"FLUX.2 [max]","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-16","last_updated":"2026-06-08","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":67300,"output":67300},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"bfl/flux-3-video":{"id":"bfl/flux-3-video","type":"video","name":"Flux 3","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"flux","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-08-04","last_updated":"2026-08-04","modalities":{"input":["text","image","video"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"bfl/flux-3-image":{"id":"bfl/flux-3-image","type":"image","name":"FLUX 3 Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"bfl/flux-2-klein-9b":{"id":"bfl/flux-2-klein-9b","type":"image","name":"FLUX.2 [klein] 9B","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-01-15","last_updated":"2026-06-08","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"bfl/flux-pro-1.1":{"id":"bfl/flux-pro-1.1","type":"image","name":"FLUX1.1 [pro]","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-10-02","last_updated":"2024-10","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":512,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"bfl/flux-kontext-max":{"id":"bfl/flux-kontext-max","type":"image","name":"FLUX.1 Kontext Max","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-05-29","last_updated":"2025-06","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":512,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"bfl/flux-pro-1.1-ultra":{"id":"bfl/flux-pro-1.1-ultra","type":"image","name":"FLUX1.1 [pro] Ultra","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-11-01","last_updated":"2024-11","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":512,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"klingai/kling-v3.0-motion-control":{"id":"klingai/kling-v3.0-motion-control","type":"video","name":"Kling v3.0 Motion Control","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"ling","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-03-04","last_updated":"2026-03-04","modalities":{"input":["text","image","video"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"klingai/kling-v2.5-turbo-t2v":{"id":"klingai/kling-v2.5-turbo-t2v","type":"video","name":"Kling v2.5 Turbo Text-to-Video","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"ling","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"klingai/kling-v2.5-turbo-i2v":{"id":"klingai/kling-v2.5-turbo-i2v","type":"video","name":"Kling v2.5 Turbo Image-to-Video","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"ling","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"klingai/kling-v3.0-t2v":{"id":"klingai/kling-v3.0-t2v","type":"video","name":"Kling v3.0 Text-to-Video","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"ling","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"klingai/kling-v2.6-i2v":{"id":"klingai/kling-v2.6-i2v","type":"video","name":"Kling v2.6 Image-to-Video","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"ling","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-03","last_updated":"2025-12-21","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"klingai/kling-v2.6-motion-control":{"id":"klingai/kling-v2.6-motion-control","type":"video","name":"Kling v2.6 Motion Control","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"ling","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-18","last_updated":"2025-12-21","modalities":{"input":["text","image","video"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"klingai/kling-v3.0-i2v":{"id":"klingai/kling-v3.0-i2v","type":"video","name":"Kling v3.0 Image-to-Video","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"ling","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"klingai/kling-v2.6-t2v":{"id":"klingai/kling-v2.6-t2v","type":"video","name":"Kling v2.6 Text-to-Video","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"ling","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-03","last_updated":"2025-12-21","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"google/gemini-embedding-2":{"id":"google/gemini-embedding-2","type":"embedding","name":"Gemini Embedding 2","description":"Multimodal embedding model mapping text, images, video, audio, and PDFs into a unified embedding space","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-11","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":3072},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"google/gemini-embedding-2"},"google/veo-3.1-fast-generate-001":{"id":"google/veo-3.1-fast-generate-001","type":"video","name":"Veo 3.1 Fast Generate","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-10-15","last_updated":"2026-06-08","modalities":{"input":["text","image","video"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"cost":{"input":0.1,"output":0.4,"cache_read":0.01},"canonical_model_id":"google/gemini-2.5-flash-lite"},"google/veo-3.1-lite-generate-001":{"id":"google/veo-3.1-lite-generate-001","type":"video","name":"Veo 3.1 Lite Generate","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.7-flash"},"google/gemini-3-pro-image":{"id":"google/gemini-3-pro-image","type":"image","name":"Nano Banana Pro","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":2,"output":12,"cache_read":0.2},"canonical_model_id":"google/gemini-3-pro-image"},"google/gemini-3.1-flash-image":{"id":"google/gemini-3.1-flash-image","type":"image","name":"Nano Banana 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":3,"cache_read":0.05},"canonical_model_id":"google/gemini-3.1-flash-image"},"google/gemini-3-flash":{"id":"google/gemini-3-flash","name":"Gemini 3 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65000},"cost":{"input":0.5,"output":3,"cache_read":0.05}},"google/gemini-3.5-transcribe":{"id":"google/gemini-3.5-transcribe","type":"transcription","name":"Gemini 3.5 Transcribe","description":"Speech-to-text model with language detection, speaker diarization, word timestamps, and custom vocabulary","family":"gemini","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":98304,"output":32768},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"cost":{"input":2,"output":12,"input_audio":2},"canonical_model_id":"google/gemini-3.5-transcribe"},"google/gemini-2.5-flash-image":{"id":"google/gemini-2.5-flash-image","type":"image","name":"Nano Banana (Gemini 2.5 Flash Image)","description":"Nano Banana image model for fast generation, edits, and character-consistent assets","family":"gemini-flash","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":32768,"output":65535},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-2.5-flash-image"},"google/gemini-3.8-live":{"id":"google/gemini-3.8-live","type":"realtime","name":"Gemini 3.8 Live","description":"Low-latency Live API model for real-time voice agents with interleaved reasoning and async tools","family":"gemini-flash","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-09-15","last_updated":"2026-09-15","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":131072,"output":65536},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"cost":{"input":0.75,"output":4.5,"input_audio":3,"output_audio":12},"canonical_model_id":"google/gemini-3.8-live"},"google/gemini-4-argon":{"id":"google/gemini-4-argon","name":"Gemini 4 Argon","description":"Gemini multimodal model for text, image, audio, video, and document tasks","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":2,"output":10,"cache_read":0.1},"canonical_model_id":"google/gemini-4-argon"},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.14,"output":0.4},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65000},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/veo-3.0-generate-001":{"id":"google/veo-3.0-generate-001","type":"video","name":"Veo 3.0","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-05-20","last_updated":"2026-06-08","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"google/gemini-omni-flash-preview":{"id":"google/gemini-omni-flash-preview","type":"video","name":"Gemini Omni Flash Preview","description":"Omni-modal model for text, vision, audio, and multimodal agent tasks","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":false,"temperature":true,"release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":57920},"cost":{"input":1.5,"output":9},"canonical_model_id":"google/gemini-omni-flash-preview"},"google/gemini-3.5-transcribe-live":{"id":"google/gemini-3.5-transcribe-live","type":"transcription","name":"Gemini 3.5 Transcribe Live","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"gemini","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"google/gemini-3.5-transcribe-live"},"google/gemini-3.8-flash-lite-tts":{"id":"google/gemini-3.8-flash-lite-tts","type":"speech","name":"Gemini 3.8 Flash-Lite TTS","description":"Fast, cost-efficient text-to-speech model for high-volume narration and voice agent pipelines","family":"gemini-flash-lite","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":8192,"output":16384},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"cost":{"input":0.5,"output":6,"output_audio":6},"canonical_model_id":"google/gemini-3.8-flash-lite-tts"},"google/gemma-4-26b-a4b-it":{"id":"google/gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemini-3.1-flash-lite-image":{"id":"google/gemini-3.1-flash-lite-image","type":"image","name":"Gemini 3.1 Flash Lite Image (Nano Banana 2 Lite)","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":4096},"cost":{"input":0.25,"output":1.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.1-flash-lite-image"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200001}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.8-flash-tts":{"id":"google/gemini-3.8-flash-tts","type":"speech","name":"Gemini 3.8 Flash TTS","description":"Flagship text-to-speech model for expressive, studio-grade voices and long-form multi-speaker audio","family":"gemini-flash","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":8192,"output":16384},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"cost":{"input":0.5,"output":9,"output_audio":9},"canonical_model_id":"google/gemini-3.8-flash-tts"},"google/text-multilingual-embedding-002":{"id":"google/text-multilingual-embedding-002","type":"embedding","name":"Text Multilingual Embedding 002","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-03-01","last_updated":"2024-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":1.5,"output":9,"cache_read":0.15},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-3.8-live-extended-thinking":{"id":"google/gemini-3.8-live-extended-thinking","type":"realtime","name":"Gemini 3.8 Live Extended Thinking","description":"Live API voice model with configurable background reasoning for multi-step real-time agents","family":"gemini-flash","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-09-15","last_updated":"2026-09-15","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":131072,"output":65536},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"cost":{"input":0.75,"output":4.5,"input_audio":3,"output_audio":12},"canonical_model_id":"google/gemini-3.8-live-extended-thinking"},"google/text-embedding-005":{"id":"google/text-embedding-005","type":"embedding","name":"Text Embedding 005","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-08-01","last_updated":"2024-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"google/gemini-embedding-001":{"id":"google/gemini-embedding-001","type":"embedding","name":"Gemini Embedding 001","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-05","release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":2048,"output":1},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"},"canonical_model_id":"google/gemini-embedding-001"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65000},"cost":{"input":0.25,"output":1.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.1-flash-lite"},"google/veo-3.0-fast-generate-001":{"id":"google/veo-3.0-fast-generate-001","type":"video","name":"Veo 3.0 Fast Generate","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-07-31","last_updated":"2026-06-08","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"google/gemini-3.1-flash-image-preview":{"id":"google/gemini-3.1-flash-image-preview","type":"image","name":"Gemini 3.1 Flash Image Preview (Nano Banana 2)","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-26","last_updated":"2026-02-26","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":3,"cache_read":0.05},"canonical_model_id":"google/gemini-3.1-flash-image-preview"},"google/veo-3.1-generate-001":{"id":"google/veo-3.1-generate-001","type":"video","name":"Veo 3.1","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-10-15","last_updated":"2026-06-08","modalities":{"input":["text","image","video"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"api":"https://ai-gateway.vercel.sh/v4/ai"}},"google/gemini-nano-banana-2.1":{"id":"google/gemini-nano-banana-2.1","type":"image","name":"Gemini Nano Banana 2.1","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"google/gemini-nano-banana-2.1"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.6-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"input_audio":1},"canonical_model_id":"google/gemini-2.5-flash"}}},"openreason":{"id":"openreason","env":["OPENREASON_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.openreason.app/v1","name":"OpenReason","doc":"https://openreason.app/docs","models":{"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.1055,"output":0.422},"canonical_model_id":"openai/gpt-oss-120b"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.0022,"output":4.22},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"deepseek-ai/deepseek-v4-flash-0731":{"id":"deepseek-ai/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.1371,"output":0.2743},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"}}},"regolo-ai":{"id":"regolo-ai","env":["REGOLO_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.regolo.ai/v1","name":"Regolo AI","doc":"https://docs.regolo.ai/","models":{"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT-OSS-120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":1.1215,"output":4.7103},"canonical_model_id":"openai/gpt-oss-120b"},"brick-complexity-pro":{"id":"brick-complexity-pro","name":"Brick Complexity Pro","description":"Complexity classifier that powers the Brick semantic router by extracting query difficulty","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-02-06","last_updated":"2026-02-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":100000,"output":15000},"cost":{"input":0.12,"output":0.46}},"qwen3.5-9b":{"id":"qwen3.5-9b","name":"Qwen3.5-9B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.078505,"output":0.392525},"canonical_model_id":"alibaba/qwen3.5-9b"},"qwen3-embedding-8b":{"id":"qwen3-embedding-8b","type":"embedding","name":"Qwen3-Embedding-8B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0.1,"output":0.1},"canonical_model_id":"alibaba/qwen3-embedding-8b"},"qwen3-reranker-4b":{"id":"qwen3-reranker-4b","type":"reranking","name":"Qwen3-Reranker-4B","description":"Reranking model for improving retrieval quality in search and recommendation systems","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-02-01","last_updated":"2026-02-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0.12,"output":0.12}},"brick-v1-beta":{"id":"brick-v1-beta","name":"Brick v1 Beta","description":"Semantic router by Regolo.ai that directs each request to the most suitable model, optimizing costs and performance","family":"model-router","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-02-06","last_updated":"2026-02-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":100000,"output":15000},"status":"beta","cost":{"input":0,"output":0}},"llama-3.3-70b-instruct":{"id":"llama-3.3-70b-instruct","name":"Llama 3.3 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"status":"deprecated","cost":{"input":0.6,"output":2.7},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"qwen3.5-122b":{"id":"qwen3.5-122b","name":"Qwen3.5-122B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":1.1215,"output":4.7103},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"deepseek-ocr-2":{"id":"deepseek-ocr-2","name":"DeepSeek OCR 2","description":"High-accuracy OCR model for extracting text from documents, screenshots, receipts, and natural scenes","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":4000,"output":4000},"cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-ocr-2"},"apertus-70b":{"id":"apertus-70b","name":"Apertus 70B","description":"Fully open 70B multilingual LLM supporting 1800+ languages with 65K context. Trained on 15T tokens of compliant open data. Apache 2.0, EU AI Act compliant.","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-09-02","last_updated":"2025-09-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":30000,"output":30000},"cost":{"input":0.46,"output":2.42},"canonical_model_id":"swiss-ai/apertus-70b"},"gpt-oss-20b":{"id":"gpt-oss-20b","name":"GPT-OSS-20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.11215,"output":0.47103},"canonical_model_id":"openai/gpt-oss-20b"},"mistral-small-4-119b":{"id":"mistral-small-4-119b","name":"Mistral Small 4 119B","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":0.56075,"output":2.35515},"canonical_model_id":"mistral/mistral-small-2603"},"qwen3.8-27b":{"id":"qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":120000,"output":120000},"cost":{"input":0.58,"output":2.42},"canonical_model_id":"alibaba/qwen3.8-27b"},"faster-whisper-large-v3":{"id":"faster-whisper-large-v3","type":"transcription","name":"Faster Whisper Large v3","description":"Open Whisper checkpoint for robust multilingual transcription and captioning","family":"whisper","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2023-11-06","last_updated":"2023-11-06","modalities":{"input":["audio"],"output":["text"]},"open_weights":true,"limit":{"context":448,"output":4096},"cost":{"input":0,"output":0},"canonical_model_id":"openai/whisper-large-v3"},"gemma4-31b":{"id":"gemma4-31b","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":100000,"output":100000},"cost":{"input":0.46,"output":2.42},"canonical_model_id":"google/gemma-4-31b-it"},"glm5.2":{"id":"glm5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":96000,"output":96000},"cost":{"input":2.31,"output":6},"canonical_model_id":"zhipuai/glm-5.2"},"qwen3-coder-next":{"id":"qwen3-coder-next","name":"Qwen3-Coder-Next","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"status":"deprecated","cost":{"input":0.3,"output":1.2},"canonical_model_id":"alibaba/qwen3-coder-next"},"qwen-image":{"id":"qwen-image","type":"image","name":"Qwen-Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-03-01","last_updated":"2026-03-01","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":8192,"output":4096},"cost":{"input":0.5,"output":2}}}},"routing-run":{"id":"routing-run","env":["ROUTING_RUN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.routing.run/v1","name":"routing.run","doc":"https://docs.routing.run/api-reference/models","models":{"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":64000},"cost":{"input":0.112,"output":0.224},"canonical_model_id":"deepseek/deepseek-v4-flash"},"kimi-k2.7-code-nitro":{"id":"kimi-k2.7-code-nitro","name":"Kimi K2.7 Code Nitro","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"cost":{"input":0.275,"output":1.1},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"cost":{"input":0.8,"output":2.4},"canonical_model_id":"zhipuai/glm-5.2"},"nemotron-3-ultra":{"id":"nemotron-3-ultra","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32000},"cost":{"input":0.1,"output":0.1},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"qwen3.5-9b":{"id":"qwen3.5-9b","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32000},"cost":{"input":0.16,"output":0.48},"canonical_model_id":"alibaba/qwen3.5-9b"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":64000},"cost":{"input":0.348,"output":0.696},"canonical_model_id":"deepseek/deepseek-v4-pro"},"kimi-k2.6-nitro":{"id":"kimi-k2.6-nitro","name":"Kimi K2.6 Nitro","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"cost":{"input":0.275,"output":1.1},"canonical_model_id":"moonshotai/kimi-k2.6"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000},"cost":{"input":0.7,"output":4.2},"canonical_model_id":"openai/gpt-5.6-luna"},"glm-5.2-nitro":{"id":"glm-5.2-nitro","name":"GLM 5.2 Nitro","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"cost":{"input":0.8,"output":2.4},"canonical_model_id":"zhipuai/glm-5.2"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"cost":{"input":0.275,"output":1.1},"canonical_model_id":"moonshotai/kimi-k2.6"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-4-8"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15},"canonical_model_id":"openai/gpt-5.6-sol"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000},"cost":{"input":1.5,"output":9},"canonical_model_id":"openai/gpt-5.6-terra"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"cost":{"input":0.275,"output":1.1},"canonical_model_id":"moonshotai/kimi-k2.7-code"}}},"ainetcafe":{"id":"ainetcafe","env":["AINETCAFE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://microquickjs.com/v1","name":"ainetcafe","doc":"https://ainetcafe.com/k3/guides/","models":{"Kimi-K3":{"id":"Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":2.1,"output":10.5,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"}}},"vultr":{"id":"vultr","env":["VULTR_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.vultrinference.com/v1","name":"Vultr","doc":"https://api.vultrinference.com/","models":{"nemotron-3-nano-omni-30b-a3b-reasoning":{"id":"nemotron-3-nano-omni-30b-a3b-reasoning","name":"Nemotron 3 Nano Omni 30B A3B Reasoning","description":"Open Nemotron omni model combining reasoning with text, vision, and audio","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.1,"output":0.25},"canonical_model_id":"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning"},"qwen3.8-flash-next":{"id":"qwen3.8-flash-next","name":"Qwen3.8 Flash Next","description":"Open-weight experimental preview of the Qwen4 architecture: hybrid-attention MoE (125B total, 6B active) with vision encoder for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.1,"output":0.2},"canonical_model_id":"alibaba/qwen3.8-flash-next"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.75,"output":3},"canonical_model_id":"zhipuai/glm-5.2"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.75,"output":3},"canonical_model_id":"zhipuai/glm-5.3"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.1,"output":0.35},"canonical_model_id":"zhipuai/glm-5.3-flash"},"nemotron-3.5-content-safety":{"id":"nemotron-3.5-content-safety","name":"Nemotron 3.5 Content Safety","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"temperature":true,"release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.05,"output":0.15},"canonical_model_id":"nvidia/nemotron-3.5-content-safety"},"mimo-v2.6-pro-rl":{"id":"mimo-v2.6-pro-rl","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.4,"output":0.8},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"muse-glimmer-30b":{"id":"muse-glimmer-30b","name":"Muse Glimmer 30B","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.25,"output":1},"canonical_model_id":"meta/muse-glimmer-30b"},"qwen3.8-27b":{"id":"qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.15,"output":1},"canonical_model_id":"alibaba/qwen3.8-27b"},"glm-5.x-menthol":{"id":"glm-5.x-menthol","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.4,"output":1.75},"canonical_model_id":"zhipuai/glm-5"},"mimo-v2.6-flash-rl":{"id":"mimo-v2.6-flash-rl","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.1,"output":0.25},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"status":"deprecated","cost":{"input":0.1,"output":0.25},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":512000},"cost":{"input":0.2,"output":0.9},"canonical_model_id":"minimax/MiniMax-M3"},"laguna-s-2.1":{"id":"laguna-s-2.1","name":"Laguna S 2.1","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":32768},"status":"deprecated","cost":{"input":0.09,"output":0.18},"canonical_model_id":"poolside/laguna-s-2.1"}}},"trustedrouter":{"id":"trustedrouter","env":["TRUSTEDROUTER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.trustedrouter.com/v1","name":"TrustedRouter","doc":"https://trustedrouter.com/docs","models":{"trustedrouter/e2e":{"id":"trustedrouter/e2e","name":"End-to-End Encrypted","description":"TrustedRouter privacy routing alias for end-to-end encrypted provider routes where available.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072}},"trustedrouter/synth":{"id":"trustedrouter/synth","name":"Synth","description":"TrustedRouter synthesis orchestration alias that combines multiple model responses into one answer.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-20","last_updated":"2026-06-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072}},"trustedrouter/fast":{"id":"trustedrouter/fast","name":"Fast","description":"TrustedRouter speed routing alias that prefers low-latency healthy model endpoints.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072}},"trustedrouter/cheap":{"id":"trustedrouter/cheap","name":"Cheap","description":"TrustedRouter low-cost routing alias that prefers inexpensive healthy model endpoints.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-01","last_updated":"2026-06-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072}},"trustedrouter/auto":{"id":"trustedrouter/auto","name":"Auto","description":"TrustedRouter automatic routing alias that chooses a healthy supported model endpoint for the request.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-01","last_updated":"2026-06-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072}},"trustedrouter/synth-code":{"id":"trustedrouter/synth-code","name":"Synth Code","description":"TrustedRouter code synthesis orchestration alias that combines multiple model responses into one answer.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-20","last_updated":"2026-06-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072}},"trustedrouter/zdr":{"id":"trustedrouter/zdr","name":"Zero Data Retention","description":"TrustedRouter privacy routing alias that prefers zero data retention model endpoints.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072}}}},"llama":{"id":"llama","env":["LLAMA_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.llama.com/compat/v1/","name":"Llama","doc":"https://llama.developer.meta.com/docs/models","models":{"llama-4-maverick-17b-128e-instruct-fp8":{"id":"llama-4-maverick-17b-128e-instruct-fp8","name":"Llama-4-Maverick-17B-128E-Instruct-FP8","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"llama-3.3-70b-instruct":{"id":"llama-3.3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"cerebras-llama-4-maverick-17b-128e-instruct":{"id":"cerebras-llama-4-maverick-17b-128e-instruct","name":"Cerebras-Llama-4-Maverick-17B-128E-Instruct","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"cerebras-llama-4-scout-17b-16e-instruct":{"id":"cerebras-llama-4-scout-17b-16e-instruct","name":"Cerebras-Llama-4-Scout-17B-16E-Instruct","description":"Open multimodal Llama model for long-context analysis and efficient agents","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"meta/llama-4-scout-17b-instruct"},"groq-llama-4-maverick-17b-128e-instruct":{"id":"groq-llama-4-maverick-17b-128e-instruct","name":"Groq-Llama-4-Maverick-17B-128E-Instruct","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"llama-4-scout-17b-16e-instruct-fp8":{"id":"llama-4-scout-17b-16e-instruct-fp8","name":"Llama-4-Scout-17B-16E-Instruct-FP8","description":"Open multimodal Llama model for long-context analysis and efficient agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"meta/llama-4-scout-17b-instruct"},"llama-3.3-8b-instruct":{"id":"llama-3.3-8b-instruct","name":"Llama-3.3-8B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0,"output":0}}}},"nebius":{"id":"nebius","env":["NEBIUS_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.tokenfactory.nebius.com/v1","name":"Nebius Token Factory","doc":"https://docs.tokenfactory.nebius.com/","models":{"meta-models/muse-spark-open":{"id":"meta-models/muse-spark-open","name":"Muse Spark Open","description":"Muse Spark Open is an 816B total / 42B active open-weight multimodal reasoning model from Meta for coding and long-horizon agentic work, with 1M-token context.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.25,"output":4.25,"cache_read":1.25},"canonical_model_id":"meta/muse-spark-open"},"Qwen/Qwen3-30B-A3B-Instruct-2507":{"id":"Qwen/Qwen3-30B-A3B-Instruct-2507","name":"Qwen3-30B-A3B-Instruct-2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":8192},"cost":{"input":0.1,"output":0.3,"cache_read":0.1},"canonical_model_id":"alibaba/qwen3-30b-a3b-instruct-2507"},"Qwen/Qwen3.5-397B-A17B":{"id":"Qwen/Qwen3.5-397B-A17B","name":"Qwen3.5-397B-A17B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07","release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":250000,"output":8192},"cost":{"input":0.6,"output":3.6,"cache_read":0.6},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"Qwen/Qwen3.8-27B":{"id":"Qwen/Qwen3.8-27B","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.45,"output":3,"cache_read":0.45},"canonical_model_id":"alibaba/qwen3.8-27b"},"Qwen/Qwen3-235B-A22B-Instruct-2507":{"id":"Qwen/Qwen3-235B-A22B-Instruct-2507","name":"Qwen3 235B A22B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-07","release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.2,"output":0.6,"cache_read":0.2},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"Qwen/Qwen3-Embedding-8B":{"id":"Qwen/Qwen3-Embedding-8B","type":"embedding","name":"Qwen3-Embedding-8B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2025-10","release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"input":40960,"output":0},"cost":{"input":0.01,"output":0},"canonical_model_id":"alibaba/qwen3-embedding-8b"},"reflection/beam":{"id":"reflection/beam","name":"Beam 1.0 501B A23B","description":"Sparse mixture-of-experts reasoning model with 23B active parameters for coding and agentic workflows","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-06-30","release_date":"2026-10-05","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.25,"output":1,"cache_read":0.25},"canonical_model_id":"reflection/beam-1.0-501b-a23b"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"gpt-oss-120b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":124000,"output":8192},"cost":{"input":0.15,"output":0.6,"reasoning":0.6,"cache_read":0.15},"canonical_model_id":"openai/gpt-oss-120b"},"zai-org/GLM-5.3-Flash":{"id":"zai-org/GLM-5.3-Flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":1024000},"cost":{"input":0.15,"output":0.5,"cache_read":0.15},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.4,"output":4.4,"cache_read":1.4},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-5.3":{"id":"zai-org/GLM-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":1024000},"cost":{"input":1.4,"output":4.4,"cache_read":1.4},"canonical_model_id":"zhipuai/glm-5.3"},"moonshotai/Kimi-K2.7-Code":{"id":"moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8000},"cost":{"input":0.95,"output":4,"cache_read":0.95},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"moonshotai/Kimi-K3":{"id":"moonshotai/Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":8000},"cost":{"input":3,"output":15,"cache_read":3},"canonical_model_id":"moonshotai/kimi-k3"},"nvidia/Nemotron-3-Ultra-550b-a55b":{"id":"nvidia/Nemotron-3-Ultra-550b-a55b","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1,"output":3,"cache_read":1},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/Nemotron-3_5-Lightning":{"id":"nvidia/Nemotron-3_5-Lightning","name":"Nemotron 3.5 Lightning 30B A3B","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.06,"output":0.24,"cache_read":0.06},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/Nemotron-3.5-Super-VL":{"id":"nvidia/Nemotron-3.5-Super-VL","name":"Nemotron 3.5 Super VL 120B A12B","description":"NVIDIA vision-language reasoning model for coding, visual understanding, and agentic tool use","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.3,"output":0.9,"cache_read":0.3},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"nvidia/nemotron-3-super-120b-a12b":{"id":"nvidia/nemotron-3-super-120b-a12b","name":"Nemotron-3-Super-120B-A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.3,"output":0.9,"cache_read":0.3},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"MiniMaxAI/MiniMax-M3":{"id":"MiniMaxAI/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.3,"output":1.2,"cache_read":0.3},"canonical_model_id":"minimax/MiniMax-M3"},"deepseek-ai/DeepSeek-V4.1-Flash":{"id":"deepseek-ai/DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048000,"output":1048000},"cost":{"input":0.3,"output":1.2,"cache_read":0.3},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek-ai/DeepSeek-V4-Pro":{"id":"deepseek-ai/DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.75,"output":3.5,"cache_read":1.75},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek-ai/DeepSeek-V4-Flash-0731":{"id":"deepseek-ai/DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":1024000},"cost":{"input":0.14,"output":0.28,"cache_read":0.14},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek-ai/DeepSeek-V4-Pro-0813":{"id":"deepseek-ai/DeepSeek-V4-Pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":979000,"output":979000},"cost":{"input":1.32,"output":3.96,"cache_read":1.32},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"NousResearch/Hermes-4-405B":{"id":"NousResearch/Hermes-4-405B","name":"Hermes-4-405B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"hermes","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":120000,"output":8192},"cost":{"input":1,"output":3,"reasoning":3,"cache_read":1},"canonical_model_id":"nousresearch/hermes-4-405b"},"google/gemma-3-27b-it":{"id":"google/gemma-3-27b-it","name":"Gemma-3-27b-it","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":110000,"input":100000,"output":8192},"cost":{"input":0.1,"output":0.3,"cache_read":0.1},"canonical_model_id":"google/gemma-3-27b-it"}}},"venice":{"id":"venice","env":["VENICE_API_KEY"],"npm":"venice-ai-sdk-provider","name":"Venice AI","doc":"https://docs.venice.ai","models":{"aion-labs-aion-3-0-mini":{"id":"aion-labs-aion-3-0-mini","name":"Aion 3.0 Mini","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-14","last_updated":"2026-05-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32768},"cost":{"input":0.875,"output":1.75,"cache_read":0.225},"canonical_model_id":"aion-labs/aion-3.0-mini"},"claude-sonnet-4-5":{"id":"claude-sonnet-4-5","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":198000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"kimi-k2-7-code":{"id":"kimi-k2-7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0.75,"output":3.5,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"z-ai-glm-5-turbo":{"id":"z-ai-glm-5-turbo","name":"GLM 5 Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32768},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5-turbo"},"xiaomi-mimo-v2-5":{"id":"xiaomi-mimo-v2-5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":0.4,"output":2,"cache_read":0.08},"canonical_model_id":"xiaomi/mimo-v2.5"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"nvidia-nemotron-3-ultra-550b-a55b":{"id":"nvidia-nemotron-3-ultra-550b-a55b","name":"NVIDIA Nemotron 3 Ultra","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32768},"cost":{"input":0.625,"output":3.125,"cache_read":0.1875},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"z-ai-glm-5-3-flash":{"id":"z-ai-glm-5-3-flash","name":"GLM 5.3 Flash","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash 0423","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32768},"cost":{"input":0.138,"output":0.275,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"grok-4-7":{"id":"grok-4-7","name":"Grok 4.7","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":200000},"cost":{"input":2.27,"output":6.8,"cache_read":0.57,"tiers":[{"input":4.53,"output":13.6,"cache_read":1.13,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4.53,"output":13.6,"cache_read":1.13}},"canonical_model_id":"xai/grok-4.7"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":3.75,"output":18.75,"cache_read":0.375},"canonical_model_id":"moonshotai/kimi-k3"},"qwen3-next-80b":{"id":"qwen3-next-80b","name":"Qwen 3 Next 80b","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":0.35,"output":1.9},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"openai-gpt-4o-2024-11-20":{"id":"openai-gpt-4o-2024-11-20","name":"GPT-4o","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-11-20","last_updated":"2024-11-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-11-20"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"seed-2-1-turbo":{"id":"seed-2-1-turbo","name":"Seed 2.1 Turbo","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":65536},"cost":{"input":0.625,"output":3.125,"cache_read":0.125},"canonical_model_id":"bytedance-seed/seed-2.1-turbo"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"zai-org-glm-5":{"id":"zai-org-glm-5","name":"GLM 5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":198000,"output":32000},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"gemini-3-flash-preview":{"id":"gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":65536},"cost":{"input":0.7,"output":3.75,"cache_read":0.07},"canonical_model_id":"google/gemini-3-flash-preview"},"openai-gpt-54-mini":{"id":"openai-gpt-54-mini","name":"GPT-5.4 Mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"google-gemma-4-26b-a4b-it":{"id":"google-gemma-4-26b-a4b-it","name":"Google Gemma 4 26B A4B Instruct","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.13,"output":0.4,"cache_read":0.05},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"minimax-m3-1-flash":{"id":"minimax-m3-1-flash","name":"MiniMax M3.1 Flash","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-10-19","last_updated":"2026-10-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.1875,"output":0.75,"cache_read":0.01875},"canonical_model_id":"minimax/MiniMax-M3.1-Flash"},"deepseek-v4-flash-0731-fast":{"id":"deepseek-v4-flash-0731-fast","name":"DeepSeek V4 Flash 0731 Fast","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32768},"cost":{"input":0.35,"output":0.7,"cache_read":0.0875},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"llama-3.2-3b":{"id":"llama-3.2-3b","name":"Llama 3.2 3B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"meta/llama-3.2-3b"},"qwen-3-8-2-4t-a95b":{"id":"qwen-3-8-2-4t-a95b","name":"Qwen 3.8 2.4T","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":2.5,"output":7.5,"cache_read":0.3125},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"qwen3-6-35b-a3b":{"id":"qwen3-6-35b-a3b","name":"Qwen 3.6 35B A3B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0.1,"output":1},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"nvidia-nemotron-3-5-super-vl-120b-a12b":{"id":"nvidia-nemotron-3-5-super-vl-120b-a12b","name":"NVIDIA Nemotron 3.5 Super VL 120B","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.25,"output":1.25,"cache_read":0.125},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"gemini-3-5-flash":{"id":"gemini-3-5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":1.55,"output":9.45,"cache_read":0.155,"cache_write":0.086},"canonical_model_id":"google/gemini-3.5-flash"},"qwen3-235b-a22b-instruct-2507":{"id":"qwen3-235b-a22b-instruct-2507","name":"Qwen 3 235B A22B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.75},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"openai-gpt-4o-mini-2024-07-18":{"id":"openai-gpt-4o-mini-2024-07-18","name":"GPT-4o Mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"xiaomi-mimo-v2-6-flash":{"id":"xiaomi-mimo-v2-6-flash","name":"MiMo-V2.6-Flash","description":"MiMo flash model for fast multimodal assistance and agent workflows","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.175,"output":0.35,"cache_read":0.00375},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"muse-spark-open":{"id":"muse-spark-open","name":"Muse Spark Open","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.5625,"output":5.3125,"cache_read":0.1875},"canonical_model_id":"meta/muse-spark-open"},"kimi-k2-6":{"id":"kimi-k2-6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0.75,"output":3.5,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"muse-wonder":{"id":"muse-wonder","name":"Muse Wonder","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-10-12","last_updated":"2026-10-15","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":5,"output":25,"cache_read":0.25}},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32768},"cost":{"input":1.65,"output":3.301,"cache_read":0.33},"canonical_model_id":"deepseek/deepseek-v4-pro"},"gemini-3-7-flash":{"id":"gemini-3-7-flash","name":"Gemini 3.7 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.9375,"output":4.6875,"cache_read":0.09375},"canonical_model_id":"google/gemini-3.7-flash"},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"google-gemma-4-31b-it":{"id":"google-gemma-4-31b-it","name":"Google Gemma 4 31B Instruct","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.12,"output":0.36,"cache_read":0.09},"canonical_model_id":"google/gemma-4-31b-it"},"aion-labs-aion-3-5-mini":{"id":"aion-labs-aion-3-5-mini","name":"Aion 3.5 Mini","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.875,"output":1.75,"cache_read":0.225}},"openai-gpt-oss-120b":{"id":"openai-gpt-oss-120b","name":"OpenAI GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.07,"output":0.3},"canonical_model_id":"openai/gpt-oss-120b"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"qwen3-235b-a22b-thinking-2507":{"id":"qwen3-235b-a22b-thinking-2507","name":"Qwen 3 235B A22B Thinking 2507","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-07-25","last_updated":"2025-07-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.45,"output":3.5},"canonical_model_id":"alibaba/qwen3-235b-a22b-thinking-2507"},"kimi-k2-5":{"id":"kimi-k2-5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0.56,"output":3.5,"cache_read":0.22},"canonical_model_id":"moonshotai/kimi-k2.5"},"grok-4-20-multi-agent":{"id":"grok-4-20-multi-agent","name":"Grok 4.20 Multi-Agent","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"release_date":"2026-03-12","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":128000},"cost":{"input":1.42,"output":2.83,"cache_read":0.23,"tiers":[{"input":2.83,"output":5.67,"cache_read":0.45,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.83,"output":5.67,"cache_read":0.45}}},"nvidia-nemotron-3-nano-30b-a3b":{"id":"nvidia-nemotron-3-nano-30b-a3b","name":"NVIDIA Nemotron 3 Nano 30B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06-25","release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.075,"output":0.3},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"venice-uncensored-role-play":{"id":"venice-uncensored-role-play","name":"Venice Role Play Uncensored","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"venice","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-02-20","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.5,"output":2}},"minimax-m3-preview":{"id":"minimax-m3-preview","name":"MiniMax M3 Preview","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax-m3","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"release_date":"2026-06-12","last_updated":"2026-06-13","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":65536},"cost":{"input":0.3,"output":1.2,"cache_read":0.06}},"qwen-3-7-max":{"id":"qwen-3-7-max","name":"Qwen 3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":2.7,"output":8.05,"cache_read":0.27,"cache_write":3.35},"canonical_model_id":"alibaba/qwen3.7-max"},"openai-gpt-56-luna-pro":{"id":"openai-gpt-56-luna-pro","name":"GPT-5.6 Luna Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"qwen-3-8-max":{"id":"qwen-3-8-max","name":"Qwen 3.8 Max","description":"Preview Qwen flagship for million-token multimodal reasoning and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-07-19","last_updated":"2026-07-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2.5,"output":7.5,"cache_read":0.3125,"cache_write":3.125},"canonical_model_id":"alibaba/qwen3.8-max-preview"},"aion-labs-aion-3-0":{"id":"aion-labs-aion-3-0","name":"Aion 3.0","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-05","last_updated":"2026-05-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32768},"cost":{"input":3.75,"output":7.5,"cache_read":0.9375},"canonical_model_id":"aion-labs/aion-3.0"},"grok-4-3":{"id":"grok-4-3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32000},"cost":{"input":1.42,"output":2.83,"cache_read":0.23,"tiers":[{"input":2.83,"output":5.67,"cache_read":0.45,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.83,"output":5.67,"cache_read":0.45}},"canonical_model_id":"xai/grok-4.3"},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"gemma-4-uncensored":{"id":"gemma-4-uncensored","name":"Gemma 4 Uncensored","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-04-13","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.1625,"output":0.5}},"qwen-3-8-27b":{"id":"qwen-3-8-27b","name":"Qwen 3.8 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.45,"output":3.2},"canonical_model_id":"alibaba/qwen3.8-27b"},"gemini-3-6-flash":{"id":"gemini-3-6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.9375,"output":4.6875,"cache_read":0.09375},"canonical_model_id":"google/gemini-3.6-flash"},"gemini-4-argon":{"id":"gemini-4-argon","name":"Gemini 4 Argon","description":"Gemini multimodal model for text, image, audio, video, and document tasks","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":2.5,"output":12.5,"cache_read":0.125},"canonical_model_id":"google/gemini-4-argon"},"qwen3-vl-235b-a22b":{"id":"qwen3-vl-235b-a22b","name":"Qwen3 VL 235B","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-01-16","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.21,"output":1.9,"cache_read":0.1}},"openai-gpt-53-codex":{"id":"openai-gpt-53-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"openai-gpt-55-pro":{"id":"openai-gpt-55-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.5-pro"},"qwen3-5-35b-a3b":{"id":"qwen3-5-35b-a3b","name":"Qwen 3.5 35B A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":0.15,"output":1,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"claude-fable-5-1":{"id":"claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"openai-gpt-6-astra-pro":{"id":"openai-gpt-6-astra-pro","name":"GPT-6 Astra Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"qwen3-5-397b-a17b":{"id":"qwen3-5-397b-a17b","name":"Qwen 3.5 397B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.75,"output":4.5},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"qwen-3-8-flash":{"id":"qwen-3-8-flash","name":"Qwen 3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.14,"output":0.49,"cache_read":0.014},"canonical_model_id":"alibaba/qwen3.8-flash"},"openai-gpt-54-pro":{"id":"openai-gpt-54-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.4-pro"},"google-gemma-3-27b-it":{"id":"google-gemma-3-27b-it","name":"Google Gemma 3 27B Instruct","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":198000,"output":16384},"cost":{"input":0.12,"output":0.2},"canonical_model_id":"google/gemma-3-27b-it"},"z-ai-glm-5-3":{"id":"z-ai-glm-5-3","name":"GLM 5.3","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.75,"output":5.5,"cache_read":0.325},"canonical_model_id":"zhipuai/glm-5.3"},"zai-org-glm-5-2":{"id":"zai-org-glm-5-2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai-glm-5v-turbo":{"id":"z-ai-glm-5v-turbo","name":"GLM 5V Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32768},"cost":{"input":1.5,"output":5,"cache_read":0.3},"canonical_model_id":"zhipuai/glm-5v-turbo"},"qwen-3-6-plus":{"id":"qwen-3-6-plus","name":"Qwen 3.6 Plus Uncensored","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.625,"output":3.75,"cache_read":0.0625,"cache_write":0.78,"tiers":[{"input":2.5,"output":7.5,"cache_read":0.0625,"cache_write":0.78,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2.5,"output":7.5,"cache_read":0.0625,"cache_write":0.78}},"canonical_model_id":"alibaba/qwen3.6-plus"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"openai-gpt-54":{"id":"openai-gpt-54","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":131072},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"grok-build-0-1":{"id":"grok-build-0-1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":65536},"cost":{"input":1,"output":2,"cache_read":0.2,"tiers":[{"input":2,"output":4,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2,"output":4,"cache_read":0.4}},"canonical_model_id":"xai/grok-build-0.1"},"openai-gpt-6-luna":{"id":"openai-gpt-6-luna","name":"GPT-6 Luna","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"zai-org-glm-4.6":{"id":"zai-org-glm-4.6","name":"GLM 4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":198000,"output":16384},"cost":{"input":0.43,"output":1.75,"cache_read":0.08},"canonical_model_id":"zhipuai/glm-4.6"},"mistral-small-3-2-24b-instruct":{"id":"mistral-small-3-2-24b-instruct","name":"Mistral Small 3.2 24B Instruct","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["image","text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":0.09375,"output":0.25},"canonical_model_id":"mistral/mistral-small-3.2-24b-instruct"},"aion-labs-aion-3-5":{"id":"aion-labs-aion-3-5","name":"Aion 3.5","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":3.75,"output":7.5,"cache_read":0.9375}},"claude-opus-5-fast":{"id":"claude-opus-5-fast","name":"Claude Opus 5 Fast","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-opus-5"},"grok-4-20":{"id":"grok-4-20","name":"Grok 4.20","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-03-12","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":128000},"cost":{"input":1.42,"output":2.83,"cache_read":0.23,"tiers":[{"input":2.83,"output":5.67,"cache_read":0.45,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.83,"output":5.67,"cache_read":0.45}}},"openai-gpt-55":{"id":"openai-gpt-55","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":922000,"output":131072},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"openai-gpt-6-astra":{"id":"openai-gpt-6-astra","name":"GPT-6 Astra","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"olafangensan-glm-4.7-flash-heretic":{"id":"olafangensan-glm-4.7-flash-heretic","name":"GLM 4.7 Flash Heretic","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-02-04","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":24000},"cost":{"input":0.07,"output":0.4,"cache_read":0.035}},"hy4-preview":{"id":"hy4-preview","name":"Hy4 Preview","description":"Preview model for early access evaluation, prototyping, and compatibility testing","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":64000},"cost":{"input":1.0425,"output":3.12625,"cache_read":0.0525},"canonical_model_id":"tencent/hy4-preview"},"minimax-m27":{"id":"minimax-m27","name":"MiniMax M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":198000,"output":32768},"cost":{"input":0.375,"output":1.5,"cache_read":0.06875},"canonical_model_id":"minimax/MiniMax-M2.7"},"openai-gpt-52":{"id":"openai-gpt-52","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":272000,"output":65536},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"qwen3-6-27b":{"id":"qwen3-6-27b","name":"Qwen 3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0.325,"output":3.25},"canonical_model_id":"alibaba/qwen3.6-27b"},"mercury-2":{"id":"mercury-2","name":"Mercury 2","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-24","last_updated":"2026-02-24","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":50000},"cost":{"input":0.3125,"output":0.9375,"cache_read":0.03125},"canonical_model_id":"inception/mercury-2"},"grok-4-6":{"id":"grok-4-6","name":"Grok 4.6","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":200000},"cost":{"input":2.27,"output":6.8,"cache_read":0.57,"tiers":[{"input":4.53,"output":13.6,"cache_read":1.13,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4.53,"output":13.6,"cache_read":1.13}},"canonical_model_id":"xai/grok-4.6"},"openai-gpt-61-sol-ultrafast":{"id":"openai-gpt-61-sol-ultrafast","name":"GPT-6.1 Sol Ultrafast","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":12,"output":60,"cache_read":0.6,"cache_write":15,"tiers":[{"input":24,"output":90,"cache_read":1.2,"cache_write":30,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":24,"output":90,"cache_read":1.2,"cache_write":30}},"canonical_model_id":"openai/gpt-6.1-sol"},"deepseek-v4-1-flash-1017":{"id":"deepseek-v4-1-flash-1017","name":"DeepSeek v4.1 Flash (1017)","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.0075},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"zai-org-glm-5-1":{"id":"zai-org-glm-5-1","name":"GLM 5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":80000},"cost":{"input":1.54,"output":4.84,"cache_read":0.286},"canonical_model_id":"zhipuai/glm-5.1"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"openai-gpt-56-sol-pro":{"id":"openai-gpt-56-sol-pro","name":"GPT-5.6 Sol Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"inkling":{"id":"inkling","name":"Inkling","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":65536},"status":"deprecated","cost":{"input":0.5625,"output":1.5,"cache_read":0.125},"canonical_model_id":"thinkingmachines/inkling"},"minimax-m25":{"id":"minimax-m25","name":"MiniMax M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":198000,"output":32768},"cost":{"input":0.27,"output":0.95,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5"},"mercury-2-5":{"id":"mercury-2-5","name":"Mercury 2.5","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":260000,"output":65536},"cost":{"input":0.25,"output":0.9375,"cache_read":0.025},"canonical_model_id":"inception/mercury-2.5"},"gemini-3-5-flash-lite":{"id":"gemini-3-5-flash-lite","name":"Gemini 3.5 Flash-Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.375,"output":3.125,"cache_read":0.0375},"canonical_model_id":"google/gemini-3.5-flash-lite"},"abliteration-abliterated-model-large-v2":{"id":"abliteration-abliterated-model-large-v2","name":"Abliterated Large V2","description":"Flagship model for demanding analysis, coding, and production agent workflows","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-10-01","last_updated":"2026-10-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":3,"output":5,"cache_read":0.3}},"zai-org-glm-4.7":{"id":"zai-org-glm-4.7","name":"GLM 4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":198000,"output":16384},"cost":{"input":0.55,"output":2.65,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.7"},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"gemini-3-1-pro-preview":{"id":"gemini-3-1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":2.5,"output":15,"cache_read":0.5,"cache_write":0.5,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"cache_write":0.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5,"cache_write":0.5}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"openai-gpt-56-sol":{"id":"openai-gpt-56-sol","name":"GPT-5.6 Sol","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"qwen3-coder-480b-a35b-instruct-turbo":{"id":"qwen3-coder-480b-a35b-instruct-turbo","name":"Qwen 3 Coder 480B Turbo","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-01-27","last_updated":"2026-06-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0.35,"output":1.5,"cache_read":0.04}},"mercury-3":{"id":"mercury-3","name":"Mercury 3","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-16","last_updated":"2026-10-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.1,"output":0.35,"cache_read":0.01},"canonical_model_id":"inception/mercury-3"},"kimi-k3-fast-api":{"id":"kimi-k3-fast-api","name":"Kimi K3 Fast","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":4.5,"output":22.5,"cache_read":0.45},"canonical_model_id":"moonshotai/kimi-k3"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32768},"cost":{"input":0.13,"output":0.26,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"qwen-3-7-plus":{"id":"qwen-3-7-plus","name":"Qwen 3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.5,"output":2,"cache_read":0.05,"cache_write":0.625,"tiers":[{"input":1.5,"output":6,"cache_read":0.15,"cache_write":1.875,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1.5,"output":6,"cache_read":0.15,"cache_write":1.875}},"canonical_model_id":"alibaba/qwen3.7-plus"},"openai-gpt-56-luna":{"id":"openai-gpt-56-luna","name":"GPT-5.6 Luna","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"gemini-3-8-flash":{"id":"gemini-3-8-flash","name":"Gemini 3.8 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.9375,"output":4.6875,"cache_read":0.09375},"canonical_model_id":"google/gemini-3.8-flash"},"llama-3.3-70b":{"id":"llama-3.3-70b","name":"Llama 3.3 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.7,"output":2.8},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"openai-gpt-61-sol":{"id":"openai-gpt-61-sol","name":"GPT-6.1 Sol","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"claude-opus-4-5":{"id":"claude-opus-4-5","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":198000,"output":32768},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"deepseek-v3.2":{"id":"deepseek-v3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":160000,"output":32768},"status":"deprecated","cost":{"input":0.33,"output":0.48,"cache_read":0.16},"canonical_model_id":"deepseek/deepseek-v3.2"},"hermes-3-llama-3.1-405b":{"id":"hermes-3-llama-3.1-405b","name":"Hermes 3 Llama 3.1 405b","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"nousresearch","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-16","last_updated":"2024-08-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":1.1,"output":3},"canonical_model_id":"nousresearch/hermes-3-llama-3.1-405b"},"deepseek-v4-1-flash":{"id":"deepseek-v4-1-flash","name":"DeepSeek V4.1 Flash","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.0075},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"grok-4-5":{"id":"grok-4-5","name":"Grok 4.5","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":32000},"cost":{"input":2.27,"output":6.8,"cache_read":0.34,"tiers":[{"input":4.53,"output":13.6,"cache_read":0.68,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4.53,"output":13.6,"cache_read":0.68}},"canonical_model_id":"xai/grok-4.5"},"openai-gpt-56-terra":{"id":"openai-gpt-56-terra","name":"GPT-5.6 Terra","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"claude-opus-5-5-fast":{"id":"claude-opus-5-5-fast","name":"Claude Opus 5.5 Fast","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":8,"output":40,"cache_read":0.4,"cache_write":10},"canonical_model_id":"anthropic/claude-opus-5-5"},"openai-gpt-56-terra-pro":{"id":"openai-gpt-56-terra-pro","name":"GPT-5.6 Terra Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai-gpt-6-sol":{"id":"openai-gpt-6-sol","name":"GPT-6 Sol","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"claude-opus-4-8-fast":{"id":"claude-opus-4-8-fast","name":"Claude Opus 4.8 Fast","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-opus-4-8"},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32768},"cost":{"input":1.65,"output":4.95,"cache_read":0.165},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"venice-uncensored-1-2":{"id":"venice-uncensored-1-2","name":"Venice Uncensored 1.2","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"venice","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-04-01","last_updated":"2026-06-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.2,"output":0.9}}}},"gmicloud":{"id":"gmicloud","env":["GMICLOUD_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.gmi-serving.com/v1","name":"GMI Cloud","doc":"https://docs.gmicloud.ai/inference-engine/api-reference/llm-api-reference","models":{"Qwen/Qwen3.8-Max":{"id":"Qwen/Qwen3.8-Max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"Qwen/Qwen3.8-Flash":{"id":"Qwen/Qwen3.8-Flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048575,"output":131072},"cost":{"input":0.16,"output":0.47,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"Qwen/Qwen3.7-Max":{"id":"Qwen/Qwen3.7-Max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2.5,"output":7.5,"cache_read":0.25,"cache_write":3.125},"canonical_model_id":"alibaba/qwen3.7-max"},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":409600,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-4.6":{"id":"anthropic/claude-opus-4.6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024,"max":127999}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":409600,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":409600,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":30,"output":150,"cache_read":3,"cache_write":37.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"cost":{"input":4.5,"output":22.5,"cache_read":0.45},"canonical_model_id":"anthropic/claude-opus-4-7"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5"},"zai-org/GLM-5.1-FP8":{"id":"zai-org/GLM-5.1-FP8","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.98,"output":3.08,"cache_read":0.182},"canonical_model_id":"zhipuai/glm-5.1"},"zai-org/GLM-5-FP8":{"id":"zai-org/GLM-5-FP8","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.6,"output":1.92,"cache_read":0.12},"canonical_model_id":"zhipuai/glm-5"},"zai-org/GLM-5.2-FP8":{"id":"zai-org/GLM-5.2-FP8","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.979,"output":3.08,"cache_read":0.182},"canonical_model_id":"zhipuai/glm-5.2"},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.855,"output":3.6,"cache_read":0.144},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2.7-code-highspeed":{"id":"moonshotai/kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code Highspeed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"MiniMaxAI/MiniMax-M2.7":{"id":"MiniMaxAI/MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7"},"MiniMaxAI/MiniMax-M3":{"id":"MiniMaxAI/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.6,"output":2.4,"cache_read":0.12,"tiers":[{"input":1.2,"output":4.8,"cache_read":0.24,"tier":{"type":"context","size":512000}}],"context_over_200k":{"input":1.2,"output":4.8,"cache_read":0.24}},"canonical_model_id":"minimax/MiniMax-M3"},"deepseek-ai/DeepSeek-V4-Pro":{"id":"deepseek-ai/DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":1.392,"output":2.784,"cache_read":0.116},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek-ai/DeepSeek-V4-Flash":{"id":"deepseek-ai/DeepSeek-V4-Flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048575,"output":384000},"cost":{"input":0.112,"output":0.224,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-flash"}}},"reflection":{"id":"reflection","env":["REFLECTION_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.reflection.ai/openai/v1","name":"Reflection","doc":"https://developers.reflection.ai/models","models":{"Beam-1.0-501B-A23B":{"id":"Beam-1.0-501B-A23B","name":"Beam 1.0 501B A23B","description":"Sparse mixture-of-experts reasoning model with 23B active parameters for coding and agentic workflows","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-06-30","release_date":"2026-10-05","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"reflection/beam-1.0-501b-a23b"}}},"ambient":{"id":"ambient","env":["AMBIENT_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.ambient.xyz/v1","name":"Ambient","doc":"https://ambient.xyz","models":{"xiaomi/mimo-v2.5":{"id":"xiaomi/mimo-v2.5","name":"MiMo-V2.5","description":"MiMo omni model for text, image, video, audio, and agents","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0.4,"output":2,"cache_read":0.08,"cache_write":0},"canonical_model_id":"xiaomi/mimo-v2.5"},"ambient/large":{"id":"ambient/large","name":"Ambient Large","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":202752},"cost":{"input":0.6,"output":2,"cache_read":0.15,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"ambient/small":{"id":"ambient/small","name":"Ambient Small","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":101072,"output":101072},"cost":{"input":0.001,"output":0.001,"cache_read":0,"cache_write":0}},"unsloth/qwen3.8-27b-gguf":{"id":"unsloth/qwen3.8-27b-gguf","name":"qwen3.8-27b-4q","description":"Tool-capable chat model for instruction following and agentic application workflows","family":"unsloth","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":101072,"output":101072},"cost":{"input":0.001,"output":0.001,"cache_read":0,"cache_write":0}},"zai-org/GLM-5.1-FP8":{"id":"zai-org/GLM-5.1-FP8","name":"GLM 5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"status":"deprecated","cost":{"input":1.4,"output":4.4,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.1"},"zai-org/GLM-5.2-FP8":{"id":"zai-org/GLM-5.2-FP8","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":202752},"status":"deprecated","cost":{"input":1.2,"output":4.2,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"qwen/qwen3-30b-a3b-instruct-2507":{"id":"qwen/qwen3-30b-a3b-instruct-2507","name":"Qwen3 30B-A3B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.09,"output":0.3,"cache_read":0.09,"cache_write":0},"canonical_model_id":"alibaba/qwen3-30b-a3b-instruct-2507"},"qwen/qwen3.6-27b":{"id":"qwen/qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0.32,"output":3.2,"cache_read":0.16,"cache_write":0},"canonical_model_id":"alibaba/qwen3.6-27b"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0.32,"output":3.2,"cache_read":0.16,"cache_write":0},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3.6-35b-a3b":{"id":"qwen/qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.15,"output":1,"cache_read":0.15,"cache_write":0},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.23,"output":0.96,"cache_read":0.05,"cache_write":0},"canonical_model_id":"minimax/MiniMax-M3"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.95,"output":4,"cache_read":0.2,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.69,"output":3.49,"cache_read":0.14,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"status":"deprecated","cost":{"input":0.14,"output":0.28,"cache_read":0.028,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"status":"deprecated","cost":{"input":0.08,"output":0.18,"cache_read":0.016,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"stepfun/step-3.7-flash":{"id":"stepfun/step-3.7-flash","name":"Step 3.7 Flash","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.19,"output":1.14,"cache_read":0.03,"cache_write":0},"canonical_model_id":"stepfun/step-3.7-flash"},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM-5.2","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":202752},"cost":{"input":0.6,"output":2,"cache_read":0.15,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"}}},"engy":{"id":"engy","env":["ENGY_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.engy.ai/v1","name":"engy","doc":"https://engy.ai/pricing","models":{"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1113088,"input":1047552,"output":65536},"cost":{"input":1.95,"output":9.75,"cache_read":0.195},"canonical_model_id":"moonshotai/kimi-k3"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":229376,"output":32768},"cost":{"input":0.68,"output":1.5,"cache_read":0.18},"canonical_model_id":"zhipuai/glm-5.2"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":983040,"output":65536},"cost":{"input":0.04,"output":0.08,"cache_read":0.008},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":327680,"input":294912,"output":32768},"cost":{"input":0.98,"output":3.08,"cache_read":0.18},"canonical_model_id":"zhipuai/glm-5.3"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":327680,"input":294912,"output":32768},"cost":{"input":0.135,"output":0.45,"cache_read":0.027},"canonical_model_id":"zhipuai/glm-5.3-flash"},"qwen3.8-27b":{"id":"qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1001536,"input":936000,"output":65536},"cost":{"input":0.045,"output":0.32,"cache_read":0.015},"canonical_model_id":"alibaba/qwen3.8-27b"},"deepseek-v4.1-flash-1017":{"id":"deepseek-v4.1-flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":983040,"output":65536},"cost":{"input":0.04,"output":0.08,"cache_read":0.008},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":920576,"output":128000},"cost":{"input":0.045,"output":0.09,"cache_read":0.009},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"qwen3.6-35b-a3b":{"id":"qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":208192,"input":200000,"output":8192},"cost":{"input":0.045,"output":0.3,"cache_read":0.015},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"}}},"vivgrid":{"id":"vivgrid","env":["VIVGRID_API_KEY"],"npm":"@ai-sdk/openai","api":"https://api.vivgrid.com/v1","name":"Vivgrid","doc":"https://docs.vivgrid.com/models","models":{"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"gemini-3.7-flash":{"id":"gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.7-flash"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.44,"output":1.32,"reasoning":1.32,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"gemini-3.1-flash-lite-preview":{"id":"gemini-3.1-flash-lite-preview","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"cache_write":1},"canonical_model_id":"google/gemini-3.1-flash-lite-preview"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":10,"output":50,"cache_read":1.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":1.2,"output":4.2,"cache_read":0.3},"canonical_model_id":"zhipuai/glm-5.2"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.31,"output":1.23,"cache_read":0.01},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":1.2,"output":4.2,"cache_read":0.3},"canonical_model_id":"zhipuai/glm-5.3"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":1.74,"output":3.48,"cache_read":0.14},"canonical_model_id":"deepseek/deepseek-v4-pro"},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.15,"output":0.5,"cache_read":0.04},"canonical_model_id":"zhipuai/glm-5.3-flash"},"viv-fast":{"id":"viv-fast","name":"Viv Fast","description":"Fast coding model","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-09","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":256000},"cost":{"input":0.13,"output":0.4,"cache_read":0.05},"canonical_model_id":"vivgrid/viv-fast"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT 5.6 Luna","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":1,"output":6,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"openai/gpt-5.6-luna"},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":2.5,"output":15,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.4"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"claude-fable-5-1":{"id":"claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":10,"output":50,"cache_read":0.5,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"gpt-5.1-codex-max":{"id":"gpt-5.1-codex-max","name":"GPT-5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex-max"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT 5.6 Sol","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"openai/gpt-5.6-sol"},"gpt-5.2-codex":{"id":"gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-codex"},"gemini-3.1-pro-preview":{"id":"gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":3,"output":12,"cache_read":0.3,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"gpt-5-mini":{"id":"gpt-5-mini","name":"GPT-5 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.25,"output":2,"cache_read":0.03},"canonical_model_id":"openai/gpt-5-mini"},"gpt-5.1-codex":{"id":"gpt-5.1-codex","name":"GPT-5.1 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex"},"gemini-3.8-flash":{"id":"gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":128000},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.75,"output":3.75,"cache_read":0.15},"canonical_model_id":"google/gemini-3.8-flash"},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT 5.6 Terra","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"cache_write":3.125},"canonical_model_id":"openai/gpt-5.6-terra"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"deepseek-v3.2":{"id":"deepseek-v3.2","name":"DeepSeek-V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":0.28,"output":0.42,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v3.2"},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"provider":{"npm":"@ai-sdk/openai-compatible"},"cost":{"input":1.35,"output":3,"reasoning":3,"cache_read":0.05},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"}}},"tokengo":{"id":"tokengo","env":["TOKENGO_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.tokengo.com/v1","name":"TokenGo","doc":"https://www.tokengo.com/docs","models":{"qwen/qwen3.5-397b-a17b":{"id":"qwen/qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.4,"output":2.65,"cache_read":0.2},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.098,"output":0.196,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v3.1":{"id":"deepseek/deepseek-v3.1","name":"DeepSeek-V3.1","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.19,"output":0.71,"cache_read":0.06},"canonical_model_id":"deepseek/deepseek-v3.1"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.435,"output":0.87},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v3.2":{"id":"deepseek/deepseek-v3.2","name":"DeepSeek V3.2","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":64000},"cost":{"input":0.2174,"output":0.326,"cache_read":0.06},"canonical_model_id":"deepseek/deepseek-v3.2"},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/glm-5":{"id":"z-ai/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.89,"output":3.2647,"cache_read":0.2226},"canonical_model_id":"zhipuai/glm-5"},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-5.1":{"id":"z-ai/glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"}}},"alibaba-coding-plan":{"id":"alibaba-coding-plan","env":["ALIBABA_CODING_PLAN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://coding-intl.dashscope.aliyuncs.com/v1","name":"Alibaba Coding Plan","doc":"https://www.alibabacloud.com/help/en/model-studio/coding-plan","models":{"glm-4.7":{"id":"glm-4.7","name":"GLM-4.7","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":16384},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3-coder-plus":{"id":"qwen3-coder-plus","name":"Qwen3 Coder Plus","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"glm-5":{"id":"glm-5","name":"GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-11","last_updated":"2026-02-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":16384},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.7-plus"},"MiniMax-M2.5":{"id":"MiniMax-M2.5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"input":196601,"output":24576},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3-max-2026-01-23":{"id":"qwen3-max-2026-01-23","name":"Qwen3 Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-23","last_updated":"2026-01-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3.6-plus":{"id":"qwen3.6-plus","name":"Qwen3.6 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3-coder-next":{"id":"qwen3-coder-next","name":"Qwen3 Coder Next","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"qwen3.5-plus":{"id":"qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}}}},"infomaniak":{"id":"infomaniak","env":["INFOMANIAK_API_KEY","INFOMANIAK_PRODUCT_ID"],"npm":"@ai-sdk/openai-compatible","api":"https://api.infomaniak.com/2/ai/${INFOMANIAK_PRODUCT_ID}/openai/v1","name":"Infomaniak","doc":"https://www.infomaniak.com/en/hosting/ai-services/open-source-models","models":{"bge_multilingual_gemma2":{"id":"bge_multilingual_gemma2","type":"embedding","name":"BGE Multilingual Gemma2","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-07-25","last_updated":"2026-08-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8000,"input":8000,"output":3584},"cost":{"input":0.08,"output":0}},"mini_lm_l12_v2":{"id":"mini_lm_l12_v2","type":"embedding","name":"All-MiniLM-L12-v2","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2021-08-30","last_updated":"2021-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128,"input":128,"output":384},"cost":{"input":0,"output":0},"canonical_model_id":"sentence-transformers/all-minilm-l12-v2"},"Qwen/Qwen3.5-397B-A17B-FP8":{"id":"Qwen/Qwen3.5-397B-A17B-FP8","name":"Qwen3.5 397B-A17B FP8","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":65536},"status":"beta","cost":{"input":0.99,"output":4.46},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"Qwen/Qwen3.5-122B-A10B-FP8":{"id":"Qwen/Qwen3.5-122B-A10B-FP8","name":"Qwen3.5 122B-A10B FP8","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":65536},"status":"deprecated","cost":{"input":0.5,"output":3.97},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"swiss-ai/Apertus-v1.5-70B":{"id":"swiss-ai/Apertus-v1.5-70B","name":"Apertus v1.5 70B","description":"Open, ethically-sourced Swiss AI model for multilingual, multimodal chat and instruction following","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-07-24","last_updated":"2026-08-01","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":100000,"input":100000,"output":8192},"status":"beta","cost":{"input":0.87,"output":3.1}},"mistralai/Mistral-Small-4-119B-2603":{"id":"mistralai/Mistral-Small-4-119B-2603","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.25,"output":0.93},"canonical_model_id":"mistral/mistral-small-2603"},"mistralai/Ministral-3-14B-Instruct-2512":{"id":"mistralai/Ministral-3-14B-Instruct-2512","name":"Ministral 3 14B Instruct","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":100000,"input":100000,"output":25600},"status":"beta","cost":{"input":0.37,"output":0.5},"canonical_model_id":"mistral/ministral-3-14b-instruct-2512"},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"status":"beta","cost":{"input":0.74,"output":3.72},"canonical_model_id":"moonshotai/kimi-k2.6"},"nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8":{"id":"nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8","name":"Nemotron 3 Nano 30B A3B FP8","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-06-25","release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":262144},"status":"deprecated","cost":{"input":0.06,"output":0.25},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"google/gemma-4-31B-it":{"id":"google/gemma-4-31B-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":100000,"input":100000,"output":32768},"cost":{"input":0.25,"output":0.5},"canonical_model_id":"google/gemma-4-31b-it"}}},"tokenrouter":{"id":"tokenrouter","env":["TOKENROUTER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.tokenrouter.com/v1","name":"TokenRouter","doc":"https://www.tokenrouter.com/docs/tokenrouter-feature-guide/","models":{"z-ai/glm-5.3-free":{"id":"z-ai/glm-5.3-free","name":"GLM-5.3 (free)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-5.3"}}},"scx-ai":{"id":"scx-ai","env":["SCX_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.scx.ai/v1","name":"SCX.ai","doc":"https://platform.scx.ai/docs","models":{"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.17,"output":0.55},"canonical_model_id":"openai/gpt-oss-120b"},"MiniMax-M2.7":{"id":"MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":196608},"cost":{"input":0.48,"output":1.79,"cache_read":0.05},"canonical_model_id":"minimax/MiniMax-M2.7"},"Qwen3.8-Max":{"id":"Qwen3.8-Max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":983616,"output":131072},"cost":{"input":1.815,"output":5.4461,"cache_read":0.17,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"GLM-5.2":{"id":"GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.55,"output":1.784,"cache_read":0.111},"canonical_model_id":"zhipuai/glm-5.2"}}},"umans-ai-coding-plan":{"id":"umans-ai-coding-plan","env":["UMANS_AI_CODING_PLAN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.code.umans.ai/v1","name":"Umans AI Coding Plan","doc":"https://app.umans.ai/offers/code/docs","models":{"umans-deepseek-v4.1-flash":{"id":"umans-deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393215},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"umans-kimi-k3":{"id":"umans-kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k3"},"umans-coder":{"id":"umans-coder","name":"Umans Coder","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131071},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"umans-glm-5.3":{"id":"umans-glm-5.3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131071},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"umans-deepseek-v4-flash-0731":{"id":"umans-deepseek-v4-flash-0731","name":"DeepSeek V4 Flash","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393215},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"umans-flash":{"id":"umans-flash","name":"Umans Flash","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"umans-glm-5.3-flash":{"id":"umans-glm-5.3-flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131071},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"umans-deepseek-v4.1-flash-1017":{"id":"umans-deepseek-v4.1-flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393215},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"umans-qwen3.6-35b-a3b":{"id":"umans-qwen3.6-35b-a3b","name":"Qwen3.6 35B A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"}}},"baseten":{"id":"baseten","env":["BASETEN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://inference.baseten.co/v1","name":"Baseten","doc":"https://docs.baseten.co/inference/model-apis/overview","models":{"thinkingmachines/inkling-small":{"id":"thinkingmachines/inkling-small","name":"Inkling Small","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":32768},"status":"deprecated","cost":{"input":0.5,"output":1.2,"cache_read":0.1},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/inkling":{"id":"thinkingmachines/inkling","name":"Inkling","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":32768},"status":"deprecated","cost":{"input":1,"output":4.05},"canonical_model_id":"thinkingmachines/inkling"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"OpenAI GPT 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128072,"output":128072},"cost":{"input":0.1,"output":0.5,"cache_read":0.1},"canonical_model_id":"openai/gpt-oss-120b"},"zai-org/GLM-4.7":{"id":"zai-org/GLM-4.7","name":"GLM 4.7","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":200000},"status":"deprecated","cost":{"input":0.6,"output":2.2,"cache_read":0.12},"canonical_model_id":"zhipuai/glm-4.7"},"zai-org/GLM-5":{"id":"zai-org/GLM-5","name":"GLM 5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-01","release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202800,"output":202800},"status":"deprecated","cost":{"input":0.95,"output":3.15,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"zai-org/GLM-5.3-Flash":{"id":"zai-org/GLM-5.3-Flash","name":"GLM 5.3 Flash","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/GLM-5.1":{"id":"zai-org/GLM-5.1","name":"GLM 5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202800,"output":202800},"status":"deprecated","cost":{"input":1.3,"output":4.3,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":1.4,"output":4.4,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-5.3":{"id":"zai-org/GLM-5.3","name":"GLM 5.3","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":1.4,"output":4.4,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.3"},"zai-org/GLM-5.3-Fast":{"id":"zai-org/GLM-5.3-Fast","name":"GLM 5.3 Fast","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":2.1,"output":6.6,"cache_read":0.21},"canonical_model_id":"zhipuai/glm-5.3"},"zai-org/GLM-5.2-Fast":{"id":"zai-org/GLM-5.2-Fast","name":"GLM 5.2 Fast","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":2.1,"output":6.6,"cache_read":0.21},"canonical_model_id":"zhipuai/glm-5.2"},"moonshotai/Kimi-K2.5":{"id":"moonshotai/Kimi-K2.5","name":"Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"status":"deprecated","cost":{"input":0.6,"output":3,"cache_read":0.12},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/Kimi-K2.7-Code":{"id":"moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"status":"deprecated","cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"status":"deprecated","cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/Kimi-K3":{"id":"moonshotai/Kimi-K3","name":"Kimi K3","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B":{"id":"nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B","name":"Nemotron Ultra","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202800,"output":202800},"cost":{"input":0.6,"output":2.4,"cache_read":0.12},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/Nemotron-120B-A12B":{"id":"nvidia/Nemotron-120B-A12B","name":"Nemotron Super","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202800,"output":202800},"status":"deprecated","cost":{"input":0.3,"output":0.75,"cache_read":0.06},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"MiniMaxAI/MiniMax-M2.5":{"id":"MiniMaxAI/MiniMax-M2.5","name":"MiniMax-M2.5","description":"Legacy model retained for compatibility with older integrations","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2026-01","release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204000,"output":204000},"status":"deprecated","cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2.5"},"deepseek-ai/DeepSeek-V4.1-Flash-1017-Fast":{"id":"deepseek-ai/DeepSeek-V4.1-Flash-1017-Fast","name":"DeepSeek V4.1 Flash 1017 Fast","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":0.6,"output":2.4,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek-ai/DeepSeek-V4.1-Flash":{"id":"deepseek-ai/DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":32768},"cost":{"input":0.3,"output":1.2,"cache_read":0.007},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek-ai/DeepSeek-V4.1-Flash-Fast":{"id":"deepseek-ai/DeepSeek-V4.1-Flash-Fast","name":"DeepSeek V4.1 Flash Fast","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":32768},"cost":{"input":0.6,"output":2.4,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek-ai/DeepSeek-V4-Pro":{"id":"deepseek-ai/DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"status":"deprecated","cost":{"input":1.74,"output":3.48,"cache_read":0.145},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek-ai/DeepSeek-V4.1-Flash-1017":{"id":"deepseek-ai/DeepSeek-V4.1-Flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":0.3,"output":1.2,"cache_read":0.007},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek-ai/DeepSeek-V4-Flash-0731":{"id":"deepseek-ai/DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.13,"output":0.26,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek-ai/DeepSeek-V4-Pro-0813":{"id":"deepseek-ai/DeepSeek-V4-Pro-0813","name":"DeepSeek V4 Pro 0813","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":1.32,"output":3.96,"cache_read":0.132},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek-ai/DeepSeek-V3.1":{"id":"deepseek-ai/DeepSeek-V3.1","name":"DeepSeek V3.1","description":"Legacy model retained for compatibility with older integrations","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":131000},"status":"deprecated","cost":{"input":0.5,"output":1.5},"canonical_model_id":"deepseek/deepseek-v3.1"}}},"tempr":{"id":"tempr","env":["TEMPR_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.temprhq.io/v1","name":"Tempr Gateway","doc":"https://temprhq.io/docs/gateway-reference.html","models":{"xai/grok-build-0.1":{"id":"xai/grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.2,"tiers":[{"input":2,"output":4,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2,"output":4,"cache_read":0.4}},"canonical_model_id":"xai/grok-build-0.1"},"xai/grok-4.3":{"id":"xai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.3"},"xai/grok-4.7":{"id":"xai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"xai/grok-4.6":{"id":"xai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"xai/grok-4.20-0309-non-reasoning":{"id":"xai/grok-4.20-0309-non-reasoning","name":"Grok 4.20 (Non-Reasoning)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-non-reasoning"},"xai/grok-4.5":{"id":"xai/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.3,"tiers":[{"input":4,"output":12,"cache_read":0.6,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":0.6}},"canonical_model_id":"xai/grok-4.5"},"xai/grok-4.20-0309-reasoning":{"id":"xai/grok-4.20-0309-reasoning","name":"Grok 4.20 (Reasoning)","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-reasoning"},"anthropic/claude-sonnet-4-5":{"id":"anthropic/claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-opus-4-7":{"id":"anthropic/claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic/claude-opus-4-6":{"id":"anthropic/claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-haiku-4-5":{"id":"anthropic/claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-fable-5-1":{"id":"anthropic/claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-opus-4-8":{"id":"anthropic/claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-opus-4-5-20251101":{"id":"anthropic/claude-opus-4-5-20251101","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"anthropic/claude-sonnet-4-6":{"id":"anthropic/claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-sonnet-4-5-20250929":{"id":"anthropic/claude-sonnet-4-5-20250929","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"anthropic/claude-haiku-4-5-20251001":{"id":"anthropic/claude-haiku-4-5-20251001","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"anthropic/claude-opus-4-5":{"id":"anthropic/claude-opus-4-5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"zai/glm-5-turbo":{"id":"zai/glm-5-turbo","name":"GLM-5-Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24,"cache_write":0},"canonical_model_id":"zhipuai/glm-5-turbo"},"zai/glm-4.5v":{"id":"zai/glm-4.5v","name":"GLM-4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":16384},"cost":{"input":0.6,"output":1.8,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5v"},"zai/glm-4.7":{"id":"zai/glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7"},"zai/glm-4.6v":{"id":"zai/glm-4.6v","name":"GLM-4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.3,"output":0.9,"cache_read":0.05},"canonical_model_id":"zhipuai/glm-4.6v"},"zai/glm-5.2":{"id":"zai/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"zai/glm-5v-turbo":{"id":"zai/glm-5v-turbo","name":"GLM-5V-Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24,"cache_write":0},"canonical_model_id":"zhipuai/glm-5v-turbo"},"zai/glm-5":{"id":"zai/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2,"cache_write":0},"canonical_model_id":"zhipuai/glm-5"},"zai/glm-5.3":{"id":"zai/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"zai/glm-5.3-flash":{"id":"zai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai/glm-4.7-flash":{"id":"zai/glm-4.7-flash","name":"GLM-4.7-Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7-flash"},"zai/glm-4.5-air":{"id":"zai/glm-4.5-air","name":"GLM-4.5-Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.2,"output":1.1,"cache_read":0.03,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5-air"},"zai/glm-5.1":{"id":"zai/glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.1"},"zai/glm-4.6":{"id":"zai/glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.6"},"zai/glm-4.5":{"id":"zai/glm-4.5","name":"GLM-4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5"},"zai/glm-4.6v-flash":{"id":"zai/glm-4.6v-flash","name":"GLM-4.6V-Flash","description":"Lightweight GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.6v-flash"},"zai/glm-4.5-flash":{"id":"zai/glm-4.5-flash","name":"GLM-4.5-Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":98304},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5-flash"},"zai/glm-5.3-flashx":{"id":"zai/glm-5.3-flashx","name":"GLM-5.3-FlashX","description":"High-speed GLM-5.3-Flash serving option for coding and agent workflows","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-18","last_updated":"2026-09-18","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.37,"output":1.25,"cache_read":0.075,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai/glm-4.7-flashx":{"id":"zai/glm-4.7-flashx","name":"GLM-4.7-FlashX","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.07,"output":0.4,"cache_read":0.01,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7-flashx"},"groq/allam-2-7b":{"id":"groq/allam-2-7b","name":"ALLaM-2-7b","description":"ALLaM-2-7b instruction tuned model by SDAIA","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-01-23","last_updated":"2025-01-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":4096},"cost":{"input":0,"output":0},"canonical_model_id":"sdaia/allam-2-7b"},"groq/openai/gpt-oss-120b":{"id":"groq/openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-oss-120b"},"groq/openai/gpt-oss-20b":{"id":"groq/openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.075,"output":0.3,"cache_read":0.0375},"canonical_model_id":"openai/gpt-oss-20b"},"groq/qwen/qwen3.8-27b":{"id":"groq/qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131042,"output":16384},"cost":{"input":0.8,"output":4,"cache_read":0.4},"canonical_model_id":"alibaba/qwen3.8-27b"},"xiaomi-mimo/mimo-v2.6-pro-ultraspeed":{"id":"xiaomi-mimo/mimo-v2.6-pro-ultraspeed","name":"MiMo-V2.6-Pro-UltraSpeed","description":"MiMo pro model for strong multimodal reasoning and agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":4.35,"output":8.7,"cache_read":0.036},"canonical_model_id":"xiaomi/mimo-v2.6-pro-ultraspeed"},"xiaomi-mimo/mimo-v2.6-flash":{"id":"xiaomi-mimo/mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"xiaomi-mimo/mimo-v2.6-pro":{"id":"xiaomi-mimo/mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"cerebras/gpt-oss-120b":{"id":"cerebras/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":40960},"cost":{"input":0.35,"output":0.75},"canonical_model_id":"openai/gpt-oss-120b"},"cerebras/qwen-3.8-27b":{"id":"cerebras/qwen-3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":40960},"cost":{"input":0.99,"output":1.49},"canonical_model_id":"alibaba/qwen3.8-27b"},"moonshot/kimi-k3":{"id":"moonshot/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshot/kimi-k2.6":{"id":"moonshot/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshot/kimi-k2.7-code-highspeed":{"id":"moonshot/kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code Highspeed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"moonshot/kimi-k2.7-code":{"id":"moonshot/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"mistral/mistral-large-2512":{"id":"mistral/mistral-large-2512","name":"Mistral Large 3","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":1.5,"cache_read":0.05},"canonical_model_id":"mistral/mistral-large-2512"},"mistral/zai-glm-5-2":{"id":"mistral/zai-glm-5-2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":1.4,"output":4.4,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.2"},"mistral/zai-glm-5-3":{"id":"mistral/zai-glm-5-3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.3"},"mistral/mistral-embed":{"id":"mistral/mistral-embed","type":"embedding","name":"Mistral Embed","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"mistral-embed","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2023-12-11","last_updated":"2023-12-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8000,"output":3072},"cost":{"input":0.1,"output":0},"canonical_model_id":"mistral/mistral-embed"},"mistral/mistral-small-2603":{"id":"mistral/mistral-small-2603","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"mistral/mistral-small-2603"},"mistral/voxtral-small-latest":{"id":"mistral/voxtral-small-latest","name":"Voxtral Small (latest)","description":"Instruct model with native audio input for speech understanding and tool use","family":"voxtral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":32000},"cost":{"input":0.1,"output":0.4},"canonical_model_id":"mistral/voxtral-small-latest"},"mistral/mistral-medium-latest":{"id":"mistral/mistral-medium-latest","name":"Mistral Medium (latest)","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"mistral/mistral-medium-latest"},"mistral/mistral-small-latest":{"id":"mistral/mistral-small-latest","name":"Mistral Small (latest)","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"mistral/mistral-small-latest"},"mistral/mistral-large-latest":{"id":"mistral/mistral-large-latest","name":"Mistral Large (latest)","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11","release_date":"2024-11-01","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":1.5,"cache_read":0.05},"canonical_model_id":"mistral/mistral-large-latest"},"mistral/mistral-medium-2604":{"id":"mistral/mistral-medium-2604","name":"Mistral Medium 3.5","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"mistral/mistral-medium-2604"},"minimax/MiniMax-M2.7":{"id":"minimax/MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/MiniMax-M3":{"id":"minimax/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"tiers":[{"input":0.6,"output":2.4,"cache_read":0.12,"tier":{"type":"context","size":512000}}],"context_over_200k":{"input":0.6,"output":2.4,"cache_read":0.12}},"canonical_model_id":"minimax/MiniMax-M3"},"minimax/MiniMax-M2.7-highspeed":{"id":"minimax/MiniMax-M2.7-highspeed","name":"MiniMax-M2.7-highspeed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","cost":{"input":0.6,"output":2.4,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.66,"output":1.98,"reasoning":1.98,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek/deepseek-flash":{"id":"deepseek/deepseek-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"reasoning":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"google/gemini-embedding-2":{"id":"google/gemini-embedding-2","type":"embedding","name":"Gemini Embedding 2","description":"Multimodal embedding model mapping text, images, video, audio, and PDFs into a unified embedding space","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-11","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1},"cost":{"input":0.2,"output":0},"canonical_model_id":"google/gemini-embedding-2"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"input_audio":0.75},"canonical_model_id":"google/gemini-3.7-flash"},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"input_audio":1},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-flash-lite-latest":{"id":"google/gemini-flash-lite-latest","name":"Gemini Flash-Lite Latest","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-flash-lite-latest"},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemma-4-26b-a4b-it":{"id":"google/gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-embedding-001":{"id":"google/gemini-embedding-001","type":"embedding","name":"Gemini Embedding 001","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-05","release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":2048,"output":1},"cost":{"input":0.15,"output":0},"canonical_model_id":"google/gemini-embedding-001"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"input_audio":0.75},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite"},"google/gemini-3.1-pro-preview-customtools":{"id":"google/gemini-3.1-pro-preview-customtools","name":"Gemini 3.1 Pro Preview Custom Tools","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview-customtools"},"google/gemini-flash-latest":{"id":"google/gemini-flash-latest","name":"Gemini Flash Latest","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"input_audio":0.75},"canonical_model_id":"google/gemini-flash-latest"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"input_audio":0.75},"canonical_model_id":"google/gemini-3.6-flash"}}},"subconscious":{"id":"subconscious","env":["SUBCONSCIOUS_API_KEY"],"npm":"@ai-sdk/anthropic","api":"https://api.subconscious.dev/v1","name":"Subconscious","doc":"https://docs.subconscious.dev","models":{"subconscious/deepseek-v4.1-flash-marathon":{"id":"subconscious/deepseek-v4.1-flash-marathon","name":"DeepSeek V4.1 Flash Marathon","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":5000000,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"subconscious/glm-5.3-marathon":{"id":"subconscious/glm-5.3-marathon","name":"GLM-5.3 Marathon","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":5000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"}}},"commandcode":{"id":"commandcode","env":["CMD_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.commandcode.ai/provider/v1","name":"CommandCode","doc":"https://commandcode.ai/docs/provider","models":{"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":2,"output":8,"cache_read":0.5,"cache_write":0},"canonical_model_id":"openai/gpt-5.3-codex"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"cache_write":0},"canonical_model_id":"openai/gpt-5.4"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075,"cache_write":0},"canonical_model_id":"openai/gpt-5.4-mini"},"claude-fable-5-1":{"id":"claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":45,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1,"cache_write":12.5}},"canonical_model_id":"openai/gpt-5.6-sol"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":0},"canonical_model_id":"openai/gpt-5.5"},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"claude-haiku-4-5-20251001":{"id":"claude-haiku-4-5-20251001","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic"},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"thinkingmachines/inkling-small":{"id":"thinkingmachines/inkling-small","name":"Inkling Small","description":"Multimodal MoE reasoning model (276B total, 12B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":1000000},"cost":{"input":0.5,"output":1.2,"cache_read":0.1},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/inkling":{"id":"thinkingmachines/inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":4.05,"cache_read":0.17},"canonical_model_id":"thinkingmachines/inkling"},"Qwen/Qwen3.8-Max":{"id":"Qwen/Qwen3.8-Max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"Qwen/Qwen3.8-Max-0902":{"id":"Qwen/Qwen3.8-Max-0902","name":"Qwen3.8 Max 0902","description":"2026-09-02 upgraded snapshot of Qwen3.8 Max with stronger coding, collaborative agents, and multimodal document understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-max-0902"},"Qwen/Qwen3.8-Omni-Flash":{"id":"Qwen/Qwen3.8-Omni-Flash","name":"Qwen3.8 Omni Flash","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-omni-flash"},"Qwen/Qwen3.8-27B":{"id":"Qwen/Qwen3.8-27B","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.4,"output":3,"cache_read":0.04},"canonical_model_id":"alibaba/qwen3.8-27b"},"Qwen/Qwen3.8-Flash":{"id":"Qwen/Qwen3.8-Flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.16,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-flash"},"xai/grok-4.7":{"id":"xai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"xai/grok-4.6":{"id":"xai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"xai/grok-4.5":{"id":"xai/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.5"},"inclusionai/ling-3.1-flash:free":{"id":"inclusionai/ling-3.1-flash:free","name":"Ling 3.1 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"inclusionai/ling-3.1-flash"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-5.3":{"id":"zai-org/GLM-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"zai-org/GLM-5.2-Fast":{"id":"zai-org/GLM-5.2-Fast","name":"GLM-5.2-Fast","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":3,"output":10.25,"cache_read":0.5},"canonical_model_id":"zhipuai/glm-5.2"},"mistral/mistral-large-4":{"id":"mistral/mistral-large-4","name":"Mistral Large 4","description":"Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":262144},"cost":{"input":1.36,"output":4.18,"cache_read":0.14},"canonical_model_id":"mistral/mistral-large-4"},"sakana/fugu-ultra":{"id":"sakana/fugu-ultra","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"sakana/fugu-ultra"},"moonshotai/Kimi-K2.7-Code":{"id":"moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"moonshotai/Kimi-K3":{"id":"moonshotai/Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/Kimi-K2.7-Code-Highspeed":{"id":"moonshotai/Kimi-K2.7-Code-Highspeed","name":"Kimi K2.7 Code Highspeed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.66,"output":1.98,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v4.1-flash-fast":{"id":"deepseek/deepseek-v4.1-flash-fast","name":"DeepSeek V4.1 Flash Fast","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.16,"output":0.58,"cache_read":0.016},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-flash-fast":{"id":"deepseek/deepseek-v4-flash-fast","name":"DeepSeek V4 Flash Fast","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.28,"output":0.56,"cache_read":0.07},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v4-flash-vision-exp":{"id":"deepseek/deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"nvidia/nemotron-3-ultra-550b-a55b":{"id":"nvidia/nemotron-3-ultra-550b-a55b","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.6,"output":2.4,"cache_read":0.12},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"tencent/hy3-paid":{"id":"tencent/hy3-paid","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":192000,"output":128000},"cost":{"input":0.14,"output":0.58,"cache_read":0.035},"canonical_model_id":"tencent/hy3"},"tencent/hy4-preview":{"id":"tencent/hy4-preview","name":"Hy4 preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":64000},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"},"MiniMaxAI/MiniMax-M2.7":{"id":"MiniMaxAI/MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7"},"MiniMaxAI/MiniMax-M2.5":{"id":"MiniMaxAI/MiniMax-M2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5"},"MiniMaxAI/MiniMax-M3":{"id":"MiniMaxAI/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":512000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"meta/muse-spark-1.3":{"id":"meta/muse-spark-1.3","name":"Muse Spark 1.3","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.3"},"meta/muse-spark-1.2":{"id":"meta/muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"meta/muse-spark-1.2-contributor":{"id":"meta/muse-spark-1.2-contributor","name":"Muse Spark 1.2 (Contributor)","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.1,"output":0.2,"cache_read":0.002},"canonical_model_id":"meta/muse-spark-1.2"},"meta/muse-spark-1.1":{"id":"meta/muse-spark-1.1","name":"Muse Spark 1.1","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.1"},"meta/muse-spark-1.3-contributor":{"id":"meta/muse-spark-1.3-contributor","name":"Muse Spark 1.3 (Contributor)","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.1,"output":0.2,"cache_read":0.002},"canonical_model_id":"meta/muse-spark-1.3"},"meta/muse-wonder-1.0":{"id":"meta/muse-wonder-1.0","name":"Muse Wonder","description":"Muse Wonder is a frontier multimodal reasoning model from Meta for personal and professional agents, long-horizon coding, and computer use. It combines Active Memory, which carries relevant context across conversations, with Active Focus, which keeps it working through blockers toward a goal.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":4,"output":20,"cache_read":0.2},"canonical_model_id":"meta/muse-wonder-1.0"},"stepfun/Step-3.5-Flash":{"id":"stepfun/Step-3.5-Flash","name":"Step 3.5 Flash","description":"StepFun flash lane for quick multimodal reasoning and coding assistance","family":"step","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.09,"output":0.3,"cache_read":0.02},"canonical_model_id":"stepfun/step-3.5-flash"},"stepfun/Step-5-Preview":{"id":"stepfun/Step-5-Preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":1000000},"cost":{"input":1,"output":2.7,"cache_read":0.05},"canonical_model_id":"stepfun/step-5-preview"},"stepfun/Step-3.7-Flash":{"id":"stepfun/Step-3.7-Flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-5.3-flashx":{"id":"z-ai/glm-5.3-flashx","name":"GLM-5.3-FlashX","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.37,"output":1.25,"cache_read":0.075},"canonical_model_id":"zhipuai/glm-5.3-flash"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"cache_read":0.15,"cache_write":0.08334},"canonical_model_id":"google/gemini-3.7-flash"},"google/gemini-4-argon":{"id":"google/gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":2,"output":10,"cache_read":0.1},"canonical_model_id":"google/gemini-4-argon"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.1-flash-lite"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"google/gemini-3.6-flash"}}},"inceptron":{"id":"inceptron","env":["INCEPTRON_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.inceptron.io/v1","name":"Inceptron","doc":"https://docs.inceptron.io","models":{"zai-org/GLM-5.3-Flash":{"id":"zai-org/GLM-5.3-Flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.15,"output":0.69,"cache_read":0.075,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.69,"output":2.52,"cache_read":0.14,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-5.3":{"id":"zai-org/GLM-5.3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.55,"output":1.96,"cache_read":0.18,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"moonshotai/Kimi-K2.7-Code":{"id":"moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6712,"output":3.35,"cache_read":0.18,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.495,"output":3.2,"cache_read":0.1125,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.6"},"deepseek-ai/DeepSeek-V4-Flash-0731":{"id":"deepseek-ai/DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.11,"output":0.4125,"cache_read":0.027,"cache_write":0},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"}}},"amazon-bedrock":{"id":"amazon-bedrock","env":["AWS_ACCESS_KEY_ID","AWS_SECRET_ACCESS_KEY","AWS_REGION","AWS_BEARER_TOKEN_BEDROCK"],"npm":"@ai-sdk/amazon-bedrock","name":"Amazon Bedrock","doc":"https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html","models":{"xai.grok-4.3":{"id":"xai.grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-06-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":1.25,"output":2.5,"cache_read":0.2},"canonical_model_id":"xai/grok-4.3"},"us.anthropic.claude-opus-4-7":{"id":"us.anthropic.claude-opus-4-7","name":"Claude Opus 4.7 (US)","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-7"},"us.meta.llama4-scout-17b-instruct-v1:0":{"id":"us.meta.llama4-scout-17b-instruct-v1:0","name":"Llama 4 Scout 17B Instruct (US)","description":"Open Llama with long-context vision for efficient multimodal agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":10000000,"output":8192},"status":"deprecated","cost":{"input":0.17,"output":0.66},"canonical_model_id":"meta/llama-4-scout-17b-instruct"},"global.openai.gpt-5.6-terra":{"id":"global.openai.gpt-5.6-terra","name":"GPT-5.6 Terra (Global)","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"global.xai.grok-4.7":{"id":"global.xai.grok-4.7","name":"Grok 4.7 (Global)","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.7"},"openai.gpt-oss-safeguard-120b":{"id":"openai.gpt-oss-safeguard-120b","name":"GPT OSS Safeguard 120B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-safeguard-120b"},"us.anthropic.claude-opus-5":{"id":"us.anthropic.claude-opus-5","name":"Claude Opus 5 (US)","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-5"},"eu.anthropic.claude-haiku-5-5":{"id":"eu.anthropic.claude-haiku-5-5","name":"Claude Haiku 5.5 (EU)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.11,"output":0.55,"cache_read":0.011,"cache_write":0.1375,"tiers":[{"input":0.55,"output":2.75,"cache_read":0.055,"cache_write":0.6875,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"minimax.minimax-m2":{"id":"minimax.minimax-m2","name":"MiniMax-M2","description":"Efficient open MiniMax model built for coding agents and tool-heavy workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204608,"output":128000},"status":"deprecated","cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2"},"writer.palmyra-x5-v1:0":{"id":"writer.palmyra-x5-v1:0","name":"Palmyra X5","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"palmyra","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1040000,"input":1040000,"output":8192},"status":"deprecated","cost":{"input":0.6,"output":6},"canonical_model_id":"writer/palmyra-x5"},"us.moonshotai.kimi-k3":{"id":"us.moonshotai.kimi-k3","name":"Kimi K3 (US)","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":128000},"cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"moonshotai/kimi-k3"},"au.anthropic.claude-sonnet-5":{"id":"au.anthropic.claude-sonnet-5","name":"Claude Sonnet 5 (AU)","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.22,"cache_write":2.75},"canonical_model_id":"anthropic/claude-sonnet-5"},"us.openai.gpt-6-astra":{"id":"us.openai.gpt-6-astra","name":"GPT-6 Astra (US)","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"ultrafast":{"cost":{"input":66,"output":330,"cache_read":6.6,"cache_write":82.5},"provider":{"body":{"additionalModelRequestFields":{"service_tier":"ultrafast"}}}}}},"cost":{"input":11,"output":55,"cache_read":1.1,"cache_write":13.75,"tiers":[{"input":22,"output":82.5,"cache_read":2.2,"cache_write":27.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":22,"output":82.5,"cache_read":2.2,"cache_write":27.5}},"canonical_model_id":"openai/gpt-6-astra"},"mistral.magistral-small-2509":{"id":"mistral.magistral-small-2509","name":"Magistral Small 1.2","description":"Open multimodal reasoning model for transparent analysis of text and images","family":"magistral","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-18","last_updated":"2025-09-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":40000},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"mistral/magistral-small-2509"},"us.anthropic.claude-fable-5-1":{"id":"us.anthropic.claude-fable-5-1","name":"Claude Fable 5.1 (US)","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":11,"output":55,"cache_read":0.275,"cache_write":13.75},"canonical_model_id":"anthropic/claude-fable-5-1"},"openai.gpt-5.5":{"id":"openai.gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-06-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":5.5,"output":33,"cache_read":0.55},"canonical_model_id":"openai/gpt-5.5"},"openai.gpt-oss-20b":{"id":"openai.gpt-oss-20b","name":"gpt-oss-20b","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/v1","shape":"responses"},"cost":{"input":0.07,"output":0.3},"canonical_model_id":"openai/gpt-oss-20b"},"google.gemma-3-27b-it":{"id":"google.gemma-3-27b-it","name":"Gemma 3 27B IT","description":"Largest open Gemma 3 instruction model for multilingual text generation and visual understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.23,"output":0.38},"canonical_model_id":"google/gemma-3-27b-it"},"us.writer.palmyra-x4-v1:0":{"id":"us.writer.palmyra-x4-v1:0","name":"Palmyra X4 (US)","description":"Enterprise language model for workflow automation, coding, data analysis, and tool use","family":"palmyra","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2024-10-09","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":122880,"output":8192},"status":"deprecated","cost":{"input":2.5,"output":10},"canonical_model_id":"writer/palmyra-x4"},"apac.anthropic.claude-sonnet-4-20250514-v1:0":{"id":"apac.anthropic.claude-sonnet-4-20250514-v1:0","name":"Claude Sonnet 4 (APAC)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-20250514"},"global.anthropic.claude-sonnet-5-5":{"id":"global.anthropic.claude-sonnet-5-5","name":"Claude Sonnet 5.5 (Global)","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"openai.gpt-6-astra":{"id":"openai.gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"ultrafast":{"cost":{"input":66,"output":330,"cache_read":6.6,"cache_write":82.5},"provider":{"body":{"service_tier":"ultrafast"}}}}},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":11,"output":55,"cache_read":1.1,"cache_write":13.75,"tiers":[{"input":22,"output":82.5,"cache_read":2.2,"cache_write":27.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":22,"output":82.5,"cache_read":2.2,"cache_write":27.5}},"canonical_model_id":"openai/gpt-6-astra"},"jp.anthropic.claude-opus-4-7":{"id":"jp.anthropic.claude-opus-4-7","name":"Claude Opus 4.7 (JP)","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-7"},"us.meta.llama3-1-8b-instruct-v1:0":{"id":"us.meta.llama3-1-8b-instruct-v1:0","name":"Llama 3.1 8B Instruct (US)","description":"Compact open Llama model for lightweight chat, drafting, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0.22,"output":0.22},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"eu.amazon.nova-lite-v1:0":{"id":"eu.amazon.nova-lite-v1:0","name":"Nova Lite (EU)","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.069,"output":0.276,"cache_read":0.01725,"cache_write":0.069},"canonical_model_id":"amazon/nova-lite"},"eu.amazon.nova-pro-v1:0":{"id":"eu.amazon.nova-pro-v1:0","name":"Nova Pro (EU)","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.92,"output":3.68,"cache_read":0.23,"cache_write":0.92},"canonical_model_id":"amazon/nova-pro"},"us.anthropic.claude-sonnet-4-5-20250929-v1:0":{"id":"us.anthropic.claude-sonnet-4-5-20250929-v1:0","name":"Claude Sonnet 4.5 (US)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"anthropic.claude-sonnet-4-5-20250929-v1:0":{"id":"anthropic.claude-sonnet-4-5-20250929-v1:0","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"us.anthropic.claude-haiku-5-5":{"id":"us.anthropic.claude-haiku-5-5","name":"Claude Haiku 5.5 (US)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.11,"output":0.55,"cache_read":0.011,"cache_write":0.1375,"tiers":[{"input":0.55,"output":2.75,"cache_read":0.055,"cache_write":0.6875,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"jp.anthropic.claude-haiku-5-5":{"id":"jp.anthropic.claude-haiku-5-5","name":"Claude Haiku 5.5 (JP)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.11,"output":0.55,"cache_read":0.011,"cache_write":0.1375,"tiers":[{"input":0.55,"output":2.75,"cache_read":0.055,"cache_write":0.6875,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"minimax.minimax-m2.5":{"id":"minimax.minimax-m2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":98304},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2.5"},"us.anthropic.claude-fable-5":{"id":"us.anthropic.claude-fable-5","name":"Claude Fable 5 (US)","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":11,"output":55,"cache_read":1.1,"cache_write":13.75},"canonical_model_id":"anthropic/claude-fable-5"},"global.openai.gpt-6.1-sol":{"id":"global.openai.gpt-6.1-sol","name":"GPT-6.1 Sol (Global)","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"ultrafast":{"cost":{"input":12,"output":60,"cache_read":0.6,"cache_write":15},"provider":{"body":{"additionalModelRequestFields":{"service_tier":"ultrafast"}}}}}},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"us.xai.grok-4.6":{"id":"us.xai.grok-4.6","name":"Grok 4.6 (US)","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2.2,"output":6.6,"cache_read":0.55},"canonical_model_id":"xai/grok-4.6"},"qwen.qwen3-vl-235b-a22b":{"id":"qwen.qwen3-vl-235b-a22b","name":"Qwen3 VL 235B A22B Instruct","description":"Qwen vision-language instruct model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262000},"cost":{"input":0.53,"output":2.66},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"us.writer.palmyra-x5-v1:0":{"id":"us.writer.palmyra-x5-v1:0","name":"Palmyra X5 (US)","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"palmyra","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1040000,"input":1040000,"output":8192},"status":"deprecated","cost":{"input":0.6,"output":6},"canonical_model_id":"writer/palmyra-x5"},"in.openai.gpt-5.6-terra":{"id":"in.openai.gpt-5.6-terra","name":"GPT-5.6 Terra (India)","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.2,"output":13.2,"cache_read":0.22,"cache_write":2.75,"tiers":[{"input":4.4,"output":19.8,"cache_read":0.44,"cache_write":5.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4.4,"output":19.8,"cache_read":0.44,"cache_write":5.5}},"canonical_model_id":"openai/gpt-5.6-terra"},"in.anthropic.claude-sonnet-5":{"id":"in.anthropic.claude-sonnet-5","name":"Claude Sonnet 5 (India)","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.22,"cache_write":2.75},"canonical_model_id":"anthropic/claude-sonnet-5"},"mistral.mistral-large-3-675b-instruct":{"id":"mistral.mistral-large-3-675b-instruct","name":"Mistral Large 3","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"mistral/mistral-large-2512"},"anthropic.claude-opus-4-8":{"id":"anthropic.claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"qwen.qwen3-235b-a22b-2507-v1:0":{"id":"qwen.qwen3-235b-a22b-2507-v1:0","name":"Qwen3 235B-A22B Instruct 2507","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-09-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.22,"output":0.88},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"deepseek.r1-v1:0":{"id":"deepseek.r1-v1:0","name":"DeepSeek-R1","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"status":"deprecated","cost":{"input":1.35,"output":5.4},"canonical_model_id":"deepseek/deepseek-r1"},"us.openai.gpt-5.6-luna":{"id":"us.openai.gpt-5.6-luna","name":"GPT-5.6 Luna (US)","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.22,"output":1.32,"cache_read":0.022,"cache_write":0.275,"tiers":[{"input":0.44,"output":1.98,"cache_read":0.044,"cache_write":0.55,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.44,"output":1.98,"cache_read":0.044,"cache_write":0.55}},"canonical_model_id":"openai/gpt-5.6-luna"},"qwen.qwen3-coder-480b-a35b-v1:0":{"id":"qwen.qwen3-coder-480b-a35b-v1:0","name":"Qwen3-Coder 480B-A35B Instruct","description":"Open Qwen coding heavyweight for repository reasoning and agentic engineering","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-09-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"status":"deprecated","cost":{"input":0.45,"output":1.8},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"nvidia.nemotron-nano-3-30b":{"id":"nvidia.nemotron-nano-3-30b","name":"NVIDIA Nemotron Nano 3 30B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06-25","release_date":"2025-12-15","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.06,"output":0.24},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"global.anthropic.claude-sonnet-5":{"id":"global.anthropic.claude-sonnet-5","name":"Claude Sonnet 5 (Global)","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"zai.glm-5":{"id":"zai.glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":1,"output":3.2},"canonical_model_id":"zhipuai/glm-5"},"au.anthropic.claude-haiku-4-5-20251001-v1:0":{"id":"au.anthropic.claude-haiku-4-5-20251001-v1:0","name":"Claude Haiku 4.5 (AU)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1.1,"output":5.5,"cache_read":0.11,"cache_write":1.375},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"us.meta.llama3-3-70b-instruct-v1:0":{"id":"us.meta.llama3-3-70b-instruct-v1:0","name":"Llama 3.3 70B Instruct (US)","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0.72,"output":0.72},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"global.moonshotai.kimi-k3":{"id":"global.moonshotai.kimi-k3","name":"Kimi K3 (Global)","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"moonshotai/kimi-k3"},"anthropic.claude-opus-4-7":{"id":"anthropic.claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"jp.anthropic.claude-opus-5":{"id":"jp.anthropic.claude-opus-5","name":"Claude Opus 5 (JP)","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-5"},"au.anthropic.claude-haiku-5-5":{"id":"au.anthropic.claude-haiku-5-5","name":"Claude Haiku 5.5 (AU)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.11,"output":0.55,"cache_read":0.011,"cache_write":0.1375,"tiers":[{"input":0.55,"output":2.75,"cache_read":0.055,"cache_write":0.6875,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"us.deepseek.r1-v1:0":{"id":"us.deepseek.r1-v1:0","name":"DeepSeek-R1 (US)","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"status":"deprecated","cost":{"input":1.35,"output":5.4},"canonical_model_id":"deepseek/deepseek-r1"},"nvidia.nemotron-nano-12b-v2":{"id":"nvidia.nemotron-nano-12b-v2","name":"NVIDIA Nemotron Nano 12B v2 VL BF16","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","family":"nemotron","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-28","last_updated":"2025-10-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.2,"output":0.6},"canonical_model_id":"nvidia/nemotron-nano-12b-v2-vl"},"anthropic.claude-opus-5":{"id":"anthropic.claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic.claude-sonnet-5":{"id":"anthropic.claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"openai.gpt-6-luna":{"id":"openai.gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":0.11,"output":0.55,"cache_read":0.011,"cache_write":0.1375,"tiers":[{"input":0.22,"output":0.825,"cache_read":0.022,"cache_write":0.275,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.22,"output":0.825,"cache_read":0.022,"cache_write":0.275}},"canonical_model_id":"openai/gpt-6-luna"},"global.anthropic.claude-fable-5":{"id":"global.anthropic.claude-fable-5","name":"Claude Fable 5 (Global)","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"global.anthropic.claude-opus-4-7":{"id":"global.anthropic.claude-opus-4-7","name":"Claude Opus 4.7 (Global)","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"eu.anthropic.claude-sonnet-5":{"id":"eu.anthropic.claude-sonnet-5","name":"Claude Sonnet 5 (EU)","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.22,"cache_write":2.75},"canonical_model_id":"anthropic/claude-sonnet-5"},"au.anthropic.claude-opus-4-8":{"id":"au.anthropic.claude-opus-4-8","name":"Claude Opus 4.8 (AU)","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-8"},"openai.gpt-5.6-terra":{"id":"openai.gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":2.2,"output":13.2,"cache_read":0.22,"cache_write":2.75,"tiers":[{"input":4.4,"output":19.8,"cache_read":0.44,"cache_write":5.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4.4,"output":19.8,"cache_read":0.44,"cache_write":5.5}},"canonical_model_id":"openai/gpt-5.6-terra"},"moonshotai.kimi-k2.5":{"id":"moonshotai.kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-02-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.6,"output":3},"canonical_model_id":"moonshotai/kimi-k2.5"},"meta.llama3-3-70b-instruct-v1:0":{"id":"meta.llama3-3-70b-instruct-v1:0","name":"Llama 3.3 70B Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0.72,"output":0.72},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"us.anthropic.claude-opus-5-5":{"id":"us.anthropic.claude-opus-5-5","name":"Claude Opus 5.5 (US)","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4.4,"output":22,"cache_read":0.22,"cache_write":5.5},"canonical_model_id":"anthropic/claude-opus-5-5"},"au.anthropic.claude-sonnet-4-5-20250929-v1:0":{"id":"au.anthropic.claude-sonnet-4-5-20250929-v1:0","name":"Claude Sonnet 4.5 (AU)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"us.amazon.nova-lite-v1:0":{"id":"us.amazon.nova-lite-v1:0","name":"Nova Lite (US)","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.06,"output":0.24,"cache_read":0.015,"cache_write":0.06},"canonical_model_id":"amazon/nova-lite"},"anthropic.claude-opus-4-1-20250805-v1:0":{"id":"anthropic.claude-opus-4-1-20250805-v1:0","name":"Claude Opus 4.1","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1-20250805"},"global.openai.gpt-6-astra":{"id":"global.openai.gpt-6-astra","name":"GPT-6 Astra (Global)","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"ultrafast":{"cost":{"input":60,"output":300,"cache_read":6,"cache_write":75},"provider":{"body":{"additionalModelRequestFields":{"service_tier":"ultrafast"}}}}}},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"us.amazon.nova-premier-v1:0":{"id":"us.amazon.nova-premier-v1:0","name":"Nova Premier (US)","description":"Multimodal model for complex analysis, long-context understanding, tool use, and model distillation","family":"nova","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10","release_date":"2025-04-30","last_updated":"2025-04-30","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":10000},"status":"deprecated","cost":{"input":2.5,"output":12.5,"cache_read":0.625,"cache_write":2.5},"canonical_model_id":"amazon/nova-premier"},"us.anthropic.claude-sonnet-5-5":{"id":"us.anthropic.claude-sonnet-5-5","name":"Claude Sonnet 5.5 (US)","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.11,"cache_write":2.75},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"global.anthropic.claude-haiku-5-5":{"id":"global.anthropic.claude-haiku-5-5","name":"Claude Haiku 5.5 (Global)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"global.anthropic.claude-opus-5-5":{"id":"global.anthropic.claude-opus-5-5","name":"Claude Opus 5.5 (Global)","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"amazon.nova-pro-v1:0":{"id":"amazon.nova-pro-v1:0","name":"Nova Pro","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.8,"output":3.2,"cache_read":0.2,"cache_write":0.8},"canonical_model_id":"amazon/nova-pro"},"eu.anthropic.claude-haiku-4-5-20251001-v1:0":{"id":"eu.anthropic.claude-haiku-4-5-20251001-v1:0","name":"Claude Haiku 4.5 (EU)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1.1,"output":5.5,"cache_read":0.11,"cache_write":1.375},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"openai.gpt-6.1-sol":{"id":"openai.gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"ultrafast":{"cost":{"input":13.2,"output":66,"cache_read":0.66,"cache_write":16.5},"provider":{"body":{"service_tier":"ultrafast"}}}}},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":2.2,"output":11,"cache_read":0.11,"cache_write":2.75,"tiers":[{"input":4.4,"output":16.5,"cache_read":0.22,"cache_write":5.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4.4,"output":16.5,"cache_read":0.22,"cache_write":5.5}},"canonical_model_id":"openai/gpt-6.1-sol"},"amazon.nova-2-lite-v1:0":{"id":"amazon.nova-2-lite-v1:0","name":"Nova 2 Lite","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-10","release_date":"2025-12-02","last_updated":"2025-12-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.33,"output":2.75,"cache_read":0.0825,"cache_write":0.33},"canonical_model_id":"amazon/nova-2-lite"},"openai.gpt-5.4":{"id":"openai.gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-06-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":2.75,"output":16.5,"cache_read":0.275},"canonical_model_id":"openai/gpt-5.4"},"anthropic.claude-sonnet-4-6":{"id":"anthropic.claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"us.openai.gpt-6-luna":{"id":"us.openai.gpt-6-luna","name":"GPT-6 Luna (US)","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.11,"output":0.55,"cache_read":0.011,"cache_write":0.1375,"tiers":[{"input":0.22,"output":0.825,"cache_read":0.022,"cache_write":0.275,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.22,"output":0.825,"cache_read":0.022,"cache_write":0.275}},"canonical_model_id":"openai/gpt-6-luna"},"us.anthropic.claude-sonnet-5":{"id":"us.anthropic.claude-sonnet-5","name":"Claude Sonnet 5 (US)","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.22,"cache_write":2.75},"canonical_model_id":"anthropic/claude-sonnet-5"},"eu.anthropic.claude-opus-4-8":{"id":"eu.anthropic.claude-opus-4-8","name":"Claude Opus 4.8 (EU)","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-8"},"us.anthropic.claude-sonnet-4-20250514-v1:0":{"id":"us.anthropic.claude-sonnet-4-20250514-v1:0","name":"Claude Sonnet 4 (US)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-20250514"},"us.anthropic.claude-opus-4-1-20250805-v1:0":{"id":"us.anthropic.claude-opus-4-1-20250805-v1:0","name":"Claude Opus 4.1 (US)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1-20250805"},"meta.llama3-1-70b-instruct-v1:0":{"id":"meta.llama3-1-70b-instruct-v1:0","name":"Llama 3.1 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0.72,"output":0.72},"canonical_model_id":"meta/llama-3.1-70b-instruct"},"in.anthropic.claude-haiku-4-5-20251001-v1:0":{"id":"in.anthropic.claude-haiku-4-5-20251001-v1:0","name":"Claude Haiku 4.5 (India)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1.1,"output":5.5,"cache_read":0.11,"cache_write":1.375},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"global.anthropic.claude-opus-4-5-20251101-v1:0":{"id":"global.anthropic.claude-opus-4-5-20251101-v1:0","name":"Claude Opus 4.5 (Global)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"zai.glm-4.7":{"id":"zai.glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"status":"deprecated","cost":{"input":0.6,"output":2.2},"canonical_model_id":"zhipuai/glm-4.7"},"openai.gpt-5.6-luna":{"id":"openai.gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":0.22,"output":1.32,"cache_read":0.022,"cache_write":0.275,"tiers":[{"input":0.44,"output":1.98,"cache_read":0.044,"cache_write":0.55,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.44,"output":1.98,"cache_read":0.044,"cache_write":0.55}},"canonical_model_id":"openai/gpt-5.6-luna"},"eu.anthropic.claude-fable-5":{"id":"eu.anthropic.claude-fable-5","name":"Claude Fable 5 (EU)","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":11,"output":55,"cache_read":1.1,"cache_write":13.75},"canonical_model_id":"anthropic/claude-fable-5"},"eu.anthropic.claude-sonnet-5-5":{"id":"eu.anthropic.claude-sonnet-5-5","name":"Claude Sonnet 5.5 (EU)","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.11,"cache_write":2.75},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"in.openai.gpt-5.6-luna":{"id":"in.openai.gpt-5.6-luna","name":"GPT-5.6 Luna (India)","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.22,"output":1.32,"cache_read":0.022,"cache_write":0.275,"tiers":[{"input":0.44,"output":1.98,"cache_read":0.044,"cache_write":0.55,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.44,"output":1.98,"cache_read":0.044,"cache_write":0.55}},"canonical_model_id":"openai/gpt-5.6-luna"},"eu.anthropic.claude-opus-5":{"id":"eu.anthropic.claude-opus-5","name":"Claude Opus 5 (EU)","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-5"},"google.gemma-3-12b-it":{"id":"google.gemma-3-12b-it","name":"Gemma 3 12B IT","description":"Open multimodal Gemma instruction model for multilingual text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.09,"output":0.29},"canonical_model_id":"google/gemma-3-12b-it"},"global.anthropic.claude-sonnet-4-5-20250929-v1:0":{"id":"global.anthropic.claude-sonnet-4-5-20250929-v1:0","name":"Claude Sonnet 4.5 (Global)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"us.anthropic.claude-sonnet-4-6":{"id":"us.anthropic.claude-sonnet-4-6","name":"Claude Sonnet 4.6 (US)","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"eu.anthropic.claude-sonnet-4-5-20250929-v1:0":{"id":"eu.anthropic.claude-sonnet-4-5-20250929-v1:0","name":"Claude Sonnet 4.5 (EU)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"au.anthropic.claude-opus-5-5":{"id":"au.anthropic.claude-opus-5-5","name":"Claude Opus 5.5 (AU)","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4.4,"output":22,"cache_read":0.22,"cache_write":5.5},"canonical_model_id":"anthropic/claude-opus-5-5"},"mistral.pixtral-large-2502-v1:0":{"id":"mistral.pixtral-large-2502-v1:0","name":"Pixtral Large (25.02)","description":"Mistral vision-language model for image understanding and multimodal chat","family":"pixtral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-04-08","last_updated":"2025-04-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":2,"output":6},"canonical_model_id":"mistral/pixtral-large-2502"},"anthropic.claude-haiku-4-5-20251001-v1:0":{"id":"anthropic.claude-haiku-4-5-20251001-v1:0","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"eu.anthropic.claude-opus-5-5":{"id":"eu.anthropic.claude-opus-5-5","name":"Claude Opus 5.5 (EU)","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4.4,"output":22,"cache_read":0.22,"cache_write":5.5},"canonical_model_id":"anthropic/claude-opus-5-5"},"au.anthropic.claude-opus-4-6-v1":{"id":"au.anthropic.claude-opus-4-6-v1","name":"AU Anthropic Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic.claude-opus-4-5-20251101-v1:0":{"id":"anthropic.claude-opus-4-5-20251101-v1:0","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"global.openai.gpt-5.6-luna":{"id":"global.openai.gpt-5.6-luna","name":"GPT-5.6 Luna (Global)","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"google.gemma-4-26b-a4b":{"id":"google.gemma-4-26b-a4b","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":0.13,"output":0.4},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"openai.gpt-5.6-sol":{"id":"openai.gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":4.4,"output":22,"cache_read":0.44,"cache_write":5.5,"tiers":[{"input":8.8,"output":33,"cache_read":0.88,"cache_write":11,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8.8,"output":33,"cache_read":0.88,"cache_write":11}},"canonical_model_id":"openai/gpt-5.6-sol"},"global.anthropic.claude-opus-4-8":{"id":"global.anthropic.claude-opus-4-8","name":"Claude Opus 4.8 (Global)","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"mistral.devstral-2-123b":{"id":"mistral.devstral-2-123b","name":"Devstral 2 123B","description":"Mistral's coding-agent model for repository work, terminal tasks, and software fixes","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"status":"deprecated","cost":{"input":0.4,"output":2},"canonical_model_id":"mistral/devstral-2512"},"jp.anthropic.claude-sonnet-4-5-20250929-v1:0":{"id":"jp.anthropic.claude-sonnet-4-5-20250929-v1:0","name":"Claude Sonnet 4.5 (JP)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"anthropic.claude-fable-5":{"id":"anthropic.claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"xai.grok-4.6":{"id":"xai.grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":2.2,"output":6.6,"cache_read":0.55},"canonical_model_id":"xai/grok-4.6"},"qwen.qwen3-32b-v1:0":{"id":"qwen.qwen3-32b-v1:0","name":"Qwen3 32B","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-09-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"alibaba/qwen3-32b"},"us.openai.gpt-6-sol":{"id":"us.openai.gpt-6-sol","name":"GPT-6 Sol (US)","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.22,"cache_write":2.75,"tiers":[{"input":4.4,"output":16.5,"cache_read":0.44,"cache_write":5.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4.4,"output":16.5,"cache_read":0.44,"cache_write":5.5}},"canonical_model_id":"openai/gpt-6-sol"},"us.mistral.pixtral-large-2502-v1:0":{"id":"us.mistral.pixtral-large-2502-v1:0","name":"Pixtral Large (25.02) (US)","description":"Mistral vision-language model for image understanding and multimodal chat","family":"pixtral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-04-08","last_updated":"2025-04-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":2,"output":6},"canonical_model_id":"mistral/pixtral-large-2502"},"jp.anthropic.claude-opus-4-8":{"id":"jp.anthropic.claude-opus-4-8","name":"Claude Opus 4.8 (JP)","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-8"},"au.anthropic.claude-opus-5":{"id":"au.anthropic.claude-opus-5","name":"Claude Opus 5 (AU)","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-5"},"apac.amazon.nova-lite-v1:0":{"id":"apac.amazon.nova-lite-v1:0","name":"Nova Lite (APAC)","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.063,"output":0.252,"cache_read":0.01575,"cache_write":0.063},"canonical_model_id":"amazon/nova-lite"},"meta.llama4-scout-17b-instruct-v1:0":{"id":"meta.llama4-scout-17b-instruct-v1:0","name":"Llama 4 Scout 17B Instruct","description":"Open Llama with long-context vision for efficient multimodal agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":10000000,"output":8192},"status":"deprecated","cost":{"input":0.17,"output":0.66},"canonical_model_id":"meta/llama-4-scout-17b-instruct"},"jp.anthropic.claude-opus-5-5":{"id":"jp.anthropic.claude-opus-5-5","name":"Claude Opus 5.5 (JP)","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4.4,"output":22,"cache_read":0.22,"cache_write":5.5},"canonical_model_id":"anthropic/claude-opus-5-5"},"global.openai.gpt-6-sol":{"id":"global.openai.gpt-6-sol","name":"GPT-6 Sol (Global)","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"openai.gpt-oss-20b-1:0":{"id":"openai.gpt-oss-20b-1:0","name":"gpt-oss-20b","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":128000},"cost":{"input":0.07,"output":0.3},"canonical_model_id":"openai/gpt-oss-20b"},"moonshot.kimi-k2-thinking":{"id":"moonshot.kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Thinking Kimi model for slower research passes, planning, and hard technical questions","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16000},"status":"deprecated","cost":{"input":0.6,"output":2.5},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"nvidia.nemotron-nano-9b-v2":{"id":"nvidia.nemotron-nano-9b-v2","name":"NVIDIA Nemotron Nano 9B v2","description":"Compact Nemotron model for efficient reasoning and deployable AI agents","family":"nemotron","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09","release_date":"2025-08-18","last_updated":"2025-08-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.06,"output":0.23},"canonical_model_id":"nvidia/nemotron-nano-9b-v2"},"eu.amazon.nova-2-lite-v1:0":{"id":"eu.amazon.nova-2-lite-v1:0","name":"Nova 2 Lite (EU)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-10","release_date":"2025-12-02","last_updated":"2025-12-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.374,"output":3.157,"cache_read":0.0935,"cache_write":0.374},"canonical_model_id":"amazon/nova-2-lite"},"eu.mistral.pixtral-large-2502-v1:0":{"id":"eu.mistral.pixtral-large-2502-v1:0","name":"Pixtral Large (25.02) (EU)","description":"Mistral vision-language model for image understanding and multimodal chat","family":"pixtral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-04-08","last_updated":"2025-04-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":2,"output":6},"canonical_model_id":"mistral/pixtral-large-2502"},"anthropic.claude-haiku-5-5":{"id":"anthropic.claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"global.amazon.nova-2-lite-v1:0":{"id":"global.amazon.nova-2-lite-v1:0","name":"Nova 2 Lite (Global)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-10","release_date":"2025-12-02","last_updated":"2025-12-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.3,"output":2.5,"cache_read":0.075,"cache_write":0.3},"canonical_model_id":"amazon/nova-2-lite"},"global.openai.gpt-5.6-sol":{"id":"global.openai.gpt-5.6-sol","name":"GPT-5.6 Sol (Global)","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"us.anthropic.claude-opus-4-5-20251101-v1:0":{"id":"us.anthropic.claude-opus-4-5-20251101-v1:0","name":"Claude Opus 4.5 (US)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"meta.llama3-1-8b-instruct-v1:0":{"id":"meta.llama3-1-8b-instruct-v1:0","name":"Llama 3.1 8B Instruct","description":"Compact open Llama model for lightweight chat, drafting, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0.22,"output":0.22},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"in.anthropic.claude-opus-5":{"id":"in.anthropic.claude-opus-5","name":"Claude Opus 5 (India)","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-5"},"au.anthropic.claude-sonnet-4-6":{"id":"au.anthropic.claude-sonnet-4-6","name":"AU Anthropic Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"mistral.ministral-3-3b-instruct":{"id":"mistral.ministral-3-3b-instruct","name":"Ministral 3 3B","description":"Compact open vision-language model for edge deployment, instruction following, and tool use","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":0.1,"output":0.1},"canonical_model_id":"mistral/ministral-3-3b-instruct-2512"},"us.openai.gpt-5.6-sol":{"id":"us.openai.gpt-5.6-sol","name":"GPT-5.6 Sol (US)","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4.4,"output":22,"cache_read":0.44,"cache_write":5.5,"tiers":[{"input":8.8,"output":33,"cache_read":0.88,"cache_write":11,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8.8,"output":33,"cache_read":0.88,"cache_write":11}},"canonical_model_id":"openai/gpt-5.6-sol"},"meta.llama4-maverick-17b-instruct-v1:0":{"id":"meta.llama4-maverick-17b-instruct-v1:0","name":"Llama 4 Maverick 17B Instruct","description":"Open multimodal Llama for strong reasoning with efficient everyday serving","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":8192},"status":"deprecated","cost":{"input":0.24,"output":0.97},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"anthropic.claude-sonnet-5-5":{"id":"anthropic.claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"writer.palmyra-x4-v1:0":{"id":"writer.palmyra-x4-v1:0","name":"Palmyra X4","description":"Enterprise language model for workflow automation, coding, data analysis, and tool use","family":"palmyra","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2024-10-09","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":122880,"output":8192},"status":"deprecated","cost":{"input":2.5,"output":10},"canonical_model_id":"writer/palmyra-x4"},"google.gemma-4-e2b":{"id":"google.gemma-4-e2b","name":"Gemma 4 E2B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":0.04,"output":0.08},"canonical_model_id":"google/gemma-4-E2B-it"},"mistral.ministral-3-14b-instruct":{"id":"mistral.ministral-3-14b-instruct","name":"Ministral 14B 3.0","description":"Open vision-language model for efficient local deployment, instruction following, and tool use","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.2,"output":0.2},"canonical_model_id":"mistral/ministral-3-14b-instruct-2512"},"mistral.voxtral-mini-3b-2507":{"id":"mistral.voxtral-mini-3b-2507","name":"Voxtral Mini 3B 2507","description":"Open audio-language model for speech transcription, audio understanding, and voice-driven tool use","family":"voxtral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":4096},"status":"deprecated","cost":{"input":0.04,"output":0.04},"canonical_model_id":"mistral/voxtral-mini-3b-2507"},"google.gemma-3-4b-it":{"id":"google.gemma-3-4b-it","name":"Gemma 3 4B IT","description":"Open multimodal Gemma instruction model for efficient text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":4096},"status":"deprecated","cost":{"input":0.04,"output":0.08},"canonical_model_id":"google/gemma-3-4b-it"},"google.gemma-4-31b":{"id":"google.gemma-4-31b","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":0.14,"output":0.4},"canonical_model_id":"google/gemma-4-31b-it"},"us.zai.glm-5.3":{"id":"us.zai.glm-5.3","name":"GLM-5.3 (US)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":1.848,"output":5.808,"cache_read":0.3432,"cache_write":2.31},"canonical_model_id":"zhipuai/glm-5.3"},"us.anthropic.claude-opus-4-8":{"id":"us.anthropic.claude-opus-4-8","name":"Claude Opus 4.8 (US)","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-8"},"eu.anthropic.claude-opus-4-6-v1":{"id":"eu.anthropic.claude-opus-4-6-v1","name":"Claude Opus 4.6 (EU)","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-6"},"us.openai.gpt-6.1-sol":{"id":"us.openai.gpt-6.1-sol","name":"GPT-6.1 Sol (US)","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"ultrafast":{"cost":{"input":13.2,"output":66,"cache_read":0.66,"cache_write":16.5},"provider":{"body":{"additionalModelRequestFields":{"service_tier":"ultrafast"}}}}}},"cost":{"input":2.2,"output":11,"cache_read":0.11,"cache_write":2.75,"tiers":[{"input":4.4,"output":16.5,"cache_read":0.22,"cache_write":5.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4.4,"output":16.5,"cache_read":0.22,"cache_write":5.5}},"canonical_model_id":"openai/gpt-6.1-sol"},"jp.anthropic.claude-haiku-4-5-20251001-v1:0":{"id":"jp.anthropic.claude-haiku-4-5-20251001-v1:0","name":"Claude Haiku 4.5 (JP)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1.1,"output":5.5,"cache_read":0.11,"cache_write":1.375},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"deepseek.v3.2":{"id":"deepseek.v3.2","name":"DeepSeek V3.2","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2026-02-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":81920},"cost":{"input":0.62,"output":1.85},"canonical_model_id":"deepseek/deepseek-v3.2"},"eu.anthropic.claude-sonnet-4-6":{"id":"eu.anthropic.claude-sonnet-4-6","name":"Claude Sonnet 4.6 (EU)","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"apac.amazon.nova-micro-v1:0":{"id":"apac.amazon.nova-micro-v1:0","name":"Nova Micro (APAC)","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-micro","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":10000},"cost":{"input":0.037,"output":0.148,"cache_read":0.00925,"cache_write":0.037},"canonical_model_id":"amazon/nova-micro"},"us.anthropic.claude-haiku-4-5-20251001-v1:0":{"id":"us.anthropic.claude-haiku-4-5-20251001-v1:0","name":"Claude Haiku 4.5 (US)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1.1,"output":5.5,"cache_read":0.11,"cache_write":1.375},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"global.anthropic.claude-opus-5":{"id":"global.anthropic.claude-opus-5","name":"Claude Opus 5 (Global)","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic.claude-opus-4-6-v1":{"id":"anthropic.claude-opus-4-6-v1","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-6"},"global.openai.gpt-6-luna":{"id":"global.openai.gpt-6-luna","name":"GPT-6 Luna (Global)","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"global.anthropic.claude-opus-4-6-v1":{"id":"global.anthropic.claude-opus-4-6-v1","name":"Claude Opus 4.6 (Global)","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"au.anthropic.claude-opus-4-7":{"id":"au.anthropic.claude-opus-4-7","name":"Claude Opus 4.7 (AU)","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-7"},"us.amazon.nova-micro-v1:0":{"id":"us.amazon.nova-micro-v1:0","name":"Nova Micro (US)","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-micro","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":10000},"cost":{"input":0.035,"output":0.14,"cache_read":0.00875,"cache_write":0.035},"canonical_model_id":"amazon/nova-micro"},"openai.gpt-oss-120b-1:0":{"id":"openai.gpt-oss-120b-1:0","name":"gpt-oss-120b","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":128000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-120b"},"us.openai.gpt-5.6-terra":{"id":"us.openai.gpt-5.6-terra","name":"GPT-5.6 Terra (US)","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.2,"output":13.2,"cache_read":0.22,"cache_write":2.75,"tiers":[{"input":4.4,"output":19.8,"cache_read":0.44,"cache_write":5.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4.4,"output":19.8,"cache_read":0.44,"cache_write":5.5}},"canonical_model_id":"openai/gpt-5.6-terra"},"us.anthropic.claude-opus-4-6-v1":{"id":"us.anthropic.claude-opus-4-6-v1","name":"Claude Opus 4.6 (US)","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-6"},"us-gov.openai.gpt-oss-120b-1:0":{"id":"us-gov.openai.gpt-oss-120b-1:0","name":"gpt-oss-120b (GovCloud)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.18,"output":0.72},"canonical_model_id":"openai/gpt-oss-120b"},"openai.gpt-oss-120b":{"id":"openai.gpt-oss-120b","name":"gpt-oss-120b","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/v1","shape":"responses"},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-120b"},"qwen.qwen3-coder-30b-a3b-v1:0":{"id":"qwen.qwen3-coder-30b-a3b-v1:0","name":"Qwen3-Coder 30B-A3B Instruct","description":"Smaller Qwen coder for efficient local agents and repo-level fixes","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-31","last_updated":"2025-09-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"status":"deprecated","cost":{"input":0.15,"output":0.6},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"ca.amazon.nova-lite-v1:0":{"id":"ca.amazon.nova-lite-v1:0","name":"Nova Lite (CA)","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.064,"output":0.256,"cache_read":0.016,"cache_write":0.064},"canonical_model_id":"amazon/nova-lite"},"mistral.ministral-3-8b-instruct":{"id":"mistral.ministral-3-8b-instruct","name":"Ministral 3 8B","description":"Compact open vision-language model for edge deployment, instruction following, and tool use","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0.15,"output":0.15},"canonical_model_id":"mistral/ministral-3-8b-instruct-2512"},"eu.anthropic.claude-sonnet-4-20250514-v1:0":{"id":"eu.anthropic.claude-sonnet-4-20250514-v1:0","name":"Claude Sonnet 4 (EU)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-20250514"},"us.meta.llama4-maverick-17b-instruct-v1:0":{"id":"us.meta.llama4-maverick-17b-instruct-v1:0","name":"Llama 4 Maverick 17B Instruct (US)","description":"Open multimodal Llama for strong reasoning with efficient everyday serving","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":8192},"status":"deprecated","cost":{"input":0.24,"output":0.97},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"eu.anthropic.claude-opus-4-5-20251101-v1:0":{"id":"eu.anthropic.claude-opus-4-5-20251101-v1:0","name":"Claude Opus 4.5 (EU)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"global.anthropic.claude-fable-5-1":{"id":"global.anthropic.claude-fable-5-1","name":"Claude Fable 5.1 (Global)","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"jp.amazon.nova-2-lite-v1:0":{"id":"jp.amazon.nova-2-lite-v1:0","name":"Nova 2 Lite (JP)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-10","release_date":"2025-12-02","last_updated":"2025-12-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.396,"output":3.311,"cache_read":0.099,"cache_write":0.396},"canonical_model_id":"amazon/nova-2-lite"},"amazon.nova-lite-v1:0":{"id":"amazon.nova-lite-v1:0","name":"Nova Lite","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.06,"output":0.24,"cache_read":0.015,"cache_write":0.06},"canonical_model_id":"amazon/nova-lite"},"global.anthropic.claude-sonnet-4-20250514-v1:0":{"id":"global.anthropic.claude-sonnet-4-20250514-v1:0","name":"Claude Sonnet 4 (Global)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-20250514"},"openai.gpt-oss-safeguard-20b":{"id":"openai.gpt-oss-safeguard-20b","name":"GPT OSS Safeguard 20B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.07,"output":0.2},"canonical_model_id":"openai/gpt-oss-safeguard-20b"},"zai.glm-4.7-flash":{"id":"zai.glm-4.7-flash","name":"GLM-4.7-Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"status":"deprecated","cost":{"input":0.07,"output":0.4},"canonical_model_id":"zhipuai/glm-4.7-flash"},"jp.anthropic.claude-sonnet-4-6":{"id":"jp.anthropic.claude-sonnet-4-6","name":"Claude Sonnet 4.6 (JP)","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3.3,"output":16.5,"cache_read":0.33,"cache_write":4.125},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"qwen.qwen3-coder-next":{"id":"qwen.qwen3-coder-next","name":"Qwen3 Coder Next","description":"Open-weight Qwen coding model for agents, repository edits, and multi-turn tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.5,"output":1.2},"canonical_model_id":"alibaba/qwen3-coder-next"},"global.zai.glm-5.3":{"id":"global.zai.glm-5.3","name":"GLM-5.3 (Global)","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":1.68,"output":5.28,"cache_read":0.312,"cache_write":2.1},"canonical_model_id":"zhipuai/glm-5.3"},"us.amazon.nova-2-lite-v1:0":{"id":"us.amazon.nova-2-lite-v1:0","name":"Nova 2 Lite (US)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-10","release_date":"2025-12-02","last_updated":"2025-12-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.33,"output":2.75,"cache_read":0.0825,"cache_write":0.33},"canonical_model_id":"amazon/nova-2-lite"},"minimax.minimax-m2.1":{"id":"minimax.minimax-m2.1","name":"MiniMax-M2.1","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":131072},"status":"deprecated","cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2.1"},"jp.anthropic.claude-sonnet-5":{"id":"jp.anthropic.claude-sonnet-5","name":"Claude Sonnet 5 (JP)","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.2,"output":11,"cache_read":0.22,"cache_write":2.75},"canonical_model_id":"anthropic/claude-sonnet-5"},"us.xai.grok-4.7":{"id":"us.xai.grok-4.7","name":"Grok 4.7 (US)","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2.2,"output":6.6,"cache_read":0.55},"canonical_model_id":"xai/grok-4.7"},"amazon.nova-micro-v1:0":{"id":"amazon.nova-micro-v1:0","name":"Nova Micro","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-micro","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":10000},"cost":{"input":0.035,"output":0.14,"cache_read":0.00875,"cache_write":0.035},"canonical_model_id":"amazon/nova-micro"},"global.anthropic.claude-sonnet-4-6":{"id":"global.anthropic.claude-sonnet-4-6","name":"Claude Sonnet 4.6 (Global)","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"nvidia.nemotron-super-3-120b":{"id":"nvidia.nemotron-super-3-120b","name":"NVIDIA Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.15,"output":0.65},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"qwen.qwen3-next-80b-a3b":{"id":"qwen.qwen3-next-80b-a3b","name":"Qwen3-Next 80B-A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-11","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262000},"cost":{"input":0.15,"output":1.2},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"anthropic.claude-opus-5-5":{"id":"anthropic.claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"mistral.voxtral-small-24b-2507":{"id":"mistral.voxtral-small-24b-2507","name":"Voxtral Small 24B 2507","description":"Open audio-language model for speech transcription, audio understanding, and voice-driven tool use","family":"voxtral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"status":"deprecated","cost":{"input":0.1,"output":0.3},"canonical_model_id":"mistral/voxtral-small-24b-2507"},"anthropic.claude-fable-5-1":{"id":"anthropic.claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"us.amazon.nova-pro-v1:0":{"id":"us.amazon.nova-pro-v1:0","name":"Nova Pro (US)","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.8,"output":3.2,"cache_read":0.2,"cache_write":0.8},"canonical_model_id":"amazon/nova-pro"},"us-gov.openai.gpt-oss-20b-1:0":{"id":"us-gov.openai.gpt-oss-20b-1:0","name":"gpt-oss-20b (GovCloud)","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.084,"output":0.36},"canonical_model_id":"openai/gpt-oss-20b"},"openai.gpt-6-sol":{"id":"openai.gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/amazon-bedrock/mantle","api":"https://bedrock-mantle.${AWS_REGION}.api.aws/openai/v1","shape":"responses"},"cost":{"input":2.2,"output":11,"cache_read":0.22,"cache_write":2.75,"tiers":[{"input":4.4,"output":16.5,"cache_read":0.44,"cache_write":5.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4.4,"output":16.5,"cache_read":0.44,"cache_write":5.5}},"canonical_model_id":"openai/gpt-6-sol"},"deepseek.v3-v1:0":{"id":"deepseek.v3-v1:0","name":"DeepSeek-V3.1","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-09-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":81920},"status":"deprecated","cost":{"input":0.58,"output":1.68},"canonical_model_id":"deepseek/deepseek-v3.1"},"global.xai.grok-4.6":{"id":"global.xai.grok-4.6","name":"Grok 4.6 (Global)","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"apac.amazon.nova-pro-v1:0":{"id":"apac.amazon.nova-pro-v1:0","name":"Nova Pro (APAC)","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":10000},"cost":{"input":0.84,"output":3.36,"cache_read":0.21,"cache_write":0.84},"canonical_model_id":"amazon/nova-pro"},"us.meta.llama3-1-70b-instruct-v1:0":{"id":"us.meta.llama3-1-70b-instruct-v1:0","name":"Llama 3.1 70B Instruct (US)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0.72,"output":0.72},"canonical_model_id":"meta/llama-3.1-70b-instruct"},"eu.amazon.nova-micro-v1:0":{"id":"eu.amazon.nova-micro-v1:0","name":"Nova Micro (EU)","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-micro","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10","release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":10000},"cost":{"input":0.04,"output":0.16,"cache_read":0.01,"cache_write":0.04},"canonical_model_id":"amazon/nova-micro"},"global.anthropic.claude-haiku-4-5-20251001-v1:0":{"id":"global.anthropic.claude-haiku-4-5-20251001-v1:0","name":"Claude Haiku 4.5 (Global)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"eu.anthropic.claude-opus-4-7":{"id":"eu.anthropic.claude-opus-4-7","name":"Claude Opus 4.7 (EU)","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.5,"output":27.5,"cache_read":0.55,"cache_write":6.875},"canonical_model_id":"anthropic/claude-opus-4-7"}}},"siliconflow":{"id":"siliconflow","env":["SILICONFLOW_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.siliconflow.com/v1","name":"SiliconFlow","doc":"https://cloud.siliconflow.com/models","models":{"Qwen/Qwen3-8B":{"id":"Qwen/Qwen3-8B","name":"Qwen/Qwen3-8B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-29","last_updated":"2025-04-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":131000},"cost":{"input":0.06,"output":0.06},"canonical_model_id":"alibaba/qwen3-8b"},"Qwen/Qwen3-30B-A3B-Instruct-2507":{"id":"Qwen/Qwen3-30B-A3B-Instruct-2507","name":"Qwen/Qwen3-30B-A3B-Instruct-2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.09,"output":0.3},"canonical_model_id":"alibaba/qwen3-30b-a3b-instruct-2507"},"Qwen/Qwen3.5-122B-A10B":{"id":"Qwen/Qwen3.5-122B-A10B","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.26,"output":2.08},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"Qwen/Qwen3.5-397B-A17B":{"id":"Qwen/Qwen3.5-397B-A17B","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.39,"output":2.34},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"Qwen/Qwen3.5-27B":{"id":"Qwen/Qwen3.5-27B","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.25,"output":2},"canonical_model_id":"alibaba/qwen3.5-27b"},"Qwen/Qwen2.5-72B-Instruct":{"id":"Qwen/Qwen2.5-72B-Instruct","name":"Qwen/Qwen2.5-72B-Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-09-18","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":33000,"output":4000},"cost":{"input":0.59,"output":0.59}},"Qwen/Qwen3.5-35B-A3B":{"id":"Qwen/Qwen3.5-35B-A3B","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.24,"output":1.8,"cache_read":0.15},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"Qwen/Qwen3-32B":{"id":"Qwen/Qwen3-32B","name":"Qwen/Qwen3-32B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":131000},"cost":{"input":0.14,"output":0.57},"canonical_model_id":"alibaba/qwen3-32b"},"Qwen/Qwen3-VL-30B-A3B-Thinking":{"id":"Qwen/Qwen3-VL-30B-A3B-Thinking","name":"Qwen/Qwen3-VL-30B-A3B-Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-11","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.29,"output":1}},"Qwen/Qwen3-VL-32B-Thinking":{"id":"Qwen/Qwen3-VL-32B-Thinking","name":"Qwen/Qwen3-VL-32B-Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-21","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.2,"output":1.5}},"Qwen/Qwen3-VL-8B-Instruct":{"id":"Qwen/Qwen3-VL-8B-Instruct","name":"Qwen/Qwen3-VL-8B-Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-15","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.18,"output":0.68}},"Qwen/Qwen3.5-9B":{"id":"Qwen/Qwen3.5-9B","name":"Qwen/Qwen3.5-9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.1,"output":0.15},"canonical_model_id":"alibaba/qwen3.5-9b"},"Qwen/Qwen3-VL-32B-Instruct":{"id":"Qwen/Qwen3-VL-32B-Instruct","name":"Qwen/Qwen3-VL-32B-Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-21","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.2,"output":0.6}},"Qwen/Qwen2.5-7B-Instruct":{"id":"Qwen/Qwen2.5-7B-Instruct","name":"Qwen/Qwen2.5-7B-Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-09-19","last_updated":"2024-09-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":33000,"output":4000},"cost":{"input":0.05,"output":0.05},"canonical_model_id":"alibaba/qwen2.5-7b-instruct"},"Qwen/Qwen3-Coder-480B-A35B-Instruct":{"id":"Qwen/Qwen3-Coder-480B-A35B-Instruct","name":"Qwen/Qwen3-Coder-480B-A35B-Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.25,"output":1},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"Qwen/Qwen3-VL-30B-A3B-Instruct":{"id":"Qwen/Qwen3-VL-30B-A3B-Instruct","name":"Qwen/Qwen3-VL-30B-A3B-Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-04","last_updated":"2025-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.29,"output":1},"canonical_model_id":"alibaba/qwen3-vl-30b-a3b-instruct"},"Qwen/Qwen3.6-27B":{"id":"Qwen/Qwen3.6-27B","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.3,"output":3.2},"canonical_model_id":"alibaba/qwen3.6-27b"},"Qwen/Qwen3-14B":{"id":"Qwen/Qwen3-14B","name":"Qwen/Qwen3-14B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-30","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":131000},"cost":{"input":0.07,"output":0.28}},"Qwen/Qwen3-Coder-30B-A3B-Instruct":{"id":"Qwen/Qwen3-Coder-30B-A3B-Instruct","name":"Qwen/Qwen3-Coder-30B-A3B-Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-31","last_updated":"2025-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.07,"output":0.28},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"Qwen/Qwen3.8-2.4T-A95B":{"id":"Qwen/Qwen3.8-2.4T-A95B","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1049000,"output":131000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"Qwen/Qwen3.6-35B-A3B":{"id":"Qwen/Qwen3.6-35B-A3B","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.24,"output":1.8,"cache_read":0.15},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"openai/gpt-oss-120b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":8000},"cost":{"input":0.05,"output":0.45},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"openai/gpt-oss-20b","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":8000},"cost":{"input":0.04,"output":0.18},"canonical_model_id":"openai/gpt-oss-20b"},"stepfun-ai/Step-3.5-Flash":{"id":"stepfun-ai/Step-3.5-Flash","name":"stepfun-ai/Step-3.5-Flash","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","family":"step","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":66000},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"stepfun/step-3.5-flash"},"zai-org/GLM-5":{"id":"zai-org/GLM-5","name":"zai-org/GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":205000,"output":131072},"cost":{"input":0.95,"output":2.55,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"zai-org/GLM-5.3-Flash":{"id":"zai-org/GLM-5.3-Flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1049000,"output":262000},"cost":{"input":0.15,"output":0.5,"cache_read":0.03,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/GLM-5.1":{"id":"zai-org/GLM-5.1","name":"zai-org/GLM-5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":205000,"output":131000},"cost":{"input":1.19,"output":3.74,"cache_read":0.6,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.1"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1049000,"output":262000},"cost":{"input":1.302,"output":4.092,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-4.5-Air":{"id":"zai-org/GLM-4.5-Air","name":"zai-org/GLM-4.5-Air","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-air","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":131000},"cost":{"input":0.14,"output":0.86},"canonical_model_id":"zhipuai/glm-4.5-air"},"zai-org/GLM-5.3":{"id":"zai-org/GLM-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1049000,"output":262000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"zai-org/GLM-5V-Turbo":{"id":"zai-org/GLM-5V-Turbo","name":"zai-org/GLM-5V-Turbo","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24,"cache_write":0},"canonical_model_id":"zhipuai/glm-5v-turbo"},"ByteDance-Seed/Seed-OSS-36B-Instruct":{"id":"ByteDance-Seed/Seed-OSS-36B-Instruct","name":"ByteDance-Seed/Seed-OSS-36B-Instruct","description":"Tool-capable chat model for instruction following and agentic application workflows","family":"seed","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-04","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.21,"output":0.57}},"moonshotai/Kimi-K2.5":{"id":"moonshotai/Kimi-K2.5","name":"moonshotai/Kimi-K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.45,"output":2.25,"cache_read":0.07},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/Kimi-K2.7-Code":{"id":"moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.85916,"output":3.8,"cache_read":0.17993},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"moonshotai/Kimi-K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"cost":{"input":0.77,"output":3.4,"cache_read":0.14},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/Kimi-K3":{"id":"moonshotai/Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262000},"cost":{"input":2.7,"output":13.5,"cache_read":0.27},"canonical_model_id":"moonshotai/kimi-k3"},"inclusionAI/Ling-flash-2.0":{"id":"inclusionAI/Ling-flash-2.0","name":"inclusionAI/Ling-flash-2.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-18","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":131000},"cost":{"input":0.14,"output":0.57}},"tencent/Hy3":{"id":"tencent/Hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":192000,"output":262144},"cost":{"input":0.132,"output":0.528,"cache_read":0.033},"canonical_model_id":"tencent/hy3"},"tencent/Hunyuan-A13B-Instruct":{"id":"tencent/Hunyuan-A13B-Instruct","name":"tencent/Hunyuan-A13B-Instruct","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"hunyuan","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-06-30","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":131000},"cost":{"input":0.14,"output":0.57}},"MiniMaxAI/MiniMax-M2.5":{"id":"MiniMaxAI/MiniMax-M2.5","name":"MiniMaxAI/MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":197000,"output":131000},"status":"deprecated","cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5"},"MiniMaxAI/MiniMax-M3":{"id":"MiniMaxAI/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"deepseek-ai/DeepSeek-V3.2-Exp":{"id":"deepseek-ai/DeepSeek-V3.2-Exp","name":"deepseek-ai/DeepSeek-V3.2-Exp","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-10","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":164000},"cost":{"input":0.27,"output":0.41}},"deepseek-ai/DeepSeek-R1":{"id":"deepseek-ai/DeepSeek-R1","name":"deepseek-ai/DeepSeek-R1","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":164000},"cost":{"input":0.5,"output":2.18},"canonical_model_id":"deepseek/deepseek-r1-0528"},"deepseek-ai/DeepSeek-V4-Flash-Vision-Exp":{"id":"deepseek-ai/DeepSeek-V4-Flash-Vision-Exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.44,"output":1.32,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"deepseek-ai/DeepSeek-V4-Pro":{"id":"deepseek-ai/DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.50162,"output":3.135,"cache_read":0.135},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek-ai/DeepSeek-V3.2":{"id":"deepseek-ai/DeepSeek-V3.2","name":"deepseek-ai/DeepSeek-V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":164000},"cost":{"input":0.27,"output":0.42,"cache_read":0.135},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepseek-ai/DeepSeek-V4-Flash":{"id":"deepseek-ai/DeepSeek-V4-Flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.13,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek-ai/DeepSeek-V4-Flash-0731":{"id":"deepseek-ai/DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.22,"output":0.66,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek-ai/DeepSeek-V4-Pro-0813":{"id":"deepseek-ai/DeepSeek-V4-Pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek-ai/DeepSeek-V3":{"id":"deepseek-ai/DeepSeek-V3","name":"deepseek-ai/DeepSeek-V3","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-03-24","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":164000},"cost":{"input":0.25,"output":1},"canonical_model_id":"deepseek/deepseek-v3-0324"},"deepseek-ai/DeepSeek-V3.1":{"id":"deepseek-ai/DeepSeek-V3.1","name":"deepseek-ai/DeepSeek-V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":164000},"cost":{"input":0.27,"output":1},"canonical_model_id":"deepseek/deepseek-v3.1"},"deepseek-ai/DeepSeek-V3.1-Terminus":{"id":"deepseek-ai/DeepSeek-V3.1-Terminus","name":"deepseek-ai/DeepSeek-V3.1-Terminus","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-29","last_updated":"2025-11-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":164000},"cost":{"input":0.27,"output":1}},"meituan-longcat/LongCat-2.0":{"id":"meituan-longcat/LongCat-2.0","name":"LongCat-2.0","description":"Meituan LongCat-2.0, a reasoning model with tool calling and a 1M-token context window","family":"longcat","attachment":false,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1049000,"output":131072},"cost":{"input":0.75,"output":2.95,"cache_read":0.015},"canonical_model_id":"meituan/longcat-2.0"},"google/gemma-4-31B-it":{"id":"google/gemma-4-31B-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.75,"output":1,"cache_read":0.25},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemma-4-12B-it":{"id":"google/gemma-4-12B-it","name":"Gemma 4 12B IT","description":"Compact Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"google/gemma-4-12b-it"},"google/gemma-4-26B-A4B-it":{"id":"google/gemma-4-26B-A4B-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.14,"output":0.4,"cache_read":0.05},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"nex-agi/Nex-N2-Pro":{"id":"nex-agi/Nex-N2-Pro","name":"Nex-N2-Pro","description":"Open agentic MoE model (397B total, 17B active) for coding, tool use, and research workflows","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"status":"deprecated","cost":{"input":0.5,"output":2.5,"cache_read":0.25},"canonical_model_id":"nex-agi/nex-n2-pro"}}},"tencent-token-plan":{"id":"tencent-token-plan","env":["TENCENT_TOKEN_PLAN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.lkeap.cloud.tencent.com/plan/v3","name":"Tencent Token Plan","doc":"https://cloud.tencent.com/document/product/1823/130060","models":{"hy4-preview":{"id":"hy4-preview","name":"Hy4 preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":64000},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"},"hy3":{"id":"hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":192000,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"tencent/hy3"}}},"anthropic":{"id":"anthropic","env":["ANTHROPIC_API_KEY"],"npm":"@ai-sdk/anthropic","name":"Anthropic","doc":"https://docs.anthropic.com/en/docs/about-claude/models","models":{"claude-sonnet-4-5":{"id":"claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-14","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-04","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-07","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5}},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":8,"output":40,"cache_read":0.4,"cache_write":10},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-29","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5}},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"claude-fable-5-1":{"id":"claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"provider":{"body":{"speed":"fast"},"headers":{"anthropic-beta":"fast-mode-2026-02-01"}}}}},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"claude-opus-4-5-20251101":{"id":"claude-opus-4-5-20251101","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25}},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75}},"claude-sonnet-4-5-20250929":{"id":"claude-sonnet-4-5-20250929","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75}},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"claude-haiku-4-5-20251001":{"id":"claude-haiku-4-5-20251001","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25}},"claude-opus-4-5":{"id":"claude-opus-4-5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"}}},"standardcompute":{"id":"standardcompute","env":["STANDARDCOMPUTE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.stdcmpt.com/v1","name":"Standard Compute","doc":"https://docs.standardcompute.com/models","models":{"standardcompute":{"id":"standardcompute","name":"Standard Compute","description":"Flat-rate smart-routing gateway: one model id, each request routed across the customer's enabled models from a curated ~1M-context catalog (Claude, GPT, Gemini, DeepSeek, GLM, Qwen, Kimi, MiniMax, Grok, MiMo) or pinned to a user-selected model","family":"auto","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-03-01","last_updated":"2026-10-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"}},"xiaomi/mimo-v2.6-flash":{"id":"xiaomi/mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"xiaomi/mimo-v2.6-pro":{"id":"xiaomi/mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.43,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"xiaomi/mimo-v2.5-pro":{"id":"xiaomi/mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"xiaomi/mimo-v2.5":{"id":"xiaomi/mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.5"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-haiku-5.5":{"id":"anthropic/claude-haiku-5.5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-opus-5.5":{"id":"anthropic/claude-opus-5.5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-sonnet-5.5":{"id":"anthropic/claude-sonnet-5.5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-fable-5.1":{"id":"anthropic/claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"x-ai/grok-4.3":{"id":"x-ai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":850000,"output":30000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.3"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"mistralai/mistral-large-4-0":{"id":"mistralai/mistral-large-4-0","name":"Mistral Large 4","description":"Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.68,"output":2.09,"cache_read":0.07},"canonical_model_id":"mistral/mistral-large-4"},"qwen/qwen3.8-flash":{"id":"qwen/qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.15,"output":0.47,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen/qwen3.8-max-0902":{"id":"qwen/qwen3.8-max-0902","name":"Qwen3.8 Max 0902","description":"2026-09-02 upgraded snapshot of Qwen3.8 Max with stronger coding, collaborative agents, and multimodal document understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max-0902"},"qwen/qwen3.7-plus":{"id":"qwen/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.32,"output":1.28,"cache_read":0.064,"cache_write":0.4,"tiers":[{"input":0.96,"output":3.84,"cache_read":0.192,"cache_write":1.2,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.96,"output":3.84,"cache_read":0.192,"cache_write":1.2}},"canonical_model_id":"alibaba/qwen3.7-plus"},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":1.475,"output":4.425,"cache_read":0.295,"cache_write":1.84375},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen3.7-flash":{"id":"qwen/qwen3.7-flash","name":"Qwen3.7 Flash","description":"Lightweight multimodal Qwen model for high-throughput text, image, and video tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":262144}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.03,"output":0.13,"cache_read":0.006,"cache_write":0.038,"tiers":[{"input":0.1,"output":0.4,"cache_read":0.02,"cache_write":0.125,"tier":{"type":"context","size":32000}},{"input":0.2,"output":0.8,"cache_read":0.04,"cache_write":0.25,"tier":{"type":"context","size":256000}}]},"canonical_model_id":"alibaba/qwen3.7-flash"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.425,"output":2.55,"cache_read":0.085,"cache_write":0.53125},"canonical_model_id":"alibaba/qwen3.8-27b"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.0826,"output":0.1652,"cache_read":0.01652},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.14,"output":0.42,"cache_read":0.0042},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":1.044,"output":2.088,"cache_read":0.2088},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.44,"output":1.32,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":1.122,"output":3.366,"cache_read":0.1122},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.5625,"output":1.8,"cache_read":0.105},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.08,"output":0.5,"cache_read":0.012},"canonical_model_id":"zhipuai/glm-5.3-flash"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":0.083333},"canonical_model_id":"google/gemini-2.5-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":1.25,"output":10,"cache_read":0.125,"cache_write":0.375,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":0.083333},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":0.375,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":850000,"output":50000},"provider":{"npm":"@openrouter/ai-sdk-provider"},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.8-flash"}}},"frogbot":{"id":"frogbot","env":["FROGBOT_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://app.frogbot.ai/api/v1","name":"FrogBot","doc":"https://docs.frogbot.ai","models":{"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-120b"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"grok-code-fast-1":{"id":"grok-code-fast-1","name":"Grok 4.1 Fast (Reasoning)","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2023-10","release_date":"2025-09-02","last_updated":"2025-09-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.2,"output":1.5,"cache_read":0.02},"canonical_model_id":"xai/grok-code-fast-1"},"gpt-5-5":{"id":"gpt-5-5","name":"GPT-5.5","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":272000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5"},"gemini-3-flash-preview":{"id":"gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05},"canonical_model_id":"google/gemini-3-flash-preview"},"minimax-m2-5":{"id":"minimax-m2-5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":192000,"output":8192},"status":"deprecated","cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5"},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.075},"canonical_model_id":"google/gemini-2.5-flash"},"gpt-4o":{"id":"gpt-4o","name":"GPT-4o","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"kimi-k2-6":{"id":"kimi-k2-6","name":"Kimi-K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":128000},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek v4 Pro","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek-thinking","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2026-01","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro"},"minimax-m2-7":{"id":"minimax-m2-7","name":"MiniMax-M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":192000,"output":8192},"status":"deprecated","cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7"},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"grok-4-1-fast-non-reasoning":{"id":"grok-4-1-fast-non-reasoning","name":"Grok 4.1 Fast (Non-Reasoning)","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-11","release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":128000},"cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"xai/grok-4.1-fast"},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi-K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":128000},"status":"deprecated","cost":{"input":0.6,"output":3,"cache_read":0.1},"canonical_model_id":"moonshotai/kimi-k2.5"},"gpt-5-3-codex":{"id":"gpt-5-3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"gemini-2.5-pro":{"id":"gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.31},"canonical_model_id":"google/gemini-2.5-pro"},"grok-4-3":{"id":"grok-4-3","name":"Grok 4.3","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11","release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2},"canonical_model_id":"xai/grok-4.3"},"zai-glm-5-1":{"id":"zai-glm-5-1","name":"Z.AI GLM-5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":198000,"output":8192},"status":"deprecated","cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"qwen-3-6-plus":{"id":"qwen-3-6-plus","name":"Qwen 3.6 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"status":"deprecated","cost":{"input":0.5,"output":3,"cache_read":0.1},"canonical_model_id":"alibaba/qwen3.6-plus"},"gpt-oss-20b":{"id":"gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.07,"output":0.2},"canonical_model_id":"openai/gpt-oss-20b"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"grok-4-1-fast-reasoning":{"id":"grok-4-1-fast-reasoning","name":"Grok 4.1 Fast (Reasoning)","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-11","release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":128000},"cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"xai/grok-4.1-fast-reasoning"},"gemini-3-1-pro-preview":{"id":"gemini-3-1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":2,"output":12,"cache_read":0.2},"canonical_model_id":"google/gemini-3.1-pro-preview"},"gpt-5-4-mini":{"id":"gpt-5-4-mini","name":"GPT-5.4 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"gpt-5-4-nano":{"id":"gpt-5-4-nano","name":"GPT-5.4 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"}}},"arcee":{"id":"arcee","env":["ARCEE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.arcee.ai/api/v1","name":"Arcee","doc":"https://docs.arcee.ai","models":{"trinity-large-thinking":{"id":"trinity-large-thinking","name":"Trinity Large Thinking","description":"Reasoning-optimized 398B MoE agent model with extended thinking for long-horizon and multi-turn tool use","family":"trinity","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-04-01","last_updated":"2026-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":80000},"status":"beta","cost":{"input":0.25,"output":0.8,"cache_read":0.06},"canonical_model_id":"arcee-ai/trinity-large-thinking"},"thinkingmachines/inkling-small":{"id":"thinkingmachines/inkling-small","name":"Inkling Small","description":"Multimodal MoE reasoning model (276B total, 12B active) for text, image, and audio","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.5,"output":1.2,"cache_read":0.1},"canonical_model_id":"thinkingmachines/inkling-small"},"zai-org/glm-5.2":{"id":"zai-org/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"status":"beta","cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/glm-5.3":{"id":"zai-org/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"beta","cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"zai-org/glm-5.3-flash":{"id":"zai-org/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"beta","cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"beta","cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"status":"beta","cost":{"input":0.22,"output":0.66,"cache_read":0.007},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"output":384000},"status":"deprecated","cost":{"input":1.74,"output":3.48,"cache_read":0.2},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v4-flash-latest":{"id":"deepseek/deepseek-v4-flash-latest","name":"DeepSeek V4 Flash Latest","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"status":"beta","cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v4.1-flash-1017":{"id":"deepseek/deepseek-v4.1-flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"status":"beta","cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"status":"beta","cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"}}},"morph":{"id":"morph","env":["MORPH_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.morphllm.com/v1","name":"Morph","doc":"https://docs.morphllm.com/api-reference/introduction","models":{"morph-v3-large":{"id":"morph-v3-large","name":"Morph v3 Large","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"morph","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-08-15","last_updated":"2024-08-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":32000},"cost":{"input":0.9,"output":1.9}},"morph-v3-fast":{"id":"morph-v3-fast","name":"Morph v3 Fast","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"morph","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-08-15","last_updated":"2024-08-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16000,"output":16000},"cost":{"input":0.8,"output":1.2}},"auto":{"id":"auto","name":"Auto","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-06-01","last_updated":"2024-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":32000},"cost":{"input":0.85,"output":1.55}}}},"upstage":{"id":"upstage","env":["UPSTAGE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.upstage.ai/v1/solar","name":"Upstage","doc":"https://developers.upstage.ai/docs/apis/chat","models":{"solar-pro2":{"id":"solar-pro2","name":"solar-pro2","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"output":8192},"cost":{"input":0.25,"output":0.25},"canonical_model_id":"upstage/solar-pro2"},"solar-pro3":{"id":"solar-pro3","name":"solar-pro3","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2026-01-26","last_updated":"2026-03-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.25,"output":0.25},"canonical_model_id":"upstage/solar-pro3"},"solar-pro4":{"id":"solar-pro4","name":"Solar Pro 4","description":"Upstage's flagship model, specialized for agentic use","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02","release_date":"2026-08-06","last_updated":"2026-08-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"upstage/solar-pro4"},"solar-mini4":{"id":"solar-mini4","name":"Solar Mini 4","description":"Upstage's compact, cost-efficient model for agentic use","family":"solar-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":131072},"cost":{"input":0.1,"output":0.4,"cache_read":0.01},"canonical_model_id":"upstage/solar-mini4"},"solar-mini":{"id":"solar-mini","name":"solar-mini","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"solar-mini","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2024-06-12","last_updated":"2025-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":4096},"cost":{"input":0.15,"output":0.15}}}},"salad-cloud":{"id":"salad-cloud","env":["SALAD_CLOUD_API_KEY"],"npm":"@saladtechnologies-oss/ai-sdk-provider","name":"SaladCloud AI Gateway","doc":"https://docs.salad.com/ai-gateway/explanation/overview","models":{"qwen3.6-35b-a3b":{"id":"qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Qwen MoE for agentic tasks, complex reasoning, code generation, and instruction following","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":262144},"cost":{"input":0.09,"output":0.6},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"}}},"berget":{"id":"berget","env":["BERGET_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.berget.ai/v1","name":"Berget.AI","doc":"https://api.berget.ai","models":{"Qwen/Qwen3.8-27B-FP8":{"id":"Qwen/Qwen3.8-27B-FP8","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.46,"output":3.48},"canonical_model_id":"alibaba/qwen3.8-27b"},"zai-org/GLM-5.3-Flash":{"id":"zai-org/GLM-5.3-Flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":16384},"cost":{"input":0.29,"output":0.58},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":32768},"status":"deprecated","cost":{"input":1.54,"output":4.84},"canonical_model_id":"zhipuai/glm-5.2"},"mistralai/Mistral-Small-3.2-24B-Instruct-2506":{"id":"mistralai/Mistral-Small-3.2-24B-Instruct-2506","name":"Mistral Small 3.2 24B Instruct 2506","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":8192},"cost":{"input":0.33645,"output":0.33645},"canonical_model_id":"mistral/mistral-small-3.2-24b-instruct"},"moonshotai/Kimi-K3":{"id":"moonshotai/Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":327680,"output":32768},"cost":{"input":3.3645,"output":16.8225,"cache_read":1.00935},"canonical_model_id":"moonshotai/kimi-k3"},"google/gemma-4-31B-it":{"id":"google/gemma-4-31B-it","name":"Gemma 4 31B Instruct","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["audio","image","text","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.280375,"output":0.56075},"canonical_model_id":"google/gemma-4-31b-it"}}},"kilo":{"id":"kilo","env":["KILO_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.kilo.ai/api/gateway","name":"Kilo Gateway","doc":"https://kilo.ai","models":{"undi95/remm-slerp-l2-13b":{"id":"undi95/remm-slerp-l2-13b","name":"ReMM SLERP 13B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-06-30","release_date":"2023-07-22","last_updated":"2023-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":6144,"output":5529},"cost":{"input":0.35,"output":0.65},"canonical_model_id":"undi95/remm-slerp-l2-13b"},"thinkingmachines/inkling-small":{"id":"thinkingmachines/inkling-small","name":"Inkling Small","description":"Inkling Small is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 12B active parameters out of 276B total. It is positioned as the smaller, more efficient member of...","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":262144},"cost":{"input":0.45,"output":1.2,"cache_read":0.1},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/inkling":{"id":"thinkingmachines/inkling","name":"Inkling","description":"Inkling is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 41B active parameters out of 975B total. It is designed for general-purpose reasoning, coding, agentic and tool-use systems,...","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":471859},"cost":{"input":0.95,"output":4.05,"cache_read":0.16},"canonical_model_id":"thinkingmachines/inkling"},"~unbiased/pareto-latest":{"id":"~unbiased/pareto-latest","name":"Pareto Latest","description":"This model always redirects to the latest model in the Pareto family.","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.8,"output":3.2,"cache_read":0.03}},"xiaomi/mimo-v2.6-pro-ultraspeed":{"id":"xiaomi/mimo-v2.6-pro-ultraspeed","name":"MiMo-V2.6-Pro-UltraSpeed","description":"MiMo-V2.6-Pro-UltraSpeed is the fast speed edition of Xiaomi's flagship foundation model, MiMo-V2.6-Pro. Built from the same 1T MiMo-V2.6-Pro checkpoint, it matches the original model in quality while delivering roughly 10x...","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":4.35,"output":8.7,"cache_read":0.036},"canonical_model_id":"xiaomi/mimo-v2.6-pro-ultraspeed"},"xiaomi/mimo-v2.6-flash":{"id":"xiaomi/mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo-V2.6-Flash is an open-source foundation model developed by Xiaomi. Built on a Mixture-of-Experts architecture with 309B total parameters and 15B activated per token, it employs a hybrid attention mechanism for...","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.1,"output":0.28,"cache_read":0.05},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"xiaomi/mimo-v2.6-pro":{"id":"xiaomi/mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"MiMo-V2.6-Pro is the flagship foundation model developed by Xiaomi. Built at a scale of over 1T parameters, it is designed to push the ceiling of capability for the most demanding...","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.43,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"xiaomi/mimo-v2.5-pro":{"id":"xiaomi/mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":945000},"status":"deprecated","cost":{"input":0.435,"output":0.87,"cache_read":0.004,"tiers":[{"input":2,"output":6,"cache_read":0.4,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.4}},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"xiaomi/mimo-v2.5":{"id":"xiaomi/mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":945000},"status":"deprecated","cost":{"input":0.14,"output":0.28,"cache_read":0.003,"tiers":[{"input":0.8,"output":4,"cache_read":0.16,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.8,"output":4,"cache_read":0.16}},"canonical_model_id":"xiaomi/mimo-v2.5"},"recursive/flint-v1.0:free":{"id":"recursive/flint-v1.0:free","name":"Recursive: Flint (free)","description":"Flint is an open-weight mixture-of-experts model from Recursive, with about 2.5B active parameters out of 40B total, built by Recursive's autoresearch system Eureka Machine for coding agents. It is suited...","family":"flint","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-21","last_updated":"2026-10-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":235929},"cost":{"input":0,"output":0}},"meituan/longcat-2.0":{"id":"meituan/longcat-2.0","name":"Meituan: LongCat 2.0","description":"LongCat 2.0 is a sparse mixture-of-experts language model from Meituan, with 48B active parameters out of 1.6T total. It is suited for coding, repository-level changes, long-horizon problem solving, and agentic...","family":"longcat","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048756,"output":262144},"cost":{"input":0.75,"output":3,"cache_read":0.015},"canonical_model_id":"meituan/longcat-2.0"},"sao10k/l3.1-euryale-70b":{"id":"sao10k/l3.1-euryale-70b","name":"Sao10K: Llama 3.1 Euryale 70B v2.2","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-28","last_updated":"2024-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.85,"output":0.85},"canonical_model_id":"sao10k/l3.1-euryale-70b"},"sao10k/l3-lunaris-8b":{"id":"sao10k/l3-lunaris-8b","name":"Sao10K: Llama 3 8B Lunaris","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-13","last_updated":"2024-08-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":7372},"cost":{"input":0.04,"output":0.05},"canonical_model_id":"sao10k/l3-lunaris-8b"},"elorian/glimpse":{"id":"elorian/glimpse","name":"Elorian: Glimpse","description":"Glimpse is a multimodal visual reasoning model from Elorian, built for visual understanding and complex visual reasoning in the physical world. It reasons directly over images and video rather than...","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":256000},"cost":{"input":0.6,"output":3,"cache_read":0.06}},"reflection/beam-free":{"id":"reflection/beam-free","name":"Reflection: Beam 1.0 (free)","description":"Your prompts and completions may be retained and used to train or improve the provider's services. Beam is Reflection's reasoning model for coding and agentic workflows, combining strong coding capabilities with fast, low-latency inference, served through Vercel AI Gateway at no cost. It supports function calling, structured outputs, and streaming, and takes text input only. Zero Data Retention is not available for this model.","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"reasoning":0,"cache_read":0}},"reflection/beam-1.0-501b-a23b":{"id":"reflection/beam-1.0-501b-a23b","name":"Reflection: Beam 1.0 501B A23B","description":"Beam 1.0 is Reflection's open-weight reasoning model for coding and long-horizon agentic workflows. It uses a sparse mixture-of-experts architecture with 501B total and 23B active parameters per token, and a...","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-06-30","release_date":"2026-10-05","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":0.25,"output":1,"cache_read":0.05},"canonical_model_id":"reflection/beam-1.0-501b-a23b"},"ibm-granite/granite-4.0-h-micro":{"id":"ibm-granite/granite-4.0-h-micro","name":"IBM: Granite 4.0 Micro","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"granite","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-10-20","last_updated":"2025-10-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":117900},"cost":{"input":0.017,"output":0.112}},"ibm-granite/granite-4.2-8b":{"id":"ibm-granite/granite-4.2-8b","name":"IBM: Granite 4.2 8B","description":"Granite 4.2 8B is a dense reasoning model from IBM. It is suited for mathematics, code generation, multilingual dialogue, and agentic workflows that need multi-step reasoning. It supports full, low-effort,...","family":"granite","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-25","last_updated":"2026-08-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.06,"output":0.25,"cache_read":0.015},"canonical_model_id":"ibm/granite-4.2-8b"},"thedrummer/skyfall-36b-v2":{"id":"thedrummer/skyfall-36b-v2","name":"TheDrummer: Skyfall 36B V2","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2025-03-10","last_updated":"2025-03-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":29491},"cost":{"input":0.55,"output":0.8,"cache_read":0.25},"canonical_model_id":"thedrummer/skyfall-36b-v2"},"thedrummer/unslopnemo-12b":{"id":"thedrummer/unslopnemo-12b","name":"TheDrummer: UnslopNemo 12B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-04-30","release_date":"2024-11-08","last_updated":"2024-11-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":819200},"cost":{"input":0.4,"output":0.4},"canonical_model_id":"thedrummer/unslopnemo-12b"},"thedrummer/cydonia-24b-v4.1":{"id":"thedrummer/cydonia-24b-v4.1","name":"TheDrummer: Cydonia 24B V4.1","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-04-30","release_date":"2025-09-27","last_updated":"2025-09-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.3,"output":0.5,"cache_read":0.15},"canonical_model_id":"thedrummer/cydonia-24b-v4.1"},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude Opus 4.8","description":"Claude Opus 4.8 is Anthropic's most capable generally available model in the Opus family. It supports text, image, and file inputs with text output, with reasoning support and a 1M-token...","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude Fable 5 is a Mythos-class model from Anthropic, built for autonomous knowledge work and coding. It supports text, image, and file inputs with text output, with reasoning support and...","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Claude Opus 5 is Anthropic’s flagship model for demanding reasoning, coding, and long-horizon agentic work. It is particularly strong at end-to-end software tasks, code review and bug finding, visual analysis...","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-haiku-5.5":{"id":"anthropic/claude-haiku-5.5","name":"Claude Haiku 5.5","description":"Claude Haiku 5.5 is Anthropic's small, fast model for high-volume, cost-sensitive work such as summarization, subagents, and browser use. It succeeds Claude Haiku 4.5 with stronger coding, computer use, and...","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude Sonnet 4.6","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-4.6":{"id":"anthropic/claude-opus-4.6","name":"Claude Opus 4.6","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Sonnet 5 is Anthropic's most capable Sonnet-class model, with frontier performance across coding, agents, and professional work. It supports adaptive thinking with selectable reasoning effort levels (low, medium, high, max,...","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-opus-5.5":{"id":"anthropic/claude-opus-5.5","name":"Claude Opus 5.5","description":"Claude Opus 5.5 is Anthropic's flagship model for demanding reasoning, coding, and long-horizon agentic work, succeeding Claude Opus 5. It is particularly strong at multi-step changes in large codebases, code...","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-haiku-4.5":{"id":"anthropic/claude-haiku-4.5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-opus-4.1":{"id":"anthropic/claude-opus-4.1","name":"Claude Opus 4.1 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1"},"anthropic/claude-sonnet-5.5":{"id":"anthropic/claude-sonnet-5.5","name":"Claude Sonnet 5.5","description":"Claude Sonnet 5.5 is Anthropic's Sonnet-class model for well-scoped everyday work, succeeding Claude Sonnet 5 as a direct upgrade. It is especially strong at building features, fixing bugs, and producing...","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-sonnet-4.5":{"id":"anthropic/claude-sonnet-4.5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-fable-5.1":{"id":"anthropic/claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude Fable 5.1 improves on Claude Fable 5 across the board, with the biggest gains in agentic coding, long-running agentic workflows, and knowledge work: long code refactors, front-end and visual...","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-opus-4.5":{"id":"anthropic/claude-opus-4.5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude Opus 4.7","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"bytedance-seed/seed-1.6-flash":{"id":"bytedance-seed/seed-1.6-flash","name":"ByteDance Seed: Seed 1.6 Flash (retires Nov 11)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-28","last_updated":"2025-08-28","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"status":"deprecated","cost":{"input":0.075,"output":0.3},"canonical_model_id":"bytedance-seed/seed-1-6-flash"},"bytedance-seed/seed-2-1-turbo":{"id":"bytedance-seed/seed-2-1-turbo","name":"ByteDance Seed: Seed 2.1 Turbo","description":"Seed 2.1 Turbo is a multimodal model from ByteDance Seed for coding and long-horizon agent workflows. It is suited for end-to-end software delivery, multi-step task execution, and understanding visual and...","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":235929},"cost":{"input":0.5,"output":2.5},"canonical_model_id":"bytedance-seed/seed-2.1-turbo"},"bytedance-seed/seed-1.6":{"id":"bytedance-seed/seed-1.6","name":"ByteDance Seed: Seed 1.6 (retires Nov 11)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"status":"deprecated","cost":{"input":0.25,"output":2},"canonical_model_id":"bytedance-seed/seed-1-6"},"bytedance-seed/seed-2.0-mini":{"id":"bytedance-seed/seed-2.0-mini","name":"Seed 2.0 Mini","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.1,"output":0.4},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"bytedance-seed/seed-2.0-code":{"id":"bytedance-seed/seed-2.0-code","name":"Seed 2.0 Code","description":"Seed 2.0 Code is a model from ByteDance Seed optimized for agentic coding. It is suited for frontend development, multilingual programming tasks, and coding-agent workflows in tools such as Claude...","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"status":"deprecated","cost":{"input":0.5,"output":3},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"bytedance-seed/seed-2.0-lite":{"id":"bytedance-seed/seed-2.0-lite","name":"Seed 2.0 Lite","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.25,"output":2},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"morph/morph-v3-large":{"id":"morph/morph-v3-large","name":"Morph: Morph V3 Large","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"morph","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-07-07","last_updated":"2025-07-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.9,"output":1.9},"canonical_model_id":"morph/morph-v3-large"},"morph/morph-v3-fast":{"id":"morph/morph-v3-fast","name":"Morph: Morph V3 Fast","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"morph","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-07-07","last_updated":"2025-07-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.8,"output":1.2},"canonical_model_id":"morph/morph-v3-fast"},"upstage/solar-pro-3":{"id":"upstage/solar-pro-3","name":"Upstage: Solar Pro 3","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07","release_date":"2026-01-26","last_updated":"2026-03-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":117964},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"upstage/solar-pro3"},"upstage/solar-pro4":{"id":"upstage/solar-pro4","name":"Upstage: Solar Pro 4","description":"Solar Pro 4 is a large language model from Upstage. It is suited for agentic workflows, office productivity, document-intensive work, and coding.","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02","release_date":"2026-08-06","last_updated":"2026-08-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"upstage/solar-pro4"},"upstage/solar-mini4":{"id":"upstage/solar-mini4","name":"Upstage: Solar Mini 4","description":"Solar Mini 4 is Upstage's compact, cost-efficient language model, a 35B-parameter mixture-of-experts with 3B active parameters and a 524K context window. It is built for agentic use cases where response...","family":"solar-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":131072},"cost":{"input":0.1,"output":0.4,"cache_read":0.01},"canonical_model_id":"upstage/solar-mini4"},"poolside/laguna-s-2.1:free":{"id":"poolside/laguna-s-2.1:free","name":"Poolside: Laguna S 2.1 (free)","description":"Laguna S 2.1 is the latest coding agent model from [Poolside]( ). Laguna S 2.1 is a 118B total parameter model with 8B active parameters, scoring 70.2% on Terminal-Bench 2.1 and...","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"poolside/laguna-s-2.1"},"poolside/laguna-xs-2.1":{"id":"poolside/laguna-xs-2.1","name":"Poolside: Laguna XS 2.1 (retires Oct 31)","description":"Laguna XS 2.1 is the latest coding agent model in the 33B-A3B category from [Poolside](https://poolside.ai/) and a step forward from their Laguna XS.2 model (released in April 2026). It combines...","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-02","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"status":"deprecated","cost":{"input":0.1,"output":0.2,"cache_read":0.05},"canonical_model_id":"poolside/laguna-xs-2.1"},"poolside/laguna-xs-2.1:free":{"id":"poolside/laguna-xs-2.1:free","name":"Poolside: Laguna XS 2.1 (free)","description":"Laguna XS 2.1 is the latest coding agent model in the 33B-A3B category from [Poolside](https://poolside.ai/) and a step forward from their Laguna XS.2 model (released in April 2026). It combines...","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-02","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"poolside/laguna-xs-2.1"},"poolside/laguna-s-2.1":{"id":"poolside/laguna-s-2.1","name":"Poolside: Laguna S 2.1 (retires Oct 31)","description":"Laguna S 2.1 is the latest coding agent model from [Poolside]( ). Laguna S 2.1 is a 118B total parameter model with 8B active parameters, scoring 70.2% on Terminal-Bench 2.1 and...","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0.1,"output":0.2,"cache_read":0.01},"canonical_model_id":"poolside/laguna-s-2.1"},"x-ai/grok-build-0.1":{"id":"x-ai/grok-build-0.1","name":"Grok Build 0.1","description":"Grok coding model for agentic engineering, edits, and codebase workflows","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":230400},"cost":{"input":1,"output":2,"cache_read":0.2},"canonical_model_id":"xai/grok-build-0.1"},"x-ai/grok-4.3":{"id":"x-ai/grok-4.3","name":"Grok 4.3","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":900000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2},"canonical_model_id":"xai/grok-4.3"},"x-ai/grok-4.7":{"id":"x-ai/grok-4.7","name":"Grok 4.7","description":"Grok 4.7 is SpaceXAI's smartest model with frontier performance on coding, knowledge work, and STEM.","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.7"},"x-ai/grok-4.20":{"id":"x-ai/grok-4.20","name":"SpaceXAI: Grok 4.20","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-31","last_updated":"2026-03-31","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":1800000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2}},"x-ai/grok-4.6":{"id":"x-ai/grok-4.6","name":"Grok 4.6","description":"Grok 4.6 is SpaceXAI's smartest model with frontier performance on coding, knowledge work, and STEM.","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"x-ai/grok-4.20-multi-agent":{"id":"x-ai/grok-4.20-multi-agent","name":"SpaceXAI: Grok 4.20 Multi-Agent","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-03-31","last_updated":"2026-03-31","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":1800000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2}},"x-ai/grok-4.5":{"id":"x-ai/grok-4.5","name":"Grok 4.5","description":"Grok 4.5 is SpaceXAI's smartest model with frontier performance on coding, knowledge work, and STEM.","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.3},"canonical_model_id":"xai/grok-4.5"},"~anthropic/claude-haiku-latest":{"id":"~anthropic/claude-haiku-latest","name":"Anthropic: Claude Haiku Latest","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125}},"~anthropic/claude-sonnet-latest":{"id":"~anthropic/claude-sonnet-latest","name":"Anthropic: Claude Sonnet Latest","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5}},"~anthropic/claude-fable-latest":{"id":"~anthropic/claude-fable-latest","name":"Anthropic: Claude Fable Latest ($$$$)","description":"This model always redirects to the latest model in the Claude Fable family.","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5}},"~anthropic/claude-opus-latest":{"id":"~anthropic/claude-opus-latest","name":"Anthropic: Claude Opus Latest","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5}},"mancer/weaver":{"id":"mancer/weaver","name":"Mancer: Weaver (alpha)","description":"An attempt to recreate Claude-style verbosity, but don't expect the same level of coherence or memory. Meant for use in roleplay/narrative situations.","family":"alpha","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-06-30","release_date":"2023-08-02","last_updated":"2023-08-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8000,"output":6000},"cost":{"input":0.4,"output":0.75},"canonical_model_id":"mancer/weaver"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"GPT-6 Sol is the cost-efficient high-end model in OpenAI's GPT-6 series, positioned below the flagship GPT-6 Astra and above the fast GPT-6 Luna tier. It is suited for demanding professional...","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-6-sol"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, positioned below GPT-6 Sol. It is suited for high-volume and latency-sensitive workloads such as chat, classification, and lightweight agentic...","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.03,"output":0.15,"cache_read":0.015},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"GPT-6.1 Sol is an upgrade to GPT-6 Sol from OpenAI, positioned below the flagship GPT-6 Astra in the GPT-6 series. It is suited for agentic coding, computer use, document-heavy professional...","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-4":{"id":"openai/gpt-4","name":"GPT-4","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-11","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":8191,"output":4096},"cost":{"input":30,"output":60},"canonical_model_id":"openai/gpt-4"},"openai/gpt-5-pro":{"id":"openai/gpt-5-pro","name":"GPT-5 Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":15,"output":120},"canonical_model_id":"openai/gpt-5-pro"},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT-5.4 Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180},"canonical_model_id":"openai/gpt-5.4-pro"},"openai/o1":{"id":"openai/o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":15,"output":60,"cache_read":7.5},"canonical_model_id":"openai/o1"},"openai/gpt-4o-2024-05-13":{"id":"openai/gpt-4o-2024-05-13","name":"GPT-4o (2024-05-13)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-05-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":5,"output":15},"canonical_model_id":"openai/gpt-4o-2024-05-13"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-6-astra-pro":{"id":"openai/gpt-6-astra-pro","name":"OpenAI: GPT-6 Astra Pro ($$$$)","description":"GPT-6 Astra Pro is the same underlying model as [GPT-6 Astra](https://openrouter.ai/openai/gpt-6-astra), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5}},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-3.5-turbo-16k":{"id":"openai/gpt-3.5-turbo-16k","name":"OpenAI: GPT-3.5 Turbo 16k","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2023-08-28","last_updated":"2023-08-28","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"output":4096},"cost":{"input":3,"output":4}},"openai/gpt-5.4-image-2":{"id":"openai/gpt-5.4-image-2","type":"image","name":"GPT-5.4 Image 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":false,"structured_output":true,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["image","text","pdf"],"output":["image","text"]},"open_weights":false,"limit":{"context":272000,"output":128000},"cost":{"input":8,"output":15,"cache_read":2},"canonical_model_id":"openai/gpt-5.4-image-2"},"openai/gpt-chat-latest":{"id":"openai/gpt-chat-latest","name":"OpenAI: GPT Chat Latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-05-05","last_updated":"2026-05-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5}},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"GPT-5.6 Luna is a fast, cost-efficient model in OpenAI's GPT-5.6 series. It is suited for high-volume, latency-sensitive tasks such as chat, classification, and lightweight agentic workflows, providing capable reasoning for...","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.2-pro":{"id":"openai/gpt-5.2-pro","name":"GPT-5.2 Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":21,"output":168},"canonical_model_id":"openai/gpt-5.2-pro"},"openai/gpt-3.5-turbo-0613":{"id":"openai/gpt-3.5-turbo-0613","name":"OpenAI: GPT-3.5 Turbo (older v0613)","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":4095,"output":3685},"cost":{"input":1,"output":2}},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-6-luna-pro":{"id":"openai/gpt-6-luna-pro","name":"OpenAI: GPT-6 Luna Pro","description":"GPT-6 Luna Pro is the same underlying model as [GPT-6 Luna](https://openrouter.ai/openai/gpt-6-luna), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125}},"openai/o1-pro":{"id":"openai/o1-pro","name":"o1-pro","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":false,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2025-03-19","last_updated":"2025-03-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":150,"output":600},"canonical_model_id":"openai/o1-pro"},"openai/o3-mini-high":{"id":"openai/o3-mini-high","name":"OpenAI: o3 Mini High","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2025-02-12","last_updated":"2025-02-12","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55}},"openai/gpt-4o-2024-08-06":{"id":"openai/gpt-4o-2024-08-06","name":"GPT-4o (2024-08-06)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-08-06","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-08-06"},"openai/gpt-5.1-codex-max":{"id":"openai/gpt-5.1-codex-max","name":"GPT-5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex-max"},"openai/gpt-oss-safeguard-20b":{"id":"openai/gpt-oss-safeguard-20b","name":"GPT OSS Safeguard 20B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.075,"output":0.3,"cache_read":0.0375},"canonical_model_id":"openai/gpt-oss-safeguard-20b"},"openai/gpt-audio":{"id":"openai/gpt-audio","type":"chat","name":"GPT-Audio","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-01","release_date":"2025-08-28","last_updated":"2025-08-28","modalities":{"input":["text","audio","pdf"],"output":["text","audio"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10},"canonical_model_id":"openai/gpt-audio"},"openai/gpt-5-image-mini":{"id":"openai/gpt-5-image-mini","type":"image","name":"GPT-5 Image Mini","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-10-16","last_updated":"2025-10-16","modalities":{"input":["pdf","image","text"],"output":["image","text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":2.5,"output":2,"cache_read":0.25},"canonical_model_id":"openai/gpt-5-image-mini"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"GPT-5.6 Sol is the flagship model in OpenAI's GPT-5.6 series. It is suited for complex reasoning, coding, and agentic workflows, and is particularly strong at command-line and multi-step coding tasks...","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-3.5-turbo-instruct":{"id":"openai/gpt-3.5-turbo-instruct","name":"OpenAI: GPT-3.5 Turbo Instruct","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2023-09-28","last_updated":"2023-09-28","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":4095,"output":3685},"cost":{"input":1.5,"output":2}},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.018,"output":0.09,"cache_read":0.009},"canonical_model_id":"openai/gpt-oss-20b"},"openai/gpt-5.2-codex":{"id":"openai/gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-codex"},"openai/gpt-4o-2024-11-20":{"id":"openai/gpt-4o-2024-11-20","name":"GPT-4o (2024-11-20)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-11-20","last_updated":"2024-11-20","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-11-20"},"openai/gpt-5-image":{"id":"openai/gpt-5-image","type":"image","name":"GPT-5 Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-10-01","release_date":"2025-10-14","last_updated":"2025-10-14","modalities":{"input":["image","text","pdf"],"output":["image","text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":10,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-5-image"},"openai/gpt-5.5-pro":{"id":"openai/gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180},"canonical_model_id":"openai/gpt-5.5-pro"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1 nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5.1-codex":{"id":"openai/gpt-5.1-codex","name":"GPT-5.1 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.13},"canonical_model_id":"openai/gpt-5.1-codex"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-4-turbo":{"id":"openai/gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":10,"output":30},"canonical_model_id":"openai/gpt-4-turbo"},"openai/o3-pro":{"id":"openai/o3-pro","name":"o3-pro","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-06-10","last_updated":"2025-06-10","modalities":{"input":["text","pdf","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":20,"output":80},"canonical_model_id":"openai/o3-pro"},"openai/o3":{"id":"openai/o3","name":"o3","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"GPT-5.6 Terra is a balanced model in OpenAI's GPT-5.6 series, positioned between the flagship Sol tier and the cost-efficient Luna tier. It is suited for everyday coding, reasoning, and agentic...","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-6.1-sol-pro":{"id":"openai/gpt-6.1-sol-pro","name":"OpenAI: GPT-6.1 Sol Pro","description":"GPT-6.1 Sol Pro is the same underlying model as [GPT-6.1 Sol](https://openrouter.ai/openai/gpt-6.1-sol), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. **Cost note:** pro mode spends far more...","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5}},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"openai/gpt-audio-mini":{"id":"openai/gpt-audio-mini","type":"chat","name":"GPT-Audio Mini","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-01","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","audio","pdf"],"output":["text","audio"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.6,"output":2.4},"canonical_model_id":"openai/gpt-audio-mini"},"openai/gpt-5.2-chat":{"id":"openai/gpt-5.2-chat","name":"OpenAI: GPT-5.2 Chat","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-chat-latest"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"openai/gpt-3.5-turbo":{"id":"openai/gpt-3.5-turbo","name":"GPT-3.5-turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"output":4096},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"openai/gpt-3.5-turbo"},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3-mini","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"openai/gpt-5.6-luna-pro":{"id":"openai/gpt-5.6-luna-pro","name":"GPT-5.6 Luna","description":"GPT-5.6 Luna Pro is the same underlying model as [GPT-5.6 Luna](https://openrouter.ai/openai/gpt-5.6-luna), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-6-sol-pro":{"id":"openai/gpt-6-sol-pro","name":"OpenAI: GPT-6 Sol Pro","description":"GPT-6 Sol Pro is the same underlying model as [GPT-6 Sol](https://openrouter.ai/openai/gpt-6-sol), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5}},"openai/gpt-5.1-codex-mini":{"id":"openai/gpt-5.1-codex-mini","name":"GPT-5.1 Codex mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.03},"canonical_model_id":"openai/gpt-5.1-codex-mini"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"openai/gpt-5.6-terra-pro":{"id":"openai/gpt-5.6-terra-pro","name":"GPT-5.6 Terra","description":"GPT-5.6 Terra Pro is the same underlying model as [GPT-5.6 Terra](https://openrouter.ai/openai/gpt-5.6-terra), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/o4-mini":{"id":"openai/o4-mini","name":"o4-mini","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.275},"canonical_model_id":"openai/o4-mini"},"openai/gpt-4o-mini-2024-07-18":{"id":"openai/gpt-4o-mini-2024-07-18","name":"OpenAI: GPT-4o-mini (2024-07-18)","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-5.6-sol-pro":{"id":"openai/gpt-5.6-sol-pro","name":"GPT-5.6 Sol","description":"GPT-5.6 Sol Pro is the same underlying model as [GPT-5.6 Sol](https://openrouter.ai/openai/gpt-5.6-sol), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's flagship model for demanding end-to-end work. It is suited for advanced analysis, software engineering, deep research, scientific work, and document creation, with particular strengths in long-horizon...","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"openai/gpt-6-astra"},"openai/o4-mini-high":{"id":"openai/o4-mini-high","name":"OpenAI: o4 Mini High","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.275}},"~deepseek/deepseek-pro-latest":{"id":"~deepseek/deepseek-pro-latest","name":"DeepSeek: DeepSeek Pro Latest","description":"This model always redirects to the latest model in the DeepSeek Pro family.","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-14","last_updated":"2026-09-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":393216},"cost":{"input":0.2235,"output":8,"cache_read":0.22}},"~deepseek/deepseek-v4-flash-latest":{"id":"~deepseek/deepseek-v4-flash-latest","name":"DeepSeek: DeepSeek V4 Flash Latest","description":"This model always redirects to the latest model in the DeepSeek V4 Flash family.","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-01","last_updated":"2026-08-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.0475,"output":0.1568,"cache_read":0.028}},"~deepseek/deepseek-flash-latest":{"id":"~deepseek/deepseek-flash-latest","name":"DeepSeek: DeepSeek Flash Latest","description":"This model always redirects to the latest model in the DeepSeek Flash family.","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-14","last_updated":"2026-09-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.07,"output":0.5,"cache_read":0.008}},"xingchen-agi/xing4.0-29b-a4b:free":{"id":"xingchen-agi/xing4.0-29b-a4b:free","name":"XingChen: Xing4.0 29B A4B (free)","description":"Xing4.0-29B-A4B is an open-weight mixture-of-experts language model from China Telecom's AI team (TeleAI) and the successor to the TeleChat series. It has 29B total parameters with 4B active per token...","family":"agi","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-16","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":235929},"cost":{"input":0,"output":0}},"inception/mercury-2":{"id":"inception/mercury-2","name":"Inception: Mercury 2","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-24","last_updated":"2026-02-24","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":50000},"cost":{"input":0.25,"output":0.75,"cache_read":0.025},"canonical_model_id":"inception/mercury-2"},"inception/mercury-3":{"id":"inception/mercury-3","name":"Inception: Mercury 3","description":"Mercury 3 is a diffusion-based language model from Inception, and the lab's most capable model to date. It is suited for agentic workflows and real-time applications where latency compounds, such...","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-16","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.2,"output":0.7,"cache_read":0.02}},"inception/mercury-2.5":{"id":"inception/mercury-2.5","name":"Inception: Mercury 2.5","description":"Mercury 2.5 is the fastest reasoning LLM, and the latest diffusion LLM (dLLM) from Inception. Instead of generating tokens sequentially, Mercury 2.5 produces and refines multiple tokens in parallel, achieving...","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":260000,"output":65536},"cost":{"input":0.2,"output":0.75,"cache_read":0.02},"canonical_model_id":"inception/mercury-2.5"},"bytedance/ui-tars-1.5-7b":{"id":"bytedance/ui-tars-1.5-7b","name":"ByteDance: UI-TARS 7B ","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":2048},"cost":{"input":0.1,"output":0.2,"cache_read":0.1}},"perplexity/sonar-reasoning-pro":{"id":"perplexity/sonar-reasoning-pro","name":"Perplexity: Sonar Reasoning Pro","description":"Web-grounded reasoning model for multi-step research and cited answers","family":"sonar-reasoning","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-03-07","last_updated":"2025-03-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":115200},"cost":{"input":2,"output":8}},"perplexity/sonar-deep-research":{"id":"perplexity/sonar-deep-research","name":"Perplexity: Sonar Deep Research","description":"Sonar search model for current answers, retrieval, and citation-backed chat","family":"sonar-deep-research","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-03-07","last_updated":"2025-03-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":115200},"cost":{"input":2,"output":8,"reasoning":3}},"perplexity/sonar":{"id":"perplexity/sonar","name":"Perplexity: Sonar","description":"Sonar search model for current answers, retrieval, and citation-backed chat","family":"sonar","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-01-27","last_updated":"2025-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":127072,"output":114364},"cost":{"input":1,"output":1}},"perplexity/sonar-pro-search":{"id":"perplexity/sonar-pro-search","name":"Perplexity: Sonar Pro Search","description":"Advanced Sonar search model for deeper research and cited synthesis","family":"sonar-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-10-30","last_updated":"2025-10-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8000},"cost":{"input":3,"output":15}},"perplexity/sonar-pro":{"id":"perplexity/sonar-pro","name":"Perplexity: Sonar Pro","description":"Advanced Sonar search model for deeper research and cited synthesis","family":"sonar-pro","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-03-07","last_updated":"2025-03-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8000},"cost":{"input":3,"output":15}},"stealth/claude-opus-4.8":{"id":"stealth/claude-opus-4.8","name":"Stealth: Claude Opus 4.8 (20% off)","description":"Your prompts and completions may be retained and used to train or improve the provider's services. This third-party-served variant of Claude Opus 4.8 is offered at 20% lower cost than standard Claude Opus 4.8 pricing and is not served by Anthropic or Kilo Code.","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"reasoning":0,"cache_read":0.4,"cache_write":5}},"stealth/claude-sonnet-4.6":{"id":"stealth/claude-sonnet-4.6","name":"Stealth: Claude Sonnet 4.6 (20% off)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":2.4,"output":12,"reasoning":0,"cache_read":0.24,"cache_write":3}},"stealth/claude-opus-4.6":{"id":"stealth/claude-opus-4.6","name":"Stealth: Claude Opus 4.6 (20% off)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"reasoning":0,"cache_read":0.4,"cache_write":5}},"stealth/qwen3.6-plus":{"id":"stealth/qwen3.6-plus","name":"Stealth: Qwen3.6 Plus (50% off)","description":"Your prompts and completions may be retained and used to train or improve the provider's services. This third-party-served variant of Qwen3.6 Plus is offered at 50% lower cost than standard Qwen3.6 Plus pricing and is not served by Alibaba or Kilo Code. Note: a surcharge applies to long-context workloads exceeding 256K input tokens.","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.25,"output":1.5,"reasoning":0,"cache_read":0.025,"cache_write":0.3125}},"stealth/claude-opus-4.7":{"id":"stealth/claude-opus-4.7","name":"Stealth: Claude Opus 4.7 (20% off)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"reasoning":0,"cache_read":0.4,"cache_write":5}},"stealth/glyph-cluster":{"id":"stealth/glyph-cluster","name":"Stealth: Glyph Cluster (free)","description":"Your prompts and completions may be retained and used to train or improve the provider's services. Glyph Cluster is a reasoning model for coding and long-context analysis, served through Vercel AI Gateway during its stealth period at no cost. It supports function calling and streaming, takes text input only, and does not support structured outputs. Zero Data Retention is not available for this model.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0,"output":0,"reasoning":0,"cache_read":0}},"relace/relace-apply-3":{"id":"relace/relace-apply-3","name":"Relace: Relace Apply 3","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2025-09-26","last_updated":"2025-09-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.85,"output":1.25},"canonical_model_id":"relace/relace-apply-3"},"relace/relace-search":{"id":"relace/relace-search","name":"Relace: Relace Search","description":"Tool-capable chat model for instruction following and agentic application workflows","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":1,"output":3},"canonical_model_id":"relace/relace-search"},"kilo-auto/free":{"id":"kilo-auto/free","name":"Auto Free","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"1970-01-01","last_updated":"1970-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32768},"cost":{"input":0,"output":0,"reasoning":0,"cache_read":0,"cache_write":0}},"kilo-auto/frontier":{"id":"kilo-auto/frontier","name":"Auto Frontier","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"1970-01-01","last_updated":"1970-01-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"reasoning":0,"cache_read":0.5,"cache_write":6.25}},"kilo-auto/balanced":{"id":"kilo-auto/balanced","name":"Auto Balanced","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"1970-01-01","last_updated":"1970-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.325,"output":1.95,"reasoning":0,"cache_read":0.0325,"cache_write":0.40625}},"kilo-auto/efficient":{"id":"kilo-auto/efficient","name":"Auto Efficient","description":"Routes each request to the cheapest model that gets the job done, based on continuously benchmarked accuracy and cost.","family":"auto","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"1970-01-01","last_updated":"1970-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.325,"output":1.95,"reasoning":0,"cache_read":0.0325,"cache_write":0.40625}},"kilo-auto/small":{"id":"kilo-auto/small","name":"Auto Small","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"1970-01-01","last_updated":"1970-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.05,"output":0.4,"reasoning":0,"cache_read":0.005}},"inclusionai/ling-3.1-flash":{"id":"inclusionai/ling-3.1-flash","name":"inclusionAI: Ling 3.1 Flash","description":"Ling 3.1 Flash is a hybrid reasoning mixture-of-experts model from inclusionAI, with 25B active parameters out of 560B total.","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.3,"output":0.9,"cache_read":0.06},"canonical_model_id":"inclusionai/ling-3.1-flash"},"inclusionai/ling-3.0-flash-vl":{"id":"inclusionai/ling-3.0-flash-vl","name":"inclusionAI: Ling 3.0 Flash VL","description":"Ling 3.0 Flash VL builds on Ling 3.0 Flash (124B total / 5.5B active MoE from InclusionAI), further strengthening its language capabilities while adding native visual perception and advanced visual...","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.06,"output":0.18,"cache_read":0.012},"canonical_model_id":"inclusionai/ling-3.0-flash-vl"},"inclusionai/ling-3.0-flash":{"id":"inclusionai/ling-3.0-flash","name":"inclusionAI: Ling 3.0 Flash","description":"*Ling-3.0-flash* is a *124B-parameter Mixture-of-Experts (MoE) model*, with approximately *5.1B parameters activated per token*. The model is designed with *token efficiency and production-scale agentic inference* as key priorities, enabling developers...","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-23","last_updated":"2026-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.06,"output":0.18,"cache_read":0.012},"canonical_model_id":"inclusionai/ling-3.0-flash"},"~openai/gpt-mini-latest":{"id":"~openai/gpt-mini-latest","name":"OpenAI: GPT Mini Latest","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075}},"~openai/gpt-terra-latest":{"id":"~openai/gpt-terra-latest","name":"OpenAI: GPT Terra Latest","description":"This model always redirects to the latest model in the OpenAI GPT Terra family.","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5}},"~openai/gpt-luna-latest":{"id":"~openai/gpt-luna-latest","name":"OpenAI: GPT Luna Latest","description":"This model always redirects to the latest model in the OpenAI GPT Luna family.","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125}},"~openai/gpt-astra-latest":{"id":"~openai/gpt-astra-latest","name":"OpenAI: GPT Astra Latest ($$$$)","description":"This model always redirects to the latest model in the OpenAI GPT Astra family.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5}},"~openai/gpt-sol-latest":{"id":"~openai/gpt-sol-latest","name":"OpenAI: GPT Sol Latest","description":"This model always redirects to the latest model in the OpenAI GPT Sol family.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5}},"openrouter/free":{"id":"openrouter/free","name":"OpenRouter Free Models Router","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-01","last_updated":"2026-02-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32768},"cost":{"input":0,"output":0}},"openrouter/bodybuilder":{"id":"openrouter/bodybuilder","name":"Body Builder (beta)","description":"Preview model for early access evaluation, prototyping, and compatibility testing","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2026-03-15","last_updated":"2026-03-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32768},"status":"beta","cost":{"input":0,"output":0}},"openrouter/pareto-code":{"id":"openrouter/pareto-code","name":"Pareto Code Router","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-05-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":65536},"cost":{"input":0,"output":0}},"openrouter/auto":{"id":"openrouter/auto","name":"Auto Router","description":"Image model for prompt-driven generation, editing, and visual design workflows","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-15","last_updated":"2026-03-15","modalities":{"input":["audio","image","pdf","text","video"],"output":["image","text"]},"open_weights":false,"limit":{"context":2000000,"output":32768},"cost":{"input":0,"output":0}},"anthracite-org/magnum-v4-72b":{"id":"anthracite-org/magnum-v4-72b","name":"Magnum v4 72B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":4096},"cost":{"input":2.5,"output":5},"canonical_model_id":"anthracite-org/magnum-v4-72b"},"prism-ml/ternary-bonsai-2-27b":{"id":"prism-ml/ternary-bonsai-2-27b","name":"PrismML: Ternary Bonsai 2 27B","description":"Bonsai 2 27B is a 27B-parameter reasoning model from PrismML derived from Qwen3.8-27B. It supports coding, mathematics, tool calling, and image understanding with a 262K-token context window. Ternary compression shrinks...","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-18","last_updated":"2026-09-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.075,"output":0.5,"cache_read":0.0375}},"writer/palmyra-x5":{"id":"writer/palmyra-x5","name":"Writer: Palmyra X5","description":"General-purpose chat model for instruction following, writing, and analysis","family":"palmyra","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1040000,"output":8192},"cost":{"input":0.6,"output":6},"canonical_model_id":"writer/palmyra-x5"},"~z-ai/glm-latest":{"id":"~z-ai/glm-latest","name":"Z.ai: GLM Latest","description":"This model always redirects to the latest GLM model from Z.ai.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-19","last_updated":"2026-08-19","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.079,"output":1.4,"cache_read":0.078}},"~z-ai/glm-flash-latest":{"id":"~z-ai/glm-flash-latest","name":"Z.ai: GLM Flash Latest","description":"This model always redirects to the latest model in the GLM Flash family.","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.018,"output":0.121,"cache_read":0.018}},"mistralai/mistral-large-2512":{"id":"mistralai/mistral-large-2512","name":"Mistral Large 3","description":"Mistral Large 3 2512 is Mistral’s most capable model to date, featuring a sparse mixture-of-experts architecture with 41B active parameters (675B total), and released under the Apache 2.0 license.","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.5,"output":1.5,"cache_read":0.05},"canonical_model_id":"mistral/mistral-large-2512"},"mistralai/ministral-8b-2512":{"id":"mistralai/ministral-8b-2512","name":"Ministral 3 8B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.15,"output":0.15,"cache_read":0.015},"canonical_model_id":"mistral/ministral-8b-2512"},"mistralai/mistral-nemo":{"id":"mistralai/mistral-nemo","name":"Mistral Nemo","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.15,"output":0.15,"cache_read":0.015},"canonical_model_id":"mistral/mistral-nemo"},"mistralai/ministral-14b-2512":{"id":"mistralai/ministral-14b-2512","name":"Ministral 3 14B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.2,"output":0.2,"cache_read":0.02},"canonical_model_id":"mistral/ministral-14b-2512"},"mistralai/ministral-3b-2512":{"id":"mistralai/ministral-3b-2512","name":"Ministral 3 3B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":104857},"cost":{"input":0.1,"output":0.1,"cache_read":0.01},"canonical_model_id":"mistral/ministral-3b-2512"},"mistralai/voxtral-small-24b-2507":{"id":"mistralai/voxtral-small-24b-2507","name":"Voxtral Small 24B 2507","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"voxtral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":26214},"cost":{"input":0.1,"output":0.3,"cache_read":0.01},"canonical_model_id":"mistral/voxtral-small-24b-2507"},"mistralai/mistral-medium-3-5":{"id":"mistralai/mistral-medium-3-5","name":"Mistral Medium 3.5","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":209715},"cost":{"input":1.5,"output":7.5},"canonical_model_id":"mistral/mistral-medium-3-5"},"mistralai/mistral-small-3.1-24b-instruct":{"id":"mistralai/mistral-small-3.1-24b-instruct","name":"Mistral Small 3.1 24B","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-03-17","last_updated":"2025-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":102400},"cost":{"input":0.351,"output":0.555},"canonical_model_id":"mistral/mistral-small-3.1-24b-instruct"},"mistralai/mistral-small-2603":{"id":"mistralai/mistral-small-2603","name":"Mistral Small 4","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"mistral/mistral-small-2603"},"mistralai/mistral-medium-3":{"id":"mistralai/mistral-medium-3","name":"Mistral Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":104857},"cost":{"input":0.4,"output":2,"cache_read":0.04},"canonical_model_id":"mistral/mistral-medium-3"},"mistralai/mistral-small-3.2-24b-instruct":{"id":"mistralai/mistral-small-3.2-24b-instruct","name":"Mistral Small 3.2 24B","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["image","text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":0.1,"output":0.3,"cache_read":0.01},"canonical_model_id":"mistral/mistral-small-3.2-24b-instruct"},"mistralai/mistral-saba":{"id":"mistralai/mistral-saba","name":"Saba","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-02-17","last_updated":"2025-02-17","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":26214},"cost":{"input":0.2,"output":0.6,"cache_read":0.02},"canonical_model_id":"mistral/mistral-saba"},"mistralai/mistral-large-2407":{"id":"mistralai/mistral-large-2407","name":"Mistral Large 2407","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-03-31","release_date":"2024-07-24","last_updated":"2024-07-24","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":104857},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"mistral/mistral-large-2407"},"mistralai/mistral-large-4-0":{"id":"mistralai/mistral-large-4-0","name":"Mistral: Mistral Large 4","description":"Mistral Large 4 is a frontier multimodal (text and image input) model from Mistral AI built for reasoning, coding, and agentic workloads. It offers a 512K-token context window with up...","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":262144},"cost":{"input":1.36,"output":4.18,"cache_read":0.14},"canonical_model_id":"mistral/mistral-large-4"},"mistralai/codestral-2508":{"id":"mistralai/codestral-2508","name":"Codestral 25.08","description":"Mistral coding model for code completion, generation, and developer workflows","family":"codestral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":204800},"cost":{"input":0.3,"output":0.9,"cache_read":0.03},"canonical_model_id":"mistral/codestral-2508"},"mistralai/mistral-small-24b-instruct-2501":{"id":"mistralai/mistral-small-24b-instruct-2501","name":"Mistral Small 3","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-01-30","last_updated":"2025-01-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"cost":{"input":0.05,"output":0.08},"canonical_model_id":"mistral/mistral-small-24b-instruct-2501"},"mistralai/devstral-2512":{"id":"mistralai/devstral-2512","name":"Devstral 2","description":"Devstral 2 is a state-of-the-art open-source model by Mistral AI specializing in agentic coding. It is a 123B-parameter dense transformer model supporting a 256K context window. Devstral 2 supports exploring...","family":"devstral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.4,"output":2,"cache_read":0.04},"canonical_model_id":"mistral/devstral-2512"},"mistralai/mixtral-8x22b-instruct":{"id":"mistralai/mixtral-8x22b-instruct","name":"Mixtral 8x22B Instruct","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-01-31","release_date":"2024-04-17","last_updated":"2024-04-17","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":52428},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"mistral/mixtral-8x22b-instruct"},"mistralai/mistral-large":{"id":"mistralai/mistral-large","name":"Mistral Large","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11-30","release_date":"2024-02-26","last_updated":"2024-02-26","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":102400},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"mistral/mistral-large"},"mistralai/mistral-medium-3.1":{"id":"mistralai/mistral-medium-3.1","name":"Mistral Medium 3.1","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06-30","release_date":"2025-08-12","last_updated":"2025-08-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":104857},"cost":{"input":0.4,"output":2,"cache_read":0.04},"canonical_model_id":"mistral/mistral-medium-3.1"},"perceptron/perceptron-mk1.5":{"id":"perceptron/perceptron-mk1.5","name":"Perceptron: Perceptron Mk1.5","description":"Perceptron Mk1.5 is Perceptron's embodied reasoning model for physical agents. It accepts text, image, video, and audio input, and answers with text plus optional structured annotations: points, boxes, polygons, tracks,...","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-25","last_updated":"2026-09-25","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":36864,"output":8192},"cost":{"input":0.15,"output":1.5}},"perceptron/perceptron-mk1":{"id":"perceptron/perceptron-mk1","name":"Perceptron: Perceptron Mk1","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-05-12","last_updated":"2026-05-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":8192},"cost":{"input":0.15,"output":1.5},"canonical_model_id":"perceptron/perceptron-mk1"},"amazon/nova-micro-v1":{"id":"amazon/nova-micro-v1","name":"Amazon: Nova Micro 1.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-micro","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":5120},"cost":{"input":0.035,"output":0.14},"canonical_model_id":"amazon/nova-micro-v1"},"amazon/nova-2-lite-v1":{"id":"amazon/nova-2-lite-v1","name":"Amazon: Nova 2 Lite","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-10","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.3,"output":2.5},"canonical_model_id":"amazon/nova-2-lite-v1"},"amazon/nova-pro-v1":{"id":"amazon/nova-pro-v1","name":"Amazon: Nova Pro 1.0","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":5120},"cost":{"input":0.8,"output":3.2},"canonical_model_id":"amazon/nova-pro-v1"},"amazon/nova-lite-v1":{"id":"amazon/nova-lite-v1","name":"Amazon: Nova Lite 1.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":5120},"cost":{"input":0.06,"output":0.24},"canonical_model_id":"amazon/nova-lite-v1"},"amazon/nova-premier-v1":{"id":"amazon/nova-premier-v1","name":"Amazon: Nova Premier 1.0","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10","release_date":"2025-04-30","last_updated":"2025-04-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32000},"status":"deprecated","cost":{"input":2.5,"output":12.5,"cache_read":0.625},"canonical_model_id":"amazon/nova-premier"},"dots-studio/dots-3-note-preview:free":{"id":"dots-studio/dots-3-note-preview:free","name":"Dots Studio: Dots3-Note Preview (free)","description":"Dots3-Note Preview is an open-weight mixture-of-experts model from Dots Studio, with 16B active parameters out of 280B total. It is the lightest model in the Dots 3 family and is...","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":512000,"output":460800},"cost":{"input":0,"output":0}},"qwen/qwen3-vl-8b-instruct":{"id":"qwen/qwen3-vl-8b-instruct","name":"Qwen: Qwen3 VL 8B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-14","last_updated":"2025-10-14","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":235929},"cost":{"input":0.25,"output":0.75,"cache_read":0.12}},"qwen/qwen3-vl-30b-a3b-instruct":{"id":"qwen/qwen3-vl-30b-a3b-instruct","name":"Qwen3 VL 30B A3B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-04","last_updated":"2025-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"alibaba/qwen3-vl-30b-a3b-instruct"},"qwen/qwen3-vl-30b-a3b-thinking":{"id":"qwen/qwen3-vl-30b-a3b-thinking","name":"Qwen: Qwen3 VL 30B A3B Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":235929},"cost":{"input":0.29,"output":1}},"qwen/qwen3-30b-a3b-instruct-2507":{"id":"qwen/qwen3-30b-a3b-instruct-2507","name":"Qwen: Qwen3 30B A3B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.09,"output":0.3},"canonical_model_id":"alibaba/qwen3-30b-a3b-instruct-2507"},"qwen/qwen3.8-flash":{"id":"qwen/qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen3.8 Flash is a multimodal reasoning model from Alibaba. It is suited for coding assistance, agentic workflows, visual understanding, document and codebase analysis, desktop interaction, chart analysis, and long-video analysis.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen/qwen3.6-flash":{"id":"qwen/qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.1875,"output":1.125,"cache_write":0.234375},"canonical_model_id":"alibaba/qwen3.6-flash"},"qwen/qwen-2.5-coder-32b-instruct":{"id":"qwen/qwen-2.5-coder-32b-instruct","name":"Qwen2.5 Coder 32B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2024-11-12","last_updated":"2024-11-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":29491},"cost":{"input":0.66,"output":1},"canonical_model_id":"alibaba/qwen2.5-coder-32b-instruct"},"qwen/qwen-2.5-72b-instruct":{"id":"qwen/qwen-2.5-72b-instruct","name":"Qwen2.5 72B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-09-19","last_updated":"2024-09-19","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":16384},"cost":{"input":0.36,"output":0.4}},"qwen/qwen3.5-35b-a3b":{"id":"qwen/qwen3.5-35b-a3b","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":81920},"cost":{"input":0.1625,"output":1.3},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"qwen/qwen3-coder-30b-a3b-instruct":{"id":"qwen/qwen3-coder-30b-a3b-instruct","name":"Qwen3-Coder 30B-A3B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-31","last_updated":"2025-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.07,"output":0.28},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"qwen/qwen3.5-9b":{"id":"qwen/qwen3.5-9b","name":"Qwen3.5 9B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","cost":{"input":0.08,"output":0.13,"cache_read":0.04},"canonical_model_id":"alibaba/qwen3.5-9b"},"qwen/qwen3-14b":{"id":"qwen/qwen3-14b","name":"Qwen: Qwen3 14B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":40960,"output":16384},"cost":{"input":0.12,"output":0.24}},"qwen/qwen2.5-vl-72b-instruct":{"id":"qwen/qwen2.5-vl-72b-instruct","name":"Qwen: Qwen2.5 VL 72B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-01-26","last_updated":"2025-01-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":115200},"cost":{"input":0.8,"output":1,"cache_read":0.4},"canonical_model_id":"alibaba/qwen2-5-vl-72b-instruct"},"qwen/qwen3.8-2.4t-a95b":{"id":"qwen/qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1010000,"output":909000},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"qwen/qwen3.6-27b":{"id":"qwen/qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.45,"output":2.7},"canonical_model_id":"alibaba/qwen3.6-27b"},"qwen/qwen-2.5-7b-instruct":{"id":"qwen/qwen-2.5-7b-instruct","name":"Qwen: Qwen2.5 7B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-10-16","last_updated":"2024-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":29491},"cost":{"input":0.1,"output":0.2}},"qwen/qwen3-235b-a22b-thinking-2507":{"id":"qwen/qwen3-235b-a22b-thinking-2507","name":"Qwen: Qwen3 235B A22B Thinking 2507","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-07-25","last_updated":"2025-07-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.45,"output":3.5},"canonical_model_id":"alibaba/qwen3-235b-a22b-thinking-2507"},"qwen/qwen3.8-omni-flash":{"id":"qwen/qwen3.8-omni-flash","name":"Qwen3.8 Omni Flash","description":"Qwen3.8 Omni Flash is an omni-modal reasoning model from Alibaba, the first Qwen model built around agentic capabilities with native audio-video understanding. It is suited for audio-video analysis and summarization,...","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-omni-flash"},"qwen/qwen3.5-flash-02-23":{"id":"qwen/qwen3.5-flash-02-23","name":"Qwen: Qwen3.5-Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.5","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-25","last_updated":"2026-02-25","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.065,"output":0.26}},"qwen/qwen3.8-max-0902":{"id":"qwen/qwen3.8-max-0902","name":"Qwen3.8 Max 0902","description":"Qwen3.8 Max 0902 is an updated snapshot of Qwen3.8 Max from Alibaba's Qwen team. It is a 2.4-trillion-parameter mixture-of-experts model that accepts text, image, and video input and returns text,...","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max-0902"},"qwen/qwen3.5-plus-20260420":{"id":"qwen/qwen3.5-plus-20260420","name":"Qwen: Qwen3.5 Plus 2026-04-20","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.5","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.3,"output":1.8,"cache_write":0.375}},"qwen/qwen3-coder-flash":{"id":"qwen/qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.195,"output":0.975,"cache_read":0.039,"cache_write":0.24375},"canonical_model_id":"alibaba/qwen3-coder-flash"},"qwen/qwen3.7-plus":{"id":"qwen/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Qwen3.7-Plus is a cost-effective model in Alibaba's Qwen3.7 series. It supports text and image input with text output, building on the series' text capabilities with a comprehensive upgrade to its...","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.32,"output":1.28,"cache_read":0.064,"cache_write":0.4},"canonical_model_id":"alibaba/qwen3.7-plus"},"qwen/qwen3.8-max-prime":{"id":"qwen/qwen3.8-max-prime","name":"Qwen 3.8 Max Prime","description":"Qwen3.8 Max Prime is a higher-throughput variant of Qwen3.8 Max from Alibaba's Qwen team, served as a separate SKU at a higher price point. It accepts text, image, and video...","family":"qwen3.8-max","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":4,"output":12,"cache_read":0.5},"canonical_model_id":"alibaba/qwen3.8-max-prime"},"qwen/qwen3.5-397b-a17b":{"id":"qwen/qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.39,"output":2.34},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"qwen/qwen3-next-80b-a3b-instruct":{"id":"qwen/qwen3-next-80b-a3b-instruct","name":"Qwen3-Next 80B-A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.09,"output":1.1},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"qwen/qwen3-30b-a3b":{"id":"qwen/qwen3-30b-a3b","name":"Qwen3 30B A3B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":16384},"cost":{"input":0.12,"output":0.5},"canonical_model_id":"alibaba/qwen3-30b-a3b"},"qwen/qwen3-32b":{"id":"qwen/qwen3-32b","name":"Qwen3 32B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":16384},"cost":{"input":0.08,"output":0.28},"canonical_model_id":"alibaba/qwen3-32b"},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":1.475,"output":4.425,"cache_read":0.295,"cache_write":1.84375},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen-plus":{"id":"qwen/qwen-plus","name":"Qwen Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.26,"output":0.78,"cache_read":0.052,"cache_write":0.325},"canonical_model_id":"alibaba/qwen-plus"},"qwen/qwen3.5-122b-a10b":{"id":"qwen/qwen3.5-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.26,"output":2.08},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"qwen/qwen3.7-flash":{"id":"qwen/qwen3.7-flash","name":"Qwen3.7 Flash","description":"Qwen3.7 Flash is a vision-language reasoning model from Alibaba. It is suited for multimodal agents, visual coding, search, and computer interaction, with strengths in object recognition, spatial understanding, and real-world...","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":991808,"output":65536},"cost":{"input":0.03,"output":0.13,"cache_read":0.006,"cache_write":0.038},"canonical_model_id":"alibaba/qwen3.7-flash"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Qwen3.8 27B is an open-weight dense vision-language model from Qwen. It is suited for coding, professional workflows, research, multimodal interaction, and long-running agent tasks, with flexible thinking that can be...","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.425,"output":2.55,"cache_read":0.085,"cache_write":0.53125},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3.6-plus":{"id":"qwen/qwen3.6-plus","name":"Qwen3.6 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.325,"output":1.95,"cache_write":0.40625},"canonical_model_id":"alibaba/qwen3.6-plus"},"qwen/qwen3-vl-235b-a22b-instruct":{"id":"qwen/qwen3-vl-235b-a22b-instruct","name":"Qwen3 VL 235B A22B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.21,"output":1.9,"cache_read":0.1},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"qwen/qwen3.5-27b":{"id":"qwen/qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.195,"output":1.56},"canonical_model_id":"alibaba/qwen3.5-27b"},"qwen/qwen3-235b-a22b-2507":{"id":"qwen/qwen3-235b-a22b-2507","name":"Qwen: Qwen3 235B A22B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.09,"output":0.55},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"qwen/qwen3-coder":{"id":"qwen/qwen3-coder","name":"Qwen: Qwen3 Coder 480B A35B","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.3,"output":1,"cache_read":0.1},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"qwen/qwen3-coder-next":{"id":"qwen/qwen3-coder-next","name":"Qwen3 Coder Next","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.12,"output":0.8,"cache_read":0.07},"canonical_model_id":"alibaba/qwen3-coder-next"},"qwen/qwen3.6-35b-a3b":{"id":"qwen/qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.1,"output":0.95,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"qwen/qwen3.5-plus-02-15":{"id":"qwen/qwen3.5-plus-02-15","name":"Qwen: Qwen3.5 Plus 2026-02-15","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.5","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.26,"output":1.56}},"qwen/qwen3-next-80b-a3b-thinking":{"id":"qwen/qwen3-next-80b-a3b-thinking","name":"Qwen3-Next 80B-A3B (Thinking)","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.15,"output":1.2},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-thinking"},"sakana/fugu-max":{"id":"sakana/fugu-max","name":"Fugu Max","description":"Fugu Max is the cost-performance model in Sakana AI's Fugu family. Rather than a single monolithic model, Fugu is a learned multi-agent orchestration system: a language model trained to route...","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"sakana/fugu-max"},"sakana/fugu-ultra":{"id":"sakana/fugu-ultra","name":"Fugu Ultra","description":"Fugu Ultra is the higher-performance model in Sakana AI's Fugu family. Rather than a single monolithic model, Fugu is a learned multi-agent orchestration system: a language model trained to route...","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"sakana/fugu-ultra"},"sakana/fugu-ultra-v2":{"id":"sakana/fugu-ultra-v2","name":"Fugu Ultra v2","description":"Fugu Ultra v2 is the higher-performance model in Sakana AI's Fugu family. Rather than a single monolithic model, Fugu is a learned multi-agent orchestration system: a language model trained to...","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-08-28","release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"sakana/fugu-ultra-v2"},"sakana/sakana-namazu":{"id":"sakana/sakana-namazu","name":"Sakana Namazu","description":"Sakana Namazu is a Japanese-specialized reasoning model from Sakana AI, based on Kimi K2.6 with additional training for Japanese language and business contexts. It is suited for Japanese instruction following,...","family":"sakana-namazu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.95,"output":4,"cache_read":0.15},"canonical_model_id":"sakana/sakana-namazu"},"rekaai/reka-edge":{"id":"rekaai/reka-edge","name":"Reka Edge","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"reka","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":14745},"cost":{"input":0.1,"output":0.1},"canonical_model_id":"rekaai/reka-edge"},"rekaai/reka-flash-3":{"id":"rekaai/reka-flash-3","name":"Reka Flash 3","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"reka","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01-31","release_date":"2025-03-10","last_updated":"2025-03-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":58982},"cost":{"input":0.1,"output":0.2},"canonical_model_id":"rekaai/reka-flash-3"},"minimax/minimax-m2.1":{"id":"minimax/minimax-m2.1","name":"MiniMax-M2.1","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.1"},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":198000,"output":32768},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5"},"minimax/minimax-01":{"id":"minimax/minimax-01","name":"MiniMax: MiniMax-01","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-01-15","last_updated":"2025-01-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000192,"output":900172},"cost":{"input":0.2,"output":1.1}},"minimax/minimax-m2":{"id":"minimax/minimax-m2","name":"MiniMax-M2","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2"},"minimax/minimax-m2.7":{"id":"minimax/minimax-m2.7","name":"MiniMax-M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/minimax-m2-her":{"id":"minimax/minimax-m2-her","name":"MiniMax-M2 Her","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-01-23","last_updated":"2026-01-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"output":2048},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2-Her"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":512000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"minimax/minimax-m1":{"id":"minimax/minimax-m1","name":"MiniMax: MiniMax M1","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":40000},"cost":{"input":0.4,"output":2.2}},"minimax/minimax-m3.1-flash:free":{"id":"minimax/minimax-m3.1-flash:free","name":"MiniMax: MiniMax M3.1 Flash (free)","description":"MiniMax-M3.1-Flash is a multimodal model from MiniMax. Compared with M3, it delivers significant improvements across multiple benchmarks, particularly in complex agentic tasks, coding, and cybersecurity. It is built for complex,...","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-19","last_updated":"2026-10-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":524288},"cost":{"input":0,"output":0},"canonical_model_id":"minimax/MiniMax-M3.1-Flash"},"cognitivecomputations/dolphin-mistral-24b-venice-edition":{"id":"cognitivecomputations/dolphin-mistral-24b-venice-edition","name":"Venice: Uncensored","description":"Venice Uncensored Dolphin Mistral 24B Venice Edition is a fine-tuned variant of Mistral-Small-24B-Instruct-2501, developed by dphn.ai in collaboration with Venice.ai. This model is designed as an “uncensored” instruct-tuned LLM, preserving...","family":"mistral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-04-30","release_date":"2025-07-09","last_updated":"2025-07-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.2,"output":0.9},"canonical_model_id":"cognitivecomputations/dolphin-mistral-24b-venice-edition"},"liquid/lfm-2.5-2.6b:free":{"id":"liquid/lfm-2.5-2.6b:free","name":"LiquidAI: LFM2.5-2.6B (free)","description":"LFM2.5-2.6B is a compact reasoning model from Liquid AI. It is suited for agent workflows, data extraction, RAG, and long-context processing. Liquid advises against using it for agentic coding or...","family":"liquid","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"output":8192},"cost":{"input":0,"output":0}},"liquid/lfm-2.5-24b-a2b":{"id":"liquid/lfm-2.5-24b-a2b","name":"LiquidAI: LFM2.5-24B-A2B","description":"LFM2.5-24B-A2B is a mixture-of-experts reasoning model from Liquid AI with 24B total and 2.45B active parameters. It always reasons before answering and is built for agents that call tools. Liquid...","family":"liquid","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.05,"output":0.7,"cache_read":0.025}},"moondream/moondream3-preview":{"id":"moondream/moondream3-preview","name":"Moondream: Moondream 3 Preview","description":"Moondream 3 Preview is a vision-language model from Moondream with 9B total parameters and 2B active (mixture-of-experts). It handles visual question answering, captioning, OCR, and visual reasoning over images, with...","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":4096},"cost":{"input":0.3,"output":2.5}},"moondream/moondream3.1-9b-a2b":{"id":"moondream/moondream3.1-9b-a2b","name":"Moondream: Moondream 3.1","description":"Moondream 3.1 is a vision-language model from Moondream, the successor to Moondream 3 Preview, with 9B total parameters and 2B active (mixture-of-experts). It handles visual question answering, captioning, OCR, and...","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":4096},"cost":{"input":0.3,"output":2.5}},"moonshotai/kimi-k2-0905":{"id":"moonshotai/kimi-k2-0905","name":"Kimi K2 Instruct 0905","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":0.6,"output":2.5},"canonical_model_id":"moonshotai/kimi-k2-0905"},"moonshotai/kimi-k2-thinking":{"id":"moonshotai/kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Kimi reasoning model for long-horizon research, planning, and tool use","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":0.6,"output":2.5,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Kimi K3 is a 2.8T parameter open-weight multimodal reasoning model from Moonshot AI. It is suited for complex coding, knowledge work, and long-horizon agentic workflows, and is particularly strong at...","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.5":{"id":"moonshotai/kimi-k2.5","name":"Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.6,"output":3},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.65,"output":3.41,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2":{"id":"moonshotai/kimi-k2","name":"Kimi K2 0711","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-12-31","release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.57,"output":2.3},"canonical_model_id":"moonshotai/kimi-k2"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"MoonshotAI: Kimi K2.7 Code is a coding-focused model in Moonshot AI's Kimi K2 family, built to complete end-to-end programming tasks reliably over long contexts. It uses a native multimodal mixture-of-experts...","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.6712,"output":3.35,"cache_read":0.18},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048575,"output":943717},"cost":{"input":0.091,"output":0.182,"cache_read":0.0182},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash is a sparse mixture-of-experts model from DeepSeek, and the cost-efficient tier of the V4.1 family. DeepSeek reports that it exceeds V4 Pro on performance, speed, and task...","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":384000},"cost":{"input":1.6,"output":3.2,"cache_read":0.135},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v3.1-terminus":{"id":"deepseek/deepseek-v3.1-terminus","name":"DeepSeek: DeepSeek V3.1 Terminus","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-22","last_updated":"2025-09-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":163840,"output":147456},"cost":{"input":0.27,"output":1}},"deepseek/deepseek-v3.2-exp":{"id":"deepseek/deepseek-v3.2-exp","name":"DeepSeek: DeepSeek V3.2 Exp","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":163840,"output":147456},"cost":{"input":0.27,"output":0.41}},"deepseek/deepseek-chat-v3.1":{"id":"deepseek/deepseek-chat-v3.1","name":"DeepSeek V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":32768},"cost":{"input":0.25,"output":0.95,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-chat-v3.1"},"deepseek/deepseek-chat":{"id":"deepseek/deepseek-chat","name":"DeepSeek Chat","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-12-01","last_updated":"2026-02-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16000},"cost":{"input":0.2574,"output":1.0287},"canonical_model_id":"deepseek/deepseek-chat"},"deepseek/deepseek-v4-flash-vision-exp":{"id":"deepseek/deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"DeepSeek V4 Flash Vision Exp is an experimental vision-enabled version of [DeepSeek V4 Flash 0731](https://openrouter.ai/deepseek/deepseek-v4-flash-0731) from DeepSeek, adding image understanding while matching the base model on text capabilities including agents,...","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":0.2156,"output":0.6468,"cache_read":0.00686},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"deepseek/deepseek-r1-0528":{"id":"deepseek/deepseek-r1-0528","name":"DeepSeek R1 0528","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":32768},"cost":{"input":0.5,"output":2.15,"cache_read":0.35},"canonical_model_id":"deepseek/deepseek-r1-0528"},"deepseek/deepseek-v4.1-flash-1017":{"id":"deepseek/deepseek-v4.1-flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"DeepSeek V4.1 Flash 1017 is the October 17, 2026 snapshot of DeepSeek V4.1 Flash, served by DeepSeek under the `deepseek-flash` API model name. V4.1 Flash is a sparse mixture-of-experts model...","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek/deepseek-chat-v3-0324":{"id":"deepseek/deepseek-chat-v3-0324","name":"DeepSeek V3 0324","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07-31","release_date":"2025-03-24","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":115200},"cost":{"input":0.29,"output":1.14,"cache_read":0.11},"canonical_model_id":"deepseek/deepseek-chat-v3-0324"},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"DeepSeek V4 Flash 0731 is a sparse mixture-of-experts model from DeepSeek, with 13B active parameters out of 284B total. This re-post-trained revision is suited for coding, reasoning, and agent workflows.","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.44,"output":1.32,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v3.2":{"id":"deepseek/deepseek-v3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.28,"output":0.42,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro 0813 is a large-scale mixture-of-experts model from DeepSeek. This is the GA release of DeepSeek V4 Pro.","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"aion-labs/aion-3.0":{"id":"aion-labs/aion-3.0","name":"AionLabs: Aion-3.0","description":"Aion-3.0 is a multi-model roleplaying and storytelling system from AionLabs, built on the GLM family of models. It uses a collaborative generation process in which multiple specialized models each contribute...","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-05-05","last_updated":"2026-05-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":3,"output":6,"cache_read":0.75},"canonical_model_id":"aion-labs/aion-3.0"},"aion-labs/aion-2.0":{"id":"aion-labs/aion-2.0","name":"AionLabs: Aion-2.0","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-21","last_updated":"2025-12-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.8,"output":1.6,"cache_read":0.2},"canonical_model_id":"aion-labs/aion-2.0"},"aion-labs/aion-rp-llama-3.1-8b":{"id":"aion-labs/aion-rp-llama-3.1-8b","name":"AionLabs: Aion-RP 1.0 (8B)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12-31","release_date":"2025-02-04","last_updated":"2025-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":29491},"cost":{"input":0.8,"output":1.6},"canonical_model_id":"aion-labs/aion-rp-llama-3.1-8b"},"aion-labs/aion-3.5-mini":{"id":"aion-labs/aion-3.5-mini","name":"AionLabs: Aion 3.5 Mini","description":"Aion 3.5 Mini is a multi-model roleplaying and storytelling system from AionLabs, built on the GLM family of models. It is the smaller, lower-cost sibling of Aion 3.5 and uses...","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.7,"output":1.4,"cache_read":0.18}},"aion-labs/aion-3.0-mini":{"id":"aion-labs/aion-3.0-mini","name":"AionLabs: Aion-3.0-Mini","description":"Aion-3.0 Mini is a multi-model roleplaying and storytelling system from AionLabs, built on the DeepSeek family of models. It uses a collaborative generation process in which multiple specialized models each...","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-05-14","last_updated":"2026-05-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.7,"output":1.4,"cache_read":0.18},"canonical_model_id":"aion-labs/aion-3.0-mini"},"aion-labs/aion-3.5":{"id":"aion-labs/aion-3.5","name":"AionLabs: Aion 3.5","description":"Aion 3.5 is a multi-model roleplaying and storytelling system from AionLabs, built on the GLM family of models. It uses a collaborative generation process in which multiple specialized models each...","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":3,"output":6,"cache_read":0.75}},"nvidia/nemotron-3-ultra-550b-a55b:free":{"id":"nvidia/nemotron-3-ultra-550b-a55b:free","name":"NVIDIA: Nemotron 3 Ultra (free)","description":"NVIDIA Nemotron 3 Ultra is an open frontier-reasoning and orchestration model from NVIDIA, with 55B active parameters out of 550B total (MoE). Built on a hybrid Transformer-Mamba mixture-of-experts architecture, it... **Terms of service** For NVIDIA free endpoints (Super/Ultra/etc): Trial use only - do not submit personal or confidential data. Your use is logged for security purposes and to improve NVIDIA products and services. The logged session data for improvement purposes is not linked to your identity or any persistent identifier. For more information about our data processing practices, see our [Privacy Policy](https://www.nvidia.com/en-us/about-nvidia/privacy-policy/). By interacting with this endpoint, you consent to our collection, recording, and use of such information and the [NVIDIA API Trial Terms of Service](https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf).","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/nemotron-3.5-content-safety:free":{"id":"nvidia/nemotron-3.5-content-safety:free","name":"NVIDIA: Nemotron 3.5 Content Safety (free)","description":"NVIDIA Nemotron 3.5 Content Safety is a compact 4B-parameter multimodal guardrail model from NVIDIA, fine-tuned from Google Gemma-3-4B. It moderates both inputs to and responses from LLMs and VLMs, accepting... **Terms of service** For NVIDIA free endpoints (Super/Ultra/etc): Trial use only - do not submit personal or confidential data. Your use is logged for security purposes and to improve NVIDIA products and services. The logged session data for improvement purposes is not linked to your identity or any persistent identifier. For more information about our data processing practices, see our [Privacy Policy](https://www.nvidia.com/en-us/about-nvidia/privacy-policy/). By interacting with this endpoint, you consent to our collection, recording, and use of such information and the [NVIDIA API Trial Terms of Service](https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf).","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-content-safety"},"nvidia/nemotron-3.5-content-safety":{"id":"nvidia/nemotron-3.5-content-safety","name":"Nemotron 3.5 Content Safety","description":"NVIDIA Nemotron 3.5 Content Safety is a compact 4B-parameter multimodal guardrail model from NVIDIA, fine-tuned from Google Gemma-3-4B. It moderates both inputs to and responses from LLMs and VLMs, accepting...","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.2,"output":0.2},"canonical_model_id":"nvidia/nemotron-3.5-content-safety"},"nvidia/nemotron-3.5-super-vl":{"id":"nvidia/nemotron-3.5-super-vl","name":"NVIDIA: Nemotron 3.5 Super VL","description":"NVIDIA Nemotron 3.5 Super VL is an open multimodal mixture-of-experts model from NVIDIA, with 12B active parameters out of 120B total. It takes text, images, documents, GUI screenshots, and video...","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.1,"output":0.4,"cache_read":0.08},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"nvidia/nemotron-3-super-120b-a12b":{"id":"nvidia/nemotron-3-super-120b-a12b","name":"Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.08,"output":0.45},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"nvidia/nemotron-3-ultra-550b-a55b":{"id":"nvidia/nemotron-3-ultra-550b-a55b","name":"Nemotron 3 Ultra 550B A55B","description":"NVIDIA Nemotron 3 Ultra is an open frontier-reasoning and orchestration model from NVIDIA, with 55B active parameters out of 550B total (MoE). Built on a hybrid Transformer-Mamba mixture-of-experts architecture, it...","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202800,"output":182520},"cost":{"input":0.4,"output":1.76,"cache_read":0.08},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/nemotron-3-super-120b-a12b:free":{"id":"nvidia/nemotron-3-super-120b-a12b:free","name":"NVIDIA: Nemotron 3 Super (free)","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"nvidia/nemotron-3.5-super-vl:free":{"id":"nvidia/nemotron-3.5-super-vl:free","name":"NVIDIA: Nemotron 3.5 Super VL (free)","description":"NVIDIA Nemotron 3.5 Super VL is an open multimodal mixture-of-experts model from NVIDIA, with 12B active parameters out of 120B total. It takes text, images, documents, GUI screenshots, and video... **Terms of service** For NVIDIA free endpoints (Super/Ultra/etc): Trial use only - do not submit personal or confidential data. Your use is logged for security purposes and to improve NVIDIA products and services. The logged session data for improvement purposes is not linked to your identity or any persistent identifier. For more information about our data processing practices, see our [Privacy Policy](https://www.nvidia.com/en-us/about-nvidia/privacy-policy/). By interacting with this endpoint, you consent to our collection, recording, and use of such information and the [NVIDIA API Trial Terms of Service](https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf).","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"nvidia/nemotron-3.5-lightning":{"id":"nvidia/nemotron-3.5-lightning","name":"Nemotron 3.5 Lightning 30B A3B","description":"NVIDIA Nemotron 3.5 Lightning is an open mixture-of-experts model from NVIDIA, with 3B active parameters out of 30B total. It is suited for high-throughput agentic workloads and specialized tasks that...","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.025,"output":0.12,"cache_read":0.0125},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/nemotron-3.5-lightning:free":{"id":"nvidia/nemotron-3.5-lightning:free","name":"NVIDIA: Nemotron 3.5 Lightning (free)","description":"NVIDIA Nemotron 3.5 Lightning is an open mixture-of-experts model from NVIDIA, with 3B active parameters out of 30B total. It is suited for high-throughput agentic workloads and specialized tasks that... **Terms of service** For NVIDIA free endpoints (Super/Ultra/etc): Trial use only - do not submit personal or confidential data. Your use is logged for security purposes and to improve NVIDIA products and services. The logged session data for improvement purposes is not linked to your identity or any persistent identifier. For more information about our data processing practices, see our [Privacy Policy](https://www.nvidia.com/en-us/about-nvidia/privacy-policy/). By interacting with this endpoint, you consent to our collection, recording, and use of such information and the [NVIDIA API Trial Terms of Service](https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf).","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-09","release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning:free":{"id":"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning:free","name":"NVIDIA: Nemotron 3 Nano Omni (free)","description":"Open Nemotron omni model combining reasoning with text, vision, and audio","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning"},"nvidia/nemotron-3-nano-30b-a3b":{"id":"nvidia/nemotron-3-nano-30b-a3b","name":"Nemotron 3 Nano 30B A3B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06-25","release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.05,"output":0.2},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"arcee-ai/trinity-large-thinking":{"id":"arcee-ai/trinity-large-thinking","name":"Trinity Large Thinking","description":"Reasoning-optimized 398B MoE agent model with extended thinking for long-horizon and multi-turn tool use","family":"trinity","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":80000},"cost":{"input":0.25,"output":0.8,"cache_read":0.06},"canonical_model_id":"arcee-ai/trinity-large-thinking"},"microsoft/phi-4":{"id":"microsoft/phi-4","name":"Microsoft: Phi 4","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","family":"phi","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-01-10","last_updated":"2025-01-10","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":14745},"cost":{"input":0.056,"output":0.112}},"unbiased/pareto-26.10":{"id":"unbiased/pareto-26.10","name":"Pareto 26.10","description":"Pareto is a multimodal composite model built for research, coding, and agentic workflows, while delivering frontier-level performance across a broad range of general-purpose tasks.","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.8,"output":3.2,"cache_read":0.03}},"unbiased/pareto-26.9":{"id":"unbiased/pareto-26.9","name":"Pareto 26.9","description":"Pareto is a multimodal composite model built for research, coding, and agentic workflows, while delivering frontier-level performance across a broad range of general-purpose tasks.","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":2.5,"output":7.5,"cache_read":0.25}},"cohere/command-r7b-12-2024":{"id":"cohere/command-r7b-12-2024","name":"Command R7B","description":"Cohere command model for multilingual enterprise agents, tools, and chat","family":"command-r","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-12-13","last_updated":"2024-12-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.0375,"output":0.15},"canonical_model_id":"cohere/command-r7b-12-2024"},"cohere/command-r-08-2024":{"id":"cohere/command-r-08-2024","name":"Command R","description":"Cohere retrieval model for long-context chat and enterprise RAG workflows","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"cohere/command-r-08-2024"},"cohere/command-a":{"id":"cohere/command-a","name":"Command A","description":"Cohere command model for multilingual enterprise agents, tools, and chat","family":"command-a","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-03-13","last_updated":"2025-03-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-a"},"cohere/command-a-plus":{"id":"cohere/command-a-plus","name":"Cohere: Command A+","description":"Command A+ is Cohere's flagship model for enterprise agentic workflows. It accepts text and image inputs with a 192K context window, supports native tool calling with strict tool schemas, structured...","family":"command-a","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04-01","release_date":"2026-05-20","last_updated":"2026-06-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":192000,"output":64000},"cost":{"input":0.3,"output":1.5,"cache_read":0.15},"canonical_model_id":"cohere/command-a-plus-05-2026"},"cohere/command-r-plus-08-2024":{"id":"cohere/command-r-plus-08-2024","name":"Command R+","description":"Cohere retrieval model for long-context chat and enterprise RAG workflows","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-r-plus-08-2024"},"cohere/north-mini-code:free":{"id":"cohere/north-mini-code:free","name":"Cohere: North Mini Code (free)","description":"North Mini Code is Cohere's first agentic coding model and the debut of its North family. A sparse mixture-of-experts model with 30B total parameters and 3B active, it is optimized...","family":"north","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-09-23","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0,"output":0},"canonical_model_id":"cohere/north-mini-code-1-0"},"inference-net/schematron-v2-turbo":{"id":"inference-net/schematron-v2-turbo","name":"Inference.net: Schematron V2 Turbo","description":"Schematron V2 Turbo is a 3B-parameter HTML-to-JSON extraction model from Inference.net. It prioritizes throughput for high-volume extraction workloads. Extraction instructions must be supplied through a JSON schema in response_format rather...","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.03,"output":0.15,"cache_read":0.03},"canonical_model_id":"inference-net/schematron-v2-turbo"},"inference-net/schematron-v2-small":{"id":"inference-net/schematron-v2-small","name":"Inference.net: Schematron V2 Small","description":"Schematron V2 Small is a 3B-parameter HTML-to-JSON extraction model from Inference.net. It prioritizes extraction quality for complex schemas and long pages. Extraction instructions must be supplied through a JSON schema...","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":0.05,"output":0.23,"cache_read":0.05},"canonical_model_id":"inference-net/schematron-v2-small"},"~moonshotai/kimi-latest":{"id":"~moonshotai/kimi-latest","name":"MoonshotAI: Kimi Latest","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.238,"output":24,"cache_read":0.228}},"meta-llama/llama-3.2-1b-instruct":{"id":"meta-llama/llama-3.2-1b-instruct","name":"Llama 3.2 1B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":60000,"output":54000},"cost":{"input":0.027,"output":0.201},"canonical_model_id":"meta/llama-3.2-1b-instruct"},"meta-llama/llama-3.2-3b-instruct":{"id":"meta-llama/llama-3.2-3b-instruct","name":"Meta: Llama 3.2 3B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":80000,"output":72000},"cost":{"input":0.05,"output":0.33},"canonical_model_id":"meta/llama-3.2-3b-instruct"},"meta-llama/llama-3.3-70b-instruct":{"id":"meta-llama/llama-3.3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.1,"output":0.32},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"meta-llama/llama-4-scout":{"id":"meta-llama/llama-4-scout","name":"Meta: Llama 4 Scout","description":"Open multimodal Llama model for long-context analysis and efficient agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":327680,"output":16384},"cost":{"input":0.08,"output":0.24},"canonical_model_id":"meta/llama-4-scout-17b-instruct"},"meta-llama/llama-guard-4-12b":{"id":"meta-llama/llama-guard-4-12b","name":"Meta: Llama Guard 4 12B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-04-29","last_updated":"2025-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":16384},"cost":{"input":0.144,"output":0.144},"canonical_model_id":"meta/llama-guard-4-12b"},"meta-llama/llama-4-maverick":{"id":"meta-llama/llama-4-maverick","name":"Meta: Llama 4 Maverick","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.1875,"output":0.6525,"cache_read":0.05},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"meta-llama/llama-3.1-8b-instruct":{"id":"meta-llama/llama-3.1-8b-instruct","name":"Llama-3.1-8B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.02,"output":0.04},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"meta-llama/llama-3.1-70b-instruct":{"id":"meta-llama/llama-3.1-70b-instruct","name":"Llama-3.1-70B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.4,"output":0.4},"canonical_model_id":"meta/llama-3.1-70b-instruct"},"scaledown/summarize":{"id":"scaledown/summarize","name":"ScaleDown: Summarize","description":"Summarize is an abstractive summarization model from ScaleDown. It condenses long text and documents into a fluent, faithful rewrite rather than lifting sentences from the source, and is suited for...","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":4000},"cost":{"input":0.05,"output":0}},"scaledown/extract":{"id":"scaledown/extract","name":"ScaleDown: Extract","description":"Extract is a description-driven entity extraction model from ScaleDown. Instead of a fixed set of entity types, callers describe the fields they want in plain English through `provider.options.scaledown.entities`, and the...","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":900000},"cost":{"input":0.05,"output":0}},"tencent/hy-mt2-1.8b":{"id":"tencent/hy-mt2-1.8b","name":"Hy-MT2-1.8B","description":"Hy-MT2-1.8B is a compact 1.8B-parameter translation model from Tencent. It supports 33 language pairs and five Chinese dialect and minority-language pairs, with workflows for structured, delimiter-based, contextual, glossary-based, and style-guided...","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":4096},"cost":{"input":0.044,"output":0.177},"canonical_model_id":"tencent/hy-mt2-1.8b"},"tencent/hy-mt2-30b-a3b":{"id":"tencent/hy-mt2-30b-a3b","name":"Hy-MT2-30B-A3B","description":"Hy-MT2-30B-A3B is Tencent's flagship translation model in the Hy-MT2 family. It supports 33 language pairs and five Chinese dialect and minority-language pairs, with workflows for structured, delimiter-based, contextual, glossary-based, and...","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":4096},"cost":{"input":0.074,"output":0.295},"canonical_model_id":"tencent/hy-mt2-30b-a3b"},"tencent/hy4-preview":{"id":"tencent/hy4-preview","name":"Hy4 preview","description":"Tencent: Hy4 preview is a mixture-of-experts model from Tencent, with 49B active parameters out of 770B total. It is designed for coding agents, complex tool-use workflows, and productivity tasks that...","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":64000},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"},"tencent/hy-mt2-7b":{"id":"tencent/hy-mt2-7b","name":"Hy-MT2-7B","description":"Hy-MT2-7B is a 7B-parameter translation model from Tencent. It supports 33 language pairs and five Chinese dialect and minority-language pairs, with workflows for structured, delimiter-based, contextual, glossary-based, and style-guided translation.","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":4096},"cost":{"input":0.074,"output":0.295},"canonical_model_id":"tencent/hy-mt2-7b"},"tencent/hy3":{"id":"tencent/hy3","name":"Hy3","description":"Hy3 is a 295B-parameter Mixture-of-Experts model from Tencent (21B active, 192 experts with top-8 routing) built for reasoning, agentic workflows, and real-world production use. It supports a configurable reasoning effort:...","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":192000,"output":128000},"cost":{"input":0.132,"output":0.528,"cache_read":0.033},"canonical_model_id":"tencent/hy3"},"tencent/hunyuan-a13b-instruct":{"id":"tencent/hunyuan-a13b-instruct","name":"Tencent: Hunyuan A13B Instruct","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"hunyuan","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-07-08","last_updated":"2025-07-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":117964},"cost":{"input":0.14,"output":0.57}},"tencent/hy3-preview":{"id":"tencent/hy3-preview","name":"Hy3 preview","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.18,"output":0.6,"cache_read":0.06},"canonical_model_id":"tencent/hy3-preview"},"meta/muse-spark-1.3":{"id":"meta/muse-spark-1.3","name":"Muse Spark 1.3","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It is designed to keep track of information across extended tasks, work through...","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.3"},"meta/muse-spark-open":{"id":"meta/muse-spark-open","name":"Muse Spark Open","description":"Muse Spark Open is a coding-optimized open-weight model. Trained specifically for agentic coding workflows, it delivers higher first-attempt accuracy, reliable tool calling, and deep codebase understanding across the repos developers...","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-open"},"meta/muse-wonder":{"id":"meta/muse-wonder","name":"Meta: Muse Wonder","description":"Muse Wonder is a frontier reasoning model from Meta, designed for complex personal and professional agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with...","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":4,"output":20,"cache_read":0.2}},"meta/muse-spark-1.2":{"id":"meta/muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a reasoning model from Meta, designed for complex agentic tasks. It accepts text, images, video, audio, and PDF documents, returns text, and offers a 1M-token context...","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"meta/muse-spark-1.2-contributor":{"id":"meta/muse-spark-1.2-contributor","name":"Meta: Muse Spark 1.2 Contributor","description":"Muse Spark 1.2 contributor tier is a reasoning model from Meta designed for developers who want to start building at an even lower cost. It’s meaningfully cheaper than Muse Spark...","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-08-21","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"meta/muse-spark-1.1":{"id":"meta/muse-spark-1.1","name":"Muse Spark 1.1","description":"Muse Spark 1.1 is a multimodal reasoning model from Meta, built for agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with a 1M-token context...","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.1"},"meta/muse-glimmer-30b":{"id":"meta/muse-glimmer-30b","name":"Muse Glimmer 30B","description":"Muse Glimmer 30B is a dense, open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark and optimized for autonomous agents on consumer hardware. It is suited for long-horizon...","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.3,"output":1.2,"cache_read":0.04},"canonical_model_id":"meta/muse-glimmer-30b"},"meta/muse-spark-1.3-contributor":{"id":"meta/muse-spark-1.3-contributor","name":"Meta: Muse Spark 1.3 Contributor","description":"Muse Spark 1.3 Contributor is the cost-efficient contributor tier of Meta’s multimodal reasoning model for experimentation, learning, and early-stage agentic, multi-agent, and coding workflows. It is designed to track information...","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"stepfun/step-3.5-flash":{"id":"stepfun/step-3.5-flash","name":"Step 3.5 Flash","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","family":"step","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"stepfun/step-3.5-flash"},"stepfun/step-5-preview":{"id":"stepfun/step-5-preview","name":"Step 5 Preview","description":"Step 5 Preview is StepFun's flagship model for agentic work, built on a sparse Mixture-of-Experts architecture (27B active / 600B total parameters). It performs strongly in software engineering and professional...","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":64000},"cost":{"input":1,"output":2.7,"cache_read":0.1},"canonical_model_id":"stepfun/step-5-preview"},"stepfun/step-3.7-flash":{"id":"stepfun/step-3.7-flash","name":"Step 3.7 Flash","description":"Step 3.7 Flash is StepFun's latest high-efficiency multimodal Mixture-of-Experts model. It pairs a 196B-parameter language backbone with a vision encoder for native image and video understanding, activating roughly 11B parameters...","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":230400},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"nousresearch/hermes-4-405b":{"id":"nousresearch/hermes-4-405b","name":"Nous: Hermes 4 405B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"hermes","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":1,"output":3},"canonical_model_id":"nousresearch/hermes-4-405b"},"nousresearch/hermes-3-llama-3.1-70b":{"id":"nousresearch/hermes-3-llama-3.1-70b","name":"Nous: Hermes 3 70B Instruct (retires Nov 2)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"nousresearch","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-18","last_updated":"2024-08-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"status":"deprecated","cost":{"input":0.7,"output":0.7},"canonical_model_id":"nousresearch/hermes-3-llama-3.1-70b"},"nousresearch/hermes-3-llama-3.1-405b":{"id":"nousresearch/hermes-3-llama-3.1-405b","name":"Nous: Hermes 3 405B Instruct (retires Nov 2)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"nousresearch","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-16","last_updated":"2024-08-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"status":"deprecated","cost":{"input":1,"output":1},"canonical_model_id":"nousresearch/hermes-3-llama-3.1-405b"},"fireworks/ember-1":{"id":"fireworks/ember-1","name":"Fireworks: Ember-1","description":"Ember-1 is a specialized reasoning model from Fireworks Research, built on [Kimi K3](https://openrouter.ai/moonshotai/kimi-k3). It is designed to make every token go further: it produces shorter reasoning traces, using roughly 40%...","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"fireworks/ember-1"},"~google/gemini-pro-latest":{"id":"~google/gemini-pro-latest","name":"Google: Gemini Pro Latest","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["audio","pdf","image","text","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":2,"output":10,"reasoning":10,"cache_read":0.1,"cache_write":0.1875}},"~google/gemini-flash-latest":{"id":"~google/gemini-flash-latest","name":"Google: Gemini Flash Latest","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"reasoning":3.75,"cache_read":0.075,"cache_write":0.041667}},"~x-ai/grok-latest":{"id":"~x-ai/grok-latest","name":"xAI: Grok Latest","description":"This model always redirects to the latest Grok model from xAI.","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.5}},"z-ai/glm-5-turbo":{"id":"z-ai/glm-5-turbo","name":"GLM-5-Turbo","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5-turbo"},"z-ai/glm-4.5v":{"id":"z-ai/glm-4.5v","name":"GLM-4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":16384},"cost":{"input":0.6,"output":1.8,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5v"},"z-ai/glm-4.7":{"id":"z-ai/glm-4.7","name":"GLM-4.7","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.54,"output":1.98,"cache_read":0.099},"canonical_model_id":"zhipuai/glm-4.7"},"z-ai/glm-4.6v":{"id":"z-ai/glm-4.6v","name":"GLM-4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.3,"output":0.9,"cache_read":0.055},"canonical_model_id":"zhipuai/glm-4.6v"},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM-5.2","description":"GLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level software engineering,...","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/glm-5v-turbo":{"id":"z-ai/glm-5v-turbo","name":"GLM-5V-Turbo","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5v-turbo"},"z-ai/glm-5":{"id":"z-ai/glm-5","name":"GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM-5.3","description":"GLM-5.3 is a large-scale reasoning model from Z.ai, built for complex software engineering and long-horizon agent tasks. It supports text input and output with a 1M-token context window, and improves...","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"GLM-5.3-Flash is a native multimodal model from Z.ai. It is suited for efficient coding and long-horizon agent tasks. Its hybrid sparse and linear attention architecture maintains accurate long-context behavior while...","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-4.7-flash":{"id":"z-ai/glm-4.7-flash","name":"GLM-4.7-Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.0605,"output":0.4},"canonical_model_id":"zhipuai/glm-4.7-flash"},"z-ai/glm-4.5-air":{"id":"z-ai/glm-4.5-air","name":"GLM-4.5-Air","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.13,"output":0.85,"cache_read":0.025},"canonical_model_id":"zhipuai/glm-4.5-air"},"z-ai/glm-5.1":{"id":"z-ai/glm-5.1","name":"GLM-5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"z-ai/glm-4.6":{"id":"z-ai/glm-4.6","name":"GLM-4.6","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.55,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.6"},"z-ai/glm-4.5":{"id":"z-ai/glm-4.5","name":"GLM-4.5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5"},"z-ai/glm-5.3-prime":{"id":"z-ai/glm-5.3-prime","name":"Z.ai: GLM 5.3 Prime","description":"GLM-5.3-Prime is the high-speed variant of Z.ai's GLM-5.3, inheriting its full capabilities while delivering 1.5–2× the output throughput through inference acceleration. It supports text input and output with a 1M-token...","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2.8,"output":8.8,"cache_read":0.56}},"z-ai/glm-5.3-flashx":{"id":"z-ai/glm-5.3-flashx","name":"Z.ai: GLM 5.3 FlashX","description":"GLM-5.3-FlashX is the high-speed variant of Z.ai's GLM-5.3-Flash, a native multimodal model delivering inference speeds of up to 200 tokens/s. Built on the same hybrid sparse and linear attention architecture...","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-18","last_updated":"2026-09-18","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.37,"output":1.25,"cache_read":0.09}},"gryphe/mythomax-l2-13b":{"id":"gryphe/mythomax-l2-13b","name":"MythoMax 13B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2023-08-10","last_updated":"2023-08-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":3686},"cost":{"input":0.08,"output":0.11},"canonical_model_id":"gryphe/mythomax-l2-13b"},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"status":"deprecated","cost":{"input":0.05,"output":0.2,"reasoning":0.2,"cache_read":0.005,"cache_write":0.041667},"canonical_model_id":"google/gemini-2.5-flash-lite"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"Gemini 3.7 Flash is a multimodal model from Google for fast agentic workflows, coding, and complex multi-step reasoning. It is designed for tasks that require responsive performance and reliable multi-step...","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"reasoning":3.75,"cache_read":0.075,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.7-flash"},"google/lyria-3-pro-preview":{"id":"google/lyria-3-pro-preview","name":"Lyria 3 Pro Preview","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"lyria","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-03-25","last_updated":"2026-03-25","modalities":{"input":["text","image"],"output":["text","audio"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"google/lyria-3-pro-preview"},"google/gemini-3-pro-image":{"id":"google/gemini-3-pro-image","type":"image","name":"Nano Banana Pro","description":"Nano Banana Pro is Google’s most advanced image-generation and editing model, built on Gemini 3 Pro. It extends the original Nano Banana with significantly improved multimodal reasoning, real-world grounding, and...","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["image","text","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":2,"output":12,"reasoning":12,"cache_read":0.2,"cache_write":0.375},"canonical_model_id":"google/gemini-3-pro-image"},"google/gemini-3.1-flash-lite-preview":{"id":"google/gemini-3.1-flash-lite-preview","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.125,"output":0.75,"reasoning":0.75,"cache_read":0.0125,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.1-flash-lite-preview"},"google/gemini-3.1-flash-image":{"id":"google/gemini-3.1-flash-image","type":"image","name":"Nano Banana 2","description":"Gemini 3.1 Flash Image, a.k.a. \"Nano Banana 2,\" is Google’s latest state of the art image generation and editing model, delivering Pro-level visual quality at Flash speed. It combines advanced...","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["image","text","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3.1-flash-image"},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"reasoning":1.5,"cache_read":0.025,"cache_write":0.041667},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"status":"deprecated","cost":{"input":0.15,"output":1.25,"reasoning":1.25,"cache_read":0.015,"cache_write":0.041667},"canonical_model_id":"google/gemini-2.5-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":0.625,"output":5,"reasoning":5,"cache_read":0.0625,"cache_write":0.1875},"canonical_model_id":"google/gemini-2.5-pro"},"google/gemini-2.5-flash-image":{"id":"google/gemini-2.5-flash-image","type":"image","name":"Nano Banana","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["image","text","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":32768,"output":8192},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":0.083333},"canonical_model_id":"google/gemini-2.5-flash-image"},"google/gemma-3-4b-it":{"id":"google/gemma-3-4b-it","name":"Gemma 3 4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.04,"output":0.05,"cache_read":0.02},"canonical_model_id":"google/gemma-3-4b-it"},"google/gemini-4-argon":{"id":"google/gemini-4-argon","name":"Gemini 4 Argon","description":"Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across...","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":2,"output":10,"reasoning":10,"cache_read":0.1,"cache_write":0.1875},"canonical_model_id":"google/gemini-4-argon"},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.1,"output":0.34,"cache_read":0.1},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Gemini 3.5 Flash Lite is a high-efficiency model from Google with upgraded agentic capabilities. It is suited for subagents that execute focused tasks within complex, multi-agent workflows.","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.15,"output":1.25,"reasoning":1.25,"cache_read":0.015,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemma-2-27b-it":{"id":"google/gemma-2-27b-it","name":"Gemma 2 27B","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2024-07-13","last_updated":"2024-07-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":2048},"cost":{"input":0.65,"output":0.65},"canonical_model_id":"google/gemma-2-27b-it"},"google/lyria-3-clip-preview":{"id":"google/lyria-3-clip-preview","name":"Lyria 3 Clip Preview","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"lyria","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-03-25","last_updated":"2026-03-25","modalities":{"input":["text","image"],"output":["text","audio"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"google/lyria-3-clip-preview"},"google/gemini-3-pro-image-preview":{"id":"google/gemini-3-pro-image-preview","type":"image","name":"Nano Banana Pro Preview","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-20","last_updated":"2025-11-20","modalities":{"input":["image","text","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":1,"output":6,"reasoning":6,"cache_read":0.1,"cache_write":0.1875},"canonical_model_id":"google/gemini-3-pro-image-preview"},"google/gemma-4-26b-a4b-it":{"id":"google/gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.042,"output":0.22,"cache_read":0.021},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemini-3.1-flash-lite-image":{"id":"google/gemini-3.1-flash-lite-image","type":"image","name":"Nano Banana 2 Lite","description":"Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) is Google's fastest, most cost-efficient Gemini image model, built for high-velocity developer pipelines and rapid-fire visual exploration. It delivers text-to-image generation...","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["image","text","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":58982},"cost":{"input":0.25,"output":1.5},"canonical_model_id":"google/gemini-3.1-flash-lite-image"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1,"output":6,"reasoning":6,"cache_read":0.1,"cache_write":0.1875},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":4.5,"reasoning":4.5,"cache_read":0.075,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-2.5-pro-preview":{"id":"google/gemini-2.5-pro-preview","name":"Gemini 2.5 Pro Preview 06-05","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01-31","release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["pdf","image","text","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.625,"output":5,"reasoning":5,"cache_read":0.0625,"cache_write":0.1875},"canonical_model_id":"google/gemini-2.5-pro-preview"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Gemini 3.8 Flash is Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows.","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"reasoning":3.75,"cache_read":0.075,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.125,"output":0.75,"reasoning":0.75,"cache_read":0.0125,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.1-flash-lite"},"google/gemma-3-27b-it":{"id":"google/gemma-3-27b-it","name":"Gemma 3 27B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.08,"output":0.16},"canonical_model_id":"google/gemma-3-27b-it"},"google/gemini-3.1-flash-image-preview":{"id":"google/gemini-3.1-flash-image-preview","type":"image","name":"Nano Banana 2 Preview","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-26","last_updated":"2026-02-26","modalities":{"input":["text","image","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":58982},"cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3.1-flash-image-preview"},"google/gemma-3-12b-it":{"id":"google/gemma-3-12b-it","name":"Gemma 3 12B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.04,"output":0.12},"canonical_model_id":"google/gemma-3-12b-it"},"google/gemini-nano-banana-2.1":{"id":"google/gemini-nano-banana-2.1","type":"image","name":"Nano Banana 2.1","description":"Nano Banana 2.1 (Gemini Nano Banana 2.1) is Google's image generation and editing model on the Flash tier, succeeding Nano Banana 2 and Nano Banana Pro. It improves product recontextualization,...","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["image","text","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":58982},"cost":{"input":1.5,"output":7.5},"canonical_model_id":"google/gemini-nano-banana-2.1"},"google/gemini-3.1-pro-preview-customtools":{"id":"google/gemini-3.1-pro-preview-customtools","name":"Gemini 3.1 Pro Preview Custom Tools","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"reasoning":12,"cache_read":0.2,"cache_write":0.375},"canonical_model_id":"google/gemini-3.1-pro-preview-customtools"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Gemini 3.6 Flash is a high-efficiency model from Google for coding, agentic workflows, and web and app development. It is designed to produce polished outputs with fewer unnecessary edits and...","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.375,"output":1.875,"reasoning":1.875,"cache_read":0.0375,"cache_write":0.020833},"canonical_model_id":"google/gemini-3.6-flash"},"nex-agi/nex-n2.5-pro":{"id":"nex-agi/nex-n2.5-pro","name":"Nex AGI: Nex-N2.5-Pro","description":"Nex-N2.5 is an agentic model built to turn goals into working, verified outcomes. Its core strength is agentic coding within a visual feedback loop: it can explore codebases, implement multi-file...","family":"agi","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":235929},"cost":{"input":0.075,"output":0.25,"cache_read":0.015}},"nex-agi/nex-n2.5-mini":{"id":"nex-agi/nex-n2.5-mini","name":"Nex AGI: Nex-N2.5-Mini","description":"Nex-N2.5 is an agentic model built to turn goals into working, verified outcomes. Its core strength is agentic coding within a visual feedback loop: it can explore codebases, implement multi-file...","family":"agi","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":235929},"cost":{"input":0.025,"output":0.1,"cache_read":0.0025}}}},"ofox":{"id":"ofox","env":["OFOX_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.ofox.ai/v1","name":"Ofox","doc":"https://ofox.ai/docs","models":{"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-haiku-5.5":{"id":"anthropic/claude-haiku-5.5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-4.6":{"id":"anthropic/claude-opus-4.6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-opus-5.5":{"id":"anthropic/claude-opus-5.5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-haiku-4.5":{"id":"anthropic/claude-haiku-4.5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-sonnet-5.5":{"id":"anthropic/claude-sonnet-5.5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-sonnet-4.5":{"id":"anthropic/claude-sonnet-4.5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-fable-5.1":{"id":"anthropic/claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-opus-4.5":{"id":"anthropic/claude-opus-4.5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://api.ofox.ai/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"x-ai/grok-4.3":{"id":"x-ai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2},"canonical_model_id":"xai/grok-4.3"},"x-ai/grok-4.7":{"id":"x-ai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":65536},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.7"},"x-ai/grok-4.20":{"id":"x-ai/grok-4.20","name":"Grok 4.20 (Reasoning)","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":128000},"cost":{"input":4,"output":12,"cache_read":0.4},"canonical_model_id":"xai/grok-4.20-0309-reasoning"},"x-ai/grok-4.6":{"id":"x-ai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":65536},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"x-ai/grok-4.1-fast":{"id":"x-ai/grok-4.1-fast","name":"Grok 4.1 Fast","description":"xAI's fast agentic tool-calling model with a 2M context window; non-reasoning variant for low-latency responses","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"xai/grok-4.1-fast"},"x-ai/grok-4.5":{"id":"x-ai/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":65536},"cost":{"input":2,"output":6,"cache_read":0.3},"canonical_model_id":"xai/grok-4.5"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":1.75,"output":14,"cache_read":0.18},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.4-pro"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":1.25,"output":10,"cache_read":0.13},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.1-codex-max":{"id":"openai/gpt-5.1-codex-max","name":"GPT-5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":1.25,"output":10,"cache_read":0.13},"canonical_model_id":"openai/gpt-5.1-codex-max"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":2.5,"output":15,"cache_read":0.25,"cache_write":3.125,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"cache_write":6.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5,"cache_write":6.25}},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-5.2-codex":{"id":"openai/gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Code-specialist GPT for repository edits, reviews, and long-running software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":1.75,"output":14,"cache_read":0.18},"canonical_model_id":"openai/gpt-5.2-codex"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32768},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":0.25,"output":2,"cache_read":0.03},"canonical_model_id":"openai/gpt-5-mini"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":1.25,"output":10,"cache_read":0.13},"canonical_model_id":"openai/gpt-5"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":0.05,"output":0.4,"cache_read":0.01},"canonical_model_id":"openai/gpt-5-nano"},"openai/gpt-5.1-codex-mini":{"id":"openai/gpt-5.1-codex-mini","name":"GPT-5.1 Codex mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":65536},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":0.25,"output":2,"cache_read":0.03},"canonical_model_id":"openai/gpt-5.1-codex-mini"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":1.75,"output":14,"cache_read":0.18},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://api.ofox.ai/v1"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"volcengine/doubao-seed-1-8":{"id":"volcengine/doubao-seed-1-8","name":"Seed 1.8","description":"ByteDance Seed model for multimodal reasoning, long-context analysis, and agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-28","last_updated":"2025-12-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"status":"deprecated","cost":{"input":0.12,"output":0.29,"cache_read":0.023},"canonical_model_id":"bytedance-seed/seed-1-8"},"volcengine/doubao-seed-evolving":{"id":"volcengine/doubao-seed-evolving","name":"Seed Evolving","description":"Rolling ByteDance Seed model for rapidly updated reasoning, coding, and agent capabilities","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.884,"output":4.42,"cache_read":0.177,"cache_write":0.0025},"canonical_model_id":"bytedance-seed/seed-evolving"},"volcengine/doubao-seed-1-6-vision":{"id":"volcengine/doubao-seed-1-6-vision","name":"Seed 1.6 Vision","description":"ByteDance Seed multimodal model for image understanding, visual reasoning, and tool-assisted tasks","family":"seed","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-15","last_updated":"2025-08-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"status":"deprecated","cost":{"input":0.12,"output":1.15,"cache_read":0.023},"canonical_model_id":"bytedance-seed/seed-1-6-vision"},"volcengine/doubao-seed-1-6":{"id":"volcengine/doubao-seed-1-6","name":"Seed 1.6","description":"ByteDance Seed model for long-context reasoning, instruction following, and tool-assisted tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"status":"deprecated","cost":{"input":0.12,"output":0.29,"cache_read":0.023},"canonical_model_id":"bytedance-seed/seed-1-6"},"volcengine/doubao-seed-character":{"id":"volcengine/doubao-seed-character","name":"Seed Character","description":"ByteDance Seed model optimized for character-driven dialogue and consistent conversational behavior","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.177,"output":0.884,"cache_read":0.024,"cache_write":0.0025},"canonical_model_id":"bytedance-seed/seed-character"},"volcengine/doubao-seed-2.0-code":{"id":"volcengine/doubao-seed-2.0-code","name":"Seed 2.0 Code","description":"ByteDance Seed coding model for multimodal software engineering and long-running agents","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.67,"output":3.36,"cache_read":0.14,"cache_write":0.0024},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"volcengine/doubao-seed-2.1-turbo":{"id":"volcengine/doubao-seed-2.1-turbo","name":"Seed 2.1 Turbo","description":"Faster ByteDance Seed 2.1 model for multimodal reasoning and latency-sensitive agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.3536,"output":1.7696,"cache_read":0.068,"cache_write":0.0019},"canonical_model_id":"bytedance-seed/seed-2.1-turbo"},"volcengine/doubao-seed-1-6-flash":{"id":"volcengine/doubao-seed-1-6-flash","name":"Seed 1.6 Flash","description":"Low-latency ByteDance Seed model for high-throughput chat, extraction, and lightweight tool use","family":"seed","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-28","last_updated":"2025-08-28","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"status":"deprecated","cost":{"input":0.03,"output":0.22,"cache_read":0.0043},"canonical_model_id":"bytedance-seed/seed-1-6-flash"},"volcengine/doubao-seed-2.1-pro":{"id":"volcengine/doubao-seed-2.1-pro","name":"Seed 2.1 Pro","description":"Flagship ByteDance Seed 2.1 model for complex multimodal reasoning, coding, and agents","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.7072,"output":3.536,"cache_read":0.1416,"cache_write":0.002},"canonical_model_id":"bytedance-seed/seed-2.1-pro"},"volcengine/doubao-seed-2.0-mini":{"id":"volcengine/doubao-seed-2.0-mini","name":"Seed 2.0 Mini","description":"Lightweight ByteDance Seed 2.0 model for low-latency multimodal reasoning and high-volume tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.06,"output":0.56,"cache_read":0.02,"cache_write":0.0024},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"volcengine/doubao-seed-2.0-lite":{"id":"volcengine/doubao-seed-2.0-lite","name":"Seed 2.0 Lite","description":"Cost-efficient ByteDance Seed 2.0 model for production chat, analysis, and structured generation","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.13,"output":0.76,"cache_read":0.03,"cache_write":0.0024},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"volcengine/doubao-seed-2.0-pro":{"id":"volcengine/doubao-seed-2.0-pro","name":"Seed 2.0 Pro","description":"Flagship ByteDance Seed 2.0 model for complex multimodal reasoning and long-horizon agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.67,"output":3.36,"cache_read":0.14,"cache_write":0.0024},"canonical_model_id":"bytedance-seed/seed-2.0-pro"},"qwen/qwen3-max":{"id":"qwen/qwen3-max","name":"Qwen3 Max","description":"Flagship Qwen3 model for coding agents, complex reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":0.36,"output":1.43,"cache_read":0.072},"canonical_model_id":"alibaba/qwen3-max"},"qwen/qwen3.8-flash":{"id":"qwen/qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.11,"output":0.39,"cache_read":0.011,"cache_write":0.14},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen/qwen3.6-flash":{"id":"qwen/qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"cache_write":0.31},"canonical_model_id":"alibaba/qwen3.6-flash"},"qwen/qwen3.5-35b-a3b":{"id":"qwen/qwen3.5-35b-a3b","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.29,"output":1.83,"cache_read":0.29},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"qwen/qwen-max":{"id":"qwen/qwen-max","name":"Qwen Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-03","last_updated":"2025-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":8000},"cost":{"input":0.35,"output":1.38,"cache_read":0.069},"canonical_model_id":"alibaba/qwen-max"},"qwen/qwen3-coder-plus":{"id":"qwen/qwen3-coder-plus","name":"Qwen3 Coder Plus","description":"Hosted Qwen coder for software agents, repo edits, and long-context code","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":1.8,"output":9,"cache_read":0.2,"cache_write":1},"canonical_model_id":"alibaba/qwen3-coder-plus"},"qwen/qwen3.8-max":{"id":"qwen/qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":1.71,"output":5.14,"cache_read":0.17,"cache_write":2.14},"canonical_model_id":"alibaba/qwen3.8-max"},"qwen/qwen3.6-27b":{"id":"qwen/qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.43,"output":2.57},"canonical_model_id":"alibaba/qwen3.6-27b"},"qwen/qwen-vl-max":{"id":"qwen/qwen-vl-max","name":"Qwen-VL Max","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-08","last_updated":"2025-08-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8000},"cost":{"input":0.23,"output":0.58,"cache_read":0.023},"canonical_model_id":"alibaba/qwen-vl-max"},"qwen/qwen-flash":{"id":"qwen/qwen-flash","name":"Qwen Flash","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32000},"cost":{"input":0.022,"output":0.22,"cache_read":0.0043,"cache_write":0.027},"canonical_model_id":"alibaba/qwen-flash"},"qwen/qwen3.8-max-0902":{"id":"qwen/qwen3.8-max-0902","name":"Qwen3.8 Max 0902","description":"2026-09-02 upgraded snapshot of Qwen3.8 Max with stronger coding, collaborative agents, and multimodal document understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":1.71,"output":5.14,"cache_read":0.17,"cache_write":2.14},"canonical_model_id":"alibaba/qwen3.8-max-0902"},"qwen/qwen3-coder-flash":{"id":"qwen/qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.5,"output":2.5,"cache_read":0.06,"cache_write":0.27},"canonical_model_id":"alibaba/qwen3-coder-flash"},"qwen/qwen3.7-plus":{"id":"qwen/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1064000,"output":64000},"cost":{"input":0.4,"output":1.6,"cache_read":0.08,"cache_write":0.5},"canonical_model_id":"alibaba/qwen3.7-plus"},"qwen/qwen3.5-397b-a17b":{"id":"qwen/qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.55,"output":3.5,"cache_read":0.55},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"qwen/qwen3.5-flash":{"id":"qwen/qwen3.5-flash","name":"Qwen3.5 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"alibaba/qwen3.5-flash"},"qwen/qwen-turbo":{"id":"qwen/qwen-turbo","name":"Qwen Turbo","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-11-01","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16000},"cost":{"input":0.043,"output":0.09,"cache_read":0.0086},"canonical_model_id":"alibaba/qwen-turbo"},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1064000,"output":64000},"cost":{"input":1.71,"output":5.14,"cache_read":0.17,"cache_write":2.14},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen-plus":{"id":"qwen/qwen-plus","name":"Qwen Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32000},"cost":{"input":0.12,"output":0.29,"cache_read":0.023},"canonical_model_id":"alibaba/qwen-plus"},"qwen/qwen3.5-122b-a10b":{"id":"qwen/qwen3.5-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.29,"output":2.29,"cache_read":0.29},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1131072,"output":131072},"cost":{"input":0.5,"output":1.71,"cache_read":0.043,"cache_write":0.63},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3.6-plus":{"id":"qwen/qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625},"canonical_model_id":"alibaba/qwen3.6-plus"},"qwen/qwen3.5-27b":{"id":"qwen/qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.29,"output":2.05,"cache_read":0.29},"canonical_model_id":"alibaba/qwen3.5-27b"},"qwen/qwen3.6-max-preview":{"id":"qwen/qwen3.6-max-preview","name":"Qwen3.6 Max Preview","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":2.15,"output":12.86,"cache_read":0.2,"cache_write":1.17},"canonical_model_id":"alibaba/qwen3.6-max-preview"},"qwen/qwen3-coder-next":{"id":"qwen/qwen3-coder-next","name":"Qwen3 Coder Next","description":"Open-weight Qwen coding model for agents, repository edits, and multi-turn tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.2,"output":1.5},"canonical_model_id":"alibaba/qwen3-coder-next"},"qwen/qwen3.5-plus":{"id":"qwen/qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.4,"output":2.4,"cache_read":0.04,"cache_write":0.4},"canonical_model_id":"alibaba/qwen3.5-plus"},"minimax/minimax-m2.1":{"id":"minimax/minimax-m2.1","name":"MiniMax-M2.1","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.1"},"minimax/minimax-m2.5-lightning":{"id":"minimax/minimax-m2.5-lightning","name":"MiniMax-M2.5 Lightning","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-13","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":2.4,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5-highspeed"},"minimax/minimax-m2.7-highspeed":{"id":"minimax/minimax-m2.7-highspeed","name":"MiniMax-M2.7-highspeed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"minimax/minimax-m2.1-lightning":{"id":"minimax/minimax-m2.1-lightning","name":"MiniMax-M2.1 Lightning","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":2.4,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.1"},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5"},"minimax/m2-her":{"id":"minimax/m2-her","name":"MiniMax-M2 Her","description":"MiniMax M2 variant tuned for conversational and character-driven agent interactions","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-01-23","last_updated":"2026-01-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"output":2048},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2-Her"},"minimax/minimax-m2":{"id":"minimax/minimax-m2","name":"MiniMax-M2","description":"Efficient open MiniMax model built for coding agents and tool-heavy workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2"},"minimax/minimax-m2.7":{"id":"minimax/minimax-m2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.6,"output":2.4,"cache_read":0.12},"canonical_model_id":"minimax/MiniMax-M3"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.5":{"id":"moonshotai/kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.6,"output":3,"cache_read":0.1},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2.7-code-highspeed":{"id":"moonshotai/kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code Highspeed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"deepseek/deepseek-v4-flash-0423":{"id":"deepseek/deepseek-v4-flash-0423","name":"DeepSeek V4 Flash 0423","description":"Initial DeepSeek V4 Flash snapshot for economical reasoning, coding, and million-token agent workloads","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.19,"output":0.51,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0423"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.44,"output":1.32,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v4-pro-0423":{"id":"deepseek/deepseek-v4-pro-0423","name":"DeepSeek V4 Pro 0423","description":"DeepSeek V4 Pro initial snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.32,"output":3.96,"cache_read":0.15},"canonical_model_id":"deepseek/deepseek-v4-pro-0423"},"deepseek/deepseek-v4-flash-vision-exp":{"id":"deepseek/deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"status":"deprecated","cost":{"input":0.44,"output":1.32,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"deepseek/deepseek-v4.1-flash-1017":{"id":"deepseek/deepseek-v4.1-flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.44,"output":1.32,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v3.2":{"id":"deepseek/deepseek-v3.2","name":"DeepSeek V3.2","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"cost":{"input":0.29,"output":0.43,"cache_read":0.06},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"z-ai/glm-5-turbo":{"id":"z-ai/glm-5-turbo","name":"GLM-5-Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5-turbo"},"z-ai/glm-4.7":{"id":"z-ai/glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.4,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.7"},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/glm-5v-turbo":{"id":"z-ai/glm-5v-turbo","name":"GLM-5V-Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5v-turbo"},"z-ai/glm-5":{"id":"z-ai/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-5.1":{"id":"z-ai/glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"z-ai/glm-4.6":{"id":"z-ai/glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.6"},"z-ai/glm-5.3-flashx":{"id":"z-ai/glm-5.3-flashx","name":"GLM-5.3-FlashX","description":"High-speed GLM-5.3-Flash serving option for coding and agent workflows","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-4.7-flashx":{"id":"z-ai/glm-4.7-flashx","name":"GLM-4.7-FlashX","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.072,"output":0.4,"cache_read":0.01},"canonical_model_id":"zhipuai/glm-4.7-flashx"},"bailian/qwen3-max":{"id":"bailian/qwen3-max","name":"Qwen3 Max","description":"Flagship Qwen3 model for coding agents, complex reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.36,"output":1.43,"cache_read":0.072},"canonical_model_id":"alibaba/qwen3-max"},"bailian/qwen3.8-flash":{"id":"bailian/qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"bailian/qwen3.6-flash":{"id":"bailian/qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"cache_write":0.31},"canonical_model_id":"alibaba/qwen3.6-flash"},"bailian/qwen3.5-35b-a3b":{"id":"bailian/qwen3.5-35b-a3b","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.29,"output":1.83,"cache_read":0.29},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"bailian/qwen-max":{"id":"bailian/qwen-max","name":"Qwen Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-03","last_updated":"2025-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":8192},"cost":{"input":0.35,"output":1.38,"cache_read":0.069},"canonical_model_id":"alibaba/qwen-max"},"bailian/qwen3-coder-plus":{"id":"bailian/qwen3-coder-plus","name":"Qwen3 Coder Plus","description":"Hosted Qwen coder for software agents, repo edits, and long-context code","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.8,"output":9,"cache_read":0.2,"cache_write":1},"canonical_model_id":"alibaba/qwen3-coder-plus"},"bailian/qwen3.8-max":{"id":"bailian/qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"bailian/qwen3.6-27b":{"id":"bailian/qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.6,"output":3.6},"canonical_model_id":"alibaba/qwen3.6-27b"},"bailian/qwen-vl-max":{"id":"bailian/qwen-vl-max","name":"Qwen-VL Max","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-08","last_updated":"2025-08-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.23,"output":0.58,"cache_read":0.046},"canonical_model_id":"alibaba/qwen-vl-max"},"bailian/qwen-flash":{"id":"bailian/qwen-flash","name":"Qwen Flash","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.022,"output":0.22,"cache_read":0.0043,"cache_write":0.027},"canonical_model_id":"alibaba/qwen-flash"},"bailian/qwen3.8-max-0902":{"id":"bailian/qwen3.8-max-0902","name":"Qwen3.8 Max 0902","description":"2026-09-02 upgraded snapshot of Qwen3.8 Max with stronger coding, collaborative agents, and multimodal document understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":0,"max":262144}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max-0902"},"bailian/qwen3-coder-flash":{"id":"bailian/qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.5,"output":2.5,"cache_read":0.06,"cache_write":0.27},"canonical_model_id":"alibaba/qwen3-coder-flash"},"bailian/qwen3.7-plus":{"id":"bailian/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.4,"output":1.6,"cache_read":0.08,"cache_write":0.5},"canonical_model_id":"alibaba/qwen3.7-plus"},"bailian/qwen3.5-397b-a17b":{"id":"bailian/qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.55,"output":3.5,"cache_read":0.55},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"bailian/qwen3.5-flash":{"id":"bailian/qwen3.5-flash","name":"Qwen3.5 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"alibaba/qwen3.5-flash"},"bailian/qwen-turbo":{"id":"bailian/qwen-turbo","name":"Qwen Turbo","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-11-01","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.05,"output":0.09,"cache_read":0.0086},"canonical_model_id":"alibaba/qwen-turbo"},"bailian/qwen3.7-max":{"id":"bailian/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2.5,"output":7.5,"cache_read":0.5,"cache_write":3.125},"canonical_model_id":"alibaba/qwen3.7-max"},"bailian/qwen-plus":{"id":"bailian/qwen-plus","name":"Qwen Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.12,"output":0.29,"cache_read":0.023},"canonical_model_id":"alibaba/qwen-plus"},"bailian/qwen3.5-122b-a10b":{"id":"bailian/qwen3.5-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.29,"output":2.29,"cache_read":0.29},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"bailian/qwen3.8-27b":{"id":"bailian/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1131072,"output":131072},"cost":{"input":0.45,"output":3.2,"cache_read":0.05,"cache_write":0.5625},"canonical_model_id":"alibaba/qwen3.8-27b"},"bailian/qwen3.6-plus":{"id":"bailian/qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625},"canonical_model_id":"alibaba/qwen3.6-plus"},"bailian/qwen3.5-27b":{"id":"bailian/qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.29,"output":2.05,"cache_read":0.29},"canonical_model_id":"alibaba/qwen3.5-27b"},"bailian/qwen3.6-max-preview":{"id":"bailian/qwen3.6-max-preview","name":"Qwen3.6 Max Preview","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":2.15,"output":12.86,"cache_read":0.2,"cache_write":1.17},"canonical_model_id":"alibaba/qwen3.6-max-preview"},"bailian/qwen3-coder-next":{"id":"bailian/qwen3-coder-next","name":"Qwen3 Coder Next","description":"Open-weight Qwen coding model for agents, repository edits, and multi-turn tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.2,"output":1.5},"canonical_model_id":"alibaba/qwen3-coder-next"},"bailian/qwen3.5-plus":{"id":"bailian/qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.4,"output":2.4,"cache_read":0.04,"cache_write":0.4},"canonical_model_id":"alibaba/qwen3.5-plus"},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":512,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"cache_write":1,"input_audio":0.3},"canonical_model_id":"google/gemini-2.5-flash-lite"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://api.ofox.ai/gemini/v1beta"},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.0415,"input_audio":0.75},"canonical_model_id":"google/gemini-3.7-flash"},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":1,"input_audio":1},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":1,"input_audio":1},"canonical_model_id":"google/gemini-2.5-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125,"cache_write":4.5,"input_audio":1.25},"canonical_model_id":"google/gemini-2.5-pro"},"google/gemini-4-argon":{"id":"google/gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://api.ofox.ai/gemini/v1beta"},"cost":{"input":2,"output":10,"cache_read":0.1,"input_audio":2},"canonical_model_id":"google/gemini-4-argon"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://api.ofox.ai/gemini/v1beta"},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":0.083,"input_audio":0.3},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://api.ofox.ai/gemini/v1beta"},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":4.5,"input_audio":2},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://api.ofox.ai/gemini/v1beta"},"cost":{"input":1.5,"output":9,"cache_read":0.15,"cache_write":0.083,"input_audio":1.5},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://api.ofox.ai/gemini/v1beta"},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.0415,"input_audio":0.75},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"cache_write":1,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://api.ofox.ai/gemini/v1beta"},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.0415,"input_audio":0.75},"canonical_model_id":"google/gemini-3.6-flash"}}},"poe":{"id":"poe","env":["POE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.poe.com/v1","name":"Poe","doc":"https://creator.poe.com/docs/external-applications/openai-compatible-api","models":{"ideogramai/ideogram-v2":{"id":"ideogramai/ideogram-v2","type":"image","name":"Ideogram-v2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"ideogram","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-08-21","last_updated":"2024-08-21","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":150,"output":0}},"ideogramai/ideogram-v2a-turbo":{"id":"ideogramai/ideogram-v2a-turbo","type":"image","name":"Ideogram-v2a-Turbo","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"ideogram","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-02-27","last_updated":"2025-02-27","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":150,"output":0}},"ideogramai/ideogram-v2a":{"id":"ideogramai/ideogram-v2a","type":"image","name":"Ideogram-v2a","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"ideogram","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-02-27","last_updated":"2025-02-27","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":150,"output":0}},"ideogramai/ideogram":{"id":"ideogramai/ideogram","type":"image","name":"Ideogram","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"ideogram","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-04-03","last_updated":"2024-04-03","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":150,"output":0}},"fireworks-ai/kimi-k2.5-fw":{"id":"fireworks-ai/kimi-k2.5-fw","name":"Kimi-K2.5-FW","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":245760,"output":16384},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"moonshotai/kimi-k2.5"},"xai/grok-code-fast-1":{"id":"xai/grok-code-fast-1","name":"Grok Code Fast 1","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-09-02","last_updated":"2025-09-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.2,"output":1.5,"cache_read":0.02},"canonical_model_id":"xai/grok-code-fast-1"},"xai/grok-4-fast-non-reasoning":{"id":"xai/grok-4-fast-non-reasoning","name":"Grok-4-Fast-Non-Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-12-18","last_updated":"2025-12-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":128000},"status":"deprecated","cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"xai/grok-4-fast-non-reasoning"},"xai/grok-4.1-fast-reasoning":{"id":"xai/grok-4.1-fast-reasoning","name":"Grok-4.1-Fast-Reasoning","description":"xAI's fast agentic tool-calling model with a 2M context window and built-in reasoning","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"status":"deprecated","canonical_model_id":"xai/grok-4.1-fast-reasoning"},"xai/grok-4-fast-reasoning":{"id":"xai/grok-4-fast-reasoning","name":"Grok-4-Fast-Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-12-18","last_updated":"2025-12-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":128000},"status":"deprecated","cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"xai/grok-4-fast-reasoning"},"xai/grok-4":{"id":"xai/grok-4","name":"Grok-4","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-07-10","last_updated":"2025-07-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.75}},"xai/grok-4.20-multi-agent":{"id":"xai/grok-4.20-multi-agent","name":"Grok-4.20-Multi-Agent","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high"]}],"tool_call":true,"temperature":false,"release_date":"2026-03-13","last_updated":"2026-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":0},"cost":{"input":1.2626,"output":2.5253,"cache_read":0.202}},"xai/grok-4.1-fast-non-reasoning":{"id":"xai/grok-4.1-fast-non-reasoning","name":"Grok-4.1-Fast-Non-Reasoning","description":"xAI's fast agentic tool-calling model with a 2M context window; non-reasoning variant for low-latency responses","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"status":"deprecated","canonical_model_id":"xai/grok-4.1-fast"},"xai/grok-3":{"id":"xai/grok-3","name":"Grok 3","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-04-11","last_updated":"2025-04-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":3,"output":15,"cache_read":0.75}},"xai/grok-3-mini":{"id":"xai/grok-3-mini","name":"Grok 3 Mini","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"release_date":"2025-04-11","last_updated":"2025-04-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.3,"output":0.5,"cache_read":0.075}},"trytako/tako":{"id":"trytako/tako","name":"Tako","description":"Tool-capable chat model for instruction following and agentic application workflows","family":"tako","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-08-15","last_updated":"2024-08-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":2048,"output":0}},"elevenlabs/elevenlabs-music":{"id":"elevenlabs/elevenlabs-music","name":"ElevenLabs-Music","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"elevenlabs","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-08-29","last_updated":"2025-08-29","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":2000,"output":0}},"elevenlabs/elevenlabs-v3":{"id":"elevenlabs/elevenlabs-v3","type":"speech","name":"ElevenLabs-v3","description":"Expressive text-to-speech model with inline audio tags across 70+ languages","family":"elevenlabs","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-08-20","last_updated":"2025-08-20","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":128000,"output":0},"canonical_model_id":"elevenlabs/eleven_v3"},"elevenlabs/elevenlabs-v2.5-turbo":{"id":"elevenlabs/elevenlabs-v2.5-turbo","type":"speech","name":"ElevenLabs-v2.5-Turbo","description":"Low-latency multilingual text-to-speech model, superseded by Flash v2.5","family":"elevenlabs","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-07-19","last_updated":"2024-07-19","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":128000,"output":0},"canonical_model_id":"elevenlabs/eleven_turbo_v2_5"},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude-Opus-4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":128000},"cost":{"input":4.2929,"output":21.4646,"cache_read":0.4293,"cache_write":5.3662},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-sonnet-3.5-june":{"id":"anthropic/claude-sonnet-3.5-june","name":"Claude-Sonnet-3.5-June","description":"Legacy model retained for compatibility with older integrations","family":"claude-sonnet","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-11-18","last_updated":"2024-11-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":189096,"output":8192},"status":"deprecated","cost":{"input":2.6,"output":13,"cache_read":0.26,"cache_write":3.2}},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude-Sonnet-4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":983040,"output":128000},"cost":{"input":2.5758,"output":12.8788,"cache_read":0.2576,"cache_write":3.2197},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-4.6":{"id":"anthropic/claude-opus-4.6","name":"Claude-Opus-4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"temperature":false,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":983040,"output":128000},"cost":{"input":4.2929,"output":21.4646,"cache_read":0.4293,"cache_write":5.3662},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-opus-4":{"id":"anthropic/claude-opus-4","name":"Claude-Opus-4","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":192512,"output":28672},"status":"deprecated","cost":{"input":13,"output":64,"cache_read":1.3,"cache_write":16},"canonical_model_id":"anthropic/claude-opus-4-0"},"anthropic/claude-sonnet-3.7":{"id":"anthropic/claude-sonnet-3.7","name":"Claude-Sonnet-3.7","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2024-10-31","release_date":"2025-02-19","last_updated":"2025-02-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":196608,"output":128000},"status":"deprecated","cost":{"input":2.6,"output":13,"cache_read":0.26,"cache_write":3.2},"canonical_model_id":"anthropic/claude-3-7-sonnet-20250219"},"anthropic/claude-haiku-4.5":{"id":"anthropic/claude-haiku-4.5","name":"Claude-Haiku-4.5","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":0,"max":63999}],"tool_call":true,"temperature":false,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":192000,"output":64000},"cost":{"input":0.8586,"output":4.2929,"cache_read":0.0859,"cache_write":1.0732},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-opus-4.1":{"id":"anthropic/claude-opus-4.1","name":"Claude-Opus-4.1","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":0,"max":31999}],"tool_call":true,"temperature":false,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":196608,"output":32000},"status":"deprecated","cost":{"input":13,"output":64,"cache_read":1.3,"cache_write":16},"canonical_model_id":"anthropic/claude-opus-4-1"},"anthropic/claude-haiku-3.5":{"id":"anthropic/claude-haiku-3.5","name":"Claude-Haiku-3.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2024-07-31","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":189096,"output":8192},"status":"deprecated","cost":{"input":0.68,"output":3.4,"cache_read":0.068,"cache_write":0.85},"canonical_model_id":"anthropic/claude-3-5-haiku-20241022"},"anthropic/claude-sonnet-4":{"id":"anthropic/claude-sonnet-4","name":"Claude-Sonnet-4","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":983040,"output":64000},"status":"deprecated","cost":{"input":2.6,"output":13,"cache_read":0.26,"cache_write":3.2},"canonical_model_id":"anthropic/claude-sonnet-4-0"},"anthropic/claude-sonnet-4.5":{"id":"anthropic/claude-sonnet-4.5","name":"Claude-Sonnet-4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":0,"max":31999}],"tool_call":true,"temperature":false,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":983040,"output":32768},"cost":{"input":2.5758,"output":12.8788,"cache_read":0.2576,"cache_write":3.2197},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-opus-4.5":{"id":"anthropic/claude-opus-4.5","name":"Claude-Opus-4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":0,"max":63999}],"tool_call":true,"temperature":false,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":196608,"output":64000},"cost":{"input":4.2929,"output":21.4646,"cache_read":0.4293,"cache_write":5.3662},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-sonnet-3.5":{"id":"anthropic/claude-sonnet-3.5","name":"Claude-Sonnet-3.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2024-04-30","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":189096,"output":8192},"status":"deprecated","cost":{"input":2.6,"output":13,"cache_read":0.26,"cache_write":3.2},"canonical_model_id":"anthropic/claude-3-5-sonnet-20241022"},"anthropic/claude-haiku-3":{"id":"anthropic/claude-haiku-3","name":"Claude-Haiku-3","description":"Legacy model retained for compatibility with older integrations","family":"claude-haiku","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2023-08-31","release_date":"2024-03-13","last_updated":"2024-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":189096,"output":8192},"status":"deprecated","cost":{"input":0.21,"output":1.1,"cache_read":0.021,"cache_write":0.26},"canonical_model_id":"anthropic/claude-3-haiku-20240307"},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude-Opus-4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":128000},"cost":{"input":4.2929,"output":21.4646,"cache_read":0.4293,"cache_write":5.3662},"canonical_model_id":"anthropic/claude-opus-4-7"},"openai/gpt-image-2":{"id":"openai/gpt-image-2","type":"image","name":"GPT-Image-2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"cost":{"input":5.0505,"output":30.303,"cache_read":1.2626},"canonical_model_id":"openai/gpt-image-2"},"openai/gpt-4o-mini-search":{"id":"openai/gpt-4o-mini-search","name":"GPT-4o-mini-Search","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-03-11","last_updated":"2025-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"status":"deprecated","cost":{"input":0.14,"output":0.54}},"openai/gpt-5.1-instant":{"id":"openai/gpt-5.1-instant","name":"GPT-5.1-Instant","description":"Chat-tuned GPT-5.1 for polished assistants, writing, and product conversations","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"status":"deprecated","cost":{"input":1.1,"output":9,"cache_read":0.11},"canonical_model_id":"openai/gpt-5.1-chat-latest"},"openai/gpt-3.5-turbo-raw":{"id":"openai/gpt-3.5-turbo-raw","name":"GPT-3.5-Turbo-Raw","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":4524,"output":2048},"status":"deprecated","cost":{"input":0.45,"output":1.4},"canonical_model_id":"openai/gpt-3.5-turbo"},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT-5.3-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.5909,"output":12.7273,"cache_read":0.1591},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-5-codex":{"id":"openai/gpt-5-codex","name":"GPT-5-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":1.1,"output":9},"canonical_model_id":"openai/gpt-5-codex"},"openai/gpt-5-pro":{"id":"openai/gpt-5-pro","name":"GPT-5-Pro","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":13.6364,"output":109.0909},"canonical_model_id":"openai/gpt-5-pro"},"openai/gpt-image-1.5":{"id":"openai/gpt-image-1.5","type":"image","name":"gpt-image-1.5","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-11-25","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":128000,"output":0},"canonical_model_id":"openai/gpt-image-1.5"},"openai/gpt-image-1":{"id":"openai/gpt-image-1","type":"image","name":"GPT-Image-1","description":"OpenAI image model for production generation, edits, and brand-safe visual workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-04-24","last_updated":"2025-04-24","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":128000,"output":0},"status":"deprecated","canonical_model_id":"openai/gpt-image-1"},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT-5.4-Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":27.2727,"output":163.6364},"canonical_model_id":"openai/gpt-5.4-pro"},"openai/o1":{"id":"openai/o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":14,"output":54},"canonical_model_id":"openai/o1"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":1.8182,"output":7.2727,"cache_read":0.4545},"canonical_model_id":"openai/gpt-4.1"},"openai/dall-e-3":{"id":"openai/dall-e-3","type":"image","name":"DALL-E-3","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"dall-e","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2023-11-06","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":800,"output":0},"status":"deprecated"},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-5.2-instant":{"id":"openai/gpt-5.2-instant","name":"GPT-5.2-Instant","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"status":"deprecated","cost":{"input":1.6,"output":13,"cache_read":0.16},"canonical_model_id":"openai/gpt-5.2-chat-latest"},"openai/gpt-5.3-instant":{"id":"openai/gpt-5.3-instant","name":"GPT-5.3-Instant","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":111616,"output":16384},"status":"deprecated","cost":{"input":1.6,"output":13,"cache_read":0.16},"canonical_model_id":"openai/gpt-5.3-chat-latest"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.1364,"output":9.0909,"cache_read":0.1136},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-5.3-codex-spark":{"id":"openai/gpt-5.3-codex-spark","name":"GPT-5.3-Codex-Spark","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex-spark","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":100000,"output":16384},"cost":{"input":0,"output":0},"canonical_model_id":"openai/gpt-5.3-codex-spark"},"openai/gpt-4o-search":{"id":"openai/gpt-4o-search","name":"GPT-4o-Search","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-03-11","last_updated":"2025-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":2.2727,"output":9.0909}},"openai/o4-mini-deep-research":{"id":"openai/o4-mini-deep-research","name":"o4-mini-deep-research","description":"Research model for long-horizon investigation, synthesis, and analytical reports","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-06-26","last_updated":"2025-06-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":1.8,"output":7.2,"cache_read":0.45},"canonical_model_id":"openai/o4-mini-deep-research"},"openai/gpt-5.2-pro":{"id":"openai/gpt-5.2-pro","name":"GPT-5.2-Pro","description":"Higher-accuracy GPT-5.2 variant for tougher reasoning and review workflows","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":19.0909,"output":152.7273},"canonical_model_id":"openai/gpt-5.2-pro"},"openai/o3-deep-research":{"id":"openai/o3-deep-research","name":"o3-deep-research","description":"Research model for long-horizon investigation, synthesis, and analytical reports","family":"o","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-06-26","last_updated":"2025-06-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":9,"output":36,"cache_read":2.2},"canonical_model_id":"openai/o3-deep-research"},"openai/gpt-4-classic":{"id":"openai/gpt-4-classic","name":"GPT-4-Classic","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2023-11","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":4096},"status":"deprecated","cost":{"input":27,"output":54},"canonical_model_id":"openai/gpt-4"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.2727,"output":13.6364,"cache_read":0.2273},"canonical_model_id":"openai/gpt-5.4"},"openai/sora-2":{"id":"openai/sora-2","type":"video","name":"Sora-2","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"sora","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"status":"deprecated"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4-Mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.6818,"output":4.0909,"cache_read":0.0682},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/o1-pro":{"id":"openai/o1-pro","name":"o1-pro","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2023-09","release_date":"2025-03-19","last_updated":"2025-03-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":140,"output":540},"canonical_model_id":"openai/o1-pro"},"openai/o3-mini-high":{"id":"openai/o3-mini-high","name":"o3-mini-high","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":0.99,"output":4},"canonical_model_id":"openai/o3-mini"},"openai/gpt-5.1-codex-max":{"id":"openai/gpt-5.1-codex-max","name":"GPT-5.1-Codex-Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":1.1,"output":9,"cache_read":0.11},"canonical_model_id":"openai/gpt-5.1-codex-max"},"openai/sora-2-pro":{"id":"openai/sora-2-pro","type":"video","name":"Sora-2-Pro","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"sora","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":0,"output":0},"status":"deprecated"},"openai/gpt-3.5-turbo-instruct":{"id":"openai/gpt-3.5-turbo-instruct","name":"GPT-3.5-Turbo-Instruct","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2023-09-20","last_updated":"2023-09-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":3500,"output":1024},"status":"deprecated","cost":{"input":1.4,"output":1.8}},"openai/chatgpt-4o-latest":{"id":"openai/chatgpt-4o-latest","name":"ChatGPT-4o-Latest","description":"Legacy model retained for compatibility with older integrations","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-08-14","last_updated":"2024-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"status":"deprecated","cost":{"input":4.5,"output":14}},"openai/gpt-5-chat":{"id":"openai/gpt-5-chat","name":"GPT-5-Chat","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":272000,"output":16384},"status":"deprecated","cost":{"input":1.1,"output":9,"cache_read":0.11},"canonical_model_id":"openai/gpt-5-chat-latest"},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1-mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.3636,"output":1.4545,"cache_read":0.0909},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-5.2-codex":{"id":"openai/gpt-5.2-codex","name":"GPT-5.2-Codex","description":"Code-specialist GPT for repository edits, reviews, and long-running software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":1.6,"output":13,"cache_read":0.16},"canonical_model_id":"openai/gpt-5.2-codex"},"openai/gpt-4-classic-0314":{"id":"openai/gpt-4-classic-0314","name":"GPT-4-Classic-0314","description":"Legacy model retained for compatibility with older integrations","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-08-26","last_updated":"2024-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":4096},"status":"deprecated","cost":{"input":27,"output":54}},"openai/gpt-5.5-pro":{"id":"openai/gpt-5.5-pro","name":"GPT-5.5-Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":400000,"input":922000,"output":128000},"cost":{"input":27.2727,"output":163.6364},"canonical_model_id":"openai/gpt-5.5-pro"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5-mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2273,"output":1.8182,"cache_read":0.0227},"canonical_model_id":"openai/gpt-5-mini"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1-nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"status":"deprecated","cost":{"input":0.09,"output":0.36,"cache_read":0.022},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5.1-codex":{"id":"openai/gpt-5.1-codex","name":"GPT-5.1-Codex","description":"Codex GPT for repository edits, code review, and practical software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":1.1,"output":9,"cache_read":0.11},"canonical_model_id":"openai/gpt-5.1-codex"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4-Nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.1818,"output":1.1364,"cache_read":0.0182},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-4-turbo":{"id":"openai/gpt-4-turbo","name":"GPT-4-Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":9,"output":27},"canonical_model_id":"openai/gpt-4-turbo"},"openai/o3-pro":{"id":"openai/o3-pro","name":"o3-pro","description":"High-effort o3 tier for difficult technical reasoning and careful answers","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-06-10","last_updated":"2025-06-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":18.1818,"output":72.7273},"canonical_model_id":"openai/o3-pro"},"openai/o3":{"id":"openai/o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.8182,"output":7.2727,"cache_read":0.4545},"canonical_model_id":"openai/o3"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":400000,"input":922000,"output":128000},"cost":{"input":4.5455,"output":27.2727,"cache_read":0.4545},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.1364,"output":9.0909,"cache_read":0.1136},"canonical_model_id":"openai/gpt-5"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5-nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.0455,"output":0.3636,"cache_read":0.0045},"canonical_model_id":"openai/gpt-5-nano"},"openai/gpt-3.5-turbo":{"id":"openai/gpt-3.5-turbo","name":"GPT-3.5-Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":2048},"status":"deprecated","cost":{"input":0.45,"output":1.4},"canonical_model_id":"openai/gpt-3.5-turbo"},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":0.99,"output":4},"canonical_model_id":"openai/o3-mini"},"openai/gpt-5.1-codex-mini":{"id":"openai/gpt-5.1-codex-mini","name":"GPT-5.1-Codex-Mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":0.22,"output":1.8,"cache_read":0.022},"canonical_model_id":"openai/gpt-5.1-codex-mini"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o-mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":124096,"output":4096},"cost":{"input":0.1364,"output":0.5455,"cache_read":0.0682},"canonical_model_id":"openai/gpt-4o-mini"},"openai/gpt-4o-aug":{"id":"openai/gpt-4o-aug","name":"GPT-4o-Aug","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-08-06","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":2.2727,"output":9.0909,"cache_read":1.1364},"canonical_model_id":"openai/gpt-4o-2024-08-06"},"openai/o4-mini":{"id":"openai/o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":0.99,"output":4,"cache_read":0.25},"canonical_model_id":"openai/o4-mini"},"openai/gpt-image-1-mini":{"id":"openai/gpt-image-1-mini","type":"image","name":"GPT-Image-1-Mini","description":"Cost-efficient GPT Image 1 variant for image generation and editing","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"output":0},"canonical_model_id":"openai/gpt-image-1-mini"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.5909,"output":12.7273,"cache_read":0.1591},"canonical_model_id":"openai/gpt-5.2"},"empiriolabs/deepseek-v4-flash-el":{"id":"empiriolabs/deepseek-v4-flash-el","name":"DeepSeek-V4-Flash-EL","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":384000},"cost":{"input":0.14,"output":0.28},"canonical_model_id":"deepseek/deepseek-v4-flash"},"empiriolabs/deepseek-v4-pro-el":{"id":"empiriolabs/deepseek-v4-pro-el","name":"DeepSeek-V4-Pro-EL","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":384000},"cost":{"input":1.67,"output":3.33},"canonical_model_id":"deepseek/deepseek-v4-pro"},"lumalabs/ray2":{"id":"lumalabs/ray2","type":"video","name":"Ray2","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"ray","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-02-20","last_updated":"2025-02-20","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":5000,"output":0}},"stabilityai/stablediffusionxl":{"id":"stabilityai/stablediffusionxl","type":"image","name":"StableDiffusionXL","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"stable-diffusion","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2023-07-09","last_updated":"2023-07-09","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":200,"output":0}},"topazlabs-co/topazlabs":{"id":"topazlabs-co/topazlabs","type":"image","name":"TopazLabs","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"topazlabs","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-12-03","last_updated":"2024-12-03","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":204,"output":0}},"cerebras/qwen3-235b-2507-cs":{"id":"cerebras/qwen3-235b-2507-cs","name":"qwen3-235b-2507-cs","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":0,"output":0},"status":"deprecated","canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"cerebras/gpt-oss-120b-cs":{"id":"cerebras/gpt-oss-120b-cs","name":"GPT-OSS-120B-CS","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":0},"cost":{"input":0.3535,"output":0.7576},"canonical_model_id":"openai/gpt-oss-120b"},"cerebras/qwen3-32b-cs":{"id":"cerebras/qwen3-32b-cs","name":"qwen3-32b-cs","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":0,"output":0},"status":"deprecated","canonical_model_id":"alibaba/qwen3-32b"},"cerebras/llama-3.1-8b-cs":{"id":"cerebras/llama-3.1-8b-cs","name":"Llama-3.1-8B-CS","description":"Compact open Llama model for lightweight chat, drafting, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":0},"cost":{"input":0.1,"output":0.1},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"cerebras/llama-3.3-70b-cs":{"id":"cerebras/llama-3.3-70b-cs","name":"llama-3.3-70b-cs","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":0,"output":0},"status":"deprecated","canonical_model_id":"meta/llama-3.3-70b-instruct"},"runwayml/runway":{"id":"runwayml/runway","type":"video","name":"Runway","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"runway","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-10-11","last_updated":"2024-10-11","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":256,"output":0},"status":"deprecated"},"runwayml/runway-gen-4-turbo":{"id":"runwayml/runway-gen-4-turbo","type":"video","name":"Runway-Gen-4-Turbo","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"runway","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-05-09","last_updated":"2025-05-09","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":256,"output":0},"status":"deprecated"},"novita/kimi-k2-thinking":{"id":"novita/kimi-k2-thinking","name":"kimi-k2-thinking","description":"Thinking Kimi model for slower research passes, planning, and hard technical questions","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":false,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":0},"status":"deprecated","canonical_model_id":"moonshotai/kimi-k2-thinking"},"novita/minimax-m2.1":{"id":"novita/minimax-m2.1","name":"minimax-m2.1","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":false,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":205000,"output":131072},"cost":{"input":0.303,"output":1.2121,"cache_read":0.1515},"canonical_model_id":"minimax/MiniMax-M2.1"},"novita/glm-4.7":{"id":"novita/glm-4.7","name":"glm-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":205000,"output":131072},"status":"deprecated","canonical_model_id":"zhipuai/glm-4.7"},"novita/glm-4.6v":{"id":"novita/glm-4.6v","name":"glm-4.6v","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":false,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":32768},"canonical_model_id":"zhipuai/glm-4.6v"},"novita/glm-5":{"id":"novita/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":205000,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"novita/glm-4.7-flash":{"id":"novita/glm-4.7-flash","name":"glm-4.7-flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":false,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":65500},"cost":{"input":0.0707,"output":0.404},"canonical_model_id":"zhipuai/glm-4.7-flash"},"novita/kimi-k2.5":{"id":"novita/kimi-k2.5","name":"Kimi-K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":262144},"status":"deprecated","cost":{"input":0.6,"output":3,"cache_read":0.1},"canonical_model_id":"moonshotai/kimi-k2.5"},"novita/kimi-k2.6":{"id":"novita/kimi-k2.6","name":"Kimi-K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":262144},"cost":{"input":0.9596,"output":4.0404,"cache_read":0.1616},"canonical_model_id":"moonshotai/kimi-k2.6"},"novita/glm-4.6":{"id":"novita/glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":false,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":0,"output":0},"cost":{"input":0.6061,"output":2.2222,"cache_read":0.1111},"canonical_model_id":"zhipuai/glm-4.6"},"novita/glm-4.7-n":{"id":"novita/glm-4.7-n","name":"glm-4.7-n","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":false,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":205000,"output":131072},"canonical_model_id":"zhipuai/glm-4.7"},"novita/deepseek-v3.2":{"id":"novita/deepseek-v3.2","name":"DeepSeek-V3.2","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":0},"cost":{"input":0.2626,"output":0.3838,"cache_read":0.1313},"canonical_model_id":"deepseek/deepseek-v3.2"},"poetools/claude-code":{"id":"poetools/claude-code","name":"claude-code","description":"Claude model for careful reasoning, writing, coding, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]},{"type":"budget_tokens"}],"tool_call":true,"temperature":false,"release_date":"2025-11-27","last_updated":"2025-11-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0}},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini-2.5-Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"temperature":false,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1024000,"output":64000},"status":"deprecated","cost":{"input":0.07,"output":0.28},"canonical_model_id":"google/gemini-2.5-flash-lite"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini-3.7-Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.7576,"output":3.7879,"cache_read":0.0758},"canonical_model_id":"google/gemini-3.7-flash"},"google/gemini-2.0-flash":{"id":"google/gemini-2.0-flash","name":"Gemini-2.0-Flash","description":"Earlier Gemini Flash workhorse for responsive multimodal apps and tool use","family":"gemini-flash","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2024-06","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":990000,"output":8192},"status":"deprecated","cost":{"input":0.1,"output":0.42},"canonical_model_id":"google/gemini-2.0-flash"},"google/veo-3.1-fast":{"id":"google/veo-3.1-fast","type":"video","name":"Veo-3.1-Fast","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image"],"output":["video"]},"open_weights":false,"limit":{"context":480,"output":0}},"google/nano-banana":{"id":"google/nano-banana","type":"image","name":"Nano-Banana","description":"Nano Banana image model for fast generation, edits, and character-consistent assets","family":"gemini-flash","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2024-06","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":0},"status":"deprecated","cost":{"input":0.21,"output":1.8,"cache_read":0.021},"canonical_model_id":"google/gemini-2.5-flash-image"},"google/gemma-4-31b":{"id":"google/gemma-4-31b","name":"Gemma-4-31B","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini-2.5-Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"temperature":false,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1065535,"output":65535},"status":"deprecated","cost":{"input":0.21,"output":1.8,"cache_read":0.021},"canonical_model_id":"google/gemini-2.5-flash"},"google/gemini-3.1-pro":{"id":"google/gemini-3.1-pro","name":"Gemini-3.1-Pro","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2.0202,"output":12.1212,"cache_read":0.202},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/imagen-4-fast":{"id":"google/imagen-4-fast","type":"image","name":"Imagen-4-Fast","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"imagen","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-06-25","last_updated":"2025-06-25","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":480,"output":0}},"google/lyria":{"id":"google/lyria","name":"Lyria","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"lyria","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-06-04","last_updated":"2025-06-04","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0}},"google/gemini-2.0-flash-lite":{"id":"google/gemini-2.0-flash-lite","name":"Gemini-2.0-Flash-Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2024-06","release_date":"2024-12-11","last_updated":"2024-12-11","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":990000,"output":8192},"status":"deprecated","cost":{"input":0.052,"output":0.21},"canonical_model_id":"google/gemini-2.0-flash-lite"},"google/imagen-4":{"id":"google/imagen-4","type":"image","name":"Imagen-4","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"imagen","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":480,"output":0}},"google/gemini-3-flash":{"id":"google/gemini-3-flash","name":"Gemini-3-Flash","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.404,"output":2.4242,"cache_read":0.0404},"canonical_model_id":"google/gemini-3-flash-preview"},"google/veo-3-fast":{"id":"google/veo-3-fast","type":"video","name":"Veo-3-Fast","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-10-13","last_updated":"2025-10-13","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":480,"output":0},"status":"deprecated"},"google/veo-3.1":{"id":"google/veo-3.1","type":"video","name":"Veo-3.1","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":480,"output":0}},"google/gemini-deep-research":{"id":"google/gemini-deep-research","name":"gemini-deep-research","description":"Legacy model retained for compatibility with older integrations","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":0},"status":"deprecated","cost":{"input":1.6,"output":9.6}},"google/gemini-omni-1.1-flash":{"id":"google/gemini-omni-1.1-flash","type":"video","name":"Gemini-Omni-1.1-Flash","description":"Video generation and editing model for scene extension, frame interpolation, and reference-guided multimodal control","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":false,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text","image","video"],"output":["video"]},"open_weights":false,"limit":{"context":131072,"output":57920},"cost":{"input":1.5152,"output":9.0909},"canonical_model_id":"google/gemini-omni-1.1-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini-2.5-Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":0,"max":32768}],"tool_call":true,"temperature":false,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1065535,"output":65535},"status":"deprecated","cost":{"input":0.87,"output":7,"cache_read":0.087},"canonical_model_id":"google/gemini-2.5-pro"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini-3.5-Flash-Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.303,"output":2.5253,"cache_read":0.0303},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/imagen-3":{"id":"google/imagen-3","type":"image","name":"Imagen-3","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"imagen","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-10-15","last_updated":"2024-10-15","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":480,"output":0},"status":"deprecated"},"google/imagen-3-fast":{"id":"google/imagen-3-fast","type":"image","name":"Imagen-3-Fast","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"imagen","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-10-17","last_updated":"2024-10-17","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":480,"output":0},"status":"deprecated"},"google/gemini-3-pro":{"id":"google/gemini-3-pro","name":"Gemini-3-Pro","description":"Preview Gemini flagship for complex reasoning, coding, and rich multimodal prompts","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2025-01","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":1.6,"output":9.6,"cache_read":0.16},"canonical_model_id":"google/gemini-3-pro-preview"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini-3.5-Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5152,"output":9.0909,"cache_read":0.1515},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini-3.8-Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.7576,"output":3.7879,"cache_read":0.0758},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini-3.1-Flash-Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.2525,"output":1.5152},"canonical_model_id":"google/gemini-3.1-flash-lite"},"google/veo-2":{"id":"google/veo-2","type":"video","name":"Veo-2","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2024-12-02","last_updated":"2024-12-02","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":480,"output":0},"status":"deprecated"},"google/veo-3":{"id":"google/veo-3","type":"video","name":"Veo-3","description":"Video model for prompt-guided generation, editing, and motion workflows","family":"veo","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-05-21","last_updated":"2025-05-21","modalities":{"input":["text"],"output":["video"]},"open_weights":false,"limit":{"context":480,"output":0},"status":"deprecated"},"google/imagen-4-ultra":{"id":"google/imagen-4-ultra","type":"image","name":"Imagen-4-Ultra","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"imagen","attachment":false,"reasoning":false,"tool_call":true,"temperature":false,"release_date":"2025-05-24","last_updated":"2025-05-24","modalities":{"input":["text"],"output":["image"]},"open_weights":false,"limit":{"context":480,"output":0},"status":"deprecated"},"google/nano-banana-pro":{"id":"google/nano-banana-pro","type":"image","name":"Nano-Banana-Pro","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":false,"tool_call":true,"temperature":false,"knowledge":"2025-01","release_date":"2025-11-20","last_updated":"2025-11-20","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":65536,"output":0},"cost":{"input":2.0202,"output":12.1212,"cache_read":0.202},"canonical_model_id":"google/gemini-3-pro-image-preview"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini-3.6-Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.7576,"output":3.7879,"cache_read":0.0758},"canonical_model_id":"google/gemini-3.6-flash"}}},"poolside":{"id":"poolside","env":["POOLSIDE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://inference.poolside.ai/v1","name":"Poolside","doc":"https://platform.poolside.ai","models":{"poolside/laguna-m.1":{"id":"poolside/laguna-m.1","name":"Laguna M.1","description":"Poolside's open-weight model for agentic coding and long-horizon work","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"poolside/laguna-m.1"},"poolside/laguna-xs-2.1":{"id":"poolside/laguna-xs-2.1","name":"Laguna XS 2.1","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-07-02","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"poolside/laguna-xs-2.1"},"poolside/laguna-s-2.1":{"id":"poolside/laguna-s-2.1","name":"Laguna S 2.1","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"poolside/laguna-s-2.1"}}},"neuralwatt":{"id":"neuralwatt","env":["NEURALWATT_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.neuralwatt.com/v1","name":"Neuralwatt","doc":"https://portal.neuralwatt.com/docs","models":{"qwen3.6-35b-fast":{"id":"qwen3.6-35b-fast","name":"Qwen3.6 35B Fast","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131056,"output":131056},"cost":{"input":0.29,"output":1.15,"cache_read":0.029},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"kimi-k3-fast":{"id":"kimi-k3-fast","name":"Kimi K3 Fast","description":"Kimi K3 with thinking disabled for low-latency tool calling, vision, and JSON work","family":"kimi-k3","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":1048560},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"deepseek-v4-flash-speed":{"id":"deepseek-v4-flash-speed","name":"DeepSeek V4 Flash (Speed)","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":393216},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"mimo-v2.6-pro-flex":{"id":"mimo-v2.6-pro-flex","name":"MiMo-V2.6-Pro Flex","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":393216},"cost":{"input":0.5655,"output":1.131,"cache_read":0.0234},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"qwen3.6-35b":{"id":"qwen3.6-35b","name":"Qwen3.6 35B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131056,"output":131056},"cost":{"input":0.29,"output":1.15,"cache_read":0.029},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":393216},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":1048560},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"glm-5.2-short-fast":{"id":"glm-5.2-short-fast","name":"GLM 5.2 Short Fast","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":199984,"output":32000},"status":"deprecated","cost":{"input":1.45,"output":4.5,"cache_read":0.145},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.2":{"id":"glm-5.2","name":"GLM 5.2","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":1048560},"status":"deprecated","cost":{"input":1.45,"output":4.5,"cache_read":0.145},"canonical_model_id":"zhipuai/glm-5.2"},"kimi-k3-flex":{"id":"kimi-k3-flex","name":"Kimi K3 Flex","description":"Kimi K3 on the flex tier: discounted, best-effort latency, requests may be held under load","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":1048560},"cost":{"input":1.95,"output":9.75,"cache_read":0.195},"canonical_model_id":"moonshotai/kimi-k3"},"gemma-4-31b":{"id":"gemma-4-31b","name":"Gemma 4 31B","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262128,"output":16384},"cost":{"input":0.144,"output":0.42,"cache_read":0.0144},"canonical_model_id":"google/gemma-4-31b-it"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","xhigh","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":393216},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"glm-5.3-flex":{"id":"glm-5.3-flex","name":"GLM 5.3 Flex","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":1048560},"cost":{"input":0.9425,"output":2.925,"cache_read":0.09425},"canonical_model_id":"zhipuai/glm-5.3"},"kimi-k2.7-code-fast":{"id":"kimi-k2.7-code-fast","name":"Kimi K2.7 Code Fast","description":"Kimi K2.7 Code with reasoning capped to a short budget for lower latency; reasoning cannot be disabled on this model","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262128,"output":262128},"status":"deprecated","cost":{"input":0.95,"output":4,"cache_read":0.095},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"glm-5.3":{"id":"glm-5.3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":1048560},"cost":{"input":1.45,"output":4.5,"cache_read":0.145},"canonical_model_id":"zhipuai/glm-5.3"},"qwen-3.8-27b":{"id":"qwen-3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262128,"output":131072},"cost":{"input":0.45,"output":3.2,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-27b"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":393216},"status":"deprecated","cost":{"input":1,"output":3,"cache_read":0.1},"canonical_model_id":"deepseek/deepseek-v4-pro"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":1048560},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"deepseek-v4.1-flash-flex":{"id":"deepseek-v4.1-flash-flex","name":"DeepSeek V4.1 Flash Flex","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","xhigh","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":393216},"cost":{"input":0.0975,"output":0.39,"cache_read":0.00975},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"qwen-3.8-27b-flex":{"id":"qwen-3.8-27b-flex","name":"Qwen3.8 27B Flex","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262128,"output":131072},"cost":{"input":0.2925,"output":2.08,"cache_read":0.1625},"canonical_model_id":"alibaba/qwen3.8-27b"},"deepseek-v4-flash-flex":{"id":"deepseek-v4-flash-flex","name":"DeepSeek V4 Flash Flex","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":393216},"cost":{"input":0.091,"output":0.182,"cache_read":0.0182},"canonical_model_id":"deepseek/deepseek-v4-flash"},"mimo-v2.6-pro":{"id":"mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":393216},"cost":{"input":0.87,"output":1.74,"cache_read":0.036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"kimi-k2.7-code-flex":{"id":"kimi-k2.7-code-flex","name":"Kimi K2.7 Code Flex","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262128,"output":262128},"status":"deprecated","cost":{"input":0.6175,"output":2.6,"cache_read":0.06175},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"glm-5.2-short":{"id":"glm-5.2-short","name":"GLM 5.2 Short","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":199984,"output":32000},"status":"deprecated","cost":{"input":1.45,"output":4.5,"cache_read":0.145},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.2-flex":{"id":"glm-5.2-flex","name":"GLM 5.2 Flex","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":1048560},"status":"deprecated","cost":{"input":0.9425,"output":2.925,"cache_read":0.09425},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.2-short-fast-flex":{"id":"glm-5.2-short-fast-flex","name":"GLM 5.2 Short Fast Flex","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":199984,"output":32000},"status":"deprecated","cost":{"input":0.9425,"output":2.925,"cache_read":0.09425},"canonical_model_id":"zhipuai/glm-5.2"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262128,"output":262128},"status":"deprecated","cost":{"input":0.95,"output":4,"cache_read":0.095},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"glm-5.2-fast":{"id":"glm-5.2-fast","name":"GLM 5.2 Fast","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":1048560},"status":"deprecated","cost":{"input":1.45,"output":4.5,"cache_read":0.145},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.3-flash-flex":{"id":"glm-5.3-flash-flex","name":"GLM-5.3 Flash Flex","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048560,"output":1048560},"cost":{"input":0.0975,"output":0.325,"cache_read":0.0195},"canonical_model_id":"zhipuai/glm-5.3-flash"},"glm-5.2-short-flex":{"id":"glm-5.2-short-flex","name":"GLM 5.2 Short Flex","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":false,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":199984,"output":32000},"status":"deprecated","cost":{"input":0.9425,"output":2.925,"cache_read":0.09425},"canonical_model_id":"zhipuai/glm-5.2"},"qwen3.6-35b-flex":{"id":"qwen3.6-35b-flex","name":"Qwen3.6 35B Flex","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131056,"output":131056},"cost":{"input":0.1885,"output":0.7475,"cache_read":0.01885},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"}}},"novita-ai":{"id":"novita-ai","env":["NOVITA_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.novita.ai/openai","name":"Novita AI","doc":"https://novita.ai/docs/guides/introduction","models":{"apodex/apodex-1.1-mini":{"id":"apodex/apodex-1.1-mini","name":"Apodex 1.1 Mini","description":"Open-weight 35B MoE model for long-horizon research, forecasting, and tool-assisted work","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-24","last_updated":"2026-08-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"apodex/apodex-1.1-mini"},"baai/bge-reranker-v2-m3":{"id":"baai/bge-reranker-v2-m3","type":"reranking","name":"BGE Reranker V2 M3","description":"Lightweight multilingual cross-encoder that scores query-document relevance","family":"bge","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-03-15","last_updated":"2024-03-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8000,"output":0},"cost":{"input":0.01,"output":0},"canonical_model_id":"baai/bge-reranker-v2-m3"},"baai/bge-m3":{"id":"baai/bge-m3","type":"embedding","name":"BGE M3","description":"Multilingual embedding model combining dense, sparse, and multi-vector retrieval","family":"bge","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2024-01-30","last_updated":"2024-01-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":0},"cost":{"input":0.01,"output":0},"canonical_model_id":"baai/bge-m3"},"xiaomimimo/mimo-v2.6-flash":{"id":"xiaomimimo/mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"xiaomimimo/mimo-v2.6-pro":{"id":"xiaomimimo/mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"xiaomimimo/mimo-v2.5-pro":{"id":"xiaomimimo/mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.522,"output":1.044,"cache_read":0.0043},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"xiaomimimo/mimo-v2.5":{"id":"xiaomimimo/mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.168,"output":0.336,"cache_read":0.0034},"canonical_model_id":"xiaomi/mimo-v2.5"},"baichuan/baichuan-m2-32b":{"id":"baichuan/baichuan-m2-32b","name":"Baichuan M2 32B","description":"Open medical model trained for clinical reasoning and patient interaction with on, off, and auto thinking modes","family":"baichuan","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"temperature":true,"release_date":"2025-08-13","last_updated":"2025-08-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.07,"output":0.07},"canonical_model_id":"baichuan/baichuan-m2-32b"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.05,"output":0.25},"canonical_model_id":"openai/gpt-oss-120b"},"inclusionai/ling-3.0-flash-fin":{"id":"inclusionai/ling-3.0-flash-fin","name":"Ling 3.0 Flash Fin","description":"Finance-enhanced model for financial research, multi-step investment workflows, and long-horizon planning and execution","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-08-27","last_updated":"2026-09-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.075,"output":0.22,"cache_read":0.015},"canonical_model_id":"inclusionai/ling-3.0-flash-fin"},"inclusionai/ling-3.1-flash":{"id":"inclusionai/ling-3.1-flash","name":"Ling 3.1 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.3,"output":0.9,"cache_read":0.06},"canonical_model_id":"inclusionai/ling-3.1-flash"},"inclusionai/ling-3.0-flash-sante":{"id":"inclusionai/ling-3.0-flash-sante","name":"Ling 3.0 Flash Sante","description":"Health and medicine specialization of Ling 3.0 Flash for medical reasoning and evidence-based retrieval","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.075,"output":0.22,"cache_read":0.015},"canonical_model_id":"inclusionai/ling-3.0-flash-sante"},"inclusionai/ling-3.0-flash-vl":{"id":"inclusionai/ling-3.0-flash-vl","name":"Ling 3.0 Flash VL","description":"Native multimodal hybrid MoE model for image and video understanding, reasoning, and visual agents","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.075,"output":0.22,"cache_read":0.015},"canonical_model_id":"inclusionai/ling-3.0-flash-vl"},"inclusionai/ling-3.0-flash":{"id":"inclusionai/ling-3.0-flash","name":"Ling 3.0 Flash","description":"Hybrid-linear MoE reasoning model with 124B total and 5.1B active parameters for efficient agents","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-07-23","last_updated":"2026-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.06,"output":0.18,"cache_read":0.012},"canonical_model_id":"inclusionai/ling-3.0-flash"},"minimaxai/minimax-m1-80k":{"id":"minimaxai/minimax-m1-80k","name":"MiniMax M1 80K","description":"Open hybrid-attention MoE reasoning model with a million-token context and an 80K thinking budget","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":40000},"cost":{"input":0.55,"output":2.2},"canonical_model_id":"minimax/minimax-m1-80k"},"paddlepaddle/paddleocr-vl":{"id":"paddlepaddle/paddleocr-vl","name":"PaddleOCR VL","description":"Compact vision-language model for multilingual document parsing, OCR, tables, formulas, and charts","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-10-16","last_updated":"2025-10-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":16384},"cost":{"input":0.02,"output":0.02},"canonical_model_id":"paddlepaddle/paddleocr-vl"},"zai-org/glm-4.5v":{"id":"zai-org/glm-4.5v","name":"GLM-4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":16384},"cost":{"input":0.6,"output":1.8,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5v"},"zai-org/glm-4.7":{"id":"zai-org/glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.7"},"zai-org/glm-4.6v":{"id":"zai-org/glm-4.6v","name":"GLM-4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.3,"output":0.9,"cache_read":0.055},"canonical_model_id":"zhipuai/glm-4.6v"},"zai-org/glm-5.2":{"id":"zai-org/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/glm-5":{"id":"zai-org/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202800,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"zai-org/glm-5.3":{"id":"zai-org/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"zai-org/glm-5.3-flash":{"id":"zai-org/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/glm-4.7-flash":{"id":"zai-org/glm-4.7-flash","name":"GLM-4.7-Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.07,"output":0.4,"cache_read":0.01},"canonical_model_id":"zhipuai/glm-4.7-flash"},"zai-org/glm-4.5-air":{"id":"zai-org/glm-4.5-air","name":"GLM-4.5-Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.13,"output":0.85,"cache_read":0.025},"canonical_model_id":"zhipuai/glm-4.5-air"},"zai-org/autoglm-phone-9b-multilingual":{"id":"zai-org/autoglm-phone-9b-multilingual","name":"AutoGLM Phone 9B Multilingual","description":"Multilingual visual model for operating smartphone interfaces and mobile agents","family":"glm","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-12-10","last_updated":"2025-12-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.035,"output":0.138},"canonical_model_id":"zhipuai/autoglm-phone-9b-multilingual"},"zai-org/glm-5.1":{"id":"zai-org/glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1.38,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"zai-org/glm-4.6":{"id":"zai-org/glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.55,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.6"},"mindai/macaron-v1-tall":{"id":"mindai/macaron-v1-tall","name":"Macaron V1 Tall","description":"Qwen3.6-based Mixture-of-LoRA model with specialists for chat, personal agents, coding, and generative UI","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.2475,"output":1.43,"cache_read":0.044},"canonical_model_id":"mindlab/macaron-v1-tall"},"mindai/macaron-v1-venti":{"id":"mindai/macaron-v1-venti","name":"Macaron V1 Venti","description":"GLM-5.2-based Mixture-of-LoRA model with specialists for chat, personal agents, coding, and generative UI","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.825,"output":2.475,"cache_read":0.165},"canonical_model_id":"mindlab/macaron-v1-venti"},"qwen/qwen3-vl-30b-a3b-instruct":{"id":"qwen/qwen3-vl-30b-a3b-instruct","name":"Qwen3 VL 30B A3B Instruct","description":"Open vision-language MoE model for image and video understanding, documents, and visual agents","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-04","last_updated":"2025-10-04","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.2,"output":0.7},"canonical_model_id":"alibaba/qwen3-vl-30b-a3b-instruct"},"qwen/qwen3.8-flash":{"id":"qwen/qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen/qwen3.5-35b-a3b":{"id":"qwen/qwen3.5-35b-a3b","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.25,"output":2},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"qwen/qwen3.8-2.4t-a95b":{"id":"qwen/qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"qwen/qwen3.8-max":{"id":"qwen/qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-max"},"qwen/qwen3-embedding-8b":{"id":"qwen/qwen3-embedding-8b","type":"embedding","name":"Qwen3 Embedding 8B","description":"Multilingual text embedding model for retrieval, code search, classification, and clustering","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":0},"cost":{"input":0.07,"output":0},"canonical_model_id":"alibaba/qwen3-embedding-8b"},"qwen/qwen3.6-27b":{"id":"qwen/qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.6,"output":3.6},"canonical_model_id":"alibaba/qwen3.6-27b"},"qwen/qwen3-reranker-8b":{"id":"qwen/qwen3-reranker-8b","type":"reranking","name":"Qwen3 Reranker 8B","description":"Multilingual query-document reranking model supporting more than 100 languages","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":0},"cost":{"input":0.05,"output":0},"canonical_model_id":"alibaba/qwen3-reranker-8b"},"qwen/qwen3.5-397b-a17b":{"id":"qwen/qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.6,"output":3.6},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"qwen/qwen3-omni-30b-a3b-thinking":{"id":"qwen/qwen3-omni-30b-a3b-thinking","name":"Qwen3 Omni 30B A3B Thinking","description":"Multimodal reasoning model accepting text, images, video, and audio with text output","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-22","last_updated":"2025-09-22","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":16384},"cost":{"input":0.25,"output":0.97,"input_audio":2.2},"canonical_model_id":"alibaba/qwen3-omni-30b-a3b-thinking"},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":1.25,"output":3.75,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen-mt-plus":{"id":"qwen/qwen-mt-plus","name":"Qwen MT Plus","description":"Flagship Qwen translation model with terminology control and support for 92 languages","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-07-24","last_updated":"2025-07-24","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"output":8192},"cost":{"input":0.25,"output":0.75},"canonical_model_id":"alibaba/qwen-mt-plus"},"qwen/qwen3.5-122b-a10b":{"id":"qwen/qwen3.5-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.4,"output":3.2},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.42,"output":3,"cache_read":0.085},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3.5-27b":{"id":"qwen/qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.3,"output":2.4},"canonical_model_id":"alibaba/qwen3.5-27b"},"qwen/qwen3.6-35b-a3b":{"id":"qwen/qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.248,"output":1.485},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"minimax/minimax-m2.7-highspeed":{"id":"minimax/minimax-m2.7-highspeed","name":"MiniMax-M2.7-highspeed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131100},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5"},"minimax/minimax-m2.7":{"id":"minimax/minimax-m2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"tiers":[{"input":0.6,"output":2.4,"cache_read":0.12,"tier":{"type":"context","size":524288}}],"context_over_200k":{"input":0.6,"output":2.4,"cache_read":0.12}},"canonical_model_id":"minimax/MiniMax-M3"},"baidu/cobuddy":{"id":"baidu/cobuddy","name":"CoBuddy","description":"Baidu Qianfan model optimized for code generation and tool-using coding agents","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-05-06","last_updated":"2026-05-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":65536},"cost":{"input":0.28,"output":1.13,"cache_read":0.07},"canonical_model_id":"baidu/cobuddy"},"baidu/ernie-4.5-21B-a3b":{"id":"baidu/ernie-4.5-21B-a3b","name":"ERNIE 4.5 21B A3B","description":"Open ERNIE text MoE with 21B total and 3B active parameters","family":"ernie","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-06-30","last_updated":"2025-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":120000,"output":8000},"cost":{"input":0.07,"output":0.28},"canonical_model_id":"baidu/ernie-4.5-21b-a3b"},"moonshotai/kimi-k2-0905":{"id":"moonshotai/kimi-k2-0905","name":"Kimi K2 Instruct 0905","description":"September 2025 Kimi K2 instruction update with a 256K context and improved agentic coding","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":0.6,"output":2.5},"canonical_model_id":"moonshotai/kimi-k2-0905"},"moonshotai/kimi-k2-thinking":{"id":"moonshotai/kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Thinking Kimi model for slower research passes, planning, and hard technical questions","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":0.6,"output":2.5,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.5":{"id":"moonshotai/kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":3,"cache_read":0.1},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/kimi-k2-instruct":{"id":"moonshotai/kimi-k2-instruct","name":"Kimi K2 Instruct","description":"Non-thinking Kimi K2 MoE instruction model for coding and tool-using agents","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.57,"output":2.3},"canonical_model_id":"moonshotai/kimi-k2-instruct"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.8,"output":3.4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"deepseek/deepseek-r1-turbo":{"id":"deepseek/deepseek-r1-turbo","name":"DeepSeek R1 (Turbo)","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":16000},"cost":{"input":0.7,"output":2.5},"canonical_model_id":"deepseek/deepseek-r1"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":1.6,"output":3.2,"cache_read":0.135},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek_v3":{"id":"deepseek/deepseek_v3","name":"DeepSeek-V3","description":"Open DeepSeek MoE chat model for coding, math, and general reasoning","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-12-26","last_updated":"2024-12-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":16000},"cost":{"input":0.89,"output":0.89},"canonical_model_id":"deepseek/deepseek-v3"},"deepseek/deepseek-ocr-2":{"id":"deepseek/deepseek-ocr-2","name":"DeepSeek OCR 2","description":"High-accuracy OCR model for extracting text from documents, screenshots, receipts, and natural scenes","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0.03,"output":0.03},"canonical_model_id":"deepseek/deepseek-ocr-2"},"deepseek/deepseek-r1-0528-qwen3-8b":{"id":"deepseek/deepseek-r1-0528-qwen3-8b","name":"DeepSeek R1 0528 Qwen3 8B","description":"DeepSeek R1 0528 distilled into Qwen3 8B for mathematics, coding, and reasoning","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"release_date":"2025-05-29","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32000},"cost":{"input":0.06,"output":0.09},"canonical_model_id":"deepseek/deepseek-r1-0528-qwen3-8b"},"deepseek/deepseek-r1-0528":{"id":"deepseek/deepseek-r1-0528","name":"DeepSeek R1 0528","description":"May 2025 DeepSeek R1 update with improved mathematics, coding, and reasoning","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":32768},"cost":{"input":0.7,"output":2.5,"cache_read":0.35},"canonical_model_id":"deepseek/deepseek-r1-0528"},"deepseek/deepseek-v4.1-flash-1017":{"id":"deepseek/deepseek-v4.1-flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.44,"output":1.32,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"nvidia/nemotron-3-nano-30b-a3b":{"id":"nvidia/nemotron-3-nano-30b-a3b","name":"Nemotron 3 Nano 30B A3B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-06-25","release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.05,"output":0.2},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"microsoft/wizardlm-2-8x22b":{"id":"microsoft/wizardlm-2-8x22b","name":"WizardLM 2 8x22B","description":"Microsoft WizardLM instruction-tuned Mixtral MoE for multilingual dialogue and complex tasks","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2024-04-15","last_updated":"2024-04-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65535,"output":8000},"cost":{"input":0.62,"output":0.62},"canonical_model_id":"microsoft/wizardlm-2-8x22b"},"meta-llama/llama-3.2-1b-instruct":{"id":"meta-llama/llama-3.2-1b-instruct","name":"Llama 3.2 1B Instruct","description":"Compact instruction-tuned Llama model for multilingual dialogue and on-device assistants","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":32000},"cost":{"input":0.02,"output":0.02},"canonical_model_id":"meta/llama-3.2-1b-instruct"},"meta-llama/llama-4-maverick-17b-128e-instruct-fp8":{"id":"meta-llama/llama-4-maverick-17b-128e-instruct-fp8","name":"Llama 4 Maverick 17B Instruct","description":"Open multimodal Llama for strong reasoning with efficient everyday serving","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":8192},"cost":{"input":0.27,"output":0.85},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"meta-llama/llama-3.3-70b-instruct":{"id":"meta-llama/llama-3.3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":12288,"output":12288},"cost":{"input":0.135,"output":0.4},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"meta-llama/llama-4-scout-17b-16e-instruct":{"id":"meta-llama/llama-4-scout-17b-16e-instruct","name":"Llama 4 Scout 17B Instruct","description":"Open Llama with long-context vision for efficient multimodal agents","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.18,"output":0.59},"canonical_model_id":"meta/llama-4-scout-17b-instruct"},"meta-llama/llama-3.1-8b-instruct":{"id":"meta-llama/llama-3.1-8b-instruct","name":"Llama-3.1-8B-Instruct","description":"Compact open Llama model for lightweight chat, drafting, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":16384},"cost":{"input":0.02,"output":0.05},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"tencent/hy4-preview":{"id":"tencent/hy4-preview","name":"Hy4 preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":64000},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"},"tencent/hy3":{"id":"tencent/hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":192000,"output":262144},"cost":{"input":0.14,"output":0.58,"cache_read":0.035},"canonical_model_id":"tencent/hy3"},"stepfun/step-5-preview":{"id":"stepfun/step-5-preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":64000},"cost":{"input":1,"output":2.7,"cache_read":0.1},"canonical_model_id":"stepfun/step-5-preview"},"stepfun/step-3.7-flash":{"id":"stepfun/step-3.7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":256000,"output":256000},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"nousresearch/hermes-2-pro-llama-3-8b":{"id":"nousresearch/hermes-2-pro-llama-3-8b","name":"Hermes 2 Pro Llama 3 8B","description":"Llama 3 fine-tune optimized for function calling, structured JSON responses, and dialogue","family":"hermes","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2024-04-30","last_updated":"2024-04-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0.14,"output":0.14},"canonical_model_id":"nousresearch/hermes-2-pro-llama-3-8b"},"gryphe/mythomax-l2-13b":{"id":"gryphe/mythomax-l2-13b","name":"MythoMax L2 13B","description":"Llama 2 merge combining MythoLogic and Huginn for creative writing and roleplay","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2023-08-10","last_updated":"2023-08-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":3200},"cost":{"input":0.09,"output":0.09},"canonical_model_id":"gryphe/mythomax-l2-13b"},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.14,"output":0.4},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemma-4-26b-a4b-it":{"id":"google/gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.13,"output":0.4},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemma-3-27b-it":{"id":"google/gemma-3-27b-it","name":"Gemma 3 27B IT","description":"Largest open Gemma 3 instruction model for multilingual text generation and visual understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":98304,"output":16384},"cost":{"input":0.119,"output":0.2},"canonical_model_id":"google/gemma-3-27b-it"},"google/gemma-3-12b-it":{"id":"google/gemma-3-12b-it","name":"Gemma 3 12B IT","description":"Open multimodal Gemma instruction model for multilingual text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.05,"output":0.1},"canonical_model_id":"google/gemma-3-12b-it"}}},"scnet-token-plan":{"id":"scnet-token-plan","env":["SCNET_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.scnet.cn/api/llm/v1","name":"SCNet Token Plan","doc":"https://www.scnet.cn/ac/openapi/doc/2.0/moduleapi/plans/token-plan.html","models":{"Kimi-K2.5":{"id":"Kimi-K2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"moonshotai/kimi-k2.5"},"MiniMax-M2.7":{"id":"MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"minimax/MiniMax-M2.7"},"Qwen3.8-Max":{"id":"Qwen3.8-Max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"alibaba/qwen3.8-max"},"Kimi-K2.7-Code":{"id":"Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"DeepSeek-V4.1-Flash":{"id":"DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"GLM-5":{"id":"GLM-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-5"},"Kimi-K2.6":{"id":"Kimi-K2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"moonshotai/kimi-k2.6"},"MiniMax-M2.5":{"id":"MiniMax-M2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"minimax/MiniMax-M2.5"},"Kimi-K3":{"id":"Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"moonshotai/kimi-k3"},"GLM-5.3-Flash":{"id":"GLM-5.3-Flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"DeepSeek-V4-Pro":{"id":"DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4-pro"},"DeepSeek-V4-Flash":{"id":"DeepSeek-V4-Flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4-flash"},"GLM-5.1":{"id":"GLM-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-5.1"},"MiniMax-M3":{"id":"MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"minimax/MiniMax-M3"},"DeepSeek-V4-Flash-0731":{"id":"DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"DeepSeek-V4-Pro-0813":{"id":"DeepSeek-V4-Pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"GLM-5.2":{"id":"GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-5.2"},"Qwen3.8-Flash":{"id":"Qwen3.8-Flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"alibaba/qwen3.8-flash"},"GLM-5.3":{"id":"GLM-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-5.3"}}},"lowrouter":{"id":"lowrouter","env":["LOWROUTER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.lowrouter.ai/v1","name":"LowRouter","doc":"https://lowrouter.ai/docs/models/available","models":{"auto/openai/gpt-6-sol":{"id":"auto/openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"auto/openai/gpt-6-luna":{"id":"auto/openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"auto/openai/gpt-oss-120b":{"id":"auto/openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.1695,"output":0.6779},"canonical_model_id":"openai/gpt-oss-120b"},"auto/openai/gpt-6.1-sol":{"id":"auto/openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"auto/openai/gpt-4.1":{"id":"auto/openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"auto/openai/gpt-4o":{"id":"auto/openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"auto/openai/gpt-5.6-luna":{"id":"auto/openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"auto/openai/gpt-5.4":{"id":"auto/openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"auto/openai/gpt-oss-safeguard-120b":{"id":"auto/openai/gpt-oss-safeguard-120b","name":"GPT OSS Safeguard 120B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.18,"output":0.73},"canonical_model_id":"openai/gpt-oss-safeguard-120b"},"auto/openai/gpt-5.4-mini":{"id":"auto/openai/gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"auto/openai/gpt-oss-safeguard-20b":{"id":"auto/openai/gpt-oss-safeguard-20b","name":"GPT OSS Safeguard 20B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.08,"output":0.24},"canonical_model_id":"openai/gpt-oss-safeguard-20b"},"auto/openai/gpt-5.6-sol":{"id":"auto/openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"auto/openai/gpt-4.1-mini":{"id":"auto/openai/gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"auto/openai/gpt-oss-20b":{"id":"auto/openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.113,"output":0.4745},"canonical_model_id":"openai/gpt-oss-20b"},"auto/openai/gpt-5-mini":{"id":"auto/openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"auto/openai/o3":{"id":"auto/openai/o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"auto/openai/gpt-5.6-terra":{"id":"auto/openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"auto/openai/gpt-5.5":{"id":"auto/openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"auto/openai/gpt-5":{"id":"auto/openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"auto/openai/gpt-5-nano":{"id":"auto/openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"auto/openai/gpt-4o-mini":{"id":"auto/openai/gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"auto/openai/gpt-5.2":{"id":"auto/openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"auto/openai/gpt-6-astra":{"id":"auto/openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"auto/mistralai/mistral-large-2512":{"id":"auto/mistralai/mistral-large-2512","name":"Mistral Large 3","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5229,"output":1.5688,"cache_read":0.0523},"canonical_model_id":"mistral/mistral-large-2512"},"auto/mistralai/ministral-8b-2512":{"id":"auto/mistralai/ministral-8b-2512","name":"Ministral 3 8B","description":"Compact open vision-language model for edge deployment, instruction following, and tool use","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.1569,"output":0.1569,"cache_read":0.0157},"canonical_model_id":"mistral/ministral-3-8b-instruct-2512"},"auto/mistralai/ministral-14b-2512":{"id":"auto/mistralai/ministral-14b-2512","name":"Ministral 3 14B","description":"Open vision-language model for efficient local deployment, instruction following, and tool use","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.2092,"output":0.2092,"cache_read":0.0209},"canonical_model_id":"mistral/ministral-3-14b-instruct-2512"},"auto/mistralai/ministral-3b-2512":{"id":"auto/mistralai/ministral-3b-2512","name":"Ministral 3 3B","description":"Compact open vision-language model for edge deployment, instruction following, and tool use","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.1046,"output":0.1046,"cache_read":0.0105},"canonical_model_id":"mistral/ministral-3-3b-instruct-2512"},"auto/mistralai/mistral-small-2603":{"id":"auto/mistralai/mistral-small-2603","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.1569,"output":0.6275,"cache_read":0.0157},"canonical_model_id":"mistral/mistral-small-2603"},"auto/mistralai/mistral-medium-3.5":{"id":"auto/mistralai/mistral-medium-3.5","name":"Mistral Medium 3.5","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.5688,"output":7.8442,"cache_read":0.1569},"canonical_model_id":"mistral/mistral-medium-2604"},"auto/mistralai/mistral-large-4":{"id":"auto/mistralai/mistral-large-4","name":"Mistral Large 4","description":"Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":262144},"status":"beta","cost":{"input":1.4367,"output":4.4156,"cache_read":0.1479},"canonical_model_id":"mistral/mistral-large-4"},"auto/mistralai/codestral-2508":{"id":"auto/mistralai/codestral-2508","name":"Codestral 25.08","description":"Mistral code model for low-latency completion, fill-in-the-middle, and code generation","family":"codestral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.3138,"output":0.9413,"cache_read":0.0314},"canonical_model_id":"mistral/codestral-2508"}}},"hpc-ai":{"id":"hpc-ai","env":["HPC_AI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.hpc-ai.com/inference/v1","name":"HPC-AI","doc":"https://www.hpc-ai.com/doc/docs/quickstart/","models":{"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-7"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"zai-org/glm-5.2":{"id":"zai-org/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/glm-5.1":{"id":"zai-org/glm-5.1","name":"GLM 5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202000,"output":202000},"cost":{"input":0.615,"output":2.46,"cache_read":0.133},"canonical_model_id":"zhipuai/glm-5.1"},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196000,"output":195000},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5"},"moonshotai/kimi-k2.5":{"id":"moonshotai/kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.6,"output":3,"cache_read":0.1},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":128000},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1002000,"output":128000},"cost":{"input":1.74,"output":3.48,"cache_read":0.145},"canonical_model_id":"deepseek/deepseek-v4-pro"}}},"infer":{"id":"infer","env":["INFER_API_KEY"],"npm":"@ai-sdk/openai","api":"https://infer.flow7.org/v1","name":"Infer by Flow7","doc":"https://infer.flow7.org/opencode","models":{"infer/gpt-5.6-sol:official":{"id":"infer/gpt-5.6-sol:official","name":"GPT-5.6 Sol (Official API)","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":271999,"output":128000},"provider":{"shape":"responses"},"cost":{"input":2.5,"output":12.5,"cache_read":0.25,"cache_write":3.125},"canonical_model_id":"openai/gpt-5.6-sol"},"infer/gpt-6-astra:official":{"id":"infer/gpt-6-astra:official","name":"GPT-6 Astra (Official API)","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":271999,"output":128000},"provider":{"shape":"responses"},"cost":{"input":12.5,"output":62.5,"cache_read":1.25,"cache_write":15.625},"canonical_model_id":"openai/gpt-6-astra"}}},"kuae-cloud-coding-plan":{"id":"kuae-cloud-coding-plan","env":["KUAE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://coding-plan-endpoint.kuaecloud.net/v1","name":"KUAE Cloud Coding Plan","doc":"https://docs.mthreads.com/kuaecloud/kuaecloud-doc-online/coding_plan/","models":{"GLM-4.7":{"id":"GLM-4.7","name":"GLM-4.7","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7"}}},"wandb":{"id":"wandb","env":["WANDB_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.inference.wandb.ai/v1","name":"CoreWeave","doc":"https://docs.wandb.ai/inference","models":{"Qwen/Qwen3.8-27B":{"id":"Qwen/Qwen3.8-27B","name":"Qwen3.8 27B","description":"Qwen3.8-27B is a dense multimodal model suited for coding, research, vision, and long-running agent tasks.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.4,"output":3,"cache_read":0.15},"canonical_model_id":"alibaba/qwen3.8-27b"},"Qwen/Qwen3.6-35B-A3B":{"id":"Qwen/Qwen3.6-35B-A3B","name":"Qwen3.6 35B A3B","description":"Qwen3.6-35B-A3B is an MoE multimodal model with 262K context optimized for agentic coding workflows.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.25,"output":1.25,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"reflection/Beam-1.0-501B-A23B":{"id":"reflection/Beam-1.0-501B-A23B","name":"Beam 1.0 501B A23B","description":"Beam is a 501B-parameter MoE model with 23B active parameters built for coding, reasoning, and agentic workflows.","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-06-30","release_date":"2026-10-05","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.3,"output":1,"cache_read":0.04},"canonical_model_id":"reflection/beam-1.0-501b-a23b"},"ibm-granite/granite-4.2-8b":{"id":"ibm-granite/granite-4.2-8b","name":"Granite 4.2 8B","description":"Granite 4.2 8B is an instruct model capable of enhanced tool calling, instruction following, and chat capabilities.","family":"granite","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-25","last_updated":"2026-08-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.1,"output":0.15,"cache_read":0.05},"canonical_model_id":"ibm/granite-4.2-8b"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"gpt-oss-120b","description":"Efficient Mixture-of-Experts model designed for high-reasoning, agentic and general-purpose use cases.","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.03,"output":0.17,"cache_read":0.03},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"gpt-oss-20b","description":"Lower latency Mixture-of-Experts model trained on OpenAI's Harmony response format with reasoning capabilities.","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.03,"output":0.13,"cache_read":0.03},"canonical_model_id":"openai/gpt-oss-20b"},"zai-org/GLM-5.3-Flash":{"id":"zai-org/GLM-5.3-Flash","name":"GLM 5.3 Flash","description":"GLM-5.3-Flash is a natively multimodal model with 320B total parameters and 18B active parameters.","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.15,"output":0.5,"cache_read":0.02},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM 5.2","description":"GLM-5.2 is a Mixture-of-Experts language model featuring 40 billion activated parameters and a total of 744 billion parameters.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.62,"output":2.42,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-5.3":{"id":"zai-org/GLM-5.3","name":"GLM 5.3","description":"GLM-5.3 is a 744B-parameter MoE model built for advanced reasoning, software engineering, and long-horizon agentic tasks.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.2,"output":4,"cache_read":0.19},"canonical_model_id":"zhipuai/glm-5.3"},"moonshotai/Kimi-K2.7-Code":{"id":"moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Kimi K2.7 Code is a 1T-parameter MoE model with 32B active parameters purpose-built for long-horizon agentic coding and software engineering.","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.71,"output":3.5,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi K2.6","description":"Kimi K2.6 is a multimodal Mixture-of-Experts language model featuring 32 billion activated parameters and a total of 1 trillion parameters.","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.65,"output":3.41,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2.6"},"nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B":{"id":"nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B","name":"Nemotron 3 Ultra","description":"Nemotron 3 Ultra is a powerful MoE model designed for long-running agents across coding, deep research, and enterprise automation.","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.5,"output":2.15,"cache_read":0.1},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B":{"id":"nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B","name":"Nemotron 3.5 Super VL","description":"Nemotron 3.5 Super VL is a multimodal MoE model built for visual understanding, reasoning, and agentic workflows.","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.15,"output":0.5,"cache_read":0.02},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B":{"id":"nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B","name":"Nemotron 3.5 Lightning","description":"Nemotron 3.5 Lightning is an MoE model built for fast, reliable agentic tasks across use cases such as financial services, cybersecurity, telecom, and retail.","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.07,"output":0.2,"cache_read":0.04},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"meta-llama/Llama-3.3-70B-Instruct":{"id":"meta-llama/Llama-3.3-70B-Instruct","name":"Llama 3.3 70B","description":"Multilingual model excelling in conversational tasks, detailed instruction-following, and coding.","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0.71,"output":0.71,"cache_read":0.71},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"meta-llama/Llama-3.1-8B-Instruct":{"id":"meta-llama/Llama-3.1-8B-Instruct","name":"Llama 3.1 8B","description":"Efficient conversational model optimized for responsive multilingual chatbot interactions.","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.22,"output":0.22,"cache_read":0.22},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"MiniMaxAI/MiniMax-M3":{"id":"MiniMaxAI/MiniMax-M3","name":"MiniMax M3","description":"MiniMax M3 is a multimodal MoE model with 23B active parameters optimized for coding and agentic workflows.","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.23,"output":0.96,"cache_read":0.05},"canonical_model_id":"minimax/MiniMax-M3"},"deepseek-ai/DeepSeek-V4.1-Flash":{"id":"deepseek-ai/DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash is a multimodal MoE model for coding, reasoning, and agentic workloads with long contexts.","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.15,"output":0.65,"cache_read":0.002},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek-ai/DeepSeek-V4-Flash-0731":{"id":"deepseek-ai/DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731","description":"DeepSeek V4-Flash-0731 is an MoE model great for coding, reasoning, and agentic workloads.","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.13,"output":0.28,"cache_read":0.07},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek-ai/DeepSeek-V4-Pro-0813":{"id":"deepseek-ai/DeepSeek-V4-Pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4-Pro-0813 is a 1.6T-parameter MoE model excelling at advanced reasoning, coding, and complex agentic workloads.","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.31,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek-ai/DeepSeek-V3.1":{"id":"deepseek-ai/DeepSeek-V3.1","name":"DeepSeek V3.1","description":"A large hybrid model that supports both thinking and non-thinking modes via prompt templates.","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":161000,"output":161000},"cost":{"input":0.55,"output":1.65,"cache_read":0.55},"canonical_model_id":"deepseek/deepseek-v3.1"},"google/gemma-4-31B-it":{"id":"google/gemma-4-31B-it","name":"Gemma 4 31B","description":"Gemma 4 31B Dense is designed for advanced reasoning, agentic workflows, and longer context and is natively trained on 140+ languages.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.1,"output":0.34,"cache_read":0.1},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemma-4-26B-A4B-it":{"id":"google/gemma-4-26B-A4B-it","name":"Gemma 4 26B A4B","description":"Gemma 4 26B A4B is a multimodal MoE model with LoRA support and function calling for agentic workflows.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.1,"output":0.3,"cache_read":0.05},"canonical_model_id":"google/gemma-4-26b-a4b-it"}}},"huggingface":{"id":"huggingface","env":["HF_TOKEN"],"npm":"@ai-sdk/openai-compatible","api":"https://router.huggingface.co/v1","name":"Hugging Face","doc":"https://huggingface.co/docs/inference-providers","models":{"thinkingmachines/Inkling":{"id":"thinkingmachines/Inkling","name":"Inkling","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1,"output":4.05},"canonical_model_id":"thinkingmachines/inkling"},"thinkingmachines/Inkling-Small":{"id":"thinkingmachines/Inkling-Small","name":"Inkling Small","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":1048576},"cost":{"input":0.5,"output":1.2},"canonical_model_id":"thinkingmachines/inkling-small"},"Qwen/Qwen3-8B":{"id":"Qwen/Qwen3-8B","name":"Qwen3 8B","description":"Dense 8B Qwen3 model with switchable thinking for chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-29","last_updated":"2025-04-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":32768},"cost":{"input":0.07,"output":0.18},"canonical_model_id":"alibaba/qwen3-8b"},"Qwen/Qwen3-Next-80B-A3B-Thinking":{"id":"Qwen/Qwen3-Next-80B-A3B-Thinking","name":"Qwen3-Next-80B-A3B-Thinking","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"status":"deprecated","cost":{"input":0.3,"output":2},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-thinking"},"Qwen/Qwen3.5-122B-A10B":{"id":"Qwen/Qwen3.5-122B-A10B","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.4,"output":3.2},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"Qwen/Qwen3.5-397B-A17B":{"id":"Qwen/Qwen3.5-397B-A17B","name":"Qwen3.5-397B-A17B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.6,"output":3.6},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"Qwen/Qwen3-235B-A22B-Thinking-2507":{"id":"Qwen/Qwen3-235B-A22B-Thinking-2507","name":"Qwen3-235B-A22B-Thinking-2507","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-25","last_updated":"2025-07-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":81920},"cost":{"input":0.3,"output":3},"canonical_model_id":"alibaba/qwen3-235b-a22b-thinking-2507"},"Qwen/Qwen3-VL-235B-A22B-Thinking":{"id":"Qwen/Qwen3-VL-235B-A22B-Thinking","name":"Qwen3 VL 235B A22B Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.98,"output":3.95},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-thinking"},"Qwen/Qwen3.5-27B":{"id":"Qwen/Qwen3.5-27B","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.3,"output":2.4},"canonical_model_id":"alibaba/qwen3.5-27b"},"Qwen/Qwen3.5-35B-A3B":{"id":"Qwen/Qwen3.5-35B-A3B","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.25,"output":2},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"Qwen/Qwen3-32B":{"id":"Qwen/Qwen3-32B","name":"Qwen3 32B","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.29,"output":0.59},"canonical_model_id":"alibaba/qwen3-32b"},"Qwen/Qwen3-235B-A22B":{"id":"Qwen/Qwen3-235B-A22B","name":"Qwen3 235B-A22B","description":"Large open Qwen MoE for multilingual reasoning, coding, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":16384},"cost":{"input":0.2,"output":0.8},"canonical_model_id":"alibaba/qwen3-235b-a22b"},"Qwen/Qwen3-30B-A3B":{"id":"Qwen/Qwen3-30B-A3B","name":"Qwen3 30B A3B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":16384},"cost":{"input":0.12,"output":0.5},"canonical_model_id":"alibaba/qwen3-30b-a3b"},"Qwen/Qwen3.5-9B":{"id":"Qwen/Qwen3.5-9B","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.17,"output":0.25},"canonical_model_id":"alibaba/qwen3.5-9b"},"Qwen/Qwen2.5-Coder-32B-Instruct":{"id":"Qwen/Qwen2.5-Coder-32B-Instruct","name":"Qwen2.5-Coder-32B-Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-11-12","last_updated":"2024-11-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.06,"output":0.2},"canonical_model_id":"alibaba/qwen2.5-coder-32b-instruct"},"Qwen/Qwen3-VL-235B-A22B-Instruct":{"id":"Qwen/Qwen3-VL-235B-A22B-Instruct","name":"Qwen3 VL 235B A22B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.3,"output":1.5},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"Qwen/Qwen3.8-27B":{"id":"Qwen/Qwen3.8-27B","name":"Qwen3.8 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.4,"output":3},"canonical_model_id":"alibaba/qwen3.8-27b"},"Qwen/Qwen3-Next-80B-A3B-Instruct":{"id":"Qwen/Qwen3-Next-80B-A3B-Instruct","name":"Qwen3-Next-80B-A3B-Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.25,"output":1},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"Qwen/Qwen3-Coder-480B-A35B-Instruct":{"id":"Qwen/Qwen3-Coder-480B-A35B-Instruct","name":"Qwen3-Coder-480B-A35B-Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":2,"output":2},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"Qwen/Qwen3-VL-30B-A3B-Instruct":{"id":"Qwen/Qwen3-VL-30B-A3B-Instruct","name":"Qwen3 VL 30B A3B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-04","last_updated":"2025-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.2,"output":0.7},"canonical_model_id":"alibaba/qwen3-vl-30b-a3b-instruct"},"Qwen/Qwen3-Embedding-4B":{"id":"Qwen/Qwen3-Embedding-4B","type":"embedding","name":"Qwen 3 Embedding 4B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2024-12","release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":0},"cost":{"input":0.01,"output":0},"canonical_model_id":"alibaba/qwen3-embedding-4b"},"Qwen/Qwen3.6-27B":{"id":"Qwen/Qwen3.6-27B","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.47,"output":3.19},"canonical_model_id":"alibaba/qwen3.6-27b"},"Qwen/Qwen3-235B-A22B-Instruct-2507":{"id":"Qwen/Qwen3-235B-A22B-Instruct-2507","name":"Qwen3 235B-A22B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.855,"output":2.565},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"Qwen/Qwen3-Coder-30B-A3B-Instruct":{"id":"Qwen/Qwen3-Coder-30B-A3B-Instruct","name":"Qwen3-Coder 30B-A3B Instruct","description":"Smaller Qwen coder for efficient local agents and repo-level fixes","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-31","last_updated":"2025-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.07,"output":0.26},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"Qwen/Qwen3.8-2.4T-A95B":{"id":"Qwen/Qwen3.8-2.4T-A95B","name":"Qwen3.8 2.4T A95B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":2.5,"output":6.25},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"Qwen/Qwen3-Coder-Next":{"id":"Qwen/Qwen3-Coder-Next","name":"Qwen3-Coder-Next","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.2,"output":1.5},"canonical_model_id":"alibaba/qwen3-coder-next"},"Qwen/Qwen3-Embedding-8B":{"id":"Qwen/Qwen3-Embedding-8B","type":"embedding","name":"Qwen 3 Embedding 8B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2024-12","release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":0},"cost":{"input":0.01,"output":0},"canonical_model_id":"alibaba/qwen3-embedding-8b"},"Qwen/Qwen3.6-35B-A3B":{"id":"Qwen/Qwen3.6-35B-A3B","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.15,"output":0.95},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.25,"output":0.69},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.1,"output":0.5},"canonical_model_id":"openai/gpt-oss-20b"},"stepfun-ai/Step-3.5-Flash":{"id":"stepfun-ai/Step-3.5-Flash","name":"Step 3.5 Flash","description":"StepFun flash lane for quick multimodal reasoning and coding assistance","family":"step","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"stepfun/step-3.5-flash"},"stepfun-ai/Step-3.7-Flash":{"id":"stepfun-ai/Step-3.7-Flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.2,"output":1.15},"canonical_model_id":"stepfun/step-3.7-flash"},"zai-org/GLM-4.6V-Flash":{"id":"zai-org/GLM-4.6V-Flash","name":"GLM-4.6V-Flash","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.3,"output":0.9},"canonical_model_id":"zhipuai/glm-4.6v-flash"},"zai-org/GLM-4.7":{"id":"zai-org/GLM-4.7","name":"GLM-4.7","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.7"},"zai-org/GLM-5":{"id":"zai-org/GLM-5","name":"GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"zai-org/GLM-4.7-Flash":{"id":"zai-org/GLM-4.7-Flash","name":"GLM-4.7-Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-4.7-flash"},"zai-org/GLM-5.3-Flash":{"id":"zai-org/GLM-5.3-Flash","name":"GLM-5.3-Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/GLM-4.5":{"id":"zai-org/GLM-4.5","name":"GLM-4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"status":"deprecated","cost":{"input":0.6,"output":2.2},"canonical_model_id":"zhipuai/glm-4.5"},"zai-org/GLM-5.1":{"id":"zai-org/GLM-5.1","name":"GLM-5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5.1"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":1.4,"output":4.4},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-4.5V":{"id":"zai-org/GLM-4.5V","name":"GLM-4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":16384},"cost":{"input":0.6,"output":1.8},"canonical_model_id":"zhipuai/glm-4.5v"},"zai-org/GLM-4.6":{"id":"zai-org/GLM-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.55,"output":2.2},"canonical_model_id":"zhipuai/glm-4.6"},"zai-org/AutoGLM-Phone-9B-Multilingual":{"id":"zai-org/AutoGLM-Phone-9B-Multilingual","name":"AutoGLM Phone 9B Multilingual","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-12-10","last_updated":"2025-12-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.035,"output":0.138},"canonical_model_id":"zhipuai/autoglm-phone-9b-multilingual"},"zai-org/GLM-4.5-Air":{"id":"zai-org/GLM-4.5-Air","name":"GLM-4.5-Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.13,"output":0.85},"canonical_model_id":"zhipuai/glm-4.5-air"},"zai-org/GLM-5.3":{"id":"zai-org/GLM-5.3","name":"GLM-5.3","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4},"canonical_model_id":"zhipuai/glm-5.3"},"XiaomiMiMo/MiMo-V2.5-Pro":{"id":"XiaomiMiMo/MiMo-V2.5-Pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1,"output":3},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"XiaomiMiMo/MiMo-V2.5":{"id":"XiaomiMiMo/MiMo-V2.5","name":"MiMo-V2.5","description":"MiMo model for long-context reasoning, perception, and agentic tasks","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.4,"output":2},"canonical_model_id":"xiaomi/mimo-v2.5"},"XiaomiMiMo/MiMo-V2-Flash":{"id":"XiaomiMiMo/MiMo-V2-Flash","name":"MiMo-V2-Flash","description":"MiMo flash model for fast multimodal assistance and agent workflows","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12-01","release_date":"2025-12-16","last_updated":"2026-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":4096},"status":"deprecated","cost":{"input":0.1,"output":0.3},"canonical_model_id":"xiaomi/mimo-v2-flash"},"moonshotai/Kimi-K2-Instruct":{"id":"moonshotai/Kimi-K2-Instruct","name":"Kimi-K2-Instruct","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":1,"output":3},"canonical_model_id":"moonshotai/kimi-k2-instruct"},"moonshotai/Kimi-K2.5":{"id":"moonshotai/Kimi-K2.5","name":"Kimi-K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":3,"cache_read":0.1},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/Kimi-K2-Instruct-0905":{"id":"moonshotai/Kimi-K2-Instruct-0905","name":"Kimi-K2-Instruct-0905","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":1,"output":3},"canonical_model_id":"moonshotai/kimi-k2-0905"},"moonshotai/Kimi-K2.7-Code":{"id":"moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi-K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/Kimi-K3":{"id":"moonshotai/Kimi-K3","name":"Kimi K3","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":3,"output":15},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/Kimi-K2-Thinking":{"id":"moonshotai/Kimi-K2-Thinking","name":"Kimi-K2-Thinking","description":"Kimi reasoning model for long-horizon research, planning, and tool use","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.6,"output":2.5,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"meta-llama/Llama-Guard-4-12B":{"id":"meta-llama/Llama-Guard-4-12B","name":"Llama Guard 4 12B","description":"Multimodal Llama 4-based safety classifier for moderating prompts and responses","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-04-29","last_updated":"2025-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":163840},"cost":{"input":0.18,"output":0.18},"canonical_model_id":"meta/llama-guard-4-12b"},"meta-llama/Llama-3.3-70B-Instruct":{"id":"meta-llama/Llama-3.3-70B-Instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":4096},"cost":{"input":0.59,"output":0.79},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"meta-llama/Llama-3.1-8B-Instruct":{"id":"meta-llama/Llama-3.1-8B-Instruct","name":"Llama-3.1-8B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":4096},"cost":{"input":0.06,"output":0.06},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"tencent/Hy3":{"id":"tencent/Hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":192000,"output":128000},"cost":{"input":0.14,"output":0.58},"canonical_model_id":"tencent/hy3"},"tencent/Hy4-preview":{"id":"tencent/Hy4-preview","name":"Hy4 preview","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":64000},"cost":{"input":0.834,"output":2.501},"canonical_model_id":"tencent/hy4-preview"},"MiniMaxAI/MiniMax-M1-80k":{"id":"MiniMaxAI/MiniMax-M1-80k","name":"MiniMax M1 80K","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":80000},"cost":{"input":0.55,"output":2.2},"canonical_model_id":"minimax/minimax-m1-80k"},"MiniMaxAI/MiniMax-M2.7":{"id":"MiniMaxAI/MiniMax-M2.7","name":"MiniMax-M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7"},"MiniMaxAI/MiniMax-M2.5":{"id":"MiniMaxAI/MiniMax-M2.5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5"},"MiniMaxAI/MiniMax-M3":{"id":"MiniMaxAI/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":512000},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M3"},"MiniMaxAI/MiniMax-M2.1":{"id":"MiniMaxAI/MiniMax-M2.1","name":"MiniMax-M2.1","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-10","release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2.1"},"MiniMaxAI/MiniMax-M2":{"id":"MiniMaxAI/MiniMax-M2","name":"MiniMax-M2","description":"Efficient open MiniMax model built for coding agents and tool-heavy workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2"},"deepseek-ai/DeepSeek-R1-0528":{"id":"deepseek-ai/DeepSeek-R1-0528","name":"DeepSeek-R1-0528","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":32768},"cost":{"input":3,"output":5},"canonical_model_id":"deepseek/deepseek-r1-0528"},"deepseek-ai/DeepSeek-V4.1-Flash":{"id":"deepseek-ai/DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek-ai/DeepSeek-R1":{"id":"deepseek-ai/DeepSeek-R1","name":"DeepSeek-R1","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":32768},"cost":{"input":0.7,"output":2.5},"canonical_model_id":"deepseek/deepseek-r1"},"deepseek-ai/DeepSeek-V4-Flash-Vision-Exp":{"id":"deepseek-ai/DeepSeek-V4-Flash-Vision-Exp","name":"DeepSeek V4 Flash Vision Exp","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.44,"output":1.32},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"deepseek-ai/DeepSeek-V4-Pro":{"id":"deepseek-ai/DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.435,"output":0.87,"cache_read":0.003625},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek-ai/DeepSeek-V4.1-Flash-1017":{"id":"deepseek-ai/DeepSeek-V4.1-Flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek-ai/DeepSeek-V3.2":{"id":"deepseek-ai/DeepSeek-V3.2","name":"DeepSeek-V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":65536},"cost":{"input":0.28,"output":0.4},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepseek-ai/DeepSeek-V4-Flash":{"id":"deepseek-ai/DeepSeek-V4-Flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.14,"output":0.28},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek-ai/DeepSeek-V4-Flash-0731":{"id":"deepseek-ai/DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.14,"output":0.28},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek-ai/DeepSeek-V3-0324":{"id":"deepseek-ai/DeepSeek-V3-0324","name":"DeepSeek V3 0324","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-03-24","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":163840},"cost":{"input":0.27,"output":1.12},"canonical_model_id":"deepseek/deepseek-v3-0324"},"deepseek-ai/DeepSeek-V4-Pro-0813":{"id":"deepseek-ai/DeepSeek-V4-Pro-0813","name":"DeepSeek V4 Pro 0813","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.32,"output":3.96},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek-ai/DeepSeek-V3":{"id":"deepseek-ai/DeepSeek-V3","name":"DeepSeek-V3","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-12-26","last_updated":"2024-12-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":8192},"cost":{"input":0.4,"output":1.3},"canonical_model_id":"deepseek/deepseek-v3"},"deepseek-ai/DeepSeek-V3.1":{"id":"deepseek-ai/DeepSeek-V3.1","name":"DeepSeek-V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.27,"output":1},"canonical_model_id":"deepseek/deepseek-v3.1"},"google/gemma-4-31B-it":{"id":"google/gemma-4-31B-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.14,"output":0.4},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemma-3-4b-it":{"id":"google/gemma-3-4b-it","name":"Gemma 3 4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.05,"output":0.1},"canonical_model_id":"google/gemma-3-4b-it"},"google/gemma-3-27b-it":{"id":"google/gemma-3-27b-it","name":"Gemma 3 27B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.08,"output":0.16},"canonical_model_id":"google/gemma-3-27b-it"},"google/gemma-3-12b-it":{"id":"google/gemma-3-12b-it","name":"Gemma 3 12B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.05,"output":0.15},"canonical_model_id":"google/gemma-3-12b-it"},"google/gemma-4-26B-A4B-it":{"id":"google/gemma-4-26B-A4B-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.13,"output":0.4},"canonical_model_id":"google/gemma-4-26b-a4b-it"}}},"impossibl":{"id":"impossibl","env":["IMPOSSIBL_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.impossibl.com/v1","name":"Impossibl","doc":"https://impossibl.com/docs/models","models":{"thinkingmachines/inkling":{"id":"thinkingmachines/inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":1.87,"output":4.68,"cache_read":0.374},"canonical_model_id":"thinkingmachines/inkling"},"xiaomi/mimo-v2.5":{"id":"xiaomi/mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.003},"canonical_model_id":"xiaomi/mimo-v2.5"},"xai/grok-build-0.1":{"id":"xai/grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.2,"tiers":[{"input":2,"output":4,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2,"output":4,"cache_read":0.4}},"canonical_model_id":"xai/grok-build-0.1"},"xai/grok-4.3":{"id":"xai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.3"},"xai/grok-4.20-0309-non-reasoning":{"id":"xai/grok-4.20-0309-non-reasoning","name":"Grok 4.20 (Non-Reasoning)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-non-reasoning"},"xai/grok-4.5":{"id":"xai/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.3,"tiers":[{"input":4,"output":12,"cache_read":0.6,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":0.6}},"canonical_model_id":"xai/grok-4.5"},"xai/grok-4.20-0309-reasoning":{"id":"xai/grok-4.20-0309-reasoning","name":"Grok 4.20 (Reasoning)","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":30000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-reasoning"},"anthropic/claude-sonnet-4-5":{"id":"anthropic/claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-opus-4-7":{"id":"anthropic/claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic/claude-opus-4-6":{"id":"anthropic/claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-haiku-4-5":{"id":"anthropic/claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-opus-4-8":{"id":"anthropic/claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-sonnet-4-6":{"id":"anthropic/claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-4-5":{"id":"anthropic/claude-opus-4-5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-5-codex":{"id":"openai/gpt-5-codex","name":"GPT-5-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5-codex"},"openai/gpt-5-pro":{"id":"openai/gpt-5-pro","name":"GPT-5 Pro","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":272000},"cost":{"input":15,"output":120},"canonical_model_id":"openai/gpt-5-pro"},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"cache_read":3,"tiers":[{"input":60,"output":270,"cache_read":3,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270,"cache_read":3}},"canonical_model_id":"openai/gpt-5.4-pro"},"openai/o1":{"id":"openai/o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":15,"output":60,"cache_read":7.5},"canonical_model_id":"openai/o1"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-5.2-codex":{"id":"openai/gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Code-specialist GPT for repository edits, reviews, and long-running software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-codex"},"openai/gpt-5.5-pro":{"id":"openai/gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"cache_read":3,"tiers":[{"input":60,"output":270,"cache_read":3,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270,"cache_read":3}},"canonical_model_id":"openai/gpt-5.5-pro"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5.1-codex":{"id":"openai/gpt-5.1-codex","name":"GPT-5.1 Codex","description":"Codex GPT for repository edits, code review, and practical software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-4-turbo":{"id":"openai/gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":10,"output":30},"canonical_model_id":"openai/gpt-4-turbo"},"openai/o3":{"id":"openai/o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"openai/gpt-3.5-turbo":{"id":"openai/gpt-3.5-turbo","name":"GPT-3.5-turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"output":4096},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"openai/gpt-3.5-turbo"},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"openai/gpt-5.1-codex-mini":{"id":"openai/gpt-5.1-codex-mini","name":"GPT-5.1 Codex mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5.1-codex-mini"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"openai/o4-mini":{"id":"openai/o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.275},"canonical_model_id":"openai/o4-mini"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"zai/glm-5-turbo":{"id":"zai/glm-5-turbo","name":"GLM-5-Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5-turbo"},"zai/glm-4.7":{"id":"zai/glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.7"},"zai/glm-5.2":{"id":"zai/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"zai/glm-5":{"id":"zai/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"zai/glm-4.5-air":{"id":"zai/glm-4.5-air","name":"GLM-4.5-Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.2,"output":1.1,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-4.5-air"},"zai/glm-5.1":{"id":"zai/glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"zai/glm-4.6":{"id":"zai/glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.6"},"zai/glm-4.5":{"id":"zai/glm-4.5","name":"GLM-4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5"},"groq/gpt-oss-120b":{"id":"groq/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"status":"deprecated","cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-oss-120b"},"groq/gpt-oss-20b":{"id":"groq/gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"status":"deprecated","cost":{"input":0.075,"output":0.3,"cache_read":0.0375},"canonical_model_id":"openai/gpt-oss-20b"},"cerebras/gpt-oss-120b":{"id":"cerebras/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"status":"deprecated","cost":{"input":0.35,"output":0.75},"canonical_model_id":"openai/gpt-oss-120b"},"qwen/qwen3.8-max-preview":{"id":"qwen/qwen3.8-max-preview","name":"Qwen3.8 Max Preview","description":"Preview Qwen flagship for million-token multimodal reasoning and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-19","last_updated":"2026-07-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":2.5,"output":7.5},"canonical_model_id":"alibaba/qwen3.8-max-preview"},"qwen/qwen3.6-flash":{"id":"qwen/qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.05,"tiers":[{"input":1,"output":4,"cache_read":0.2,"tier":{"type":"context","size":262144}}],"context_over_200k":{"input":1,"output":4,"cache_read":0.2}},"canonical_model_id":"alibaba/qwen3.6-flash"},"qwen/qwen3.7-plus":{"id":"qwen/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.4,"output":1.6,"cache_read":0.08,"tiers":[{"input":1.2,"output":4.8,"cache_read":0.24,"tier":{"type":"context","size":262144}}],"context_over_200k":{"input":1.2,"output":4.8,"cache_read":0.24}},"canonical_model_id":"alibaba/qwen3.7-plus"},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2.5,"output":7.5,"cache_read":0.5},"canonical_model_id":"alibaba/qwen3.7-max"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.19,"output":0.51,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.74,"output":3.48,"cache_read":0.145},"canonical_model_id":"deepseek/deepseek-v4-pro"},"fireworks/gpt-oss-120b":{"id":"fireworks/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"status":"deprecated","cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"openai/gpt-oss-120b"},"fireworks/glm-5.2":{"id":"fireworks/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":1.4,"output":4.4,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.2"},"fireworks/gpt-oss-20b":{"id":"fireworks/gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"status":"deprecated","cost":{"input":0.07,"output":0.3,"cache_read":0.035},"canonical_model_id":"openai/gpt-oss-20b"},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":512,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"input_audio":0.3},"canonical_model_id":"google/gemini-2.5-flash-lite"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"input_audio":1},"canonical_model_id":"google/gemini-2.5-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.6-flash"}}},"google-vertex":{"id":"google-vertex","env":["GOOGLE_VERTEX_PROJECT","GOOGLE_VERTEX_LOCATION","GOOGLE_APPLICATION_CREDENTIALS"],"npm":"@ai-sdk/google-vertex","name":"Vertex","doc":"https://cloud.google.com/vertex-ai/generative-ai/docs/models","models":{"claude-sonnet-4-5@20250929":{"id":"claude-sonnet-4-5@20250929","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"claude-opus-4-1@20250805":{"id":"claude-opus-4-1@20250805","name":"Claude Opus 4.1","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1-20250805"},"gemini-2.5-flash-lite":{"id":"gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":512,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":0.1,"output":0.4,"cache_read":0.01,"input_audio":0.3},"canonical_model_id":"google/gemini-2.5-flash-lite"},"gemini-3.7-flash":{"id":"gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"input_audio":0.75},"canonical_model_id":"google/gemini-3.7-flash"},"gemini-3-pro-image":{"id":"gemini-3-pro-image","type":"image","name":"Nano Banana Pro","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":2,"output":120,"cache_read":0.2},"canonical_model_id":"google/gemini-3-pro-image"},"claude-fable-5-1@default":{"id":"claude-fable-5-1@default","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"claude-opus-4-8@default":{"id":"claude-opus-4-8@default","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"gemini-2.5-pro-tts":{"id":"gemini-2.5-pro-tts","type":"speech","name":"Gemini 2.5 Pro TTS","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gemini-pro","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-01","release_date":"2025-09-30","last_updated":"2025-12-10","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":32768,"input":8192,"output":16384},"cost":{"input":1,"output":20},"canonical_model_id":"google/gemini-2.5-pro-tts"},"gemini-3.1-flash-image":{"id":"gemini-3.1-flash-image","type":"image","name":"Nano Banana 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","video","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":60,"cache_read":0.05},"canonical_model_id":"google/gemini-3.1-flash-image"},"mistral-small-2503":{"id":"mistral-small-2503","name":"Mistral Small 3.1 24B","description":"Efficient multimodal model for instruction following, coding, reasoning, and function calling","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-03-17","last_updated":"2025-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"provider":{"npm":"@ai-sdk/mistral","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/publishers/mistralai/models"},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"mistral/mistral-small-3-1-24b-instruct-2503"},"gemini-2.5-flash-tts":{"id":"gemini-2.5-flash-tts","type":"speech","name":"Gemini 2.5 Flash TTS","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gemini-flash","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-01","release_date":"2025-09-30","last_updated":"2025-12-10","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":32768,"input":8192,"output":16384},"cost":{"input":0.5,"output":10},"canonical_model_id":"google/gemini-2.5-flash-tts"},"gemini-3-flash-preview":{"id":"gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"beta","cost":{"input":0.5,"output":3,"cache_read":0.05,"input_audio":1},"canonical_model_id":"google/gemini-3-flash-preview"},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":0.3,"output":2.5,"cache_read":0.03,"input_audio":1}},"claude-opus-4@20250514":{"id":"claude-opus-4@20250514","name":"Claude Opus 4","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-20250514"},"claude-haiku-5-5@default":{"id":"claude-haiku-5-5@default","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"claude-opus-5-5@default":{"id":"claude-opus-5-5@default","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"gemini-2.5-pro":{"id":"gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":1.25,"output":10,"cache_read":0.125,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro"},"gemini-2.5-flash-image":{"id":"gemini-2.5-flash-image","type":"image","name":"Nano Banana","description":"Nano Banana image model for fast generation, edits, and character-consistent assets","family":"gemini-flash","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.3,"output":30},"canonical_model_id":"google/gemini-2.5-flash-image"},"claude-sonnet-4-6@default":{"id":"claude-sonnet-4-6@default","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"gemini-4-argon":{"id":"gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":10,"cache_read":0.1,"input_audio":2},"canonical_model_id":"google/gemini-4-argon"},"gemini-3.5-flash-lite":{"id":"gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"claude-opus-4-6@default":{"id":"claude-opus-4-6@default","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"claude-haiku-4-5@20251001":{"id":"claude-haiku-4-5@20251001","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"claude-sonnet-4@20250514":{"id":"claude-sonnet-4@20250514","name":"Claude Sonnet 4","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-20250514"},"claude-sonnet-5-5@default":{"id":"claude-sonnet-5-5@default","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"mistral-medium-3":{"id":"mistral-medium-3","name":"Mistral Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":131072},"provider":{"npm":"@ai-sdk/mistral","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/publishers/mistralai/models"},"cost":{"input":0.4,"output":2},"canonical_model_id":"mistral/mistral-medium-2505"},"claude-opus-5@default":{"id":"claude-opus-5@default","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"codestral-2":{"id":"codestral-2","name":"Codestral 2","description":"Mistral code model for low-latency completion, fill-in-the-middle, and code generation","family":"codestral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"provider":{"npm":"@ai-sdk/mistral","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/publishers/mistralai/models"},"cost":{"input":0.3,"output":0.9},"canonical_model_id":"mistral/codestral-2508"},"gemini-3.1-flash-lite-image":{"id":"gemini-3.1-flash-lite-image","type":"image","name":"Nano Banana 2 Lite","description":"Fastest, most cost-efficient Gemini image model for high-volume 1K generation and editing","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","video","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":4096},"cost":{"input":0.25,"output":30,"cache_read":0.025},"canonical_model_id":"google/gemini-3.1-flash-lite-image"},"gemini-3.1-pro-preview":{"id":"gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"beta","cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.5-flash"},"gemini-embedding-001":{"id":"gemini-embedding-001","type":"embedding","name":"Gemini Embedding 001","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"gemini","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2025-05","release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":2048,"output":1},"cost":{"input":0.15,"output":0},"canonical_model_id":"google/gemini-embedding-001"},"claude-opus-4-5@20251101":{"id":"claude-opus-4-5@20251101","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"claude-sonnet-5@default":{"id":"claude-sonnet-5@default","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"gemini-3.8-flash":{"id":"gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"input_audio":0.75},"canonical_model_id":"google/gemini-3.8-flash"},"claude-opus-4-7@default":{"id":"claude-opus-4-7@default","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"gemini-3.1-flash-lite":{"id":"gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite"},"claude-fable-5@default":{"id":"claude-fable-5@default","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/google-vertex/anthropic"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"gemini-nano-banana-2.1":{"id":"gemini-nano-banana-2.1","type":"image","name":"Nano Banana 2.1","description":"Image model for prompt-driven generation, multi-turn editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image","video","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":1.5,"output":30,"cache_read":0.15},"canonical_model_id":"google/gemini-nano-banana-2.1"},"gemini-3.1-pro-preview-customtools":{"id":"gemini-3.1-pro-preview-customtools","name":"Gemini 3.1 Pro Preview Custom Tools","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"beta","cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview-customtools"},"gemini-3.6-flash":{"id":"gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":0.75,"output":3.75,"cache_read":0.075,"input_audio":0.75},"canonical_model_id":"google/gemini-3.6-flash"},"xai/grok-4.3":{"id":"xai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":30000},"status":"beta","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.3"},"xai/grok-4.1-fast-reasoning":{"id":"xai/grok-4.1-fast-reasoning","name":"Grok 4.1 Fast (Reasoning)","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":30000},"status":"deprecated","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"xai/grok-4.1-fast-reasoning"},"xai/grok-4.7":{"id":"xai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":500000},"status":"beta","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"xai/grok-4.20-non-reasoning":{"id":"xai/grok-4.20-non-reasoning","name":"Grok 4.20 (Non-Reasoning)","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-non-reasoning"},"xai/grok-4.6":{"id":"xai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":500000},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"xai/grok-4.1-fast-non-reasoning":{"id":"xai/grok-4.1-fast-non-reasoning","name":"Grok 4.1 Fast","description":"Fast Grok model for responsive chat, tool-assisted work, and low-latency responses","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-11-19","last_updated":"2025-11-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":30000},"status":"deprecated","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.2,"output":0.5,"cache_read":0.05},"canonical_model_id":"xai/grok-4.1-fast"},"xai/grok-4.20-reasoning":{"id":"xai/grok-4.20-reasoning","name":"Grok 4.20 (Reasoning)","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.20-0309-reasoning"},"openai/gpt-oss-120b-maas":{"id":"openai/gpt-oss-120b-maas","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.09,"output":0.36},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-oss-20b-maas":{"id":"openai/gpt-oss-20b-maas","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"status":"deprecated","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.07,"output":0.25,"cache_read":0.007}},"zai-org/glm-5.2-maas":{"id":"zai-org/glm-5.2-maas","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":64000},"status":"beta","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":1.4,"output":4.4,"cache_read":0.14},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/glm-4.7-maas":{"id":"zai-org/glm-4.7-maas","name":"GLM-4.7","description":"GLM model for coding, tool use, and complex reasoning","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-06","last_updated":"2026-01-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"status":"deprecated","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.6,"output":2.2,"cache_read":0.06}},"zai-org/glm-5-maas":{"id":"zai-org/glm-5-maas","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"status":"deprecated","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":1,"output":3.2,"cache_read":0.1},"canonical_model_id":"zhipuai/glm-5"},"qwen/qwen3-235b-a22b-instruct-2507-maas":{"id":"qwen/qwen3-235b-a22b-instruct-2507-maas","name":"Qwen3 235B A22B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-13","last_updated":"2025-08-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"status":"deprecated","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.22,"output":0.88}},"moonshotai/kimi-k2-thinking-maas":{"id":"moonshotai/kimi-k2-thinking-maas","name":"Kimi K2 Thinking","description":"Kimi reasoning model for long-horizon research, planning, and tool use","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.6,"output":2.5,"cache_read":0.06}},"deepseek-ai/deepseek-v3.2-maas":{"id":"deepseek-ai/deepseek-v3.2-maas","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-12-17","last_updated":"2026-04-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":65536},"status":"deprecated","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.56,"output":1.68,"cache_read":0.056}},"deepseek-ai/deepseek-v3.1-maas":{"id":"deepseek-ai/deepseek-v3.1-maas","name":"DeepSeek V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-28","last_updated":"2025-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":32768},"status":"deprecated","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.6,"output":1.7,"cache_read":0.06}},"meta/llama-3.3-70b-instruct-maas":{"id":"meta/llama-3.3-70b-instruct-maas","name":"Llama 3.3 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2025-04-29","last_updated":"2025-04-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"status":"deprecated","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.72,"output":0.72}},"meta/llama-4-maverick-17b-128e-instruct-maas":{"id":"meta/llama-4-maverick-17b-128e-instruct-maas","name":"Llama 4 Maverick 17B 128E Instruct","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-29","last_updated":"2025-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":8192},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.35,"output":1.15}},"meta/llama-4-scout-17b-16e-instruct-maas":{"id":"meta/llama-4-scout-17b-16e-instruct-maas","name":"Llama 4 Scout 17B Instruct","description":"Open Llama with long-context vision for efficient multimodal agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1310720,"output":8192},"provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.25,"output":0.7},"canonical_model_id":"meta/llama-4-scout-17b-instruct"},"google/gemma-4-26b-a4b-it-maas":{"id":"google/gemma-4-26b-a4b-it-maas","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":128000},"status":"alpha","provider":{"npm":"@ai-sdk/openai-compatible","api":"https://${GOOGLE_VERTEX_ENDPOINT}/v1/projects/${GOOGLE_VERTEX_PROJECT}/locations/${GOOGLE_VERTEX_LOCATION}/endpoints/openapi"},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"google/gemma-4-26b-a4b-it"}}},"stepfun-step-plan":{"id":"stepfun-step-plan","env":["STEPFUN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.stepfun.com/step_plan/v1","name":"StepFun Step Plan (China)","doc":"https://platform.stepfun.com/docs/zh/step-plan/integrations/reasoning-api","models":{"step-3.5-flash":{"id":"step-3.5-flash","name":"Step 3.5 Flash","description":"StepFun flash lane for quick multimodal reasoning and coding assistance","family":"step","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"canonical_model_id":"stepfun/step-3.5-flash"},"step-router-v1":{"id":"step-router-v1","name":"Step Router v1","description":"StepFun routing model that dispatches requests to the appropriate Step model.","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":256000}},"step-5-preview":{"id":"step-5-preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":65536},"canonical_model_id":"stepfun/step-5-preview"},"step-3.7-flash":{"id":"step-3.7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"canonical_model_id":"stepfun/step-3.7-flash"},"step-3.5-flash-2603":{"id":"step-3.5-flash-2603","name":"Step 3.5 Flash 2603","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","family":"step","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"canonical_model_id":"stepfun/step-3.5-flash-2603"}}},"cline-pass":{"id":"cline-pass","env":["CLINE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.cline.bot/api/v1","name":"ClinePass","doc":"https://docs.cline.bot/getting-started/clinepass","models":{"cline-pass/deepseek-v4-flash":{"id":"cline-pass/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"status":"deprecated","cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"cline-pass/kimi-k3":{"id":"cline-pass/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"cline-pass/glm-5.2":{"id":"cline-pass/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"cline-pass/deepseek-v4.1-flash":{"id":"cline-pass/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"cline-pass/glm-5.3":{"id":"cline-pass/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"cline-pass/qwen3.8-max":{"id":"cline-pass/qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"cline-pass/deepseek-v4-pro":{"id":"cline-pass/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.66,"output":1.98,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-pro"},"cline-pass/glm-5.3-flash":{"id":"cline-pass/glm-5.3-flash","name":"cline-pass/glm-5.3-flash","description":"Latest natively multimodal model in the GLM-5 series","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"cline-pass/mimo-v2.6-flash":{"id":"cline-pass/mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"cline-pass/qwen3.7-plus":{"id":"cline-pass/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.4,"output":1.6,"cache_read":0.04,"cache_write":0.5,"tiers":[{"input":1.2,"output":4.8,"cache_read":0.12,"cache_write":1.5,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1.2,"output":4.8,"cache_read":0.12,"cache_write":1.5}},"canonical_model_id":"alibaba/qwen3.7-plus"},"cline-pass/kimi-k2.6":{"id":"cline-pass/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"cline-pass/qwen3.7-max":{"id":"cline-pass/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2.5,"output":7.5,"cache_read":0.5,"cache_write":3.125},"canonical_model_id":"alibaba/qwen3.7-max"},"cline-pass/mimo-v2.6-pro":{"id":"cline-pass/mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"cline-pass/mimo-v2.5-pro":{"id":"cline-pass/mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.74,"output":3.48,"cache_read":0.0145},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"cline-pass/mimo-v2.5":{"id":"cline-pass/mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.5"},"cline-pass/muse-spark-1.3-contributor":{"id":"cline-pass/muse-spark-1.3-contributor","name":"Muse Spark 1.3 Contributor","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.1,"output":0.2,"cache_read":0.002},"canonical_model_id":"meta/muse-spark-1.3"},"cline-pass/minimax-m3":{"id":"cline-pass/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"cline-pass/kimi-k2.7-code":{"id":"cline-pass/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"}}},"lmstudio":{"id":"lmstudio","env":["LMSTUDIO_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"http://127.0.0.1:1234/v1","name":"LMStudio","doc":"https://lmstudio.ai/models","models":{"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"openai/gpt-oss-20b"},"qwen/qwen3-30b-a3b-2507":{"id":"qwen/qwen3-30b-a3b-2507","name":"Qwen3 30B A3B 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3-30b-a3b-instruct-2507"},"qwen/qwen3-coder-30b":{"id":"qwen/qwen3-coder-30b","name":"Qwen3 Coder 30B","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-31","last_updated":"2025-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"}}},"abacus":{"id":"abacus","env":["ABACUS_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://routellm.abacus.ai/v1","name":"Abacus","doc":"https://abacus.ai/help/api","models":{"qwen3-max":{"id":"qwen3-max","name":"Qwen3 Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":16384},"status":"deprecated","cost":{"input":1.2,"output":6},"canonical_model_id":"alibaba/qwen3-max"},"claude-opus-4-1-20250805":{"id":"claude-opus-4-1-20250805","name":"Claude Opus 4.1","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","cost":{"input":15,"output":75},"canonical_model_id":"anthropic/claude-opus-4-1-20250805"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-4-7"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-4-6"},"gemini-3.7-flash":{"id":"gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.7-flash"},"claude-3-7-sonnet-20250219":{"id":"claude-3-7-sonnet-20250219","name":"Claude Sonnet 3.7","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-10-31","release_date":"2025-02-19","last_updated":"2025-02-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15},"canonical_model_id":"anthropic/claude-3-7-sonnet-20250219"},"gemini-3-pro-image":{"id":"gemini-3-pro-image","type":"image","name":"Nano Banana Pro","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":2,"output":12,"cache_read":0.2},"canonical_model_id":"google/gemini-3-pro-image"},"gpt-5-codex":{"id":"gpt-5-codex","name":"GPT-5-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5-codex"},"grok-4.3":{"id":"grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":1.25,"output":2.5,"cache_read":0.2},"canonical_model_id":"xai/grok-4.3"},"gemini-3.1-flash-lite-preview":{"id":"gemini-3.1-flash-lite-preview","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":0.25,"output":1.5,"cache_read":0.025,"cache_write":1},"canonical_model_id":"google/gemini-3.1-flash-lite-preview"},"grok-code-fast-1":{"id":"grok-code-fast-1","name":"Grok Code Fast 1","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-09-02","last_updated":"2025-09-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":16384},"status":"deprecated","cost":{"input":0.2,"output":1.5},"canonical_model_id":"xai/grok-code-fast-1"},"gemini-3.1-flash-image":{"id":"gemini-3.1-flash-image","type":"image","name":"Nano Banana 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":1048576,"output":32768},"status":"deprecated","cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3.1-flash-image"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50},"canonical_model_id":"anthropic/claude-fable-5"},"gpt-5.3-chat-latest":{"id":"gpt-5.3-chat-latest","name":"GPT-5.3 Chat Latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"status":"deprecated","cost":{"input":1.75,"output":14},"canonical_model_id":"openai/gpt-5.3-chat-latest"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-5"},"gpt-5.2-chat-latest":{"id":"gpt-5.2-chat-latest","name":"GPT-5.2 Chat Latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"status":"deprecated","cost":{"input":1.75,"output":14},"canonical_model_id":"openai/gpt-5.2-chat-latest"},"gemini-3-flash-preview":{"id":"gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05},"canonical_model_id":"google/gemini-3-flash-preview"},"grok-4-fast-non-reasoning":{"id":"grok-4-fast-non-reasoning","name":"Grok 4 Fast (Non-Reasoning)","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-12-18","last_updated":"2025-12-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":16384},"status":"deprecated","cost":{"input":0.2,"output":0.5},"canonical_model_id":"xai/grok-4-fast-non-reasoning"},"gpt-4.1":{"id":"gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-2.5-flash"},"gpt-4o":{"id":"gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-max"},"grok-4-0709":{"id":"grok-4-0709","name":"Grok 4","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-07-09","last_updated":"2025-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":16384},"status":"deprecated","cost":{"input":3,"output":15}},"gpt-5.1":{"id":"gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"grok-4-1-fast-non-reasoning":{"id":"grok-4-1-fast-non-reasoning","name":"Grok 4.1 Fast (Non-Reasoning)","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-11-17","last_updated":"2025-11-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":16384},"status":"deprecated","cost":{"input":0.2,"output":0.5}},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":2,"output":10},"canonical_model_id":"anthropic/claude-sonnet-5"},"muse-spark-1.2":{"id":"muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"claude-sonnet-4-20250514":{"id":"claude-sonnet-4-20250514","name":"Claude Sonnet 4","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15},"canonical_model_id":"anthropic/claude-sonnet-4-20250514"},"claude-opus-4-20250514":{"id":"claude-opus-4-20250514","name":"Claude Opus 4","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","cost":{"input":15,"output":75},"canonical_model_id":"anthropic/claude-opus-4-20250514"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.6-luna"},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"status":"deprecated","cost":{"input":0.6,"output":3},"canonical_model_id":"moonshotai/kimi-k2.5"},"gemini-2.5-pro":{"id":"gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"google/gemini-2.5-pro"},"gemini-2.5-flash-image":{"id":"gemini-2.5-flash-image","type":"image","name":"Nano Banana","description":"Nano Banana image model for fast generation, edits, and character-consistent assets","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":32768,"output":32768},"cost":{"input":0.3,"output":30},"canonical_model_id":"google/gemini-2.5-flash-image"},"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.4"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"gemini-3.5-flash-lite":{"id":"gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"muse-spark-1.1":{"id":"muse-spark-1.1","name":"Muse Spark 1.1","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32000},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.1"},"gpt-5.1-codex-max":{"id":"gpt-5.1-codex-max","name":"GPT-5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":1.25,"output":10},"canonical_model_id":"openai/gpt-5.1-codex-max"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-4-8"},"mimo-v2-pro":{"id":"mimo-v2-pro","name":"MiMo-V2-Pro","description":"Earlier MiMo Pro model for multimodal agents, reasoning, and code tasks","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1,"output":3,"cache_read":0.2},"canonical_model_id":"xiaomi/mimo-v2-pro"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4},"canonical_model_id":"openai/gpt-5.6-sol"},"claude-opus-4-5-20251101":{"id":"claude-opus-4-5-20251101","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25},"canonical_model_id":"anthropic/claude-opus-4-5-20251101"},"qwen3.7-max":{"id":"qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":2.5,"output":7.5},"canonical_model_id":"alibaba/qwen3.7-max"},"gemini-3-pro-image-preview":{"id":"gemini-3-pro-image-preview","type":"image","name":"Nano Banana Pro Preview","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-20","last_updated":"2025-11-20","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"status":"deprecated","cost":{"input":2,"output":12,"cache_read":0.2},"canonical_model_id":"google/gemini-3-pro-image-preview"},"route-llm":{"id":"route-llm","name":"RouteLLM","description":"RouteLLM routes prompts to an appropriate Abacus-backed text-generation model","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-01-01","last_updated":"2026-07-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"cost":{"input":2,"output":10,"cache_read":0.1}},"gpt-4.1-mini":{"id":"gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"gpt-5.2-codex":{"id":"gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Code-specialist GPT for repository edits, reviews, and long-running software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-codex"},"gpt-4o-2024-11-20":{"id":"gpt-4o-2024-11-20","name":"GPT-4o (2024-11-20)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2024-11-20","last_updated":"2024-11-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"status":"deprecated","cost":{"input":2.5,"output":10},"canonical_model_id":"openai/gpt-4o-2024-11-20"},"gpt-5.1-chat-latest":{"id":"gpt-5.1-chat-latest","name":"GPT-5.1 Chat Latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"status":"deprecated","cost":{"input":1.25,"output":10},"canonical_model_id":"openai/gpt-5.1-chat-latest"},"gemini-3.1-pro-preview":{"id":"gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2},"canonical_model_id":"google/gemini-3.1-pro-preview"},"grok-4.6":{"id":"grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":32768},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15},"canonical_model_id":"google/gemini-3.5-flash"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"gpt-5-mini":{"id":"gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"claude-sonnet-4-5-20250929":{"id":"claude-sonnet-4-5-20250929","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15},"canonical_model_id":"anthropic/claude-sonnet-4-5-20250929"},"gpt-4.1-nano":{"id":"gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"gpt-5.1-codex":{"id":"gpt-5.1-codex","name":"GPT-5.1 Codex","description":"Codex GPT for repository edits, code review, and practical software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex"},"llama-3.3-70b-versatile":{"id":"llama-3.3-70b-versatile","name":"Llama 3.3 70B Versatile","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"status":"deprecated","cost":{"input":0.59,"output":0.79},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"grok-4.5":{"id":"grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":32768},"cost":{"input":2,"output":6,"cache_read":0.3},"canonical_model_id":"xai/grok-4.5"},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"o3-pro":{"id":"o3-pro","name":"o3-pro","description":"High-effort o3 tier for difficult technical reasoning and careful answers","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-06-10","last_updated":"2025-06-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":20,"output":80},"canonical_model_id":"openai/o3-pro"},"gemini-3.1-flash-lite":{"id":"gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025},"canonical_model_id":"google/gemini-3.1-flash-lite"},"gpt-5.3-codex-xhigh":{"id":"gpt-5.3-codex-xhigh","name":"GPT-5.3 Codex XHigh","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":1.75,"output":14},"canonical_model_id":"openai/gpt-5.3-codex"},"o3":{"id":"o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2},"canonical_model_id":"openai/gpt-5.6-terra"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5"},"gpt-5":{"id":"gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"gemini-3.1-flash-image-preview":{"id":"gemini-3.1-flash-image-preview","type":"image","name":"Nano Banana 2 Preview","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-26","last_updated":"2026-02-26","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":1048576,"output":32768},"status":"deprecated","cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3.1-flash-image-preview"},"gpt-5-nano":{"id":"gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"o3-mini":{"id":"o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"kimi-k2-turbo-preview":{"id":"kimi-k2-turbo-preview","name":"Kimi K2 Turbo Preview","description":"Fast Kimi model for responsive chat, coding help, and agent loops","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-08","last_updated":"2025-07-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":8192},"status":"deprecated","cost":{"input":0.15,"output":8}},"claude-haiku-4-5-20251001":{"id":"claude-haiku-4-5-20251001","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"gpt-4o-mini":{"id":"gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-4o-mini"},"o4-mini":{"id":"o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4},"canonical_model_id":"openai/o4-mini"},"qwen-2.5-coder-32b":{"id":"qwen-2.5-coder-32b","name":"Qwen 2.5 Coder 32B","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-11-12","last_updated":"2024-11-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"status":"deprecated","cost":{"input":0.79,"output":0.79},"canonical_model_id":"alibaba/qwen2.5-coder-32b-instruct"},"gpt-5.2":{"id":"gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"gemini-3.6-flash":{"id":"gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.6-flash"},"thinkingmachines/Inkling":{"id":"thinkingmachines/Inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":3.74,"output":9.36,"cache_read":0.748},"canonical_model_id":"thinkingmachines/inkling"},"Qwen/Qwen2.5-72B-Instruct":{"id":"Qwen/Qwen2.5-72B-Instruct","name":"Qwen 2.5 72B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-09-19","last_updated":"2024-09-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"status":"deprecated","cost":{"input":0.11,"output":0.38}},"Qwen/Qwen3-32B":{"id":"Qwen/Qwen3-32B","name":"Qwen3 32B","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.08,"output":0.28},"canonical_model_id":"alibaba/qwen3-32b"},"Qwen/Qwen3-Coder-480B-A35B-Instruct":{"id":"Qwen/Qwen3-Coder-480B-A35B-Instruct","name":"Qwen3-Coder 480B-A35B Instruct","description":"Open Qwen coding heavyweight for repository reasoning and agentic engineering","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.38,"output":1.55},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"Qwen/Qwen3.6-27B":{"id":"Qwen/Qwen3.6-27B","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.32,"output":3.2},"canonical_model_id":"alibaba/qwen3.6-27b"},"Qwen/Qwen3-235B-A22B-Instruct-2507":{"id":"Qwen/Qwen3-235B-A22B-Instruct-2507","name":"Qwen3 235B A22B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"status":"deprecated","cost":{"input":0.13,"output":0.6},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"Qwen/QwQ-32B":{"id":"Qwen/QwQ-32B","name":"QwQ 32B","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-03-05","last_updated":"2025-03-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0.4,"output":0.4},"canonical_model_id":"alibaba/qwq-32b"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.037,"output":0.17},"canonical_model_id":"openai/gpt-oss-120b"},"zai-org/GLM-4.7":{"id":"zai-org/GLM-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2},"canonical_model_id":"zhipuai/glm-4.7"},"zai-org/GLM-5":{"id":"zai-org/GLM-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1,"output":3.2},"canonical_model_id":"zhipuai/glm-5"},"zai-org/GLM-4.5":{"id":"zai-org/GLM-4.5","name":"GLM-4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":96000},"status":"deprecated","cost":{"input":0.6,"output":2.2},"canonical_model_id":"zhipuai/glm-4.5"},"zai-org/GLM-5.1":{"id":"zai-org/GLM-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1.38,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-4.6":{"id":"zai-org/GLM-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":0.55,"output":2.2},"canonical_model_id":"zhipuai/glm-4.6"},"moonshotai/Kimi-K2.7-Code":{"id":"moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/Kimi-K3":{"id":"moonshotai/Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"deepseek/deepseek-v3.1":{"id":"deepseek/deepseek-v3.1","name":"DeepSeek V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"status":"deprecated","cost":{"input":0.55,"output":1.66},"canonical_model_id":"deepseek/deepseek-v3.1"},"meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8":{"id":"meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8","name":"Llama 4 Maverick 17B Instruct","description":"Open multimodal Llama for strong reasoning with efficient everyday serving","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":8192},"status":"deprecated","cost":{"input":0.14,"output":0.59},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"meta-llama/Meta-Llama-3.1-8B-Instruct":{"id":"meta-llama/Meta-Llama-3.1-8B-Instruct","name":"Llama 3.1 8B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0.02,"output":0.05},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo":{"id":"meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo","name":"Llama 3.1 405B Instruct Turbo","description":"Compact Llama instruction model for fast chat and local deployment","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":3.5,"output":3.5}},"meta-llama/Meta-Llama-3.3-70B-Instruct":{"id":"meta-llama/Meta-Llama-3.3-70B-Instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.59,"output":0.79},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"MiniMaxAI/MiniMax-M2.7":{"id":"MiniMaxAI/MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2.7"},"MiniMaxAI/MiniMax-M3":{"id":"MiniMaxAI/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M3"},"deepseek-ai/DeepSeek-R1":{"id":"deepseek-ai/DeepSeek-R1","name":"DeepSeek R1","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"status":"deprecated","cost":{"input":3,"output":7},"canonical_model_id":"deepseek/deepseek-r1"},"deepseek-ai/DeepSeek-V4-Pro":{"id":"deepseek-ai/DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32768},"status":"deprecated","cost":{"input":1.74,"output":3.48,"cache_read":0.15},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek-ai/DeepSeek-V3.2":{"id":"deepseek-ai/DeepSeek-V3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"status":"deprecated","cost":{"input":0.27,"output":0.4},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepseek-ai/DeepSeek-V4-Flash":{"id":"deepseek-ai/DeepSeek-V4-Flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32768},"status":"deprecated","cost":{"input":0.14,"output":0.28,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek-ai/DeepSeek-V3.1-Terminus":{"id":"deepseek-ai/DeepSeek-V3.1-Terminus","name":"DeepSeek V3.1 Terminus","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-06-01","last_updated":"2025-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"status":"deprecated","cost":{"input":0.27,"output":1}},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.14,"output":0.4},"canonical_model_id":"google/gemma-4-31b-it"}}},"wafer.ai":{"id":"wafer.ai","env":["WAFER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://pass.wafer.ai/v1","name":"Wafer","doc":"https://docs.wafer.ai/wafer-pass","models":{"glm5.2-fast":{"id":"glm5.2-fast","name":"GLM5.2-Fast","description":"The same model served for high TPS.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":3,"output":10.25,"cache_read":0.5,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"Kimi-K2.6":{"id":"Kimi-K2.6","name":"Kimi K2.6","description":"Kimi K2.6 sparse MoE model with a 262K context window. Available serverless and not included in standard Wafer Pass. Non-ZDR only: requests with `Wafer-ZDR: required` are rejected.","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","cost":{"input":1.14,"output":4.8,"cache_read":0.19,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.6"},"GLM-5.1":{"id":"GLM-5.1","name":"GLM-5.1","description":"General Language Model 5.1 — high-quality bilingual (EN/ZH) generation with strong coding and reasoning capabilities.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"status":"deprecated","cost":{"input":1,"output":3.2,"cache_read":0.1,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.1"},"MiniMax-M3":{"id":"MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"status":"deprecated","cost":{"input":0.33,"output":1.32,"cache_read":0.07,"cache_write":0,"tiers":[{"input":0.66,"output":2.64,"cache_read":0.13,"cache_write":0,"tier":{"type":"context","size":512000}}],"context_over_200k":{"input":0.66,"output":2.64,"cache_read":0.13,"cache_write":0}},"canonical_model_id":"minimax/MiniMax-M3"},"GLM-5.2":{"id":"GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"}}},"openai":{"id":"openai","env":["OPENAI_API_KEY"],"npm":"@ai-sdk/openai","name":"OpenAI","doc":"https://platform.openai.com/docs/models","models":{"gpt-image-2":{"id":"gpt-image-2","type":"image","name":"gpt-image-2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"input":0,"output":0},"cost":{"input":5,"output":30,"cache_read":1.25},"canonical_model_id":"openai/gpt-image-2"},"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5},"provider":{"body":{"service_tier":"priority"}}},"pro":{"provider":{"body":{"reasoning":{"mode":"pro"}}}}}},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":0.2,"output":1,"cache_read":0.02,"cache_write":0.25},"provider":{"body":{"service_tier":"priority"}}},"pro":{"provider":{"body":{"reasoning":{"mode":"pro"}}}}}},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"provider":{"body":{"service_tier":"priority"}}},"pro":{"provider":{"body":{"reasoning":{"mode":"pro"}}}},"ultrafast":{"cost":{"input":12,"output":60,"cache_read":0.6,"cache_write":15},"provider":{"body":{"service_tier":"ultrafast"}}}}},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":3.5,"output":28,"cache_read":0.35},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"gpt-4":{"id":"gpt-4","name":"GPT-4","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-11","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":8192},"status":"deprecated","cost":{"input":30,"output":60}},"gpt-5-pro":{"id":"gpt-5-pro","name":"GPT-5 Pro","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":272000},"cost":{"input":15,"output":120}},"gpt-image-1.5":{"id":"gpt-image-1.5","type":"image","name":"gpt-image-1.5","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-11-25","last_updated":"2025-11-25","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":0,"input":0,"output":0},"canonical_model_id":"openai/gpt-image-1.5"},"gpt-image-1":{"id":"gpt-image-1","type":"image","name":"gpt-image-1","description":"OpenAI image model for production generation, edits, and brand-safe visual workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-04-24","last_updated":"2025-04-24","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":0,"input":0,"output":0},"status":"deprecated","canonical_model_id":"openai/gpt-image-1"},"gpt-5.4-pro":{"id":"gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}}},"gpt-realtime-2.1":{"id":"gpt-realtime-2.1","type":"realtime","name":"GPT-Realtime-2.1","description":"Realtime speech-to-speech model with configurable reasoning, tool use, and robust voice-agent behavior","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2024-09-30","release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text","audio","image"],"output":["text","audio"]},"open_weights":false,"limit":{"context":128000,"input":96000,"output":32000},"cost":{"input":4,"output":24,"cache_read":0.4,"input_audio":32,"output_audio":64},"canonical_model_id":"openai/gpt-realtime-2.1"},"o1":{"id":"o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":15,"output":60,"cache_read":7.5}},"gpt-4o-2024-05-13":{"id":"gpt-4o-2024-05-13","name":"GPT-4o (2024-05-13)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-05-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"status":"deprecated","experimental":{"modes":{"fast":{"cost":{"input":8.75,"output":26.25},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":5,"output":15}},"gpt-4.1":{"id":"gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"experimental":{"modes":{"fast":{"cost":{"input":3.5,"output":14,"cache_read":0.875},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2,"output":8,"cache_read":0.5}},"gpt-4o":{"id":"gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"experimental":{"modes":{"fast":{"cost":{"input":4.25,"output":17,"cache_read":2.125},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2.5,"output":10,"cache_read":1.25}},"text-embedding-3-small":{"id":"text-embedding-3-small","type":"embedding","name":"text-embedding-3-small","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2024-01","release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8191,"output":1536},"cost":{"input":0.02,"output":0}},"gpt-daybreak-red-latest":{"id":"gpt-daybreak-red-latest","name":"Daybreak Red","description":"Alias for advanced cybersecurity models for authorized vulnerability research and security testing","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-08-07","last_updated":"2026-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":12.5,"output":75,"cache_read":1.25,"cache_write":15.625},"canonical_model_id":"openai/gpt-5.6-cyber"},"gpt-5.1":{"id":"gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":2.5,"output":20,"cache_read":0.25},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":0.625,"output":5,"cache_read":0.0625},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":1.25,"output":10,"cache_read":0.125}},"gpt-5.3-codex-spark":{"id":"gpt-5.3-codex-spark","name":"GPT-5.3 Codex Spark","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex-spark","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":100000,"output":32000},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":0.4,"output":2.4,"cache_read":0.04,"cache_write":0.5},"provider":{"body":{"service_tier":"priority"}}},"pro":{"provider":{"body":{"reasoning":{"mode":"pro"}}}}}},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"gpt-5.2-pro":{"id":"gpt-5.2-pro","name":"GPT-5.2 Pro","description":"Higher-accuracy GPT-5.2 variant for tougher reasoning and review workflows","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":21,"output":168}},"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":5,"output":30,"cache_read":0.5},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}}},"gpt-daybreak-blue-latest":{"id":"gpt-daybreak-blue-latest","name":"Daybreak Blue","description":"Alias for flagship general-purpose models with safeguards for defensive cybersecurity work","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-08-07","last_updated":"2026-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":1.5,"output":9,"cache_read":0.15},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":0.375,"output":2.25,"cache_read":0.0375},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":0.75,"output":4.5,"cache_read":0.075}},"text-embedding-ada-002":{"id":"text-embedding-ada-002","type":"embedding","name":"text-embedding-ada-002","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2022-12","release_date":"2022-12-15","last_updated":"2022-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"output":1536},"cost":{"input":0.1,"output":0}},"o1-pro":{"id":"o1-pro","name":"o1-pro","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2025-03-19","last_updated":"2025-03-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":150,"output":600}},"gpt-4o-2024-08-06":{"id":"gpt-4o-2024-08-06","name":"GPT-4o (2024-08-06)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-08-06","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25}},"chatgpt-image-latest":{"id":"chatgpt-image-latest","type":"image","name":"chatgpt-image-latest","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":0,"input":0,"output":0}},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":8,"output":40,"cache_read":0.8,"cache_write":10},"provider":{"body":{"service_tier":"priority"}}},"pro":{"provider":{"body":{"reasoning":{"mode":"pro"}}}}}},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"text-embedding-3-large":{"id":"text-embedding-3-large","type":"embedding","name":"text-embedding-3-large","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2024-01","release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8191,"output":3072},"cost":{"input":0.13,"output":0}},"gpt-4.1-mini":{"id":"gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"experimental":{"modes":{"fast":{"cost":{"input":0.7,"output":2.8,"cache_read":0.175},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.4,"output":1.6,"cache_read":0.1}},"gpt-4o-2024-11-20":{"id":"gpt-4o-2024-11-20","name":"GPT-4o (2024-11-20)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-11-20","last_updated":"2024-11-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25}},"gpt-5.5-pro":{"id":"gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}}},"gpt-5-mini":{"id":"gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":0.45,"output":3.6,"cache_read":0.045},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":0.125,"output":1,"cache_read":0.0125},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":0.25,"output":2,"cache_read":0.025}},"gpt-4.1-nano":{"id":"gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"status":"deprecated","experimental":{"modes":{"fast":{"cost":{"input":0.2,"output":0.8,"cache_read":0.05},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.1,"output":0.4,"cache_read":0.025}},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"flex":{"cost":{"input":0.1,"output":0.625,"cache_read":0.01},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":0.2,"output":1.25,"cache_read":0.02}},"gpt-4-turbo":{"id":"gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":10,"output":30}},"o3-pro":{"id":"o3-pro","name":"o3-pro","description":"High-effort o3 tier for difficult technical reasoning and careful answers","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-06-10","last_updated":"2025-06-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":20,"output":80}},"gpt-5.6":{"id":"gpt-5.6","name":"GPT-5.6","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":8,"output":40,"cache_read":0.8,"cache_write":10},"provider":{"body":{"service_tier":"priority"}}},"pro":{"provider":{"body":{"reasoning":{"mode":"pro"}}}}}},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"o3":{"id":"o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"experimental":{"modes":{"fast":{"cost":{"input":3.5,"output":14,"cache_read":0.875},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":1,"output":4,"cache_read":0.25},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":2,"output":8,"cache_read":0.5}},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":4,"output":24,"cache_read":0.4,"cache_write":5},"provider":{"body":{"service_tier":"priority"}}},"pro":{"provider":{"body":{"reasoning":{"mode":"pro"}}}}}},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":12.5,"output":75,"cache_read":1.25},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}}},"gpt-5":{"id":"gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":2.5,"output":20,"cache_read":0.25},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":0.625,"output":5,"cache_read":0.0625},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"gpt-5-nano":{"id":"gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"flex":{"cost":{"input":0.025,"output":0.2,"cache_read":0.0025},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":0.05,"output":0.4,"cache_read":0.005}},"gpt-3.5-turbo":{"id":"gpt-3.5-turbo","name":"GPT-3.5-turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"output":4096},"status":"deprecated","cost":{"input":0.5,"output":1.5,"cache_read":0}},"o3-mini":{"id":"o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","cost":{"input":1.1,"output":4.4,"cache_read":0.55}},"gpt-4o-mini":{"id":"gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"experimental":{"modes":{"fast":{"cost":{"input":0.25,"output":1,"cache_read":0.125},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.15,"output":0.6,"cache_read":0.075}},"o4-mini":{"id":"o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"status":"deprecated","experimental":{"modes":{"fast":{"cost":{"input":2,"output":8,"cache_read":0.5},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":0.55,"output":2.2,"cache_read":0.1375},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":1.1,"output":4.4,"cache_read":0.275}},"gpt-image-1-mini":{"id":"gpt-image-1-mini","type":"image","name":"gpt-image-1-mini","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-09-26","last_updated":"2025-09-26","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":0,"input":0,"output":0}},"gpt-5.2":{"id":"gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":3.5,"output":28,"cache_read":0.35},"provider":{"body":{"service_tier":"priority"}}},"flex":{"cost":{"input":0.875,"output":7,"cache_read":0.0875},"provider":{"body":{"service_tier":"flex"}}}}},"cost":{"input":1.75,"output":14,"cache_read":0.175}},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":20,"output":100,"cache_read":2,"cache_write":25},"provider":{"body":{"service_tier":"priority"}}},"pro":{"provider":{"body":{"reasoning":{"mode":"pro"}}}},"ultrafast":{"cost":{"input":60,"output":300,"cache_read":6,"cache_write":75},"provider":{"body":{"service_tier":"ultrafast"}}}}},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"}}},"minimax-cn-coding-plan":{"id":"minimax-cn-coding-plan","env":["MINIMAX_API_KEY"],"npm":"@ai-sdk/anthropic","api":"https://api.minimax.cn/anthropic/v1","name":"MiniMax Token Plan (minimax.cn)","doc":"https://platform.minimaxi.com/docs/token-plan/intro","models":{"MiniMax-M3.1-Flash-Preview":{"id":"MiniMax-M3.1-Flash-Preview","name":"MiniMax-M3.1-Flash-Preview","description":"Frontier multimodal coding model with 1M context window and tunable thinking depth","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-09-27","last_updated":"2026-09-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":512000},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"minimax/MiniMax-M3.1-Flash-Preview"},"MiniMax-M2.7":{"id":"MiniMax-M2.7","name":"MiniMax-M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"MiniMax-M3.1-Flash":{"id":"MiniMax-M3.1-Flash","name":"MiniMax-M3.1-Flash","description":"Frontier multimodal coding model with 1M context window and tunable thinking depth","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-19","last_updated":"2026-10-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":524288},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"minimax/MiniMax-M3.1-Flash"},"MiniMax-M2.5-highspeed":{"id":"MiniMax-M2.5-highspeed","name":"MiniMax-M2.5-highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-13","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"MiniMax-M2.5":{"id":"MiniMax-M2.5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"MiniMax-M3":{"id":"MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-25","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":524288},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"MiniMax-M2.7-highspeed":{"id":"MiniMax-M2.7-highspeed","name":"MiniMax-M2.7-highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"MiniMax-M2.1":{"id":"MiniMax-M2.1","name":"MiniMax-M2.1","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"MiniMax-M2":{"id":"MiniMax-M2","name":"MiniMax-M2","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","cost":{"input":0,"output":0}}}},"togetherai":{"id":"togetherai","env":["TOGETHER_API_KEY"],"npm":"@ai-sdk/togetherai","name":"Together AI","doc":"https://docs.together.ai/docs/serverless-models","models":{"thinkingmachines/Inkling":{"id":"thinkingmachines/Inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":131072},"cost":{"input":1,"output":4.05,"cache_read":0.17},"canonical_model_id":"thinkingmachines/inkling"},"meta-models/Muse-Spark-Open-816B-A42B":{"id":"meta-models/Muse-Spark-Open-816B-A42B","name":"Muse Spark Open","description":"Muse Spark Open is an 816B total / 42B active open-weight multimodal reasoning model from Meta for coding and long-horizon agentic work, with 1M-token context.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-open"},"Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8":{"id":"Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8","name":"Qwen3 Coder 480B A35B Instruct","description":"Open Qwen coding heavyweight for repository reasoning and agentic engineering","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":2,"output":2},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"Qwen/Qwen2.5-7B-Instruct-Turbo":{"id":"Qwen/Qwen2.5-7B-Instruct-Turbo","name":"Qwen 2.5 7B Instruct Turbo","description":"Small open Qwen2.5 instruction model for chat, structured output, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2024-09-19","last_updated":"2024-09-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0.3,"output":0.3},"canonical_model_id":"alibaba/qwen2.5-7b-instruct"},"Qwen/Qwen3.5-397B-A17B":{"id":"Qwen/Qwen3.5-397B-A17B","name":"Qwen3.5 397B A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":130000},"status":"deprecated","cost":{"input":0.6,"output":3.6,"cache_read":0.35},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"Qwen/Qwen3-235B-A22B-Instruct-2507-tput":{"id":"Qwen/Qwen3-235B-A22B-Instruct-2507-tput","name":"Qwen3 235B A22B Instruct 2507 FP8","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.2,"output":0.6},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"Qwen/Qwen3.5-9B":{"id":"Qwen/Qwen3.5-9B","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.17,"output":0.25},"canonical_model_id":"alibaba/qwen3.5-9b"},"Qwen/Qwen3-Coder-Next-FP8":{"id":"Qwen/Qwen3-Coder-Next-FP8","name":"Qwen3 Coder Next FP8","description":"Open-weight Qwen coding model for agents, repository edits, and multi-turn tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.5,"output":1.2},"canonical_model_id":"alibaba/qwen3-coder-next"},"Qwen/Qwen3.6-Plus":{"id":"Qwen/Qwen3.6-Plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.5,"output":3},"canonical_model_id":"alibaba/qwen3.6-plus"},"Qwen/Qwen3.7-Max":{"id":"Qwen/Qwen3.7-Max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2.5,"output":7.5,"cache_read":0.5},"canonical_model_id":"alibaba/qwen3.7-max"},"LiquidAI/LFM2-24B-A2B":{"id":"LiquidAI/LFM2-24B-A2B","name":"LFM2-24B-A2B","description":"Efficient open Liquid MoE instruct model for on-device chat and tool calling","family":"liquid","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-02-24","last_updated":"2026-02-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0.03,"output":0.12},"canonical_model_id":"liquid/lfm2-24b-a2b"},"reflection/Beam-1.0-501B-A23B":{"id":"reflection/Beam-1.0-501B-A23B","name":"Beam 1.0 501B A23B","description":"Sparse mixture-of-experts reasoning model with 23B active parameters for coding and agentic workflows","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-06-30","release_date":"2026-10-05","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.4,"output":1.2,"cache_read":0.04},"canonical_model_id":"reflection/beam-1.0-501b-a23b"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-120b"},"zai-org/GLM-5":{"id":"zai-org/GLM-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"status":"deprecated","cost":{"input":1,"output":3.2},"canonical_model_id":"zhipuai/glm-5"},"zai-org/GLM-5.3-Flash":{"id":"zai-org/GLM-5.3-Flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048575,"output":400000},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/GLM-5.1":{"id":"zai-org/GLM-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"status":"deprecated","cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048575,"output":164000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-5.3":{"id":"zai-org/GLM-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048575,"output":262144},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"essentialai/Rnj-1-Instruct":{"id":"essentialai/Rnj-1-Instruct","name":"Rnj-1 Instruct","description":"Open 8B Essential AI model for code, STEM reasoning, and agentic tool use","family":"rnj","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-12-04","last_updated":"2025-12-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0.15,"output":0.15},"canonical_model_id":"essentialai/rnj-1-instruct"},"moonshotai/Kimi-K3":{"id":"moonshotai/Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"nvidia/nemotron-3-ultra-550b-a55b":{"id":"nvidia/nemotron-3-ultra-550b-a55b","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512300,"output":512300},"status":"deprecated","cost":{"input":0.6,"output":3.6,"cache_read":0.2},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/NVIDIA-Nemotron-3.5-Super-VL":{"id":"nvidia/NVIDIA-Nemotron-3.5-Super-VL","name":"Nemotron 3.5 Super VL 120B A12B","description":"NVIDIA vision-language reasoning model for text, image, and video understanding and agentic tool use","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.15,"output":0.5,"cache_read":0.02},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"meta-llama/Llama-3.3-70B-Instruct-Turbo":{"id":"meta-llama/Llama-3.3-70B-Instruct-Turbo","name":"Llama 3.3 70B","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"status":"deprecated","cost":{"input":1.04,"output":1.04},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"MiniMaxAI/MiniMax-M2.7":{"id":"MiniMaxAI/MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":131072},"status":"deprecated","cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7"},"MiniMaxAI/MiniMax-M2.5":{"id":"MiniMaxAI/MiniMax-M2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.5"},"MiniMaxAI/MiniMax-M3":{"id":"MiniMaxAI/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":524288},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"deepseek-ai/DeepSeek-V3-1":{"id":"deepseek-ai/DeepSeek-V3-1","name":"DeepSeek V3.1","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"status":"deprecated","cost":{"input":0.6,"output":1.7},"canonical_model_id":"deepseek/deepseek-v3.1"},"deepseek-ai/DeepSeek-V4.1-Flash":{"id":"deepseek-ai/DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek-ai/DeepSeek-R1":{"id":"deepseek-ai/DeepSeek-R1","name":"DeepSeek-R1","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163839,"output":163839},"status":"deprecated","cost":{"input":3,"output":7},"canonical_model_id":"deepseek/deepseek-r1"},"deepseek-ai/DeepSeek-V4-Flash-0731":{"id":"deepseek-ai/DeepSeek-V4-Flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"status":"deprecated","cost":{"input":0.14,"output":0.28,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek-ai/DeepSeek-V4-Pro-0813":{"id":"deepseek-ai/DeepSeek-V4-Pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":1.32,"output":3.96,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek-ai/DeepSeek-V3":{"id":"deepseek-ai/DeepSeek-V3","name":"DeepSeek-V3","description":"Open DeepSeek MoE chat model for coding, math, and general reasoning","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-12-26","last_updated":"2024-12-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"status":"deprecated","cost":{"input":1.25,"output":1.25},"canonical_model_id":"deepseek/deepseek-v3"}}},"modelscope":{"id":"modelscope","env":["MODELSCOPE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api-inference.modelscope.cn/v1","name":"ModelScope","doc":"https://modelscope.cn/docs/model-service/API-Inference/intro","models":{"Qwen/Qwen3-30B-A3B-Instruct-2507":{"id":"Qwen/Qwen3-30B-A3B-Instruct-2507","name":"Qwen3 30B A3B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3-30b-a3b-instruct-2507"},"Qwen/Qwen3-235B-A22B-Thinking-2507":{"id":"Qwen/Qwen3-235B-A22B-Thinking-2507","name":"Qwen3-235B-A22B-Thinking-2507","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-25","last_updated":"2025-07-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3-235b-a22b-thinking-2507"},"Qwen/Qwen3-30B-A3B-Thinking-2507":{"id":"Qwen/Qwen3-30B-A3B-Thinking-2507","name":"Qwen3 30B A3B Thinking 2507","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0}},"Qwen/Qwen3-235B-A22B-Instruct-2507":{"id":"Qwen/Qwen3-235B-A22B-Instruct-2507","name":"Qwen3 235B A22B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"Qwen/Qwen3-Coder-30B-A3B-Instruct":{"id":"Qwen/Qwen3-Coder-30B-A3B-Instruct","name":"Qwen3 Coder 30B A3B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-31","last_updated":"2025-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"ZhipuAI/GLM-4.5":{"id":"ZhipuAI/GLM-4.5","name":"GLM-4.5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-4.5"},"ZhipuAI/GLM-4.6":{"id":"ZhipuAI/GLM-4.6","name":"GLM-4.6","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-07","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":98304},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-4.6"}}},"neon":{"id":"neon","env":["NEON_AI_GATEWAY_BASE_URL","NEON_AI_GATEWAY_TOKEN"],"npm":"@ai-sdk/openai-compatible","api":"${NEON_AI_GATEWAY_BASE_URL}/v1","name":"Neon","doc":"https://neon.com/docs","models":{"gemma-3-12b":{"id":"gemma-3-12b","name":"Gemma 3 12B","description":"Google's open-weight Gemma 3 vision-language model for text and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.15,"output":0.5},"canonical_model_id":"google/gemma-3-12b-it"},"claude-sonnet-4-5":{"id":"claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"qwen35-122b-a10b":{"id":"qwen35-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":25000},"cost":{"input":0.22,"output":2.2},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":25000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-120b"},"gemini-3-1-pro":{"id":"gemini-3-1-pro","name":"Gemini 3.1 Pro Preview Custom Tools","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview-customtools"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":127999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"grok-4-7":{"id":"grok-4-7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":2.5,"output":7.5,"cache_read":0.5},"canonical_model_id":"xai/grok-4.7"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"gpt-5-5":{"id":"gpt-5-5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"gpt-5-5-pro":{"id":"gpt-5-5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.5-pro"},"gpt-5-6-terra":{"id":"gpt-5-6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"gpt-5-1":{"id":"gpt-5-1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"gemini-3-1-flash-lite":{"id":"gemini-3-1-flash-lite","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite-preview"},"gemini-3-5-flash":{"id":"gemini-3-5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.5-flash"},"gemini-3-7-flash":{"id":"gemini-3-7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"google/gemini-3.7-flash"},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"gpt-5-6-sol":{"id":"gpt-5-6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":45,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1,"cache_write":12.5}},"canonical_model_id":"openai/gpt-5.6-sol"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"glm-5-3-flash":{"id":"glm-5-3-flash","name":"GLM-5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"gemini-3-flash":{"id":"gemini-3-flash","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05,"input_audio":1},"canonical_model_id":"google/gemini-3-flash-preview"},"gpt-5-3-codex":{"id":"gpt-5-3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"gemini-3-6-flash":{"id":"gemini-3-6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.6-flash"},"qwen3-next-80b-a3b-instruct":{"id":"qwen3-next-80b-a3b-instruct","name":"Qwen3-Next 80B-A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":10000},"cost":{"input":0.15,"output":1.2},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"claude-fable-5-1":{"id":"claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"gpt-5-6-luna":{"id":"gpt-5-6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"meta-llama-3-3-70b-instruct":{"id":"meta-llama-3-3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"gpt-oss-20b":{"id":"gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":25000},"cost":{"input":0.07,"output":0.3},"canonical_model_id":"openai/gpt-oss-20b"},"grok-4-6":{"id":"grok-4-6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":524288},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"gpt-5-mini":{"id":"gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"inkling":{"id":"inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":1,"output":4.05,"cache_read":0.17},"canonical_model_id":"thinkingmachines/inkling"},"gemini-3-5-flash-lite":{"id":"gemini-3-5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"gpt-5":{"id":"gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"llama-4-maverick":{"id":"llama-4-maverick","name":"Llama 4 Maverick 17B Instruct","description":"Open multimodal Llama for strong reasoning with efficient everyday serving","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":8192},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"meta-llama-3-1-8b-instruct":{"id":"meta-llama-3-1-8b-instruct","name":"Llama 3.1 8B Instruct","description":"Meta's compact open-weight Llama 3.1 model for fast, low-cost text generation","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"cost":{"input":0.15,"output":0.45},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"glm-5-2":{"id":"glm-5-2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"gpt-5-nano":{"id":"gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"gemini-3-8-flash":{"id":"gemini-3-8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":7.5,"cache_read":0.15},"canonical_model_id":"google/gemini-3.8-flash"},"claude-opus-4-1":{"id":"claude-opus-4-1","name":"Claude Opus 4.1 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":31999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1"},"gpt-5-4-mini":{"id":"gpt-5-4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"claude-opus-4-5":{"id":"claude-opus-4-5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024,"max":63999}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"gpt-5-4-nano":{"id":"gpt-5-4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"deepseek-v4-1-flash":{"id":"deepseek-v4-1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"status":"deprecated","cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"gpt-6-1-sol":{"id":"gpt-6-1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"glm-5-3":{"id":"glm-5-3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"gpt-5-2":{"id":"gpt-5-2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"gpt-5-4":{"id":"gpt-5-4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"${NEON_AI_GATEWAY_BASE_URL}/openai/v1","shape":"responses"},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"}}},"volcengine":{"id":"volcengine","env":["ARK_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://ark.cn-beijing.volces.com/api/v3","name":"Volcengine Ark","doc":"https://www.volcengine.com/docs/82379/1330310","models":{"doubao-seed-evolving":{"id":"doubao-seed-evolving","name":"Seed Evolving","description":"Rolling ByteDance Seed model for rapidly updated reasoning, coding, and agent capabilities","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.8906,"output":4.45301,"cache_read":0.17812},"canonical_model_id":"bytedance-seed/seed-evolving"},"deepseek-v4-pro-ga-260813":{"id":"deepseek-v4-pro-ga-260813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.3359,"output":4.00771,"cache_read":0.04453},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"doubao-seed-2-0-mini-260428":{"id":"doubao-seed-2-0-mini-260428","name":"Seed 2.0 Mini","description":"Lightweight ByteDance Seed 2.0 model for low-latency multimodal reasoning and high-volume tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":131072},"cost":{"input":0.02969,"output":0.29687,"cache_read":0.00594,"tiers":[{"input":0.05937,"output":0.59374,"cache_read":0.01187,"tier":{"type":"context","size":32000}},{"input":0.11875,"output":1.18747,"cache_read":0.02375,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"glm-5-3-flash-260828":{"id":"glm-5-3-flash-260828","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.11875,"output":0.41563,"cache_read":0.03414},"canonical_model_id":"zhipuai/glm-5.3-flash"},"doubao-seed-2-0-lite-260428":{"id":"doubao-seed-2-0-lite-260428","name":"Seed 2.0 Lite","description":"Cost-efficient ByteDance Seed 2.0 model for production chat, analysis, and structured generation","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":131072},"cost":{"input":0.08906,"output":0.53436,"cache_read":0.01781,"tiers":[{"input":0.13359,"output":0.80154,"cache_read":0.02672,"tier":{"type":"context","size":32000}},{"input":0.26718,"output":1.60308,"cache_read":0.05344,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"doubao-seed-2-0-pro-260215":{"id":"doubao-seed-2-0-pro-260215","name":"Seed 2.0 Pro","description":"Flagship ByteDance Seed 2.0 model for complex multimodal reasoning and long-horizon agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"status":"deprecated","cost":{"input":0.47499,"output":2.37494,"cache_read":0.095,"tiers":[{"input":0.71248,"output":3.56241,"cache_read":0.1425,"tier":{"type":"context","size":32000}},{"input":1.42496,"output":7.12482,"cache_read":0.28499,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-pro"},"doubao-seed-1-6-251015":{"id":"doubao-seed-1-6-251015","name":"Seed 1.6","description":"ByteDance Seed model for long-context reasoning, instruction following, and tool-assisted tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"status":"deprecated","cost":{"input":0.11875,"output":1.18747,"cache_read":0.02375,"tiers":[{"input":0.17812,"output":2.37494,"cache_read":0.02375,"tier":{"type":"context","size":32000}},{"input":0.35624,"output":3.56241,"cache_read":0.02375,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-1-6"},"doubao-seed-1-6-flash-250828":{"id":"doubao-seed-1-6-flash-250828","name":"Seed 1.6 Flash","description":"Low-latency ByteDance Seed model for high-throughput chat, extraction, and lightweight tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-08-28","last_updated":"2025-08-28","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"status":"deprecated","cost":{"input":0.02227,"output":0.22265,"cache_read":0.00445,"tiers":[{"input":0.04453,"output":0.4453,"cache_read":0.00445,"tier":{"type":"context","size":32000}},{"input":0.08906,"output":0.8906,"cache_read":0.00445,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-1-6-flash"},"doubao-seed-2-1-pro-260628":{"id":"doubao-seed-2-1-pro-260628","name":"Seed 2.1 Pro","description":"Flagship ByteDance Seed 2.1 model for complex multimodal reasoning, coding, and agents","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.8906,"output":4.45301,"cache_read":0.17812},"canonical_model_id":"bytedance-seed/seed-2.1-pro"},"deepseek-v4-flash-ga-260731":{"id":"deepseek-v4-flash-ga-260731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.4453,"output":1.3359,"cache_read":0.01484},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"doubao-seed-2-0-code-preview-260215":{"id":"doubao-seed-2-0-code-preview-260215","name":"Seed 2.0 Code","description":"ByteDance Seed coding model for multimodal software engineering and long-running agents","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"status":"deprecated","cost":{"input":0.47499,"output":2.37494,"cache_read":0.095,"tiers":[{"input":0.71248,"output":3.56241,"cache_read":0.1425,"tier":{"type":"context","size":32000}},{"input":1.42496,"output":7.12482,"cache_read":0.28499,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"doubao-seed-1-6-vision-250815":{"id":"doubao-seed-1-6-vision-250815","name":"Seed 1.6 Vision","description":"ByteDance Seed multimodal model for image understanding, visual reasoning, and tool-assisted tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-08-15","last_updated":"2025-08-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"status":"deprecated","cost":{"input":0.11875,"output":1.18747,"cache_read":0.02375,"tiers":[{"input":0.17812,"output":2.37494,"cache_read":0.02375,"tier":{"type":"context","size":32000}},{"input":0.35624,"output":3.56241,"cache_read":0.02375,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-1-6-vision"},"doubao-seed-character-260628":{"id":"doubao-seed-character-260628","name":"Seed Character","description":"ByteDance Seed model optimized for character-driven dialogue and consistent conversational behavior","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.11875,"output":0.29687,"cache_read":0.02375,"tiers":[{"input":0.17812,"output":0.8906,"cache_read":0.02375,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"bytedance-seed/seed-character"},"glm-5-2-260617":{"id":"glm-5-2-260617","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.18747,"output":4.15615,"cache_read":0.29687},"canonical_model_id":"zhipuai/glm-5.2"},"doubao-seed-2-1-turbo-260628":{"id":"doubao-seed-2-1-turbo-260628","name":"Seed 2.1 Turbo","description":"Faster ByteDance Seed 2.1 model for multimodal reasoning and latency-sensitive agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0.4453,"output":2.22651,"cache_read":0.08906},"canonical_model_id":"bytedance-seed/seed-2.1-turbo"},"doubao-seed-1-8-251228":{"id":"doubao-seed-1-8-251228","name":"Seed 1.8","description":"ByteDance Seed model for multimodal reasoning, long-context analysis, and agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2025-12-28","last_updated":"2025-12-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"status":"deprecated","cost":{"input":0.11875,"output":1.18747,"cache_read":0.02375,"tiers":[{"input":0.17812,"output":2.37494,"cache_read":0.02375,"tier":{"type":"context","size":32000}},{"input":0.35624,"output":3.56241,"cache_read":0.02375,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-1-8"}}},"stepfun-ai":{"id":"stepfun-ai","env":["STEPFUN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.stepfun.ai/v1","name":"StepFun (Global)","doc":"https://platform.stepfun.ai/docs/en/overview/concept","models":{"stepaudio-2.5-tts":{"id":"stepaudio-2.5-tts","type":"speech","name":"StepAudio 2.5 TTS","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"step","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-16","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"npm":"@ai-sdk/openai"}},"step-3.5-flash":{"id":"step-3.5-flash","name":"Step 3.5 Flash","description":"StepFun flash lane for quick multimodal reasoning and coding assistance","family":"step","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.1,"output":0.3,"cache_read":0.02},"canonical_model_id":"stepfun/step-3.5-flash"},"step-1-32k":{"id":"step-1-32k","name":"Step 1 (32K)","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-01-01","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"input":32768,"output":32768},"status":"deprecated","cost":{"input":2.05,"output":9.59,"cache_read":0.41}},"step-5-preview":{"id":"step-5-preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"input":1024000,"output":65536},"cost":{"input":1,"output":2.7,"cache_read":0.1},"canonical_model_id":"stepfun/step-5-preview"},"step-tts-2":{"id":"step-tts-2","type":"speech","name":"Step TTS 2","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"step","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-03-01","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":0,"output":0},"provider":{"npm":"@ai-sdk/openai"}},"step-3.7-flash":{"id":"step-3.7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"step-3.5-flash-2603":{"id":"step-3.5-flash-2603","name":"Step 3.5 Flash 2603","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","family":"step","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.1,"output":0.3,"cache_read":0.02},"canonical_model_id":"stepfun/step-3.5-flash-2603"},"step-2-16k":{"id":"step-2-16k","name":"Step 2 (16K)","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-01-01","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"input":16384,"output":8192},"status":"deprecated","cost":{"input":5.21,"output":16.44,"cache_read":1.04}},"stepaudio-2.5-asr":{"id":"stepaudio-2.5-asr","type":"transcription","name":"StepAudio 2.5 ASR","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"step","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-24","last_updated":"2026-07-02","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":0}}}},"greenpt":{"id":"greenpt","env":["GREENPT_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.greenpt.ai/v1","name":"GreenPT","doc":"https://docs.greenpt.ai","models":{"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.228,"output":0.798},"canonical_model_id":"openai/gpt-oss-120b"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3.762,"output":18.81,"cache_read":0.9405},"canonical_model_id":"moonshotai/kimi-k3"},"green-s-pro":{"id":"green-s-pro","type":"transcription","name":"Green S Pro","description":"GreenPT advanced speech-to-text model with multilingual transcription support","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-02","last_updated":"2025-02","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":8192}},"gemma4":{"id":"gemma4","name":"gemma4","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.57,"output":1.71},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"qwen3-coder-30b-a3b-instruct":{"id":"qwen3-coder-30b-a3b-instruct","name":"Qwen3-Coder 30B-A3B Instruct","description":"Smaller Qwen coder for efficient local agents and repo-level fixes","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-31","last_updated":"2025-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"status":"deprecated","cost":{"input":0.285,"output":1.083},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"green-r-raw":{"id":"green-r-raw","name":"Green R Raw","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.399,"output":1.083},"canonical_model_id":"openai/gpt-oss-120b"},"voxtral-small-24b-2507":{"id":"voxtral-small-24b-2507","name":"Voxtral Small 24B","description":"Mistral Voxtral audio-understanding model for speech and transcription tasks","family":"voxtral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-07","release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"status":"deprecated","cost":{"input":0.228,"output":0.513},"canonical_model_id":"mistral/voxtral-small-24b-2507"},"kimi-k2.6-fast":{"id":"kimi-k2.6-fast","name":"Kimi K2.6 Fast","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":1.655,"output":8.778},"canonical_model_id":"moonshotai/kimi-k2.6"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.738325,"output":5.1589,"cache_read":0.4486},"canonical_model_id":"zhipuai/glm-5.2"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.255552,"output":1.27776,"cache_read":0.0127776},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"qwen3-235b-a22b-instruct-2507":{"id":"qwen3-235b-a22b-instruct-2507","name":"Qwen3 235B A22B Instruct 2507","description":"Qwen3 235B MoE instruct model for long-context multilingual chat and reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":1.026,"output":3.078},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.27754,"output":5.11016,"cache_read":0.319385},"canonical_model_id":"zhipuai/glm-5.3"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.127754,"output":0.511016,"cache_read":0.0255508},"canonical_model_id":"zhipuai/glm-5.3-flash"},"pixtral-12b-2409":{"id":"pixtral-12b-2409","name":"Pixtral 12B","description":"Mistral vision-language model for image understanding and multimodal chat","family":"pixtral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2024-09-11","last_updated":"2024-09-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0.285,"output":0.285},"canonical_model_id":"mistral/pixtral-12b"},"glm-5.2-caveman-lite":{"id":"glm-5.2-caveman-lite","name":"GLM-5.2 Caveman Lite","description":"glm-5.2 carrying a built-in ruleset that compresses prose, keeping code and technical detail verbatim. The gentlest tier: it cuts filler only and keeps the explanation intact. Same upstream model and price per token as glm-5.2, with fewer output tokens.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.738325,"output":5.1589,"cache_read":0.4486},"canonical_model_id":"zhipuai/glm-5.2"},"holo2-30b-a3b":{"id":"holo2-30b-a3b","name":"Holo2 30B A3B","description":"H Company Holo2 vision model for GUI navigation and computer-use agents","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-11","last_updated":"2025-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":22016,"output":16384},"status":"deprecated","cost":{"input":0.399,"output":0.969}},"llama-3.3-70b-instruct":{"id":"llama-3.3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":100000,"output":16384},"cost":{"input":1.254,"output":1.254},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"minimax-m2.5":{"id":"minimax-m2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.49346,"output":2.4673,"cache_read":0.123365},"canonical_model_id":"minimax/MiniMax-M2.5"},"qwen3.5-397b-a17b":{"id":"qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.798,"output":4.959},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"glm-5.2-honey-ultra":{"id":"glm-5.2-honey-ultra","name":"GLM-5.2 Honey Ultra","description":"glm-5.2 carrying a built-in ruleset that compresses both generated code and prose. The most aggressive tier, close to answer-only. Same upstream model and price per token as glm-5.2, with fewer output tokens.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.738325,"output":5.1589,"cache_read":0.4486},"canonical_model_id":"zhipuai/glm-5.2"},"green-l":{"id":"green-l","name":"Green L","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.285,"output":0.912},"canonical_model_id":"mistral/mistral-small-2506"},"mistral-medium-3.5-128b":{"id":"mistral-medium-3.5-128b","name":"Mistral Medium 3.5","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":2.052,"output":10.26},"canonical_model_id":"mistral/mistral-medium-2604"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.7524,"output":4.275,"cache_read":0.2508},"canonical_model_id":"moonshotai/kimi-k2.6"},"glm-5.2-ponytail-lite":{"id":"glm-5.2-ponytail-lite","name":"GLM-5.2 Ponytail Lite","description":"glm-5.2 carrying a built-in ruleset that compresses generated code, preferring platform features over custom code. The gentlest tier: it cuts filler only and keeps the explanation intact. Same upstream model and price per token as glm-5.2, with fewer output tokens.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.738325,"output":5.1589,"cache_read":0.4486},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.2-caveman-ultra":{"id":"glm-5.2-caveman-ultra","name":"GLM-5.2 Caveman Ultra","description":"glm-5.2 carrying a built-in ruleset that compresses prose, keeping code and technical detail verbatim. The most aggressive tier, close to answer-only. Same upstream model and price per token as glm-5.2, with fewer output tokens.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.738325,"output":5.1589,"cache_read":0.4486},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"status":"deprecated","cost":{"input":1.756,"output":5.518},"canonical_model_id":"zhipuai/glm-5.1"},"mistral-small-3.2-24b-instruct-2506":{"id":"mistral-small-3.2-24b-instruct-2506","name":"Mistral Small 3.2","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.228,"output":0.456},"canonical_model_id":"mistral/mistral-small-2506"},"devstral-2-123b-instruct-2512":{"id":"devstral-2-123b-instruct-2512","name":"Devstral 2","description":"Mistral's coding-agent model for repository work, terminal tasks, and software fixes","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":16384},"status":"deprecated","cost":{"input":0.57,"output":2.736},"canonical_model_id":"mistral/devstral-2512"},"green-r":{"id":"green-r","name":"Green R","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.399,"output":1.083},"canonical_model_id":"openai/gpt-oss-120b"},"glm-5.2-ponytail-ultra":{"id":"glm-5.2-ponytail-ultra","name":"GLM-5.2 Ponytail Ultra","description":"glm-5.2 carrying a built-in ruleset that compresses generated code, preferring platform features over custom code. The most aggressive tier, close to answer-only. Same upstream model and price per token as glm-5.2, with fewer output tokens.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.738325,"output":5.1589,"cache_read":0.4486},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.2-caveman":{"id":"glm-5.2-caveman","name":"GLM-5.2 Caveman","description":"glm-5.2 carrying a built-in ruleset that compresses prose, keeping code and technical detail verbatim. The middle tier, and the ruleset as its authors wrote it. Same upstream model and price per token as glm-5.2, with fewer output tokens.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.738325,"output":5.1589,"cache_read":0.4486},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.2-honey":{"id":"glm-5.2-honey","name":"GLM-5.2 Honey","description":"glm-5.2 carrying a built-in ruleset that compresses both generated code and prose. The middle tier, and the ruleset as its authors wrote it. Same upstream model and price per token as glm-5.2, with fewer output tokens.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.738325,"output":5.1589,"cache_read":0.4486},"canonical_model_id":"zhipuai/glm-5.2"},"gemma-3-27b-it":{"id":"gemma-3-27b-it","name":"Gemma 3 27B","description":"Google Gemma 3 multimodal model for chat, reasoning, and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":40000,"output":8192},"status":"deprecated","cost":{"input":0.342,"output":0.684},"canonical_model_id":"google/gemma-3-27b-it"},"green-l-raw":{"id":"green-l-raw","name":"Green L Raw","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-03","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.285,"output":0.912},"canonical_model_id":"mistral/mistral-small-2506"},"green-s":{"id":"green-s","type":"transcription","name":"Green S","description":"GreenPT speech-to-text model for pre-recorded and live transcription","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-01","last_updated":"2025-01","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":0,"output":8192}},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.1596,"output":0.399,"cache_read":0.0456},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.863555,"output":4.317775,"cache_read":0.222057},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"glm-5.2-honey-lite":{"id":"glm-5.2-honey-lite","name":"GLM-5.2 Honey Lite","description":"glm-5.2 carrying a built-in ruleset that compresses both generated code and prose. The gentlest tier: it cuts filler only and keeps the explanation intact. Same upstream model and price per token as glm-5.2, with fewer output tokens.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.738325,"output":5.1589,"cache_read":0.4486},"canonical_model_id":"zhipuai/glm-5.2"},"qwen3.6-35b-a3b":{"id":"qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.342,"output":2.052},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"glm-5.2-ponytail":{"id":"glm-5.2-ponytail","name":"GLM-5.2 Ponytail","description":"glm-5.2 carrying a built-in ruleset that compresses generated code, preferring platform features over custom code. The middle tier, and the ruleset as its authors wrote it. Same upstream model and price per token as glm-5.2, with fewer output tokens.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.738325,"output":5.1589,"cache_read":0.4486},"canonical_model_id":"zhipuai/glm-5.2"}}},"empiriolabs":{"id":"empiriolabs","env":["EMPIRIOLABS_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.empiriolabs.ai/v1","name":"EmpirioLabs AI","doc":"https://docs.empiriolabs.ai","models":{"fugu-ultra-v1-1":{"id":"fugu-ultra-v1-1","name":"Fugu Ultra v1.1","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"sakana/fugu-ultra"},"fugu-ultra-v2-0":{"id":"fugu-ultra-v2-0","name":"Fugu Ultra v2.0","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-08-28","release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"sakana/fugu-ultra-v2"},"qwen3-5-27b":{"id":"qwen3-5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":80000}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.086,"output":0.688,"cache_read":0.086,"tiers":[{"input":0.258,"output":2.064,"cache_read":0.258,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3.5-27b"},"qwen3-6-plus":{"id":"qwen3-6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.5,"tiers":[{"input":2,"output":6,"cache_read":2,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":2}},"canonical_model_id":"alibaba/qwen3.6-plus"},"kimi-k2-7-code":{"id":"kimi-k2-7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":131072},"cost":{"input":0.95,"output":4,"cache_read":0.95},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"qwen3-8-27b":{"id":"qwen3-8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.17,"output":0.5,"cache_read":0.08},"canonical_model_id":"alibaba/qwen3.8-27b"},"mimo-v2-6-pro":{"id":"mimo-v2-6-pro","name":"MiMo V2.6 Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.435},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"qwen3-5-flash":{"id":"qwen3-5-flash","name":"Qwen3.5 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":81920}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.09,"output":0.368,"cache_read":0.09},"canonical_model_id":"alibaba/qwen3.5-flash"},"seed-2-0-code":{"id":"seed-2-0-code","name":"Seed 2.0 Code","description":"ByteDance Seed coding model for multimodal software engineering and long-running agents","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.4,"output":2.4,"cache_read":0.4,"tiers":[{"input":0.8,"output":4.8,"cache_read":0.8,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"seed-2-0-lite":{"id":"seed-2-0-lite","name":"Seed 2.0 Lite","description":"Cost-efficient ByteDance Seed 2.0 model for production chat, analysis, and structured generation","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.31,"output":2.5,"cache_read":0.31,"tiers":[{"input":0.62,"output":5,"cache_read":0.62,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"fugu-max":{"id":"fugu-max","name":"Fugu Max","description":"Multi-agent model for routing expert agents across complex analytical tasks","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"sakana/fugu-max"},"mimo-v2-6-flash":{"id":"mimo-v2-6-flash","name":"MiMo V2.6 Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.14},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"seed-2-0-pro":{"id":"seed-2-0-pro","name":"Seed 2.0 Pro","description":"Flagship ByteDance Seed 2.0 model for complex multimodal reasoning and long-horizon agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.63,"output":3.79,"cache_read":0.63,"tiers":[{"input":1.26,"output":7.58,"cache_read":1.26,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-pro"},"mimo-v2-6-pro-ultraspeed":{"id":"mimo-v2-6-pro-ultraspeed","name":"MiMo V2.6 Pro UltraSpeed","description":"MiMo pro model for strong multimodal reasoning and agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":4.35,"output":8.7,"cache_read":4.35},"canonical_model_id":"xiaomi/mimo-v2.6-pro-ultraspeed"},"gemma-4-26b-a4b":{"id":"gemma-4-26b-a4b","name":"Gemma 4 26B-A4B","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.05,"output":0.29,"cache_read":0.025},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":3,"output":15,"cache_read":3},"canonical_model_id":"moonshotai/kimi-k3"},"qwen3-8-max":{"id":"qwen3-8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":262144}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":2},"canonical_model_id":"alibaba/qwen3.8-max"},"seed-2-1-turbo":{"id":"seed-2-1-turbo","name":"Seed 2.1 Turbo","description":"Faster ByteDance Seed 2.1 model for multimodal reasoning and latency-sensitive agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":65536},"cost":{"input":0.63,"output":3.13,"cache_read":0.63},"canonical_model_id":"bytedance-seed/seed-2.1-turbo"},"muse-spark-1-1":{"id":"muse-spark-1-1","name":"Muse Spark 1.1","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":1},"canonical_model_id":"meta/muse-spark-1.1"},"fugu-ultra-v1-0":{"id":"fugu-ultra-v1-0","name":"Fugu Ultra v1.0","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":7.5,"output":45,"cache_read":1.5,"tiers":[{"input":15,"output":67.5,"cache_read":3,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":15,"output":67.5,"cache_read":3}},"canonical_model_id":"sakana/fugu-ultra"},"qwen3-6-flash":{"id":"qwen3-6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":64000}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.25,"tiers":[{"input":1,"output":4,"cache_read":1,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1,"output":4,"cache_read":1}},"canonical_model_id":"alibaba/qwen3.6-flash"},"minimax-m3-1-flash":{"id":"minimax-m3-1-flash","name":"MiniMax M3.1 Flash","description":"Frontier multimodal coding model with 1M context window and tunable thinking depth","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-19","last_updated":"2026-10-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":524288},"cost":{"input":0.1125,"output":0.45,"cache_read":0.01125},"canonical_model_id":"minimax/MiniMax-M3.1-Flash"},"qwen3-8-omni-flash":{"id":"qwen3-8-omni-flash","name":"Qwen3.8 Omni Flash","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":262144}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.3,"output":0.94,"cache_read":0.3},"canonical_model_id":"alibaba/qwen3.8-omni-flash"},"seed-2-0-mini":{"id":"seed-2-0-mini","name":"Seed 2.0 Mini","description":"Lightweight ByteDance Seed 2.0 model for low-latency multimodal reasoning and high-volume tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.12,"output":0.5,"cache_read":0.12,"tiers":[{"input":0.24,"output":1,"cache_read":0.24,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"qwen3-5-4b":{"id":"qwen3-5-4b","name":"Qwen3.5 4B","description":"Qwen3.5 4B is a low-cost multimodal reasoning model with 256K context, image and video input, function tools, and structured output.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1024,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-02","last_updated":"2026-03-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.04,"output":0.07,"cache_read":0.02},"canonical_model_id":"alibaba/qwen3.5-4b"},"qwen3-6-35b-a3b":{"id":"qwen3-6-35b-a3b","name":"Qwen3.6 35B A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.07,"output":0.42,"cache_read":0.035},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"kimi-k2-6":{"id":"kimi-k2-6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":81920}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16000},"cost":{"input":0.8939,"output":3.7131,"cache_read":0.1788},"canonical_model_id":"moonshotai/kimi-k2.6"},"qwen3-7-max":{"id":"qwen3-7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":64000}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":2.5,"output":7.5,"cache_read":2.5},"canonical_model_id":"alibaba/qwen3.7-max"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":393216}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":1.65,"output":3.3,"cache_read":1.65},"canonical_model_id":"deepseek/deepseek-v4-pro"},"minimax-m2-7":{"id":"minimax-m2-7","name":"MiniMax M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32768},"status":"deprecated","cost":{"input":0.15,"output":0.6,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.7"},"step-3-5-flash-2603":{"id":"step-3-5-flash-2603","name":"Step 3.5 Flash 2603","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","family":"step","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":131072},"cost":{"input":0.1,"output":0.3,"cache_read":0.02},"canonical_model_id":"stepfun/step-3.5-flash-2603"},"step-3-7-flash":{"id":"step-3-7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":131072},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"qwen3-5-plus":{"id":"qwen3-5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1,"max":81920}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"status":"deprecated","cost":{"input":0.36,"output":2.21,"cache_read":0.36,"tiers":[{"input":1.08,"output":6.62,"cache_read":1.08,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1.08,"output":6.62,"cache_read":1.08}},"canonical_model_id":"alibaba/qwen3.5-plus"},"glm-5-3-flash":{"id":"glm-5-3-flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.075,"output":0.25,"cache_read":0.075},"canonical_model_id":"zhipuai/glm-5.3-flash"},"step-5-preview":{"id":"step-5-preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":131072},"cost":{"input":1,"output":2.7,"cache_read":0.05},"canonical_model_id":"stepfun/step-5-preview"},"glm-4-7-flash":{"id":"glm-4-7-flash","name":"GLM 4.7 Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-4.7-flash"},"muse-spark-1-2":{"id":"muse-spark-1-2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":1},"canonical_model_id":"meta/muse-spark-1.2"},"gemma-3-27b":{"id":"gemma-3-27b","name":"Gemma 3 27B","description":"Largest open Gemma 3 instruction model for multilingual text generation and visual understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemma-3-27b-it"},"qwen3-5-35b-a3b":{"id":"qwen3-5-35b-a3b","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":80000}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.057,"output":0.459,"cache_read":0.057,"tiers":[{"input":0.229,"output":1.835,"cache_read":0.229,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"qwen3-5-122b-a10b":{"id":"qwen3-5-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":80000}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.115,"output":0.917,"cache_read":0.115,"tiers":[{"input":0.287,"output":2.294,"cache_read":0.287,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"qwen3-5-397b-a17b":{"id":"qwen3-5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":80000}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"status":"deprecated","cost":{"input":0.172,"output":1.032,"cache_read":0.172,"tiers":[{"input":0.43,"output":2.58,"cache_read":0.43,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"kimi-k2-7-code-highspeed":{"id":"kimi-k2-7-code-highspeed","name":"Kimi K2.7 Code Highspeed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":131072},"cost":{"input":1.9,"output":8,"cache_read":1.9},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"glm-4-5-flash":{"id":"glm-4-5-flash","name":"GLM 4.5 Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":98304},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-4.5-flash"},"qwen3-8-max-0902":{"id":"qwen3-8-max-0902","name":"Qwen3.8 Max 0902","description":"2026-09-02 upgraded snapshot of Qwen3.8 Max with stronger coding, collaborative agents, and multimodal document understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":262144}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":2},"canonical_model_id":"alibaba/qwen3.8-max-0902"},"muse-spark-1-3":{"id":"muse-spark-1-3","name":"Muse Spark 1.3","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":1},"canonical_model_id":"meta/muse-spark-1.3"},"qwen3-6-27b":{"id":"qwen3-6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":80000}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0.412564,"output":2.475384,"cache_read":0.412564},"canonical_model_id":"alibaba/qwen3.6-27b"},"glm-4-6v-flash":{"id":"glm-4-6v-flash","name":"GLM 4.6V Flash","description":"Lightweight GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-4.6v-flash"},"glm-5-1":{"id":"glm-5-1","name":"GLM 5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":38912}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202000,"output":128000},"cost":{"input":0.825,"output":3.301,"cache_read":0.165,"tiers":[{"input":1.1,"output":3.851,"cache_read":0.22,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-5.1"},"deepseek-v4-1-flash-1017":{"id":"deepseek-v4-1-flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":393216}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":0.3,"output":1.2,"cache_read":0.3},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"muse-glimmer-30b":{"id":"muse-glimmer-30b","name":"Muse Glimmer 30B","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.2,"output":0.8,"cache_read":0.05},"canonical_model_id":"meta/muse-glimmer-30b"},"qwen3-8-flash":{"id":"qwen3-8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":262144}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.16,"output":0.47,"cache_read":0.16},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen3-5-9b":{"id":"qwen3-5-9b","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1024,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.09,"output":0.13,"cache_read":0.045},"canonical_model_id":"alibaba/qwen3.5-9b"},"glm-5-2":{"id":"glm-5-2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":1.4},"canonical_model_id":"zhipuai/glm-5.2"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":393216}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":0.424,"output":1.272,"cache_read":0.424},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":524288},"cost":{"input":0.225,"output":0.9,"cache_read":0.045,"tiers":[{"input":0.45,"output":1.8,"cache_read":0.09,"tier":{"type":"context","size":512000}}],"context_over_200k":{"input":0.45,"output":1.8,"cache_read":0.09}},"canonical_model_id":"minimax/MiniMax-M3"},"minimax-m2-7-highspeed":{"id":"minimax-m2-7-highspeed","name":"MiniMax M2.7 Highspeed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32768},"status":"deprecated","cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"qwen3-7-flash":{"id":"qwen3-7-flash","name":"Qwen3.7 Flash","description":"Lightweight multimodal Qwen model for high-throughput text, image, and video tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":131072}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":991808,"output":65536},"cost":{"input":0.03,"output":0.13,"cache_read":0.006,"tiers":[{"input":0.1,"output":0.4,"cache_read":0.02,"tier":{"type":"context","size":32000}},{"input":0.2,"output":0.8,"cache_read":0.04,"tier":{"type":"context","size":256000}}]},"canonical_model_id":"alibaba/qwen3.7-flash"},"mistral-small-4":{"id":"mistral-small-4","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0.15,"output":0.6,"cache_read":0.15},"canonical_model_id":"mistral/mistral-small-2603"},"step-3-5-flash":{"id":"step-3-5-flash","name":"Step 3.5 Flash","description":"StepFun flash lane for quick multimodal reasoning and coding assistance","family":"step","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":131072},"cost":{"input":0.1,"output":0.3,"cache_read":0.02},"canonical_model_id":"stepfun/step-3.5-flash"},"deepseek-v4-1-flash":{"id":"deepseek-v4-1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":393216}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"status":"deprecated","cost":{"input":0.3,"output":1.2,"cache_read":0.3},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"qwen3-7-plus":{"id":"qwen3-7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":256000}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.4,"output":1.6,"cache_read":0.4,"tiers":[{"input":1.2,"output":4.8,"cache_read":1.2,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1.2,"output":4.8,"cache_read":1.2}},"canonical_model_id":"alibaba/qwen3.7-plus"},"glm-5-3":{"id":"glm-5-3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":1.4},"canonical_model_id":"zhipuai/glm-5.3"},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens","min":1,"max":393216}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":393216},"cost":{"input":1.32,"output":3.96,"cache_read":1.32},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"}}},"volcengine-coding-plan":{"id":"volcengine-coding-plan","env":["ARK_CODING_PLAN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://ark.cn-beijing.volces.com/api/coding/v3","name":"Volcengine Ark Coding Plan","doc":"https://www.volcengine.com/docs/82379/1928261","models":{"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4-flash"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"moonshotai/kimi-k3"},"doubao-seed-evolving":{"id":"doubao-seed-evolving","name":"Seed Evolving","description":"Rolling ByteDance Seed model for rapidly updated reasoning, coding, and agent capabilities","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"bytedance-seed/seed-evolving"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-5.3"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4-pro"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"doubao-seed-2.1-turbo":{"id":"doubao-seed-2.1-turbo","name":"Seed 2.1 Turbo","description":"Faster ByteDance Seed 2.1 model for multimodal reasoning and latency-sensitive agent workflows","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"bytedance-seed/seed-2.1-turbo"},"doubao-seed-2.0-lite":{"id":"doubao-seed-2.0-lite","name":"Seed 2.0 Lite","description":"Cost-efficient ByteDance Seed 2.0 model for production chat, analysis, and structured generation","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"minimax/MiniMax-M3"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"moonshotai/kimi-k2.7-code"}}},"pioneer":{"id":"pioneer","env":["PIONEER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.fastino.ai/v1","name":"Pioneer","doc":"https://agent.pioneer.ai/llms.txt","models":{"claude-sonnet-4-5":{"id":"claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"status":"deprecated","cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":1.75,"output":14,"cache_read":0.175,"cache_write":1.75},"canonical_model_id":"openai/gpt-5.3-codex"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"status":"deprecated","cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"qwen3.6-flash":{"id":"qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"status":"deprecated","cost":{"input":0.1875,"output":1.125,"cache_read":0.0375,"cache_write":0.234375},"canonical_model_id":"alibaba/qwen3.6-flash"},"devstral-2":{"id":"devstral-2","name":"Devstral 2","description":"Mistral's coding-agent model for repository work, terminal tasks, and software fixes","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":131072},"status":"deprecated","cost":{"input":0.4,"output":2,"cache_read":0.4,"cache_write":0.4},"canonical_model_id":"mistral/devstral-2512"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"status":"deprecated","cost":{"input":11,"output":55,"cache_read":1.1,"cache_write":13.75},"canonical_model_id":"anthropic/claude-fable-5"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"status":"deprecated","cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"gpt-4.1":{"id":"gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"status":"deprecated","cost":{"input":2,"output":8,"cache_read":1,"cache_write":2},"canonical_model_id":"openai/gpt-4.1"},"gpt-4o":{"id":"gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"status":"deprecated","cost":{"input":2.5,"output":10,"cache_read":1.25,"cache_write":2.5},"canonical_model_id":"openai/gpt-4o"},"gemini-3.1-pro":{"id":"gemini-3.1-pro","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"status":"deprecated","cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":0.375},"canonical_model_id":"google/gemini-3.1-pro-preview"},"gpt-5.1":{"id":"gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":131072},"status":"deprecated","cost":{"input":1.25,"output":10,"cache_read":0.125,"cache_write":1.25},"canonical_model_id":"openai/gpt-5.1"},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"status":"deprecated","cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"claude-3-7-sonnet-latest":{"id":"claude-3-7-sonnet-latest","name":"Claude Sonnet 3.7","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-10-31","release_date":"2025-02-19","last_updated":"2025-02-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-3-7-sonnet-20250219"},"ministral-3b":{"id":"ministral-3b","name":"Ministral 3B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-03","release_date":"2024-10-16","last_updated":"2024-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"status":"deprecated","cost":{"input":0.1,"output":0.1,"cache_read":0.1,"cache_write":0.1},"canonical_model_id":"mistral/ministral-3b"},"gemini-3-flash":{"id":"gemini-3-flash","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65000},"status":"deprecated","cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.083333},"canonical_model_id":"google/gemini-3-flash-preview"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"status":"deprecated","cost":{"input":1,"output":6,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"openai/gpt-5.6-luna"},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"status":"deprecated","cost":{"input":0.32,"output":1.28,"cache_read":0.064,"cache_write":0.4},"canonical_model_id":"alibaba/qwen3.7-plus"},"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"status":"deprecated","cost":{"input":2.5,"output":15,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.4"},"mistral-medium":{"id":"mistral-medium","name":"Mistral Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"status":"deprecated","cost":{"input":0.4,"output":2,"cache_read":0.4,"cache_write":0.4},"canonical_model_id":"mistral/mistral-medium-2505"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":0.75,"output":4.5,"cache_read":0.075,"cache_write":0.75},"canonical_model_id":"openai/gpt-5.4-mini"},"gemini-3.5-flash-lite":{"id":"gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65000},"status":"deprecated","cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":0.3},"canonical_model_id":"google/gemini-3.5-flash-lite"},"mistral-medium-3.5":{"id":"mistral-medium-3.5","name":"Mistral Medium 3.5","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":131072},"status":"deprecated","cost":{"input":1.5,"output":7.5,"cache_read":1.5,"cache_write":1.5},"canonical_model_id":"mistral/mistral-medium-2604"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"status":"deprecated","cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"status":"deprecated","cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"openai/gpt-5.6-sol"},"qwen3.7-max":{"id":"qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":991000,"output":64000},"status":"deprecated","cost":{"input":1.25,"output":3.75,"cache_read":0.25,"cache_write":1.5625},"canonical_model_id":"alibaba/qwen3.7-max"},"claude-opus-5-fast":{"id":"claude-opus-5-fast","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"status":"deprecated","cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-opus-5"},"mistral-large-3":{"id":"mistral-large-3","name":"Mistral Large 3","description":"Mistral's largest general model for enterprise agents, coding, and multilingual reasoning","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":131072},"status":"deprecated","cost":{"input":0.5,"output":1.5,"cache_read":0.5,"cache_write":0.5},"canonical_model_id":"mistral/mistral-large-2512"},"gpt-4.1-mini":{"id":"gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"status":"deprecated","cost":{"input":0.4,"output":1.6,"cache_read":0.2,"cache_write":0.4},"canonical_model_id":"openai/gpt-4.1-mini"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"status":"deprecated","cost":{"input":1.5,"output":9,"cache_read":0.15,"cache_write":0.083333},"canonical_model_id":"google/gemini-3.5-flash"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"gpt-5-mini":{"id":"gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":0.25,"output":2,"cache_read":0.025,"cache_write":0.25},"canonical_model_id":"openai/gpt-5-mini"},"magistral-medium":{"id":"magistral-medium","name":"Magistral Medium (latest)","description":"Mistral reasoning model for transparent analysis, math, and complex decisions","family":"magistral-medium","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-06","release_date":"2025-03-17","last_updated":"2025-03-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"status":"deprecated","cost":{"input":2,"output":5,"cache_read":2,"cache_write":2},"canonical_model_id":"mistral/magistral-medium-latest"},"gpt-4.1-nano":{"id":"gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"status":"deprecated","cost":{"input":0.1,"output":0.4,"cache_read":0.05,"cache_write":0.1},"canonical_model_id":"openai/gpt-4.1-nano"},"grok-4.5":{"id":"grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":131072},"status":"deprecated","cost":{"input":2,"output":6,"cache_read":0.5,"cache_write":2},"canonical_model_id":"xai/grok-4.5"},"qwen3.6-plus":{"id":"qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"status":"deprecated","cost":{"input":0.325,"output":1.95,"cache_read":0.065,"cache_write":0.40625},"canonical_model_id":"alibaba/qwen3.6-plus"},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":128000},"status":"deprecated","cost":{"input":0.2,"output":1.25,"cache_read":0.02,"cache_write":0.2},"canonical_model_id":"openai/gpt-5.4-nano"},"gemini-3.1-flash-lite":{"id":"gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65000},"status":"deprecated","cost":{"input":0.25,"output":1.5,"cache_read":0.03,"cache_write":0.25},"canonical_model_id":"google/gemini-3.1-flash-lite"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"status":"deprecated","cost":{"input":2.5,"output":15,"cache_read":0.25,"cache_write":3.125},"canonical_model_id":"openai/gpt-5.6-terra"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"status":"deprecated","cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":5},"canonical_model_id":"openai/gpt-5.5"},"ministral-14b":{"id":"ministral-14b","name":"Ministral 14B","description":"Compact multimodal Mistral model for local assistants, edge agents, and efficient tool use","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":131072},"status":"deprecated","cost":{"input":0.2,"output":0.2,"cache_read":0.2,"cache_write":0.2},"canonical_model_id":"mistral/ministral-14b"},"gpt-5-nano":{"id":"gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":0.05,"output":0.4,"cache_read":0.005,"cache_write":0.05},"canonical_model_id":"openai/gpt-5-nano"},"qwen3.6-max-preview":{"id":"qwen3.6-max-preview","name":"Qwen3.6 Max Preview","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":240000,"output":64000},"status":"deprecated","cost":{"input":1.04,"output":6.24,"cache_read":0.208,"cache_write":1.3},"canonical_model_id":"alibaba/qwen3.6-max-preview"},"gpt-4o-mini":{"id":"gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"status":"deprecated","cost":{"input":0.15,"output":0.6,"cache_read":0.075,"cache_write":0.15},"canonical_model_id":"openai/gpt-4o-mini"},"claude-opus-4-1":{"id":"claude-opus-4-1","name":"Claude Opus 4.1 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1"},"claude-opus-4-5":{"id":"claude-opus-4-5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"gemini-3.6-flash":{"id":"gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"status":"deprecated","cost":{"input":1.5,"output":7.5,"cache_read":0.15,"cache_write":1.5},"canonical_model_id":"google/gemini-3.6-flash"},"devstral-small-2":{"id":"devstral-small-2","name":"Devstral Small 2","description":"Compact multimodal coding model for repository exploration, file editing, and software agents","family":"devstral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":131072},"status":"deprecated","cost":{"input":0.1,"output":0.3,"cache_read":0.1,"cache_write":0.1},"canonical_model_id":"mistral/devstral-small-2"},"thinkingmachines/inkling-small":{"id":"thinkingmachines/inkling-small","name":"Inkling Small","description":"Multimodal MoE reasoning model (276B total, 12B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":0.5,"output":1.2,"cache_read":0.1,"cache_write":0.5},"canonical_model_id":"thinkingmachines/inkling-small"},"Qwen/Qwen3-8B":{"id":"Qwen/Qwen3-8B","name":"Qwen3 8B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-03-31","release_date":"2025-03-31","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":40960},"status":"deprecated","cost":{"input":0.2,"output":0.2,"cache_read":0.2,"cache_write":0.2}},"Qwen/Qwen2.5-Coder-0.5B":{"id":"Qwen/Qwen2.5-Coder-0.5B","name":"Qwen2.5-Coder-0.5B","description":"Tiny open Qwen code model for lightweight completion and on-device coding","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-11-12","last_updated":"2024-11-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0.1,"output":0.1,"cache_read":0.1,"cache_write":0.1},"canonical_model_id":"alibaba/qwen2.5-coder-0.5b"},"Qwen/Qwen3-1.7B-Base":{"id":"Qwen/Qwen3-1.7B-Base","name":"Qwen3 1.7B Base","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-03-31","last_updated":"2025-03-31","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0.1,"output":0.1,"cache_read":0.1,"cache_write":0.1}},"Qwen/Qwen3-32B":{"id":"Qwen/Qwen3-32B","name":"Qwen3 32B","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.9,"output":0.9,"cache_read":0.9,"cache_write":0.9},"canonical_model_id":"alibaba/qwen3-32b"},"Qwen/Qwen3.5-9B":{"id":"Qwen/Qwen3.5-9B","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0.3,"output":0.3,"cache_read":0.3,"cache_write":0.3},"canonical_model_id":"alibaba/qwen3.5-9b"},"Qwen/Qwen3-4B-Base":{"id":"Qwen/Qwen3-4B-Base","name":"Qwen3 4B Base","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-03-31","last_updated":"2025-03-31","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15}},"Qwen/Qwen3.6-27B":{"id":"Qwen/Qwen3.6-27B","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0.6,"output":0.6,"cache_read":0.6,"cache_write":0.6},"canonical_model_id":"alibaba/qwen3.6-27b"},"Qwen/Qwen3-235B-A22B-Instruct-2507":{"id":"Qwen/Qwen3-235B-A22B-Instruct-2507","name":"Qwen3 235B-A22B Instruct 2507","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"status":"deprecated","cost":{"input":1.2,"output":1.2,"cache_read":1.2,"cache_write":1.2},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"Qwen/Qwen3-4B-Instruct-2507":{"id":"Qwen/Qwen3-4B-Instruct-2507","name":"Qwen3 4B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-31","last_updated":"2025-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0.2,"output":0.2,"cache_read":0.2,"cache_write":0.2}},"Qwen/Qwen3.6-35B-A3B":{"id":"Qwen/Qwen3.6-35B-A3B","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"status":"deprecated","cost":{"input":0.14,"output":1,"cache_read":0.028,"cache_write":0.175},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"LiquidAI/LFM2-24B-A2B":{"id":"LiquidAI/LFM2-24B-A2B","name":"LFM2 24B A2B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","family":"liquid","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-01-31","last_updated":"2026-02-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0.03,"output":0.12,"cache_read":0.03,"cache_write":0.03}},"poolside/laguna-s-2.1":{"id":"poolside/laguna-s-2.1","name":"Laguna S 2.1","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":0.1,"output":0.2,"cache_read":0.01,"cache_write":0.1},"canonical_model_id":"poolside/laguna-s-2.1"},"HuggingFaceTB/SmolLM3-3B-Base":{"id":"HuggingFaceTB/SmolLM3-3B-Base","name":"SmolLM3 3B Base","description":"Tool-capable chat model for instruction following and agentic application workflows","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-06-30","last_updated":"2025-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15}},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"status":"deprecated","cost":{"input":0.15,"output":0.6,"cache_read":0.015,"cache_write":0.15},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":8192},"status":"deprecated","cost":{"input":0.07,"output":0.3,"cache_read":0.035,"cache_write":0.07},"canonical_model_id":"openai/gpt-oss-20b"},"pioneer/auto":{"id":"pioneer/auto","name":"Pioneer Auto","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2024-01-01","last_updated":"2025-06-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":4096},"status":"deprecated"},"zai-org/GLM-5.1":{"id":"zai-org/GLM-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202000,"output":131072},"status":"deprecated","cost":{"input":0.98,"output":3.08,"cache_read":0.182,"cache_write":0.98},"canonical_model_id":"zhipuai/glm-5.1"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1040000,"output":128000},"status":"deprecated","cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":1.4},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-5.2-Fast":{"id":"zai-org/GLM-5.2-Fast","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"status":"deprecated","cost":{"input":2.1,"output":6.6,"cache_read":0.21,"cache_write":2.1},"canonical_model_id":"zhipuai/glm-5.2"},"mistralai/Magistral-Small-2506":{"id":"mistralai/Magistral-Small-2506","name":"Magistral Small","description":"Open Mistral reasoning model for transparent step-by-step problem solving","family":"magistral","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2025-06-10","last_updated":"2025-06-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":64000},"status":"deprecated","cost":{"input":0.5,"output":1.5,"cache_read":0.5,"cache_write":0.5},"canonical_model_id":"mistral/magistral-small-2506"},"mistralai/Codestral-22B-v0.1":{"id":"mistralai/Codestral-22B-v0.1","name":"Codestral-22B-v0.1","description":"Open Mistral code model for fill-in-the-middle and 80+ programming languages","family":"codestral","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-05-29","last_updated":"2024-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"status":"deprecated","cost":{"input":0.3,"output":0.9,"cache_read":0.3,"cache_write":0.3},"canonical_model_id":"mistral/codestral-22b-v0.1"},"mistralai/Pixtral-12B-2409":{"id":"mistralai/Pixtral-12B-2409","name":"Pixtral 12B","description":"Mistral vision-language model for image understanding and multimodal chat","family":"pixtral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09","release_date":"2024-09-11","last_updated":"2024-09-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"status":"deprecated","cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15},"canonical_model_id":"mistral/pixtral-12b"},"mistralai/Mistral-Small-4-119B-2603":{"id":"mistralai/Mistral-Small-4-119B-2603","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":32000},"status":"deprecated","cost":{"input":0.15,"output":0.6,"cache_read":0.015,"cache_write":0.15},"canonical_model_id":"mistral/mistral-small-2603"},"mistralai/Mistral-Nemo-Instruct-2407":{"id":"mistralai/Mistral-Nemo-Instruct-2407","name":"Mistral Nemo","description":"Efficient Mistral-NVIDIA open model for multilingual chat and local deployment","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"status":"deprecated","cost":{"input":0.02,"output":0.03,"cache_read":0.02,"cache_write":0.02},"canonical_model_id":"mistral/mistral-nemo"},"mistralai/Mistral-7B-Instruct-v0.3":{"id":"mistralai/Mistral-7B-Instruct-v0.3","name":"Mistral 7B Instruct v0.3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2023-04-30","last_updated":"2023-04-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0.2,"output":0.2,"cache_read":0.2,"cache_write":0.2}},"mistralai/Ministral-8B-Instruct-2410":{"id":"mistralai/Ministral-8B-Instruct-2410","name":"Ministral 8B Instruct","description":"Efficient open Mistral edge model for on-device chat and function calling","family":"ministral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-10-16","last_updated":"2024-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"status":"deprecated","cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15},"canonical_model_id":"mistral/ministral-8b-instruct-2410"},"XiaomiMiMo/MiMo-V2.5-Pro":{"id":"XiaomiMiMo/MiMo-V2.5-Pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":131000},"status":"deprecated","cost":{"input":0.435,"output":0.87,"cache_read":0.0036,"cache_write":0.435},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"XiaomiMiMo/MiMo-V2.5":{"id":"XiaomiMiMo/MiMo-V2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":131072},"status":"deprecated","cost":{"input":0.14,"output":0.28,"cache_read":0.0028,"cache_write":0.14},"canonical_model_id":"xiaomi/mimo-v2.5"},"sakana/fugu-ultra":{"id":"sakana/fugu-ultra","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":5,"output":30,"cache_read":0.5,"cache_write":5},"canonical_model_id":"sakana/fugu-ultra"},"moonshotai/Kimi-K2.7-Code":{"id":"moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32768},"status":"deprecated","cost":{"input":0.95,"output":4,"cache_read":0.19,"cache_write":0.95},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"moonshotai/Kimi-K3-Fast":{"id":"moonshotai/Kimi-K3-Fast","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":4.5,"output":22.5,"cache_read":0.45,"cache_write":4.5},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":131072},"status":"deprecated","cost":{"input":0.95,"output":4,"cache_read":0.34,"cache_write":0.95},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/Kimi-K3":{"id":"moonshotai/Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3},"canonical_model_id":"moonshotai/kimi-k3"},"fastino/gliner2-multi-large-v1":{"id":"fastino/gliner2-multi-large-v1","name":"GLiNER2 Multi Large","description":"High-accuracy multilingual NER and span extraction.","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-11-30","last_updated":"2025-11-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0.03,"output":0,"cache_read":0.03,"cache_write":0.03}},"fastino/GLiNER-2.5-Decide":{"id":"fastino/GLiNER-2.5-Decide","name":"GLiNER-2.5-Decide","description":"Classification-tuned GLiNER2 large. Entities, relations, and JSON extraction still work.","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-09-24","last_updated":"2026-09-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0.03,"output":0,"cache_read":0.03,"cache_write":0.03}},"fastino/gliner2-base-v1":{"id":"fastino/gliner2-base-v1","name":"GLiNER2 Base","description":"Named entity recognition; zero-shot span extraction.","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-06-30","last_updated":"2025-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0.03,"output":0,"cache_read":0.03,"cache_write":0.03}},"fastino/gliguard-LLMGuardrails-300M":{"id":"fastino/gliguard-LLMGuardrails-300M","name":"GLiGuard LLM Guardrails 300M","description":"LLM safety, PII, and adversarial-attack guardrails; 300M-param encoder.","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15}},"fastino/gliner2-multi-v1":{"id":"fastino/gliner2-multi-v1","name":"GLiNER2 Multi","description":"Multilingual NER for cross-lingual extraction.","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-11-30","last_updated":"2025-11-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0.03,"output":0,"cache_read":0.03,"cache_write":0.03}},"fastino/gliguard-PII-multi":{"id":"fastino/gliguard-PII-multi","name":"GLiNER2-Guardrails-PII-Multi","description":"A 300M-parameter multilingual model that runs LLM safety moderation and PII detection in a single forward pass.","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15}},"fastino/gliner2.5-multi-v1":{"id":"fastino/gliner2.5-multi-v1","name":"GLiNER 2.5 Multi","description":"Multilingual boundary NER and span extraction; non-trainable encoder.","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-08-24","last_updated":"2026-08-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":4096},"cost":{"input":0.03,"output":0,"cache_read":0.03,"cache_write":0.03}},"fastino/gliner2-large-v1":{"id":"fastino/gliner2-large-v1","name":"GLiNER2 Large","description":"Higher-accuracy NER; broader entity coverage.","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-06-30","last_updated":"2025-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0.03,"output":0,"cache_read":0.03,"cache_write":0.03}},"fastino/gliner2.5-base-v1":{"id":"fastino/gliner2.5-base-v1","name":"GLiNER 2.5 Base","description":"English boundary NER and structured extraction with LoRA fine-tuning.","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-08-24","last_updated":"2026-08-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":4096},"cost":{"input":0.03,"output":0,"cache_read":0.03,"cache_write":0.03}},"fastino/gliner2-privacy-filter-PII-multi":{"id":"fastino/gliner2-privacy-filter-PII-multi","name":"GLiNER2 Privacy Filter PII (Multi)","description":"Multilingual PII entity detection across 40+ languages; non-trainable encoder.","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0.03,"output":0,"cache_read":0.03,"cache_write":0.03}},"nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-FP8":{"id":"nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-FP8","name":"Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32000},"status":"deprecated","cost":{"input":0.09,"output":0.45,"cache_read":0.09,"cache_write":0.09},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16":{"id":"nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16","name":"Nemotron 3 Nano 30B A3B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-06-25","release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"status":"deprecated","cost":{"input":0.05,"output":0.2,"cache_read":0.05,"cache_write":0.05},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16":{"id":"nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16","name":"Nemotron 3.5 Lightning 30B A3B","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":4096},"cost":{"input":0.07,"output":0.2,"cache_read":0.035,"cache_write":0.07},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-NVFP4":{"id":"nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-NVFP4","name":"Nemotron 3.5 Super VL 120B A12B","description":"NVIDIA vision-language reasoning model for text, image, and video understanding and agentic tool use","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":4096},"cost":{"input":0.08,"output":0.45,"cache_read":0.04,"cache_write":0.08},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16":{"id":"nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65000},"status":"deprecated","cost":{"input":0.5,"output":2.5,"cache_read":0.15,"cache_write":0.5},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"meta-llama/Llama-3.3-70B-Instruct":{"id":"meta-llama/Llama-3.3-70B-Instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":16384},"status":"deprecated","cost":{"input":0.9,"output":0.9,"cache_read":0.9,"cache_write":0.9},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"meta-llama/Llama-3.1-8B-Instruct":{"id":"meta-llama/Llama-3.1-8B-Instruct","name":"Llama 3.1 8B Instruct","description":"Compact open Llama model for lightweight chat, drafting, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"status":"deprecated","cost":{"input":0.2,"output":0.2,"cache_read":0.2,"cache_write":0.2},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"meta-llama/Llama-3.2-1B-Instruct":{"id":"meta-llama/Llama-3.2-1B-Instruct","name":"Llama 3.2 1B Instruct","description":"Compact instruction-tuned Llama model for multilingual dialogue and on-device assistants","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":60000},"status":"deprecated","cost":{"input":0.1,"output":0.201,"cache_read":0.1,"cache_write":0.1},"canonical_model_id":"meta/llama-3.2-1b-instruct"},"meta-llama/Llama-3.2-1B":{"id":"meta-llama/Llama-3.2-1B","name":"Llama-3.2-1B","description":"Compact open Llama base model for lightweight and on-device use","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"status":"deprecated","cost":{"input":0.1,"output":0.1,"cache_read":0.1,"cache_write":0.1},"canonical_model_id":"meta/llama-3.2-1b"},"meta-llama/Llama-3.2-3B":{"id":"meta-llama/Llama-3.2-3B","name":"Llama-3.2-3B","description":"Small open Llama base model for lightweight text generation and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"status":"deprecated","cost":{"input":0.1,"output":0.1,"cache_read":0.1,"cache_write":0.1},"canonical_model_id":"meta/llama-3.2-3b"},"meta-llama/Llama-3.2-3B-Instruct":{"id":"meta-llama/Llama-3.2-3B-Instruct","name":"Llama 3.2 3B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-31","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":80000},"status":"deprecated","cost":{"input":0.1,"output":0.335,"cache_read":0.1,"cache_write":0.1}},"MiniMaxAI/MiniMax-M2.7":{"id":"MiniMaxAI/MiniMax-M2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131000},"status":"deprecated","cost":{"input":0.279,"output":1.2,"cache_read":0.279,"cache_write":0.279},"canonical_model_id":"minimax/MiniMax-M2.7"},"MiniMaxAI/MiniMax-M3":{"id":"MiniMaxAI/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":0.3},"canonical_model_id":"minimax/MiniMax-M3"},"deepseek-ai/DeepSeek-V4-Pro":{"id":"deepseek-ai/DeepSeek-V4-Pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":0.435,"output":0.87,"cache_read":0.003625,"cache_write":0.435},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek-ai/DeepSeek-V4-Flash":{"id":"deepseek-ai/DeepSeek-V4-Flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":0.1,"output":0.2,"cache_read":0.0197,"cache_write":0.1},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek-ai/DeepSeek-V3":{"id":"deepseek-ai/DeepSeek-V3","name":"DeepSeek-V3","description":"Open DeepSeek MoE chat model for coding, math, and general reasoning","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2024-12-26","last_updated":"2024-12-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":8192},"status":"deprecated","cost":{"input":0.27,"output":1.12,"cache_read":0.135,"cache_write":0.27},"canonical_model_id":"deepseek/deepseek-v3"},"deepseek-ai/DeepSeek-V3.1":{"id":"deepseek-ai/DeepSeek-V3.1","name":"DeepSeek-V3.1","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":131072},"status":"deprecated","cost":{"input":0.56,"output":1.68,"cache_read":0.56,"cache_write":0.56},"canonical_model_id":"deepseek/deepseek-v3.1"},"meta/muse-spark-1.1":{"id":"meta/muse-spark-1.1","name":"Muse Spark 1.1","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":1.25,"output":4.25,"cache_read":0.15,"cache_write":1.25},"canonical_model_id":"meta/muse-spark-1.1"},"google/gemma-3-4b-pt":{"id":"google/gemma-3-4b-pt","name":"Gemma 3 4B (Pretrained)","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-02-28","last_updated":"2025-02-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0.15,"output":0.15,"cache_read":0.15,"cache_write":0.15}},"google/gemma-4-E4B-it":{"id":"google/gemma-4-E4B-it","name":"Gemma 4 E4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0.2,"output":0.2,"cache_read":0.2,"cache_write":0.2},"canonical_model_id":"google/gemma-4-E4B-it"},"google/gemma-4-31B-it":{"id":"google/gemma-4-31B-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0.5,"output":0.5,"cache_read":0.5,"cache_write":0.5},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemma-4-E2B-it":{"id":"google/gemma-4-E2B-it","name":"Gemma 4 E2B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0.1,"output":0.1,"cache_read":0.1,"cache_write":0.1},"canonical_model_id":"google/gemma-4-E2B-it"},"google/diffusiongemma-26B-A4B-it":{"id":"google/diffusiongemma-26B-A4B-it","name":"DiffusionGemma 26B-A4B IT","description":"Gemma 4 based discrete text diffusion model for fast chat, reasoning, and tool use","family":"gemma","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-06-09","last_updated":"2026-07-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"status":"deprecated","cost":{"input":0.5,"output":0.5,"cache_read":0.5,"cache_write":0.5},"canonical_model_id":"google/diffusiongemma-26b-a4b-it"},"google/gemma-4-12B-it":{"id":"google/gemma-4-12B-it","name":"Gemma 4 12B IT","description":"Compact Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"status":"deprecated","cost":{"input":0.25,"output":0.25,"cache_read":0.25,"cache_write":0.25},"canonical_model_id":"google/gemma-4-12b-it"}}},"pareto":{"id":"pareto","env":["PARETO_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.paretoinference.com/v1","name":"Pareto Inference","doc":"https://docs.paretoinference.com/","models":{"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.06,"output":0.2,"cache_read":0.012},"canonical_model_id":"zhipuai/glm-5.3-flash"}}},"synthetic":{"id":"synthetic","env":["SYNTHETIC_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.synthetic.new/openai/v1","name":"Synthetic","doc":"https://synthetic.new/pricing","models":{"hf:deepseek-ai/DeepSeek-V4.1-Flash":{"id":"hf:deepseek-ai/DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","xhigh","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":65536},"cost":{"input":0.6,"output":1.2,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"hf:deepseek-ai/DeepSeek-V4.1-Flash-1017":{"id":"hf:deepseek-ai/DeepSeek-V4.1-Flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","xhigh","max"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":65536},"cost":{"input":0.6,"output":1.2,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"hf:MiniMaxAI/MiniMax-M3":{"id":"hf:MiniMaxAI/MiniMax-M3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":65536},"status":"deprecated","cost":{"input":0.6,"output":1.2,"cache_read":0.6},"canonical_model_id":"minimax/MiniMax-M3"},"hf:Qwen/Qwen3.6-27B":{"id":"hf:Qwen/Qwen3.6-27B","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","cost":{"input":0.45,"output":3.6,"cache_read":0.45},"canonical_model_id":"alibaba/qwen3.6-27b"},"hf:zai-org/GLM-4.7-Flash":{"id":"hf:zai-org/GLM-4.7-Flash","name":"GLM-4.7-Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":196608,"output":65536},"cost":{"input":0.1,"output":0.5,"cache_read":0.02},"canonical_model_id":"zhipuai/glm-4.7-flash"},"hf:zai-org/GLM-5.3-Flash":{"id":"hf:zai-org/GLM-5.3-Flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":65536},"cost":{"input":0.15,"output":0.5,"cache_read":0.04},"canonical_model_id":"zhipuai/glm-5.3-flash"},"hf:zai-org/GLM-5.2":{"id":"hf:zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":65536},"status":"deprecated","cost":{"input":1.4,"output":4.4,"cache_read":1.4},"canonical_model_id":"zhipuai/glm-5.2"},"hf:zai-org/GLM-5.3":{"id":"hf:zai-org/GLM-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":65536},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"hf:nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-NVFP4":{"id":"hf:nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-NVFP4","name":"Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.3,"output":1,"cache_read":0.06},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"hf:openai/gpt-oss-120b":{"id":"hf:openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.1,"output":0.1,"cache_read":0.02},"canonical_model_id":"openai/gpt-oss-120b"},"hf:moonshotai/Kimi-K2.7-Code":{"id":"hf:moonshotai/Kimi-K2.7-Code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","cost":{"input":0.95,"output":4,"cache_read":0.95},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"hf:moonshotai/Kimi-K3":{"id":"hf:moonshotai/Kimi-K3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":65536},"cost":{"input":3,"output":15,"cache_read":0.45},"canonical_model_id":"moonshotai/kimi-k3"}}},"melious":{"id":"melious","env":["MELIOUS_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.melious.ai/v1","name":"Melious","doc":"https://melious.ai/docs/reference/models","models":{"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":3.196275,"output":15.981375,"cache_read":0.841125},"canonical_model_id":"moonshotai/kimi-k3"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.23184,"output":1.1592,"cache_read":0.011592},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"glm-5":{"id":"glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":203000,"output":131072},"status":"deprecated","cost":{"input":1.10124,"output":3.36168,"cache_read":0.266616},"canonical_model_id":"zhipuai/glm-5"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.1592,"output":3.4776,"cache_read":0.23184},"canonical_model_id":"zhipuai/glm-5.3"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.11592,"output":0.46368,"cache_read":0.023184},"canonical_model_id":"zhipuai/glm-5.3-flash"},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":262000},"status":"deprecated","cost":{"input":0.5796,"output":2.95596,"cache_read":0.139104},"canonical_model_id":"moonshotai/kimi-k2.5"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.78505,"output":3.3645,"cache_read":0.280375},"canonical_model_id":"moonshotai/kimi-k2.6"},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":203000,"output":131072},"status":"deprecated","cost":{"input":1.50696,"output":4.6368,"cache_read":0.370944},"canonical_model_id":"zhipuai/glm-5.1"},"deepseek-r1-0528":{"id":"deepseek-r1-0528","name":"DeepSeek-R1","description":"Classic open reasoning model for transparent math, coding, and deliberate problem solving","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-07","release_date":"2025-01-20","last_updated":"2025-05-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":32768},"status":"deprecated","cost":{"input":0.69552,"output":2.78208,"cache_read":0.185472},"canonical_model_id":"deepseek/deepseek-r1"},"deepseek-v4.1-flash-1017":{"id":"deepseek-v4.1-flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.33675,"output":1.347,"cache_read":0.033675},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.11592,"output":0.2898,"cache_read":0.023184},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.728975,"output":3.644875,"cache_read":0.190655},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"deepseek-v3.2":{"id":"deepseek-v3.2","name":"DeepSeek V3.2","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"output":64000},"status":"deprecated","cost":{"input":0.34776,"output":0.5796,"cache_read":0.092736},"canonical_model_id":"deepseek/deepseek-v3.2"}}},"xiaomi-token-plan-sgp":{"id":"xiaomi-token-plan-sgp","env":["XIAOMI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://token-plan-sgp.xiaomimimo.com/v1","name":"Xiaomi Token Plan (Singapore)","doc":"https://platform.xiaomimimo.com/#/docs","models":{"mimo-v2.6-flash":{"id":"mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"mimo-v2.6-pro":{"id":"mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"mimo-v2-tts":{"id":"mimo-v2-tts","type":"speech","name":"MiMo-V2-TTS","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mimo","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":8192,"output":8192},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"xiaomi/mimo-v2-tts"},"mimo-v2.5":{"id":"mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.5"},"mimo-v2.5-tts":{"id":"mimo-v2.5-tts","type":"speech","name":"MiMo-V2.5-TTS","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mimo","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":8192,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"xiaomi/mimo-v2.5-tts"},"mimo-v2.5-pro":{"id":"mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"mimo-v2-pro":{"id":"mimo-v2-pro","name":"MiMo-V2-Pro","description":"Earlier MiMo Pro model for multimodal agents, reasoning, and code tasks","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2-pro"},"mimo-v2.5-tts-voicedesign":{"id":"mimo-v2.5-tts-voicedesign","type":"speech","name":"MiMo-V2.5-TTS-VoiceDesign","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mimo","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":8192,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"xiaomi/mimo-v2.5-tts-voicedesign"},"mimo-v2.5-tts-voiceclone":{"id":"mimo-v2.5-tts-voiceclone","type":"speech","name":"MiMo-V2.5-TTS-VoiceClone","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"mimo","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":8192,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"xiaomi/mimo-v2.5-tts-voiceclone"}}},"atomic-chat":{"id":"atomic-chat","env":["ATOMIC_CHAT_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"http://127.0.0.1:1337/v1","name":"Atomic Chat","doc":"https://atomic.chat","models":{"Qwen3_5-9B-Q4_K_M":{"id":"Qwen3_5-9B-Q4_K_M","name":"Qwen 3.5 9B (Q4_K_M)","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3.5-9b"},"gemma-4-E4B-it-IQ4_XS":{"id":"gemma-4-E4B-it-IQ4_XS","name":"Gemma 4 E4B Instruct (IQ4_XS)","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemma-4-E4B-it"},"Qwen3_5-9B-MLX-4bit":{"id":"Qwen3_5-9B-MLX-4bit","name":"Qwen 3.5 9B (MLX 4-bit)","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3.5-9b"},"gemma-4-E4B-it-MLX-4bit":{"id":"gemma-4-E4B-it-MLX-4bit","name":"Gemma 4 E4B Instruct (MLX 4-bit)","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemma-4-E4B-it"},"Meta-Llama-3_1-8B-Instruct-GGUF":{"id":"Meta-Llama-3_1-8B-Instruct-GGUF","name":"Meta Llama 3.1 8B Instruct (GGUF)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":4096},"cost":{"input":0,"output":0},"canonical_model_id":"meta/llama-3.1-8b-instruct"}}},"pendra":{"id":"pendra","env":["PENDRA_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.pendra.ai/api/v1","name":"Pendra","doc":"https://pendra.ai/docs/integrations/opencode","models":{"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-v4-flash"},"qwen3-coder:30b":{"id":"qwen3-coder:30b","name":"Qwen3-Coder 30B-A3B Instruct","description":"Smaller Qwen coder for efficient local agents and repo-level fixes","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-31","last_updated":"2025-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"glm-4.7-flash":{"id":"glm-4.7-flash","name":"GLM-4.7-Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-4.7-flash"},"qwen3.6:27b":{"id":"qwen3.6:27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3.6-27b"},"gpt-oss:120b":{"id":"gpt-oss:120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"openai/gpt-oss-120b"},"llama3.3:70b":{"id":"llama3.3:70b","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":0,"output":0},"canonical_model_id":"meta/llama-3.3-70b-instruct"}}},"sarvam":{"id":"sarvam","env":["SARVAM_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.sarvam.ai/v1","name":"Sarvam AI","doc":"https://docs.sarvam.ai/api-reference-docs/getting-started/models","models":{"sarvam-30b":{"id":"sarvam-30b","name":"Sarvam-30B","description":"Efficient Indian-language reasoning model for chat, coding, and multilingual work","family":"sarvam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-18","last_updated":"2026-02-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"status":"deprecated","canonical_model_id":"sarvam/sarvam-30b"},"sarvam-105b":{"id":"sarvam-105b","name":"Sarvam-105B","description":"Flagship Indian-language reasoning model for enterprise multilingual applications","family":"sarvam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-18","last_updated":"2026-02-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.15790269,"output":0.63161075,"cache_read":0.05263423},"canonical_model_id":"sarvam/sarvam-105b"}}},"inception":{"id":"inception","env":["INCEPTION_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.inceptionlabs.ai/v1/","name":"Inception","doc":"https://docs.inceptionlabs.ai/get-started/models","models":{"mercury-edit-2":{"id":"mercury-edit-2","name":"Mercury Edit 2","description":"Code editing dLLM for autocomplete (FIM) and next-edit suggestions","family":"mercury","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-03-30","last_updated":"2026-03-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":8192},"cost":{"input":0.25,"output":0.75,"cache_read":0.025},"canonical_model_id":"inception/mercury-edit-2"},"mercury-2":{"id":"mercury-2","name":"Mercury 2","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-02-24","last_updated":"2026-02-24","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":50000},"cost":{"input":0.25,"output":0.75,"cache_read":0.025},"canonical_model_id":"inception/mercury-2"},"mercury-3":{"id":"mercury-3","name":"Mercury 3","description":"Inception's diffusion reasoning model for chat, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-16","last_updated":"2026-10-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.1,"output":0.35,"cache_read":0.01},"canonical_model_id":"inception/mercury-3"},"mercury-2.5":{"id":"mercury-2.5","name":"Mercury 2.5","description":"Mercury 2.5 is the fastest reasoning LLM, and the latest diffusion LLM (dLLM) from Inception","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-11-01","release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":260000,"output":65536},"cost":{"input":0.2,"output":0.75,"cache_read":0.02},"canonical_model_id":"inception/mercury-2.5"}}},"hyper":{"id":"hyper","env":["HYPER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://hyper.charm.land/v1","name":"Charm Hyper","doc":"https://hyper.charm.land","models":{"prism":{"id":"prism","name":"Prism","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":true,"release_date":"1970-01-01","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":16000},"cost":{"input":3.2664,"output":16.332,"cache_read":0.32664}},"kimi-k2-thinking":{"id":"kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Thinking Kimi model for slower research passes, planning, and hard technical questions","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":26214},"cost":{"input":0.6,"output":2.5,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":13107},"cost":{"input":0.178,"output":0.68,"cache_read":0.089},"canonical_model_id":"openai/gpt-oss-120b"},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-flash"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":16000},"cost":{"input":3.2664,"output":16.332,"cache_read":0.32664},"canonical_model_id":"moonshotai/kimi-k3"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":32768},"cost":{"input":1.52432,"output":4.79072,"cache_read":0.152432},"canonical_model_id":"zhipuai/glm-5.2"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":0.33,"output":1.31,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":1.52432,"output":4.79072,"cache_read":0.283088},"canonical_model_id":"zhipuai/glm-5.3"},"qwen3.8-2.4t-a95b":{"id":"qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max Preview","description":"Preview Qwen flagship for million-token multimodal reasoning and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-19","last_updated":"2026-07-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-max-preview"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.16332,"output":0.5444,"cache_read":0.031575},"canonical_model_id":"zhipuai/glm-5.3-flash"},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":1.2,"output":4.8,"cache_read":0.24},"canonical_model_id":"alibaba/qwen3.7-plus"},"qwen3.7-max":{"id":"qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":2.5,"output":7.5,"cache_read":0.5},"canonical_model_id":"alibaba/qwen3.7-max"},"gemma-4-26b-a4b-it":{"id":"gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":25600},"cost":{"input":0.098,"output":0.334,"cache_read":0.049},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"minimax-m2.7":{"id":"minimax-m2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262100,"output":6553},"cost":{"input":0.484,"output":1.852,"cache_read":0.242},"canonical_model_id":"minimax/MiniMax-M2.7"},"inkling":{"id":"inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":1.0888,"output":4.40964,"cache_read":0.185096},"canonical_model_id":"thinkingmachines/inkling"},"qwen3.7-flash":{"id":"qwen3.7-flash","name":"Qwen3.7 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":991808,"output":64000},"cost":{"input":0.2,"output":0.8,"cache_read":0.04},"canonical_model_id":"alibaba/qwen3.7-flash"},"qwen3.8-27b":{"id":"qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.5,"output":3,"cache_read":0.1},"canonical_model_id":"alibaba/qwen3.8-27b"},"deepseek-v4.1-flash-1017":{"id":"deepseek-v4.1-flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":262144},"cost":{"input":0.33,"output":1.31,"cache_read":0.03},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek-v4-flash-0731":{"id":"deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.44,"output":1.32,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"output":512000},"cost":{"input":0.32664,"output":1.30656,"cache_read":0.064239},"canonical_model_id":"minimax/MiniMax-M3"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16000},"cost":{"input":1.03436,"output":4.3552,"cache_read":0.206872},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"deepseek-v4-pro-0813":{"id":"deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":262144},"cost":{"input":1.437216,"output":4.311648,"cache_read":0.047907},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"}}},"stepfun-ai-step-plan":{"id":"stepfun-ai-step-plan","env":["STEPFUN_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.stepfun.ai/step_plan/v1","name":"StepFun Step Plan (Global)","doc":"https://platform.stepfun.ai/docs/en/step-plan/integrations/reasoning-api","models":{"step-3.5-flash":{"id":"step-3.5-flash","name":"Step 3.5 Flash","description":"StepFun flash lane for quick multimodal reasoning and coding assistance","family":"step","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"canonical_model_id":"stepfun/step-3.5-flash"},"step-5-preview":{"id":"step-5-preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":65536},"canonical_model_id":"stepfun/step-5-preview"},"step-3.7-flash":{"id":"step-3.7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"canonical_model_id":"stepfun/step-3.7-flash"},"step-3.5-flash-2603":{"id":"step-3.5-flash-2603","name":"Step 3.5 Flash 2603","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","family":"step","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"canonical_model_id":"stepfun/step-3.5-flash-2603"}}},"perplexity":{"id":"perplexity","env":["PERPLEXITY_API_KEY"],"npm":"@ai-sdk/perplexity","name":"Perplexity","doc":"https://docs.perplexity.ai","models":{"sonar-reasoning-pro":{"id":"sonar-reasoning-pro","name":"Sonar Reasoning Pro","description":"Web-grounded Sonar for multi-step research questions that need cited reasoning","family":"sonar-reasoning","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":2,"output":8},"canonical_model_id":"perplexity/sonar-reasoning-pro"},"sonar-deep-research":{"id":"sonar-deep-research","name":"Perplexity Sonar Deep Research","description":"Sonar search model for current answers, retrieval, and citation-backed chat","family":"sonar","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":false,"temperature":false,"knowledge":"2025-01","release_date":"2025-02-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32768},"status":"deprecated","cost":{"input":2,"output":8,"reasoning":3},"canonical_model_id":"perplexity/sonar-deep-research"},"sonar":{"id":"sonar","name":"Sonar","description":"Fast web-grounded Sonar for current answers, citations, and lightweight retrieval","family":"sonar","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":1,"output":1},"canonical_model_id":"perplexity/sonar"},"sonar-pro":{"id":"sonar-pro","name":"Sonar Pro","description":"Deeper Sonar search model with broader retrieval and stronger synthesis","family":"sonar-pro","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"status":"deprecated","cost":{"input":3,"output":15},"canonical_model_id":"perplexity/sonar-pro"}}},"clarifai":{"id":"clarifai","env":["CLARIFAI_PAT"],"npm":"@ai-sdk/openai-compatible","api":"https://api.clarifai.com/v2/ext/openai/v1","name":"Clarifai","doc":"https://docs.clarifai.com/compute/inference/","models":{"arcee_ai/AFM/models/trinity-mini":{"id":"arcee_ai/AFM/models/trinity-mini","name":"Trinity Mini","description":"Reasoning-tuned 26B MoE model with 3B active parameters for agents, tools, and multi-step workloads","family":"trinity","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-12-01","last_updated":"2026-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.045,"output":0.15},"canonical_model_id":"arcee-ai/trinity-mini"},"openai/chat-completion/models/gpt-oss-20b":{"id":"openai/chat-completion/models/gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.045,"output":0.18},"canonical_model_id":"openai/gpt-oss-20b"},"openai/chat-completion/models/gpt-oss-120b-high-throughput":{"id":"openai/chat-completion/models/gpt-oss-120b-high-throughput","name":"GPT OSS 120B High Throughput","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.09,"output":0.36},"canonical_model_id":"openai/gpt-oss-120b"},"clarifai/main/models/mm-poly-8b":{"id":"clarifai/main/models/mm-poly-8b","name":"MM Poly 8B","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"mm-poly","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-06","last_updated":"2026-02-25","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":4096},"cost":{"input":0.658,"output":1.11}},"minimaxai/chat-completion/models/MiniMax-M2_5-high-throughput":{"id":"minimaxai/chat-completion/models/MiniMax-M2_5-high-throughput","name":"MiniMax-M2.5 High Throughput","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2},"canonical_model_id":"minimax/MiniMax-M2.5"},"mistralai/completion/models/Ministral-3-14B-Reasoning-2512":{"id":"mistralai/completion/models/Ministral-3-14B-Reasoning-2512","name":"Ministral 3 14B Reasoning 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-01","last_updated":"2025-12-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":2.5,"output":1.7}},"mistralai/completion/models/Ministral-3-3B-Reasoning-2512":{"id":"mistralai/completion/models/Ministral-3-3B-Reasoning-2512","name":"Ministral 3 3B Reasoning 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-12","last_updated":"2026-02-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.039,"output":0.54825}},"qwen/qwenLM/models/Qwen3-30B-A3B-Instruct-2507":{"id":"qwen/qwenLM/models/Qwen3-30B-A3B-Instruct-2507","name":"Qwen3 30B A3B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.3,"output":0.5},"canonical_model_id":"alibaba/qwen3-30b-a3b-instruct-2507"},"qwen/qwenLM/models/Qwen3-30B-A3B-Thinking-2507":{"id":"qwen/qwenLM/models/Qwen3-30B-A3B-Thinking-2507","name":"Qwen3 30B A3B Thinking 2507","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-31","last_updated":"2026-02-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.36,"output":1.3}},"qwen/qwenCoder/models/Qwen3-Coder-30B-A3B-Instruct":{"id":"qwen/qwenCoder/models/Qwen3-Coder-30B-A3B-Instruct","name":"Qwen3 Coder 30B A3B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-31","last_updated":"2025-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.11458,"output":0.74812},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"moonshotai/chat-completion/models/Kimi-K2_6":{"id":"moonshotai/chat-completion/models/Kimi-K2_6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4},"canonical_model_id":"moonshotai/kimi-k2.6"},"deepseek-ai/deepseek-ocr/models/DeepSeek-OCR":{"id":"deepseek-ai/deepseek-ocr/models/DeepSeek-OCR","name":"DeepSeek OCR","description":"OCR model for extracting structured text from documents and screenshots","family":"deepseek","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-10-20","last_updated":"2026-02-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":8192},"cost":{"input":0.2,"output":0.7}}}},"zhipuai-coding-plan":{"id":"zhipuai-coding-plan","env":["ZHIPU_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://open.bigmodel.cn/api/coding/paas/v4","name":"Zhipu AI Coding Plan","doc":"https://docs.bigmodel.cn/cn/coding-plan/overview","models":{"glm-5.3-highspeed":{"id":"glm-5.3-highspeed","name":"GLM-5.3 Highspeed","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"glm-4.6v":{"id":"glm-4.6v","name":"GLM-4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.6v"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"}}},"nearai":{"id":"nearai","env":["NEARAI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://cloud-api.near.ai/v1","name":"NEAR AI Cloud","doc":"https://docs.near.ai/","models":{"Qwen/Qwen3.8-27B":{"id":"Qwen/Qwen3.8-27B","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.04,"output":1.35,"cache_read":0.018},"canonical_model_id":"alibaba/qwen3.8-27b"},"Qwen/Qwen3.6-35B-A3B-FP8":{"id":"Qwen/Qwen3.6-35B-A3B-FP8","name":"Qwen 3.6 35B A3B FP8","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":8192},"cost":{"input":0.17,"output":1.1,"cache_read":0.056},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"Qwen/Qwen3-VL-30B-A3B-Instruct":{"id":"Qwen/Qwen3-VL-30B-A3B-Instruct","name":"Qwen3-VL 30B-A3B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-04","last_updated":"2025-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":8192},"cost":{"input":0.15,"output":0.55,"cache_read":0.03},"canonical_model_id":"alibaba/qwen3-vl-30b-a3b-instruct"},"Qwen/Qwen3-Reranker-0.6B":{"id":"Qwen/Qwen3-Reranker-0.6B","type":"reranking","name":"Qwen3 Reranker 0.6B","description":"Reranking model for improving retrieval quality in search and recommendation systems","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":1024},"cost":{"input":0.01,"output":0.01},"canonical_model_id":"alibaba/qwen3-reranker-0.6b"},"Qwen/Qwen3-Embedding-0.6B":{"id":"Qwen/Qwen3-Embedding-0.6B","type":"embedding","name":"Qwen3 Embedding 0.6B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":1024},"cost":{"input":0.01,"output":0.01},"canonical_model_id":"alibaba/qwen3-embedding-0.6b"},"anthropic/claude-sonnet-4-5":{"id":"anthropic/claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-opus-4-7":{"id":"anthropic/claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic/claude-opus-4-6":{"id":"anthropic/claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-opus-5-5":{"id":"anthropic/claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-haiku-4-5":{"id":"anthropic/claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-haiku-5-5":{"id":"anthropic/claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-fable-5-1":{"id":"anthropic/claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-opus-4-8":{"id":"anthropic/claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-sonnet-4-6":{"id":"anthropic/claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-sonnet-5-5":{"id":"anthropic/claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"x-ai/grok-4.7":{"id":"x-ai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.7"},"x-ai/grok-4.6":{"id":"x-ai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2},"canonical_model_id":"openai/gpt-6-sol"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/o3":{"id":"openai/o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"openai/whisper-large-v3":{"id":"openai/whisper-large-v3","type":"transcription","name":"Whisper Large v3","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"whisper","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2023-11-06","last_updated":"2023-11-06","modalities":{"input":["audio"],"output":["text"]},"open_weights":true,"limit":{"context":448,"output":448},"cost":{"input":0.01,"output":0.01},"canonical_model_id":"openai/whisper-large-v3"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"openai/o4-mini":{"id":"openai/o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.275},"canonical_model_id":"openai/o4-mini"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1},"canonical_model_id":"openai/gpt-6-astra"},"qwen/qwen3.5-397b-a17b":{"id":"qwen/qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.5,"output":3.3,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2.8,"output":7.5},"canonical_model_id":"alibaba/qwen3.7-max"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3.3,"output":16.5,"cache_read":0.33},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.81,"output":3.85,"cache_read":0.41},"canonical_model_id":"moonshotai/kimi-k2.6"},"deepseek/deepseek-v4.1-flash-1017":{"id":"deepseek/deepseek-v4.1-flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek/deepseek-v3.2":{"id":"deepseek/deepseek-v3.2","name":"DeepSeek V3.2","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":64000},"cost":{"input":1.1,"output":1.1,"cache_read":0.55},"canonical_model_id":"deepseek/deepseek-v3.2"},"black-forest-labs/FLUX.2-klein-4B":{"id":"black-forest-labs/FLUX.2-klein-4B","type":"image","name":"FLUX.2 Klein 4B","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"flux","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-01-15","last_updated":"2026-01-15","modalities":{"input":["text","image"],"output":["image"]},"open_weights":true,"limit":{"context":0,"output":0},"canonical_model_id":"black-forest-labs/flux-2-klein-4b"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.08,"output":0.5,"cache_read":0.012},"canonical_model_id":"zhipuai/glm-5.3-flash"},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"input_audio":0.3},"canonical_model_id":"google/gemini-2.5-flash-lite"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"input_audio":1},"canonical_model_id":"google/gemini-2.5-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite"}}},"amd":{"id":"amd","env":["AMD_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://developer.amd.com.cn/radeon/api/v1","name":"AMD","doc":"https://developer.amd.com.cn/radeon/tokenfactory","models":{"MiniCPM-V-4.7-1B":{"id":"MiniCPM-V-4.7-1B","name":"MiniCPM-V 4.7 1B","description":"Compact MiniCPM-V model for single-image, multi-image and video understanding","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"openbmb/minicpm-v-4.7-1b"},"Gemma-4-31B-IT":{"id":"Gemma-4-31B-IT","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"google/gemma-4-31b-it"},"MiMo-V2.6-Flash":{"id":"MiMo-V2.6-Flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"DeepSeek-V4.1-Flash":{"id":"DeepSeek-V4.1-Flash","name":"DeepSeek V4.1 Flash","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"MiniCPM5-2B":{"id":"MiniCPM5-2B","name":"MiniCPM5-2B","description":"Dense 2B-class open-source model for on-device and resource-constrained use, with native long-context support, tool calling, and agentic tasks","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-09-06","last_updated":"2026-09-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"openbmb/minicpm5-2b"},"DeepSeek-V4-Flash-Vision-Exp":{"id":"DeepSeek-V4-Flash-Vision-Exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"GLM-5.3-Flash":{"id":"GLM-5.3-Flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"Qwen3.8-27B":{"id":"Qwen3.8-27B","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"alibaba/qwen3.8-27b"},"MiniCPM-V-4.7-35B-A3B":{"id":"MiniCPM-V-4.7-35B-A3B","name":"MiniCPM-V 4.7 35B-A3B","description":"First MoE MiniCPM-V model for single-image, multi-image and video understanding","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"openbmb/minicpm-v-4.7-35b-a3b"},"DeepSeek-V4-Flash":{"id":"DeepSeek-V4-Flash","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"Qwen3.8-Flash-Next":{"id":"Qwen3.8-Flash-Next","name":"Qwen3.8 Flash Next","description":"Open-weight experimental preview of the Qwen4 architecture: hybrid-attention MoE (125B total, 6B active) with vision encoder for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"alibaba/qwen3.8-flash-next"}}},"hetzner":{"id":"hetzner","env":["HETZNER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://inference.hetzner.com/api/v1","name":"Hetzner","doc":"https://experiments.hetzner.com/docs/inference","models":{"Qwen3.8-27B":{"id":"Qwen3.8-27B","name":"Qwen3.8-27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"beta","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"alibaba/qwen3.8-27b"},"Qwen/Qwen3.6-35B-A3B-FP8":{"id":"Qwen/Qwen3.6-35B-A3B-FP8","name":"Qwen3.6 35B A3B FP8","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"beta","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"}}},"zai":{"id":"zai","env":["ZHIPU_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.z.ai/api/paas/v4","name":"Z.AI","doc":"https://docs.z.ai/guides/overview/pricing","models":{"glm-5-turbo":{"id":"glm-5-turbo","name":"GLM-5-Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24,"cache_write":0},"canonical_model_id":"zhipuai/glm-5-turbo"},"glm-4.5v":{"id":"glm-4.5v","name":"GLM-4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":64000,"output":16384},"cost":{"input":0.6,"output":1.8,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5v"},"glm-4.7":{"id":"glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7"},"glm-4.6v":{"id":"glm-4.6v","name":"GLM-4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0.3,"output":0.9,"cache_read":0.05,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.6v"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5v-turbo":{"id":"glm-5v-turbo","name":"GLM-5V-Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24,"cache_write":0},"canonical_model_id":"zhipuai/glm-5v-turbo"},"glm-5":{"id":"glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2,"cache_write":0},"canonical_model_id":"zhipuai/glm-5"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"glm-4.7-flash":{"id":"glm-4.7-flash","name":"GLM-4.7-Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7-flash"},"glm-4.5-air":{"id":"glm-4.5-air","name":"GLM-4.5-Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.2,"output":1.1,"cache_read":0.03,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5-air"},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.1"},"glm-4.6":{"id":"glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.6"},"glm-4.5":{"id":"glm-4.5","name":"GLM-4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.6,"output":2.2,"cache_read":0.11,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5"},"glm-4.6v-flash":{"id":"glm-4.6v-flash","name":"GLM-4.6V-Flash","description":"Lightweight GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.6v-flash"},"glm-4.5-flash":{"id":"glm-4.5-flash","name":"GLM-4.5-Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":98304},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.5-flash"},"glm-5.3-flashx":{"id":"glm-5.3-flashx","name":"GLM-5.3-FlashX","description":"High-speed GLM-5.3-Flash serving option for coding and agent workflows","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-18","last_updated":"2026-09-18","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.37,"output":1.25,"cache_read":0.075,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"glm-4.7-flashx":{"id":"glm-4.7-flashx","name":"GLM-4.7-FlashX","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0.07,"output":0.4,"cache_read":0.01,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7-flashx"}}},"bee":{"id":"bee","env":["BEE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.bee.heossi.com/bee","name":"Bee by HEOSSI","doc":"https://bee.heossi.com/docs/sdks","models":{"bee-buzz":{"id":"bee-buzz","name":"Bee Buzz 1.0","description":"Mid-tier production model for tool-using agents, multi-step workflows, and builder/integration work. Bigger context than Comb, deeper planning, faster than Hive on routine tasks.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-10","last_updated":"2026-09-28","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":24576},"cost":{"input":2.5,"output":10,"cache_read":0.25,"cache_write":3}},"bee-hive":{"id":"bee-hive","name":"Bee Hive 1.0","description":"Scalable Bee serving with quantum-reasoning routing and multi-base domain-adapter routing for shared knowledge workflows, document intelligence, and lower-cost cloud inference. Domain adapters activate per customer domain after evaluation.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-10","last_updated":"2026-09-28","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":5,"output":20,"cache_read":0.5,"cache_write":6}},"bee-swarm":{"id":"bee-swarm","name":"Bee Swarm 1.0","description":"Premium reasoning, multi-model cloud execution, large-document analysis, and high-value technical work. Includes the evolution engine and stronger eval gates by default.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":false,"structured_output":false,"release_date":"2026-07-10","last_updated":"2026-09-28","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":25,"output":150,"cache_read":2.5,"cache_write":30}},"bee-comb":{"id":"bee-comb","name":"Bee Comb 2.0","description":"Stronger local/workstation AI for coding, architecture, security reasoning, larger RAG, and domain-specific workflows. The default workhorse for engineers and dev teams.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-10","last_updated":"2026-09-28","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":16384},"cost":{"input":1.25,"output":5,"cache_read":0.125,"cache_write":1.5}},"bee-cell":{"id":"bee-cell","name":"Bee Cell 1.0","description":"Fast hosted AI for chat, coding help, document question answering, image understanding, and lightweight technical reasoning.","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-10","last_updated":"2026-09-28","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.36}},"bee-brood":{"id":"bee-brood","name":"Bee Brood 1.0","description":"Production multimodal reasoning for image and video analysis, tool-enabled workflows, and multi-step planning at controlled cost.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-10","last_updated":"2026-09-28","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":16384},"cost":{"input":0.6,"output":2.4,"cache_read":0.06,"cache_write":0.72}}}},"nano-gpt":{"id":"nano-gpt","env":["NANO_GPT_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://nano-gpt.com/api/v1","name":"NanoGPT","doc":"https://docs.nano-gpt.com","models":{"command-a-reasoning-08-2025":{"id":"command-a-reasoning-08-2025","name":"Cohere Command A (08/2025)","description":"Cohere reasoning model for multilingual enterprise agents, tools, and complex workflows","family":"command-a","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-06-01","release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":8192},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"cohere/command-a-reasoning-08-2025"},"gemini-2.5-flash-preview-05-20:thinking":{"id":"gemini-2.5-flash-preview-05-20:thinking","name":"Gemini 2.5 Flash 0520 Thinking","description":"Preview snapshot of Gemini 2.5 Flash with controllable thinking budgets","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048000,"input":1048000,"output":65536},"status":"deprecated","cost":{"input":0.15,"output":3.5,"cache_read":0.015},"canonical_model_id":"google/gemini-2.5-flash-preview-05-20"},"glm-4.1v-thinking-flashx":{"id":"glm-4.1v-thinking-flashx","name":"GLM 4.1V Thinking FlashX","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"glm-flash","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-07-09","last_updated":"2025-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":64000,"input":64000,"output":8192},"cost":{"input":0.3,"output":0.3,"cache_read":0.15}},"phi-4-mini-instruct":{"id":"phi-4-mini-instruct","name":"Phi 4 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"phi","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-02-26","last_updated":"2025-02-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":0.17,"output":0.68,"cache_read":0.085},"canonical_model_id":"microsoft/phi-4-mini"},"asi1-mini":{"id":"asi1-mini","name":"ASI1 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-03-25","last_updated":"2025-03-25","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":1,"output":1,"cache_read":0.5}},"gemma-4-12b-it":{"id":"gemma-4-12b-it","name":"Gemma 4 12B Instruct","description":"Compact Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.05,"output":0.25,"cache_read":0.025},"canonical_model_id":"google/gemma-4-12b-it"},"hermes-high":{"id":"hermes-high","name":"Hermes High","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"hermes","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-11","last_updated":"2026-05-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.6,"output":1.1,"cache_read":0.2}},"gemini-2.5-pro-preview-05-06":{"id":"gemini-2.5-pro-preview-05-06","name":"Gemini 2.5 Pro Preview 0506","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"release_date":"2025-05-06","last_updated":"2025-05-06","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":2.5,"output":10,"cache_read":0.25}},"gemini-2.5-flash-lite":{"id":"gemini-2.5-flash-lite","name":"Gemini 2.5 Flash Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.01},"canonical_model_id":"google/gemini-2.5-flash-lite"},"agnes-3.0-flash":{"id":"agnes-3.0-flash","name":"Agnes 3.0 Flash","description":"Agnes 3.0 Flash is a low-cost model for coding, tool use, and multi-turn agent tasks. It supports text and image input, optional thinking, and a 512K-token context window.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-09-09","last_updated":"2026-09-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"input":524288,"output":65536},"cost":{"input":0.05,"output":0.15,"cache_read":0.005}},"gemma-4-12b-it-station-keeper":{"id":"gemma-4-12b-it-station-keeper","name":"Gemma 4 12B StationKeeper","description":"Gemma 4 12B StationKeeper is an open-weight roleplay finetune with image understanding, tool calling, optional reasoning, and a 131,072-token context window.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-09-09","last_updated":"2026-09-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.05,"output":0.25,"cache_read":0.025}},"gemini-2.5-flash-preview-09-2025":{"id":"gemini-2.5-flash-preview-09-2025","name":"Gemini 2.5 Flash Preview (09/2025)","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2025-09-25","last_updated":"2025-09-25","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03}},"gemma-4-26b-a4b-it-darksoul":{"id":"gemma-4-26b-a4b-it-darksoul","name":"Dark Soul","description":"Dark Soul is a Gemma 4 26B A4B multimodal mixture-of-experts fine-tune for creative writing, expressive dialogue, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.12,"output":0.38,"cache_read":0.06}},"holo3-35b-a3b:thinking":{"id":"holo3-35b-a3b:thinking","name":"Holo3-35B-A3B Thinking","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":8192},"cost":{"input":0.25,"output":1.8,"cache_read":0.125}},"GLM-4.6-Derestricted-v5":{"id":"GLM-4.6-Derestricted-v5","name":"GLM 4.6 Derestricted v5","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":8192},"cost":{"input":0.4,"output":1.5,"cache_read":0.2}},"holo3-35b-a3b":{"id":"holo3-35b-a3b","name":"Holo3-35B-A3B","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":8192},"cost":{"input":0.25,"output":1.8,"cache_read":0.125}},"doubao-1.5-pro-256k":{"id":"doubao-1.5-pro-256k","name":"Doubao 1.5 Pro 256k","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":16384},"cost":{"input":0.799,"output":1.445,"cache_read":0.3995}},"gemini-2.5-pro-exp-03-25":{"id":"gemini-2.5-pro-exp-03-25","name":"Gemini 2.5 Pro Experimental 0325","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"release_date":"2025-03-25","last_updated":"2025-03-25","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":2.5,"output":10,"cache_read":0.25}},"auto-model-premium":{"id":"auto-model-premium","name":"Auto model (Premium)","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2025-04-16","last_updated":"2024-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":1000000},"cost":{"input":9.996,"output":19.992,"cache_read":4.998}},"qwen3-vl-235b-a22b-instruct-original":{"id":"qwen3-vl-235b-a22b-instruct-original","name":"Qwen3 VL 235B A22B Instruct Original","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":32768},"cost":{"input":0.3,"output":1.9,"cache_read":0.15},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"gemini-2.5-flash-lite-preview-09-2025-thinking":{"id":"gemini-2.5-flash-lite-preview-09-2025-thinking","name":"Gemini 2.5 Flash Lite Preview (09/2025) – Thinking","description":"September 2025 preview of Gemini 2.5 Flash-Lite with better instruction following and multimodal quality","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-09-25","last_updated":"2025-09-25","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"status":"deprecated","cost":{"input":0.1,"output":0.4,"cache_read":0.01},"canonical_model_id":"google/gemini-2.5-flash-lite-preview-09-2025"},"gemini-2.5-pro-preview-03-25":{"id":"gemini-2.5-pro-preview-03-25","name":"Gemini 2.5 Pro Preview 0325","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"release_date":"2025-03-25","last_updated":"2025-03-25","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":2.5,"output":10,"cache_read":0.25}},"Gemma-4-31B-DarkIdol":{"id":"Gemma-4-31B-DarkIdol","name":"Gemma 4 31B DarkIdol","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-05-01","last_updated":"2026-05-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.306,"output":0.306,"cache_read":0.153}},"doubao-seed-2-0-mini-260215":{"id":"doubao-seed-2-0-mini-260215","name":"Doubao Seed 2.0 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":32000},"cost":{"input":0.0493,"output":0.4845,"cache_read":0.02465},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"gemma-4-31b-it-isometry":{"id":"gemma-4-31b-it-isometry","name":"Isometry","description":"Isometry is a multimodal Gemma 4 31B creative finetune for expressive dialogue, long-form storytelling, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"fastgpt":{"id":"fastgpt","name":"Web Answer","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-12-23","last_updated":"2024-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"input":32768,"output":32768},"cost":{"input":7.5,"output":7.5}},"auto-model-basic":{"id":"auto-model-basic","name":"Auto model (Basic)","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2025-04-16","last_updated":"2024-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":1000000},"cost":{"input":9.996,"output":19.992,"cache_read":4.998}},"universal-summarizer":{"id":"universal-summarizer","name":"Universal Summarizer","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-12-23","last_updated":"2024-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"input":32768,"output":32768},"cost":{"input":30,"output":30}},"MiniMax-M1":{"id":"MiniMax-M1","name":"MiniMax M1","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"minimax","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-01-08","last_updated":"2025-06-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":131072},"cost":{"input":0.1394,"output":1.3328,"cache_read":0.0697}},"gemma-4-26b-a4b-it-luminous":{"id":"gemma-4-26b-a4b-it-luminous","name":"Luminous Mirror","description":"Luminous Mirror is a Gemma 4 26B A4B multimodal mixture-of-experts fine-tune for creative writing, expressive dialogue, and roleplay.","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.12,"output":0.38,"cache_read":0.06}},"gemini-2.5-flash":{"id":"gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-2.5-flash"},"longcat-2.0":{"id":"longcat-2.0","name":"LongCat 2.0","description":"Meituan LongCat-2.0, a reasoning model with tool calling and a 1M-token context window","family":"longcat","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":131072},"cost":{"input":0.75,"output":3,"cache_read":0.015},"canonical_model_id":"meituan/longcat-2.0"},"doubao-seed-2-0-pro-260215":{"id":"doubao-seed-2-0-pro-260215","name":"Doubao Seed 2.0 Pro","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":128000},"cost":{"input":0.782,"output":3.876,"cache_read":0.391},"canonical_model_id":"bytedance-seed/seed-2.0-pro"},"auto-model-standard":{"id":"auto-model-standard","name":"Auto model (Standard)","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2025-04-16","last_updated":"2024-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":1000000},"cost":{"input":9.996,"output":19.992,"cache_read":4.998}},"gemini-2.5-flash-preview-04-17":{"id":"gemini-2.5-flash-preview-04-17","name":"Gemini 2.5 Flash Preview","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"release_date":"2025-04-17","last_updated":"2025-04-17","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"status":"deprecated","cost":{"input":0.15,"output":0.6,"cache_read":0.015}},"phi-4-multimodal-instruct":{"id":"phi-4-multimodal-instruct","name":"Phi 4 Multimodal","description":"Compact Microsoft multimodal model for text, image, and speech understanding","family":"phi","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-02-26","last_updated":"2025-02-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":0.07,"output":0.11,"cache_read":0.035},"canonical_model_id":"microsoft/phi-4-multimodal-instruct"},"Gemma-4-31B-Queen":{"id":"Gemma-4-31B-Queen","name":"Gemma 4 31B Queen","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-05-01","last_updated":"2026-05-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.306,"output":0.306,"cache_read":0.153}},"doubao-seed-2-0-lite-260215":{"id":"doubao-seed-2-0-lite-260215","name":"Doubao Seed 2.0 Lite","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":32000},"cost":{"input":0.1462,"output":0.8738,"cache_read":0.0731},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"gemma-4-26b-a4b-it-chimerax":{"id":"gemma-4-26b-a4b-it-chimerax","name":"Chimera X","description":"Chimera X is a Gemma 4 26B A4B multimodal mixture-of-experts fine-tune for creative writing, expressive dialogue, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.12,"output":0.38,"cache_read":0.06}},"ernie-5.1:thinking":{"id":"ernie-5.1:thinking","name":"ERNIE 5.1 Thinking","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"ernie","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"release_date":"2026-05-10","last_updated":"2026-05-10","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":119000,"input":119000,"output":64000},"cost":{"input":0.75,"output":3,"cache_read":0.75}},"gemini-2.0-pro-reasoner":{"id":"gemini-2.0-pro-reasoner","name":"Gemini 2.0 Pro Reasoner","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-02-05","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":1.292,"output":4.998,"cache_read":0.323}},"gemma-4-31b-it-garnet":{"id":"gemma-4-31b-it-garnet","name":"Garnet","description":"Garnet is a multimodal Gemma 4 31B creative finetune for expressive dialogue, long-form storytelling, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"gemma-4-31b-it-novelist":{"id":"gemma-4-31b-it-novelist","name":"Novelist","description":"Novelist is a multimodal Gemma 4 31B creative finetune for expressive dialogue, long-form storytelling, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"gemma-4-31b-it-scarlet":{"id":"gemma-4-31b-it-scarlet","name":"Gemma 4 31B Scarlet","description":"Scarlet is a multimodal Gemma 4 31B creative finetune for expressive dialogue, long-form storytelling, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-10-08","last_updated":"2026-10-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"gemma-4-26b-a4b-it-moonlight":{"id":"gemma-4-26b-a4b-it-moonlight","name":"Moonlight Dusk","description":"Moonlight Dusk is a Gemma 4 26B A4B multimodal mixture-of-experts fine-tune for creative writing, expressive dialogue, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.12,"output":0.38,"cache_read":0.06}},"gemini-2.5-pro":{"id":"gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":1.25,"output":10,"cache_read":0.125,"cache_write":0.375},"canonical_model_id":"google/gemini-2.5-pro"},"glm-4-air-0111":{"id":"glm-4-air-0111","name":"GLM 4 Air 0111","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"glm","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-01-11","last_updated":"2025-01-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":4096},"cost":{"input":0.1394,"output":0.1394,"cache_read":0.0697}},"longcat-2.5-preview":{"id":"longcat-2.5-preview","name":"LongCat 2.5 Preview","description":"Meituan's multimodal reasoning model for coding and agent tasks, with image understanding and a 1M-token context window","family":"longcat","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":false,"release_date":"2026-09-25","last_updated":"2026-09-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":131072},"cost":{"input":0.75,"output":2.95,"cache_read":0.015},"canonical_model_id":"meituan/longcat-2.5-preview"},"deepseek-chat-cheaper":{"id":"deepseek-chat-cheaper","name":"DeepSeek V3/Chat Cheaper","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"deepseek","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2025-04-15","last_updated":"2025-04-15","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.1,"output":0.425,"cache_read":0.05}},"gemma-4-31b-it-gemsicle":{"id":"gemma-4-31b-it-gemsicle","name":"Gemsicle","description":"Gemsicle is a multimodal Gemma 4 31B creative finetune for expressive dialogue, long-form storytelling, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"glm-4-long":{"id":"glm-4-long","name":"GLM-4 Long","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"glm","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-08-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":4095},"cost":{"input":0.2006,"output":0.2006,"cache_read":0.1003}},"Meta-Llama-3-1-8B-Instruct-FP8":{"id":"Meta-Llama-3-1-8B-Instruct-FP8","name":"Llama 3.1 8B (decentralized)","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":0.02,"output":0.03,"cache_read":0.01}},"ernie-5.1":{"id":"ernie-5.1","name":"ERNIE 5.1","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"ernie","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-05-10","last_updated":"2026-05-10","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":119000,"input":119000,"output":64000},"cost":{"input":0.75,"output":3,"cache_read":0.75}},"kimi-k2-instruct-fast":{"id":"kimi-k2-instruct-fast","name":"Kimi K2 0711 Fast","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"kimi-k2","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":16384},"status":"deprecated","cost":{"input":0.4,"output":1.8,"cache_read":0.2},"canonical_model_id":"moonshotai/kimi-k2-instruct"},"gemini-2.0-pro-exp-02-05":{"id":"gemini-2.0-pro-exp-02-05","name":"Gemini 2.0 Pro 0205","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-02-05","last_updated":"2025-02-05","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":2097152,"input":2097152,"output":8192},"cost":{"input":1.989,"output":7.956,"cache_read":0.49725}},"gemma-4-12b-it-semancer":{"id":"gemma-4-12b-it-semancer","name":"Gemma 4 12B Semancer","description":"Gemma 4 12B Semancer is an open-weight roleplay finetune with image understanding, tool calling, optional reasoning, and a 131,072-token context window.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-09-09","last_updated":"2026-09-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.05,"output":0.25,"cache_read":0.025}},"gemini-2.5-pro-preview-06-05":{"id":"gemini-2.5-pro-preview-06-05","name":"Gemini 2.5 Pro Preview 0605","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01-31","release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":2.5,"output":10,"cache_read":0.25},"canonical_model_id":"google/gemini-2.5-pro-preview"},"doubao-seed-2-0-code-preview-260215":{"id":"doubao-seed-2-0-code-preview-260215","name":"Doubao Seed 2.0 Code Preview","description":"ByteDance Seed coding model for multimodal software engineering and long-running agents","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":128000},"cost":{"input":0.782,"output":3.893,"cache_read":0.391},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"gemini-2.5-flash-preview-05-20":{"id":"gemini-2.5-flash-preview-05-20","name":"Gemini 2.5 Flash 0520","description":"Preview snapshot of Gemini 2.5 Flash with controllable thinking budgets","family":"gemini-flash","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-05-20","last_updated":"2025-05-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048000,"input":1048000,"output":65536},"status":"deprecated","cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"google/gemini-2.5-flash-preview-05-20"},"auto-model":{"id":"auto-model","name":"Auto model","description":"Automatic model router for matching prompts to suitable backends and budgets","family":"auto","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2025-04-16","last_updated":"2024-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":1000000},"cost":{"input":0,"output":0}},"gemma-4-26b-a4b-it-shadowsiren":{"id":"gemma-4-26b-a4b-it-shadowsiren","name":"Shadow Siren","description":"Shadow Siren is a Gemma 4 26B A4B multimodal mixture-of-experts fine-tune for creative writing, expressive dialogue, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.12,"output":0.38,"cache_read":0.06}},"sarvam-105b":{"id":"sarvam-105b","name":"Sarvam 105B","description":"Flagship Indian-language reasoning model for enterprise multilingual applications","family":"sarvam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-18","last_updated":"2026-02-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":4096},"cost":{"input":0.054,"output":0.2124,"cache_read":0.0336},"canonical_model_id":"sarvam/sarvam-105b"},"gemini-3-pro-image-preview":{"id":"gemini-3-pro-image-preview","type":"image","name":"Gemini 3 Pro Image","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-20","last_updated":"2025-11-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"input":65536,"output":32768},"cost":{"input":2,"output":12,"cache_read":0.2},"canonical_model_id":"google/gemini-3-pro-image-preview"},"claw-high":{"id":"claw-high","name":"Claw High","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-11","last_updated":"2026-05-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.6,"output":1.1,"cache_read":0.2}},"Gemma-4-31B-Claude-4.6-Opus-Reasoning-Distilled":{"id":"Gemma-4-31B-Claude-4.6-Opus-Reasoning-Distilled","name":"Gemma 4 31B Claude 4.6 Opus Reasoning Distilled","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"claude","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-05-01","last_updated":"2026-05-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.306,"output":0.306,"cache_read":0.0306}},"longcat-2.0:thinking":{"id":"longcat-2.0:thinking","name":"LongCat 2.0 Thinking","description":"Meituan LongCat-2.0, a reasoning model with tool calling and a 1M-token context window","family":"longcat","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":131072},"cost":{"input":0.75,"output":3,"cache_read":0.015},"canonical_model_id":"meituan/longcat-2.0"},"Gemma-4-31B-MeroMero-v2":{"id":"Gemma-4-31B-MeroMero-v2","name":"Gemma 4 31B MeroMero v2","description":"Gemma 4 31B MeroMero v2 is a LoRA finetune for emotive dialogue, relationship scenes, creative writing, and multimodal roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-08-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"glm-4.1v-thinking-flash":{"id":"glm-4.1v-thinking-flash","name":"GLM 4.1V Thinking Flash","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"glm-flash","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-07-09","last_updated":"2025-07-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":64000,"input":64000,"output":8192},"cost":{"input":0.3,"output":0.3,"cache_read":0.15}},"celeris-1":{"id":"celeris-1","name":"Celeris 1","description":"Celeris 1 is a diffusion language model built for ultra-low-latency classification, extraction, judging, query rewriting, and other short structured responses.","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-07-25","last_updated":"2026-07-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"input":8192,"output":8192},"cost":{"input":2,"output":6,"cache_read":1}},"glm-4-plus-0111":{"id":"glm-4-plus-0111","name":"GLM 4 Plus 0111","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"glm","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-02-19","last_updated":"2025-02-19","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":4096},"cost":{"input":9.996,"output":9.996,"cache_read":4.998}},"gemini-2.5-flash-preview-04-17:thinking":{"id":"gemini-2.5-flash-preview-04-17:thinking","name":"Gemini 2.5 Flash Preview Thinking","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"release_date":"2025-04-17","last_updated":"2025-04-17","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"status":"deprecated","cost":{"input":0.15,"output":3.5,"cache_read":0.015}},"mercury-2":{"id":"mercury-2","name":"Mercury 2","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-24","last_updated":"2026-02-24","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":50000},"cost":{"input":0.25,"output":0.75,"cache_read":0.025},"canonical_model_id":"inception/mercury-2"},"Qwen3.5-27B-Queen-Derestricted":{"id":"Qwen3.5-27B-Queen-Derestricted","name":"Qwen3.5 27B Queen Derestricted","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"qwen3.5","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.306,"output":0.306,"cache_read":0.153}},"glm-z1-airx":{"id":"glm-z1-airx","name":"GLM Z1 AirX","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"glm","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2025-04-15","last_updated":"2025-04-15","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"input":32000,"output":16384},"cost":{"input":0.7,"output":0.7,"cache_read":0.35}},"gemma-4-31b-it-gembrain":{"id":"gemma-4-31b-it-gembrain","name":"Gembrain","description":"Gembrain is a multimodal Gemma 4 31B creative finetune for expressive dialogue, long-form storytelling, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"gemma-4-31b-it-darkidol":{"id":"gemma-4-31b-it-darkidol","name":"DarkIdol","description":"DarkIdol is a multimodal Gemma 4 31B creative finetune for expressive dialogue, long-form storytelling, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"gemma-4-26b-a4b-it-chimeraxheretic":{"id":"gemma-4-26b-a4b-it-chimeraxheretic","name":"Gemma 4 26B A4B Chimera X Heretic","description":"Chimera X Heretic is a Gemma 4 26B A4B multimodal mixture-of-experts fine-tune for creative writing, expressive dialogue, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-10-08","last_updated":"2026-10-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.12,"output":0.38,"cache_read":0.06}},"mistral-code-latest":{"id":"mistral-code-latest","name":"Mistral Code Latest","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"mistral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":32768},"cost":{"input":0.3,"output":0.9,"cache_read":0.15}},"mistral-code-agent-latest":{"id":"mistral-code-agent-latest","name":"Mistral Code Agent Latest","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"mistral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.4,"output":2,"cache_read":0.2}},"doubao-1.5-pro-32k":{"id":"doubao-1.5-pro-32k","name":"Doubao 1.5 Pro 32k","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-11-20","last_updated":"2025-01-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"input":32000,"output":8192},"cost":{"input":0.1343,"output":0.3349,"cache_read":0.06715}},"gemma-4-26b-a4b-it-opusdistill":{"id":"gemma-4-26b-a4b-it-opusdistill","name":"Opus Distill","description":"Opus Distill is a Gemma 4 26B A4B multimodal mixture-of-experts fine-tune for creative writing, expressive dialogue, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.12,"output":0.38,"cache_read":0.06}},"deepseek-chat":{"id":"deepseek-chat","name":"DeepSeek V3/Deepseek Chat","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-12-01","last_updated":"2026-02-28","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.1,"output":0.425,"cache_read":0.05},"canonical_model_id":"deepseek/deepseek-chat"},"hermes-low":{"id":"hermes-low","name":"Hermes Low","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"hermes","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-11","last_updated":"2026-05-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.6,"output":1.1,"cache_read":0.2,"cache_write":0.08333}},"Gemma-4-26B-A4B-MeroMero":{"id":"Gemma-4-26B-A4B-MeroMero","name":"Gemma 4 26B A4B MeroMero","description":"Gemma 4 26B A4B MeroMero is an NVFP4 multimodal mixture-of-experts fine-tune for emotive dialogue, relationship scenes, creative writing, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.12,"output":0.38,"cache_read":0.06}},"hermes-medium":{"id":"hermes-medium","name":"Hermes Medium","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"hermes","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-11","last_updated":"2026-05-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.6,"output":1.1,"cache_read":0.2}},"gemma-4-26b-a4b-it-musica":{"id":"gemma-4-26b-a4b-it-musica","name":"Musica","description":"Musica is a Gemma 4 26B A4B multimodal mixture-of-experts fine-tune for creative writing, expressive dialogue, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.12,"output":0.38,"cache_read":0.06}},"claw-medium":{"id":"claw-medium","name":"Claw Medium","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-11","last_updated":"2026-05-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.6,"output":1.1,"cache_read":0.2}},"claw-low":{"id":"claw-low","name":"Claw Low","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-11","last_updated":"2026-05-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.6,"output":1.1,"cache_read":0.2,"cache_write":0.08333}},"ernie-5.0-thinking-preview":{"id":"ernie-5.0-thinking-preview","name":"Ernie 5.0 Thinking Preview","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"ernie","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":1,"output":3.5,"cache_read":0.5}},"doubao-1.5-vision-pro-32k":{"id":"doubao-1.5-vision-pro-32k","name":"Doubao 1.5 Vision Pro 32k","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-11-20","last_updated":"2025-01-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"input":32000,"output":8192},"cost":{"input":0.459,"output":1.377,"cache_read":0.2295}},"gemini-2.5-flash-nothinking":{"id":"gemini-2.5-flash-nothinking","name":"Gemini 2.5 Flash (No Thinking)","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03}},"Gemma-4-26B-A4B-MeroMero:thinking":{"id":"Gemma-4-26B-A4B-MeroMero:thinking","name":"Gemma 4 26B A4B MeroMero Thinking","description":"Gemma 4 26B A4B MeroMero with thinking enabled for more deliberate emotive dialogue, relationship scenes, creative writing, and multimodal roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.12,"output":0.38,"cache_read":0.06}},"gemini-2.5-flash-lite-preview-06-17":{"id":"gemini-2.5-flash-lite-preview-06-17","name":"Gemini 2.5 Flash Lite Preview","description":"First preview of Gemini 2.5 Flash-Lite, the low-cost, low-latency 2.5 model","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"google/gemini-2.5-flash-lite-preview-06-17"},"Gemma-4-31B-Cognitive-Unshackled":{"id":"Gemma-4-31B-Cognitive-Unshackled","name":"Gemma 4 31B Cognitive Unshackled","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-05-01","last_updated":"2026-05-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.306,"output":0.306,"cache_read":0.153}},"nano-gpt-help":{"id":"nano-gpt-help","name":"NanoGPT Help","description":"Text-only NanoGPT support assistant. Questions are processed by the Help inference provider; do not paste secrets or account credentials. Covers the website, models, API, pricing, memory, media generation, and support.","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-06-06","last_updated":"2026-06-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":6000,"input":6000,"output":512},"cost":{"input":0,"output":0}},"Gemma-4-31B-MeroMero-v2:thinking":{"id":"Gemma-4-31B-MeroMero-v2:thinking","name":"Gemma 4 31B MeroMero v2 Thinking","description":"Gemma 4 31B MeroMero v2 with thinking enabled for more deliberate emotive dialogue, relationship scenes, creative writing, and multimodal roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-08-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"pokee-isaac":{"id":"pokee-isaac","name":"Pokee-Isaac 28B","description":"Pokee-Isaac is a 28B agentic model with a roughly 10-million-token context window, function calling, and OpenAI-compatible structured output. Pokee bills in $0.01 increments, rounding each non-zero request up to the next cent.","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-08-04","last_updated":"2026-08-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":10000000,"input":10000000,"output":60000},"cost":{"input":0.15,"output":1,"cache_read":0.075}},"gemini-2.5-flash-preview-09-2025-thinking":{"id":"gemini-2.5-flash-preview-09-2025-thinking","name":"Gemini 2.5 Flash Preview (09/2025) – Thinking","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2025-09-25","last_updated":"2025-09-25","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03}},"qvq-max":{"id":"qvq-max","name":"Qwen: QvQ Max","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-03-28","last_updated":"2025-03-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":1.2,"output":4.8,"cache_read":0.6}},"Gemma-4-31B-GarnetV2":{"id":"Gemma-4-31B-GarnetV2","name":"Gemma 4 31B Garnet V2","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-05-01","last_updated":"2026-05-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.306,"output":0.306,"cache_read":0.153}},"gemini-2.5-flash-lite-preview-09-2025":{"id":"gemini-2.5-flash-lite-preview-09-2025","name":"Gemini 2.5 Flash Lite Preview (09/2025)","description":"September 2025 preview of Gemini 2.5 Flash-Lite with better instruction following and multimodal quality","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-09-25","last_updated":"2025-09-25","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"status":"deprecated","cost":{"input":0.1,"output":0.4,"cache_read":0.01},"canonical_model_id":"google/gemini-2.5-flash-lite-preview-09-2025"},"gemma-4-31b-it-fabled":{"id":"gemma-4-31b-it-fabled","name":"Fabled","description":"Fabled is a multimodal Gemma 4 31B creative finetune for expressive dialogue, long-form storytelling, and roleplay.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-07-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"deepseek-v3-0324":{"id":"deepseek-v3-0324","name":"DeepSeek Chat 0324","description":"March 2025 checkpoint of DeepSeek-V3 with improved reasoning and coding","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-03-24","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.2,"output":0.77,"cache_read":0.135},"canonical_model_id":"deepseek/deepseek-v3-0324"},"gemini-exp-1206":{"id":"gemini-exp-1206","name":"Gemini 2.0 Pro 1206","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gemini","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":2097152,"input":2097152,"output":8192},"cost":{"input":1.258,"output":4.998,"cache_read":0.629}},"mercury-coder-small":{"id":"mercury-coder-small","name":"Mercury Coder Small","description":"Model by Inception AI. A diffusion large language model that runs incredibly quickly (500+ tokens/second) while matching Claude 3.5 Haiku and GPT-4o-mini. 1st in speed on Copilot arena, and matching 2nd in quality.","family":"mercury","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":0.25,"output":1,"cache_read":0.125}},"Qwen3.5-27B-BlueStar-v3-Derestricted":{"id":"Qwen3.5-27B-BlueStar-v3-Derestricted","name":"Qwen3.5 27B BlueStar v3 Derestricted","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"qwen3.5","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.306,"output":0.306,"cache_read":0.153}},"venice-uncensored":{"id":"venice-uncensored","name":"Venice Uncensored","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"venice","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-10-01","last_updated":"2025-02-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.4,"output":1.8,"cache_read":0.4}},"lightonai/LightOnOCR-2-1B":{"id":"lightonai/LightOnOCR-2-1B","name":"LightOnOCR 2","description":"LightOnOCR 2 hosted by IONOS in Berlin, Germany. Zero data retention.","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":8192},"cost":{"input":0.1785,"output":0.3465}},"undi95/remm-slerp-l2-13b":{"id":"undi95/remm-slerp-l2-13b","name":"ReMM SLERP 13B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-06-30","release_date":"2023-07-22","last_updated":"2023-07-22","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":6144,"input":6144,"output":4096},"cost":{"input":0.799,"output":1.207,"cache_read":0.3995},"canonical_model_id":"undi95/remm-slerp-l2-13b"},"thinkingmachines/Inkling-Small":{"id":"thinkingmachines/Inkling-Small","name":"Inkling Small","description":"Multimodal MoE reasoning model (276B total, 12B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"input":524288,"output":32768},"cost":{"input":0.45,"output":1.2,"cache_read":0.1},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/inkling:thinking":{"id":"thinkingmachines/inkling:thinking","name":"Inkling Thinking","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048000,"input":1048000,"output":32768},"cost":{"input":0.95,"output":4.05,"cache_read":0.16},"canonical_model_id":"thinkingmachines/inkling"},"thinkingmachines/Inkling-Small:thinking":{"id":"thinkingmachines/Inkling-Small:thinking","name":"Inkling Small Thinking","description":"Multimodal MoE reasoning model (276B total, 12B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"input":524288,"output":32768},"cost":{"input":0.45,"output":1.2,"cache_read":0.1},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/inkling":{"id":"thinkingmachines/inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048000,"input":1048000,"output":32768},"cost":{"input":0.95,"output":4.05,"cache_read":0.16},"canonical_model_id":"thinkingmachines/inkling"},"soob3123/Veiled-Calla-12B":{"id":"soob3123/Veiled-Calla-12B","name":"Veiled Calla 12B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-04-13","last_updated":"2025-04-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":8192},"cost":{"input":0.3,"output":0.3,"cache_read":0.15}},"soob3123/amoral-gemma3-27B-v2":{"id":"soob3123/amoral-gemma3-27B-v2","name":"Amoral Gemma3 27B v2","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-05-23","last_updated":"2025-05-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":8192},"cost":{"input":0.3,"output":0.3,"cache_read":0.15}},"reka/reka-edge-2603":{"id":"reka/reka-edge-2603","name":"Reka Edge 2603","description":"Reka's compact multimodal model for visual understanding and tool use, served directly by Reka.","family":"reka","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":16384},"cost":{"input":0.105,"output":0.105},"canonical_model_id":"rekaai/reka-edge"},"reka/reka-flash-3":{"id":"reka/reka-flash-3","name":"Reka Flash 3","description":"Reka's 21B reasoning model for chat and coding, served directly by Reka.","family":"reka","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01-31","release_date":"2025-03-10","last_updated":"2025-03-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":65536},"cost":{"input":0.105,"output":0.21},"canonical_model_id":"rekaai/reka-flash-3"},"xiaomi/mimo-v2.6-pro-ultraspeed":{"id":"xiaomi/mimo-v2.6-pro-ultraspeed","name":"MiMo V2.6 Pro UltraSpeed","description":"MiMo pro model for strong multimodal reasoning and agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":4.35,"output":8.7,"cache_read":0.036,"cache_write":0},"canonical_model_id":"xiaomi/mimo-v2.6-pro-ultraspeed"},"xiaomi/mimo-v2.6-flash":{"id":"xiaomi/mimo-v2.6-flash","name":"MiMo V2.6 Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028,"cache_write":0},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"xiaomi/mimo-v2.6-flash-abliterated":{"id":"xiaomi/mimo-v2.6-flash-abliterated","name":"MiMo V2.6 Flash Abliterated","description":"A MiMo V2.6 Flash finetune with refusal-direction ablation, image input, a 1M-token context window, separate reasoning output, and tool calling.","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-09-25","last_updated":"2026-09-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.5,"output":1.5,"cache_read":0.275}},"xiaomi/mimo-v2.6-pro":{"id":"xiaomi/mimo-v2.6-pro","name":"MiMo V2.6 Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036,"cache_write":0},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"xiaomi/mimo-v2.5-pro":{"id":"xiaomi/mimo-v2.5-pro","name":"MiMo V2.5 Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036,"cache_write":0},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"xiaomi/mimo-v2.5":{"id":"xiaomi/mimo-v2.5","name":"MiMo V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028,"cache_write":0},"canonical_model_id":"xiaomi/mimo-v2.5"},"xiaomi/mimo-v2.6-flash-uncensored":{"id":"xiaomi/mimo-v2.6-flash-uncensored","name":"MiMo V2.6 Flash Uncensored","description":"A text-only, lower-refusal MiMo V2.6 Flash finetune served by Heabsy with a 1M-token context window, separate reasoning output, and tool calling.","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-09-25","last_updated":"2026-09-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.5,"output":1.5,"cache_read":0.1995}},"xiaomi/mimo-v2.5-pro:thinking":{"id":"xiaomi/mimo-v2.5-pro:thinking","name":"MiMo V2.5 Pro Thinking","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036,"cache_write":0},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"xiaomi/mimo-v2.5:thinking":{"id":"xiaomi/mimo-v2.5:thinking","name":"MiMo V2.5 Thinking","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028,"cache_write":0},"canonical_model_id":"xiaomi/mimo-v2.5"},"xiaomi/mimo-v2.6-flash-uncensored:thinking":{"id":"xiaomi/mimo-v2.6-flash-uncensored:thinking","name":"MiMo V2.6 Flash Uncensored Thinking","description":"MiMo V2.6 Flash Uncensored with maximum thinking enabled. Supports a 1M-token context window and tool calling.","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-09-26","last_updated":"2026-09-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.5,"output":1.5,"cache_read":0.1995}},"MarinaraSpaghetti/NemoMix-Unleashed-12B":{"id":"MarinaraSpaghetti/NemoMix-Unleashed-12B","name":"NemoMix 12B Unleashed","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":8192},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"NeverSleep/Lumimaid-v0.2-70B":{"id":"NeverSleep/Lumimaid-v0.2-70B","name":"Lumimaid v0.2","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":1,"output":1.5,"cache_read":0.5}},"elorian/glimpse":{"id":"elorian/glimpse","name":"Elorian Glimpse","description":"Glimpse is Elorian's visual reasoning model for understanding images and video and answering in text. It can analyze charts, count objects, follow events over time, and reason about spatial relationships and physical cause and effect. It supports tool calling and structured output across a shared 262,144-token context window, with up to 256,000 output tokens within the remaining context.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"input":262144,"output":256000},"cost":{"input":0.63,"output":3.15,"cache_read":0.063}},"reflection/beam-1.0":{"id":"reflection/beam-1.0","name":"Beam 1.0 501B A23B","description":"Reflection's Apache 2.0 open-weight text model with 501.3B total and 23.4B active parameters, built for coding, reasoning and tool use. It supports a shared 1,048,576-token context window, up to 131,072 output tokens, JSON mode and structured output. Reasoning is always enabled with low, medium, high, xhigh and max effort; NanoGPT defaults to max. Knowledge cutoff: June 30, 2026.","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-06-30","release_date":"2026-10-05","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.5,"output":1.5,"cache_read":0.05},"canonical_model_id":"reflection/beam-1.0-501b-a23b"},"ibm-granite/granite-4.2-8b":{"id":"ibm-granite/granite-4.2-8b","name":"Granite 4.2 8B","description":"IBM Granite 4.2 8B is an Apache 2.0-licensed dense model with native step-by-step reasoning and specialized training for agentic work. It can plan before acting, sequence tools, navigate codebases, work in terminals, and verify results across coding, search, mathematics, science, and complex instruction-following tasks.","family":"granite","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-25","last_updated":"2026-08-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":117964},"cost":{"input":0.1,"output":0.15,"cache_read":0.05},"canonical_model_id":"ibm/granite-4.2-8b"},"baseten/Kimi-K2-Instruct-FP4":{"id":"baseten/Kimi-K2-Instruct-FP4","name":"Kimi K2 0711 Instruct FP4","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":131072},"status":"deprecated","cost":{"input":0.4,"output":1.8,"cache_read":0.2}},"unsloth/gemma-3-4b-it":{"id":"unsloth/gemma-3-4b-it","name":"Gemma 3 4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.2006,"output":0.2006,"cache_read":0.1003},"canonical_model_id":"google/gemma-3-4b-it"},"unsloth/gemma-3-27b-it":{"id":"unsloth/gemma-3-27b-it","name":"Gemma 3 27B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":96000},"cost":{"input":0.2992,"output":0.2992,"cache_read":0.1496},"canonical_model_id":"google/gemma-3-27b-it"},"unsloth/gemma-3-12b-it":{"id":"unsloth/gemma-3-12b-it","name":"Gemma 3 12B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":16384},"cost":{"input":0.272,"output":0.272,"cache_read":0.136},"canonical_model_id":"google/gemma-3-12b-it"},"ornith-ai/ornith-1.5-35b-a3b:thinking":{"id":"ornith-ai/ornith-1.5-35b-a3b:thinking","name":"Ornith 1.5 35B Thinking","description":"Ornith 1.5 35B A3B is an open-weight mixture-of-experts model for agentic coding, reasoning, tool use, image understanding, and long-context work. This variant enables thinking by default.","family":"ornith","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-07-29","last_updated":"2026-08-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.05}},"ornith-ai/ornith-1.5-122b":{"id":"ornith-ai/ornith-1.5-122b","name":"Ornith 1.5 122B","description":"Ornith 1.5 122B is an MIT-licensed open-weight model for coding, reasoning, tool use and image understanding. It accepts text and images across a shared 262,144-token context, with up to 32,768 output tokens. Reasoning is enabled by default; JSON object output and streaming are supported.","family":"ornith","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-10-20","last_updated":"2026-10-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.2,"output":0.8,"cache_read":0.05}},"ornith-ai/ornith-1.5-35b-a3b":{"id":"ornith-ai/ornith-1.5-35b-a3b","name":"Ornith 1.5 35B","description":"Ornith 1.5 35B A3B is an open-weight mixture-of-experts model for agentic coding, tool use, image understanding, and long-context work. This variant disables thinking for faster direct responses.","family":"ornith","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-07-29","last_updated":"2026-08-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.05}},"LatitudeGames/Wayfarer-Large-70B-Llama-3.3":{"id":"LatitudeGames/Wayfarer-Large-70B-Llama-3.3","name":"Llama 3.3 70B Wayfarer","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-02-20","last_updated":"2025-02-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":0.7,"output":0.7,"cache_read":0.35}},"Envoid/Llama-3.05-Nemotron-Tenyxchat-Storybreaker-70B":{"id":"Envoid/Llama-3.05-Nemotron-Tenyxchat-Storybreaker-70B","name":"Nemotron Tenyxchat Storybreaker 70b","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"Envoid/Llama-3.05-NT-Storybreaker-Ministral-70B":{"id":"Envoid/Llama-3.05-NT-Storybreaker-Ministral-70B","name":"Llama 3.05 Storybreaker Ministral 70b","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"EVA-UNIT-01/EVA-Qwen2.5-72B-v0.2":{"id":"EVA-UNIT-01/EVA-Qwen2.5-72B-v0.2","name":"EVA-Qwen2.5-72B-v0.2","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-09-25","last_updated":"2025-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.799,"output":0.799,"cache_read":0.3995}},"EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.0":{"id":"EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.0","name":"EVA Llama 3.33 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-07-26","last_updated":"2025-07-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":2.006,"output":2.006,"cache_read":1.003}},"EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1":{"id":"EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1","name":"EVA-LLaMA-3.33-70B-v0.1","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-09-25","last_updated":"2025-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":2.006,"output":2.006,"cache_read":1.003}},"EVA-UNIT-01/EVA-Qwen2.5-32B-v0.2":{"id":"EVA-UNIT-01/EVA-Qwen2.5-32B-v0.2","name":"EVA-Qwen2.5-32B-v0.2","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-07-26","last_updated":"2025-07-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.799,"output":0.799,"cache_read":0.3995}},"ReadyArt/MS3.2-The-Omega-Directive-24B-Unslop-v2.0":{"id":"ReadyArt/MS3.2-The-Omega-Directive-24B-Unslop-v2.0","name":"Omega Directive 24B Unslop v2.0","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":32768},"cost":{"input":0.5,"output":0.5,"cache_read":0.25}},"anthropic/claude-haiku-latest":{"id":"anthropic/claude-haiku-latest","name":"Claude Haiku Latest","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-03-29","last_updated":"2026-03-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]}},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-opus-4.6:thinking:medium":{"id":"anthropic/claude-opus-4.6:thinking:medium","name":"Claude 4.6 Opus Thinking Medium","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-sonnet-4.6:thinking":{"id":"anthropic/claude-sonnet-4.6:thinking","name":"Claude Sonnet 4.6 Thinking","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-haiku-5.5":{"id":"anthropic/claude-haiku-5.5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-sonnet-latest":{"id":"anthropic/claude-sonnet-latest","name":"Claude Sonnet Latest","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-03-01","last_updated":"2026-03-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5}},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-haiku-4.5:thinking":{"id":"anthropic/claude-haiku-4.5:thinking","name":"Claude Haiku 4.5 Thinking","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-opus-4.7:thinking":{"id":"anthropic/claude-opus-4.7:thinking","name":"Claude 4.7 Opus Thinking","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic/claude-opus-4.6":{"id":"anthropic/claude-opus-4.6","name":"Claude 4.6 Opus","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-sonnet-4.5:thinking":{"id":"anthropic/claude-sonnet-4.5:thinking","name":"Claude Sonnet 4.5 Thinking","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-opus-4.1:thinking:8192":{"id":"anthropic/claude-opus-4.1:thinking:8192","name":"Claude 4.1 Opus Thinking (8K)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5},"canonical_model_id":"anthropic/claude-opus-4-1"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-opus-4.1:thinking:1024":{"id":"anthropic/claude-opus-4.1:thinking:1024","name":"Claude 4.1 Opus Thinking (1K)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5},"canonical_model_id":"anthropic/claude-opus-4-1"},"anthropic/claude-opus-5.5":{"id":"anthropic/claude-opus-5.5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-fable-latest":{"id":"anthropic/claude-fable-latest","name":"Claude Fable Latest","description":"Compatibility alias for Claude Fable.","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5}},"anthropic/claude-sonnet-5:thinking":{"id":"anthropic/claude-sonnet-5:thinking","name":"Claude Sonnet 5 Thinking","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-haiku-4.5":{"id":"anthropic/claude-haiku-4.5","name":"Claude Haiku 4.5","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-opus-4.1":{"id":"anthropic/claude-opus-4.1","name":"Claude 4.1 Opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5},"canonical_model_id":"anthropic/claude-opus-4-1"},"anthropic/claude-opus-4.6:thinking:low":{"id":"anthropic/claude-opus-4.6:thinking:low","name":"Claude 4.6 Opus Thinking Low","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-opus-4.1:thinking:32768":{"id":"anthropic/claude-opus-4.1:thinking:32768","name":"Claude 4.1 Opus Thinking (32K)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5},"canonical_model_id":"anthropic/claude-opus-4-1"},"anthropic/claude-sonnet-5.5":{"id":"anthropic/claude-sonnet-5.5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-sonnet-4.5":{"id":"anthropic/claude-sonnet-4.5","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-fable-5.1":{"id":"anthropic/claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-opus-4.6:thinking:max":{"id":"anthropic/claude-opus-4.6:thinking:max","name":"Claude 4.6 Opus Thinking Max","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-opus-4.5":{"id":"anthropic/claude-opus-4.5","name":"Claude 4.5 Opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-opus-latest":{"id":"anthropic/claude-opus-latest","name":"Claude Opus Latest","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-03-29","last_updated":"2026-03-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5}},"anthropic/claude-opus-4.8:thinking":{"id":"anthropic/claude-opus-4.8:thinking","name":"Claude Opus 4.8 Thinking","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-opus-4.6:thinking":{"id":"anthropic/claude-opus-4.6:thinking","name":"Claude 4.6 Opus Thinking","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-sonnet-5.5:thinking":{"id":"anthropic/claude-sonnet-5.5:thinking","name":"Claude Sonnet 5.5 Thinking","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude 4.7 Opus","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-7"},"anthropic/claude-opus-4.5:thinking":{"id":"anthropic/claude-opus-4.5:thinking","name":"Claude 4.5 Opus Thinking","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-opus-4.1:thinking":{"id":"anthropic/claude-opus-4.1:thinking","name":"Claude 4.1 Opus Thinking","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5},"canonical_model_id":"anthropic/claude-opus-4-1"},"bytedance-seed/seed-2-1-turbo":{"id":"bytedance-seed/seed-2-1-turbo","name":"ByteDance Seed 2.1 Turbo","description":"ByteDance Seed 2.1 Turbo is a multimodal model for coding and long-horizon agent workflows, including end-to-end software delivery and multi-step task execution. It supports text, image, and video input with a 262k context window.","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"input":262144,"output":235929},"cost":{"input":0.5,"output":2.5,"cache_read":0.25},"canonical_model_id":"bytedance-seed/seed-2.1-turbo"},"bytedance-seed/seed-2.0-code":{"id":"bytedance-seed/seed-2.0-code","name":"ByteDance Seed 2.0 Code","description":"ByteDance Seed coding model for multimodal software engineering and long-running agents","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"input":262144,"output":131072},"cost":{"input":0.5,"output":3,"cache_read":0.25},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"bytedance-seed/seed-2.0-lite":{"id":"bytedance-seed/seed-2.0-lite","name":"ByteDance Seed 2.0 Lite","description":"Cost-efficient ByteDance Seed 2.0 model for production chat, analysis, and structured generation","family":"seed","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"input":262144,"output":131072},"cost":{"input":0.25,"output":2,"cache_read":0.125},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"upstage/solar-mini4:thinking":{"id":"upstage/solar-mini4:thinking","name":"Solar Mini 4 Thinking","description":"Upstage's compact, cost-efficient model for agentic use","family":"solar-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"input":524288,"output":131072},"cost":{"input":0.05,"output":0.2,"cache_read":0.005},"canonical_model_id":"upstage/solar-mini4"},"upstage/solar-pro-3":{"id":"upstage/solar-pro-3","name":"Solar Pro 3","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"solar-pro","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-07","release_date":"2026-01-26","last_updated":"2026-03-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"input":131072,"output":117964},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"upstage/solar-pro3"},"upstage/solar-pro4":{"id":"upstage/solar-pro4","name":"Solar Pro 4","description":"Upstage's flagship model, specialized for agentic use","family":"solar-pro","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02","release_date":"2026-08-06","last_updated":"2026-08-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"input":524288,"output":131072},"cost":{"input":0.03,"output":0.12,"cache_read":0.006},"canonical_model_id":"upstage/solar-pro4"},"upstage/solar-mini4":{"id":"upstage/solar-mini4","name":"Solar Mini 4","description":"Upstage's compact, cost-efficient model for agentic use","family":"solar-mini","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"input":524288,"output":131072},"cost":{"input":0.05,"output":0.2,"cache_read":0.005},"canonical_model_id":"upstage/solar-mini4"},"upstage/solar-pro4:thinking":{"id":"upstage/solar-pro4:thinking","name":"Solar Pro 4 Thinking","description":"Upstage's flagship model, specialized for agentic use","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02","release_date":"2026-08-06","last_updated":"2026-08-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"input":524288,"output":131072},"cost":{"input":0.03,"output":0.12,"cache_read":0.006},"canonical_model_id":"upstage/solar-pro4"},"poolside/laguna-s-2.1:thinking":{"id":"poolside/laguna-s-2.1:thinking","name":"Laguna S 2.1 Thinking","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.1,"output":0.2,"cache_read":0.01},"canonical_model_id":"poolside/laguna-s-2.1"},"poolside/laguna-s-2.1":{"id":"poolside/laguna-s-2.1","name":"Laguna S 2.1","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.1,"output":0.2,"cache_read":0.01},"canonical_model_id":"poolside/laguna-s-2.1"},"x-ai/grok-build-0.1":{"id":"x-ai/grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":230400},"cost":{"input":1,"output":2,"cache_read":0.2},"canonical_model_id":"xai/grok-build-0.1"},"x-ai/grok-4.3":{"id":"x-ai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":900000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2},"canonical_model_id":"xai/grok-4.3"},"x-ai/grok-latest":{"id":"x-ai/grok-latest","name":"Grok Latest","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-03","last_updated":"2026-05-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"input":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.5}},"x-ai/grok-4.7":{"id":"x-ai/grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"input":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.7"},"x-ai/grok-4.20":{"id":"x-ai/grok-4.20","name":"Grok 4.20","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-03-31","last_updated":"2026-03-31","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"input":2000000,"output":131072},"cost":{"input":1.25,"output":2.5,"cache_read":0.2}},"x-ai/grok-4.6":{"id":"x-ai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"input":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.5},"canonical_model_id":"xai/grok-4.6"},"x-ai/grok-4.20-multi-agent":{"id":"x-ai/grok-4.20-multi-agent","name":"Grok 4.20 Multi-Agent","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"release_date":"2026-03-31","last_updated":"2026-03-31","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"input":2000000,"output":131072},"cost":{"input":1.25,"output":2.5,"cache_read":0.2}},"x-ai/grok-4.5":{"id":"x-ai/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"input":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.3},"canonical_model_id":"xai/grok-4.5"},"failspy/Meta-Llama-3-70B-Instruct-abliterated-v3.5":{"id":"failspy/Meta-Llama-3-70B-Instruct-abliterated-v3.5","name":"Llama 3 70B abliterated","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-07-26","last_updated":"2025-07-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"input":8192,"output":8192},"cost":{"input":0.7,"output":0.7,"cache_read":0.35}},"THUDM/GLM-4-32B-0414":{"id":"THUDM/GLM-4-32B-0414","name":"GLM 4 32B 0414","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-04-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":0.2,"output":0.2,"cache_read":0.1}},"THUDM/GLM-4-9B-0414":{"id":"THUDM/GLM-4-9B-0414","name":"GLM 4 9B 0414","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-04-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"input":32000,"output":8000},"cost":{"input":0.2,"output":0.2,"cache_read":0.1}},"THUDM/GLM-Z1-9B-0414":{"id":"THUDM/GLM-Z1-9B-0414","name":"GLM Z1 9B 0414","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm-z","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-04-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"input":32000,"output":8000},"cost":{"input":0.2,"output":0.2,"cache_read":0.1}},"Doctor-Shotgun/MS3.2-24B-Magnum-Diamond":{"id":"Doctor-Shotgun/MS3.2-24B-Magnum-Diamond","name":"MS3.2 24B Magnum Diamond","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":32768},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"LLM360/K2-Think":{"id":"LLM360/K2-Think","name":"K2-Think","description":"Kimi reasoning model for long-horizon research, planning, and tool use","family":"kimi-thinking","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-07-26","last_updated":"2025-07-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":32768},"cost":{"input":0.17,"output":0.68,"cache_read":0.085}},"Sao10K/L3-8B-Stheno-v3.2":{"id":"Sao10K/L3-8B-Stheno-v3.2","name":"Sao10K Stheno 8b","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-11-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.2006,"output":0.2006,"cache_read":0.1003}},"Sao10K/L3.3-70B-Euryale-v2.3":{"id":"Sao10K/L3.3-70B-Euryale-v2.3","name":"Llama 3.3 70B Euryale","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-12-18","last_updated":"2024-12-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":20480,"input":20480,"output":16384},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465},"canonical_model_id":"sao10k/l3.3-euryale-70b"},"Sao10K/L3.1-70B-Euryale-v2.2":{"id":"Sao10K/L3.1-70B-Euryale-v2.2","name":"Llama 3.1 70B Euryale","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-28","last_updated":"2024-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":20480,"input":20480,"output":16384},"cost":{"input":0.306,"output":0.357,"cache_read":0.153},"canonical_model_id":"sao10k/l3.1-euryale-70b"},"Sao10K/L3.1-70B-Hanami-x1":{"id":"Sao10K/L3.1-70B-Hanami-x1","name":"Llama 3.1 70B Hanami","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT 6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-6-sol"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT 6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":0.03,"output":0.15,"cache_read":0.03},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT 6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT 5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-5-pro":{"id":"openai/gpt-5-pro","name":"GPT 5 Pro","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":15,"output":120,"cache_read":1.5},"canonical_model_id":"openai/gpt-5-pro"},"openai/o1":{"id":"openai/o1","name":"OpenAI o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":100000},"cost":{"input":15,"output":60,"cache_read":7.5},"canonical_model_id":"openai/o1"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT 4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"input":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-6-astra-pro":{"id":"openai/gpt-6-astra-pro","name":"GPT 6 Astra Pro","description":"GPT 6 Astra in Pro reasoning mode. Uses additional model work for difficult tasks, with higher latency and token usage at the same per-token rates. Reasoning effort remains independently configurable.","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5}},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-terra-latest":{"id":"openai/gpt-terra-latest","name":"GPT Terra Latest","description":"Compatibility alias that routes to GPT 5.6 Terra, the latest supported GPT Terra model.","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5}},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT 5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-5.1-2025-11-13":{"id":"openai/gpt-5.1-2025-11-13","name":"GPT-5.1 (2025-11-13)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-latest":{"id":"openai/gpt-latest","name":"GPT Latest","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-03-29","last_updated":"2026-03-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5}},"openai/gpt-chat-latest":{"id":"openai/gpt-chat-latest","name":"GPT Chat Latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-03","last_updated":"2026-05-03","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5}},"openai/o3-pro-2025-06-10":{"id":"openai/o3-pro-2025-06-10","name":"OpenAI o3-pro (2025-06-10)","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-06-10","last_updated":"2025-06-10","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":100000},"cost":{"input":22,"output":88,"cache_read":11},"canonical_model_id":"openai/o3-pro"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT 5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT 5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT 5.4 Mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-6-luna-pro":{"id":"openai/gpt-6-luna-pro","name":"GPT 6 Luna Pro","description":"GPT-6 Luna Pro uses the same underlying model as GPT-6 Luna with Pro reasoning mode enabled for higher-quality responses on complex tasks.","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125}},"openai/o1-pro":{"id":"openai/o1-pro","name":"OpenAI o1 Pro","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-pro","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2023-09","release_date":"2025-03-19","last_updated":"2025-03-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":100000},"cost":{"input":150,"output":600,"cache_read":75},"canonical_model_id":"openai/o1-pro"},"openai/o3-mini-high":{"id":"openai/o3-mini-high","name":"OpenAI o3-mini (High)","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"openai/gpt-4o-2024-08-06":{"id":"openai/gpt-4o-2024-08-06","name":"GPT-4o (2024-08-06)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-09","release_date":"2024-08-06","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-08-06"},"openai/gpt-5.1-codex-max":{"id":"openai/gpt-5.1-codex-max","name":"GPT 5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":2.5,"output":20,"cache_read":0.25},"canonical_model_id":"openai/gpt-5.1-codex-max"},"openai/gpt-oss-safeguard-20b":{"id":"openai/gpt-oss-safeguard-20b","name":"GPT OSS Safeguard 20B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":0.075,"output":0.3},"canonical_model_id":"openai/gpt-oss-safeguard-20b"},"openai/gpt-luna-latest":{"id":"openai/gpt-luna-latest","name":"GPT Luna Latest","description":"Compatibility alias that routes to GPT 5.6 Luna, the latest supported GPT Luna model.","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125}},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT 5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT 4.1 Mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"input":1047576,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":16384},"cost":{"input":0.02,"output":0.1},"canonical_model_id":"openai/gpt-oss-20b"},"openai/gpt-5.2-codex":{"id":"openai/gpt-5.2-codex","name":"GPT 5.2 Codex","description":"Code-specialist GPT for repository edits, reviews, and long-running software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-codex"},"openai/gpt-4o-2024-11-20":{"id":"openai/gpt-4o-2024-11-20","name":"GPT-4o (2024-11-20)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-09","release_date":"2024-11-20","last_updated":"2024-11-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-11-20"},"openai/gpt-astra-latest":{"id":"openai/gpt-astra-latest","name":"GPT Astra Latest","description":"Compatibility alias that routes to GPT 6 Astra, the latest supported GPT Astra model.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5}},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT 5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT 4.1 Nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"input":1047576,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5.1-codex":{"id":"openai/gpt-5.1-codex","name":"GPT 5.1 Codex","description":"Codex GPT for repository edits, code review, and practical software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT 5.4 Nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-4-turbo":{"id":"openai/gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":4096},"cost":{"input":10,"output":30},"canonical_model_id":"openai/gpt-4-turbo"},"openai/o3":{"id":"openai/o3","name":"OpenAI o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":1},"canonical_model_id":"openai/o3"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT 5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-6.1-sol-pro":{"id":"openai/gpt-6.1-sol-pro","name":"GPT 6.1 Sol Pro","description":"GPT-6.1 Sol Pro uses the same underlying model as GPT-6.1 Sol with Pro reasoning mode enabled for higher-quality responses on complex tasks.","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5}},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT 5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT 5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT 5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"openai/gpt-3.5-turbo":{"id":"openai/gpt-3.5-turbo","name":"GPT-3.5 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"input":16385,"output":4096},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"openai/gpt-3.5-turbo"},"openai/o3-mini":{"id":"openai/o3-mini","name":"OpenAI o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"openai/o3-mini-low":{"id":"openai/o3-mini-low","name":"OpenAI o3-mini (Low)","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"openai/gpt-5.6-luna-pro":{"id":"openai/gpt-5.6-luna-pro","name":"GPT 5.6 Luna Pro","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-6-sol-pro":{"id":"openai/gpt-6-sol-pro","name":"GPT 6 Sol Pro","description":"GPT-6 Sol Pro uses the same underlying model as GPT-6 Sol with Pro reasoning mode enabled for higher-quality responses on complex tasks.","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5}},"openai/gpt-sol-latest":{"id":"openai/gpt-sol-latest","name":"GPT Sol Latest","description":"Compatibility alias that routes to GPT 5.6 Sol, the latest supported GPT Sol model.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5}},"openai/gpt-5.1-codex-mini":{"id":"openai/gpt-5.1-codex-mini","name":"GPT 5.1 Codex Mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5.1-codex-mini"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"openai/gpt-5.6-terra-pro":{"id":"openai/gpt-5.6-terra-pro","name":"GPT 5.6 Terra Pro","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/o4-mini":{"id":"openai/o4-mini","name":"OpenAI o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o4-mini"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT 5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":400000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-5.6-sol-pro":{"id":"openai/gpt-5.6-sol-pro","name":"GPT 5.6 Sol Pro","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT 6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":1050000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"openai/gpt-6-astra"},"openai/o4-mini-high":{"id":"openai/o4-mini-high","name":"OpenAI o4-mini high","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o4-mini"},"stepfun-ai/step-3.5-flash":{"id":"stepfun-ai/step-3.5-flash","name":"Step 3.5 Flash","description":"StepFun flash lane for quick multimodal reasoning and coding assistance","family":"step","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.1,"output":0.3,"cache_read":0.05},"canonical_model_id":"stepfun/step-3.5-flash"},"stepfun-ai/step-3.5-flash-2603":{"id":"stepfun-ai/step-3.5-flash-2603","name":"Step 3.5 Flash 2603","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","family":"step","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.1,"output":0.3,"cache_read":0.05},"canonical_model_id":"stepfun/step-3.5-flash-2603"},"inception/mercury-2.5-preview":{"id":"inception/mercury-2.5-preview","name":"Mercury 2.5 Preview","description":"Mercury 2.5 Preview is Inception's latest and most intelligent diffusion language model. Instead of generating tokens strictly one at a time, it produces and refines multiple tokens in parallel, reaching up to 1,107 tokens per second on standard GPUs. It delivers a 10+ point intelligence gain over Mercury 2, with tunable reasoning, parallel tool calls, schema-aligned JSON output, and a 260K context window. It is built for latency-sensitive production work such as search agents, voice pipelines, customer support, rapid coding iteration, and coding subagents.","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":260000,"input":260000,"output":65536},"cost":{"input":0.04,"output":0.15,"cache_read":0.004}},"inception/mercury-3":{"id":"inception/mercury-3","name":"Mercury 3","description":"Inception's diffusion reasoning model for chat, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-16","last_updated":"2026-10-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":131072},"cost":{"input":0.1,"output":0.35,"cache_read":0.01},"canonical_model_id":"inception/mercury-3"},"bytedance/doubao-seed-character":{"id":"bytedance/doubao-seed-character","name":"Doubao Seed Character","description":"ByteDance's character-focused Doubao Seed model for roleplay, persona consistency, dialogue, and creative character interactions. It supports text and image input with a 128k context window. Requests route through ZenMux to ByteDance; ZenMux does not publish a model-API zero-retention or training guarantee, so avoid sensitive data.","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":32768},"cost":{"input":0.15,"output":0.37,"cache_read":0.03,"cache_write":0.003},"canonical_model_id":"bytedance-seed/seed-character"},"bytedance/doubao-seed-2.1-turbo":{"id":"bytedance/doubao-seed-2.1-turbo","name":"Doubao Seed 2.1 Turbo","description":"Fast, lower-cost model in the Doubao Seed 2.1 family for everyday chat, coding assistance, document work, and high-throughput productivity tasks. Supports a 256k context window and up to 128k output tokens. Note: privacy and logging guarantees may be limited.","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":128000},"cost":{"input":0.5,"output":2.5,"cache_read":0.25},"canonical_model_id":"bytedance-seed/seed-2.1-turbo"},"bytedance/doubao-seed-2.1-pro":{"id":"bytedance/doubao-seed-2.1-pro","name":"Doubao Seed 2.1 Pro","description":"Higher-capability model in the Doubao Seed 2.1 family for agentic coding, long-context analysis, complex instruction following, and productivity workflows. Supports a 256k context window and up to 128k output tokens. Note: privacy and logging guarantees may be limited.","family":"seed","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":128000},"cost":{"input":1,"output":5,"cache_read":0.5},"canonical_model_id":"bytedance-seed/seed-2.1-pro"},"ateron/gemma-4-dark-thoughts-v2-31b":{"id":"ateron/gemma-4-dark-thoughts-v2-31b","name":"Gemma 4 Dark Thoughts V2 31B","description":"Ateron's second Dark Thoughts merge combines Dark Scarlett V2, MeroMero V2, and Scotoma 2 for creative dialogue and extended character roleplay. This text-only Gemma 4 31B deployment supports a 65,536-token context window and up to 8,192 output tokens.","family":"gemma","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":false,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":8192},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"nanogpt/coding-router:max":{"id":"nanogpt/coding-router:max","name":"Coding Router Max","description":"Automatic model router for matching prompts to suitable backends and budgets","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-05-12","last_updated":"2026-05-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5}},"nanogpt/coding-router:medium":{"id":"nanogpt/coding-router:medium","name":"Coding Router Medium","description":"Automatic model router for matching prompts to suitable backends and budgets","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-05-12","last_updated":"2026-05-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":0.14,"output":0.28,"cache_read":0.028}},"nanogpt/coding-router":{"id":"nanogpt/coding-router","name":"Coding Router","description":"Automatic model router for matching prompts to suitable backends and budgets","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-05-12","last_updated":"2026-05-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":1.1,"output":2.2,"cache_read":0.11}},"nanogpt/coding-router:low":{"id":"nanogpt/coding-router:low","name":"Coding Router Low","description":"Automatic model router for matching prompts to suitable backends and budgets","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-05-12","last_updated":"2026-05-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":0.14,"output":0.28,"cache_read":0.028}},"nanogpt/coding-router:high":{"id":"nanogpt/coding-router:high","name":"Coding Router High","description":"Automatic model router for matching prompts to suitable backends and budgets","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-05-12","last_updated":"2026-05-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":1.1,"output":2.2,"cache_read":0.11}},"featherless-ai/Qwerky-72B":{"id":"featherless-ai/Qwerky-72B","name":"Qwerky 72B","description":"General-purpose chat model for instruction following, writing, and analysis","family":"qwerky","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-03-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"input":32000,"output":8192},"cost":{"input":0.5,"output":0.5,"cache_read":0.25}},"pamanseau/OpenReasoning-Nemotron-32B":{"id":"pamanseau/OpenReasoning-Nemotron-32B","name":"OpenReasoning Nemotron 32B","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.05}},"abliteration-ai/abliterated-model-large-v2":{"id":"abliteration-ai/abliterated-model-large-v2","name":"Abliterated Model Large V2","description":"Abliteration.ai's default large text reasoning model is derived from GLM-5.3 for harder reasoning and evaluation workloads, with automatic prompt caching and a one-million-token context window.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-31","last_updated":"2026-08-31","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":999990},"cost":{"input":3,"output":5,"cache_read":0.3}},"abliteration-ai/abliterated-model":{"id":"abliteration-ai/abliterated-model","name":"Abliterated Model","description":"Abliteration.ai's multimodal reasoning model supports text and image input, structured output, automatic prompt caching, and a 262K-token context window.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":false,"structured_output":true,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"input":262144,"output":262134},"cost":{"input":1,"output":3,"cache_read":0.1}},"abliteration-ai/abliterated-model-large":{"id":"abliteration-ai/abliterated-model-large","name":"Abliterated Model Large","description":"Abliteration.ai's large text reasoning model is derived from GLM-5.2 and supports native tool calling, structured output, automatic prompt caching, and a one-million-token context window.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":999990},"cost":{"input":3,"output":5,"cache_read":0.3}},"inclusionai/ling-3.0-flash:thinking":{"id":"inclusionai/ling-3.0-flash:thinking","name":"Ling 3.0 Flash Thinking","description":"Hybrid-linear MoE reasoning model with 124B total and 5.1B active parameters for efficient agents","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-23","last_updated":"2026-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.075,"output":0.22,"cache_read":0.015},"canonical_model_id":"inclusionai/ling-3.0-flash"},"inclusionai/ling-3.1-flash":{"id":"inclusionai/ling-3.1-flash","name":"Ling 3.1 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.075,"output":0.22,"cache_read":0.015},"canonical_model_id":"inclusionai/ling-3.1-flash"},"inclusionai/ling-3.0-flash-vl":{"id":"inclusionai/ling-3.0-flash-vl","name":"Ling 3.0 Flash VL","description":"Native multimodal hybrid MoE model for image and video understanding, reasoning, and visual agents","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.06,"output":0.18,"cache_read":0.012},"canonical_model_id":"inclusionai/ling-3.0-flash-vl"},"inclusionai/ling-3.0-flash":{"id":"inclusionai/ling-3.0-flash","name":"Ling 3.0 Flash","description":"Hybrid-linear MoE reasoning model with 124B total and 5.1B active parameters for efficient agents","family":"ling","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-23","last_updated":"2026-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.075,"output":0.22,"cache_read":0.015},"canonical_model_id":"inclusionai/ling-3.0-flash"},"anthracite-org/magnum-v4-72b":{"id":"anthracite-org/magnum-v4-72b","name":"Magnum v4 72B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-06-30","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":2.006,"output":2.992,"cache_read":1.003},"canonical_model_id":"anthracite-org/magnum-v4-72b"},"anthracite-org/magnum-v2-72b":{"id":"anthracite-org/magnum-v2-72b","name":"Magnum V2 72B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":2.006,"output":2.992,"cache_read":1.003}},"abacusai/Dracarys-72B-Instruct":{"id":"abacusai/Dracarys-72B-Instruct","name":"Llama 3.1 70B Dracarys 2","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-08-02","last_updated":"2025-08-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":8192},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"prism-ml/ternary-bonsai-2-27b":{"id":"prism-ml/ternary-bonsai-2-27b","name":"Ternary Bonsai 2 27B","description":"Ternary Bonsai 2 27B is a 27B-parameter reasoning model from PrismML derived from Qwen3.8-27B. It supports coding, mathematics, tool calling, and image understanding with a 262K-token context window.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","xhigh"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-18","last_updated":"2026-09-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.075,"output":0.5,"cache_read":0.0375}},"mistralai/ministral-8b-2512":{"id":"mistralai/ministral-8b-2512","name":"Ministral 8B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.15,"output":0.15,"cache_read":0.075},"canonical_model_id":"mistral/ministral-8b-2512"},"mistralai/ministral-14b-2512":{"id":"mistralai/ministral-14b-2512","name":"Ministral 14B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.2,"output":0.2,"cache_read":0.1},"canonical_model_id":"mistral/ministral-14b-2512"},"mistralai/ministral-3b-2512":{"id":"mistralai/ministral-3b-2512","name":"Ministral 3B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.1,"output":0.1,"cache_read":0.05},"canonical_model_id":"mistral/ministral-3b-2512"},"mistralai/devstral-small-2505":{"id":"mistralai/devstral-small-2505","name":"Mistral Devstral Small 2505","description":"OpenHands+Devstral is 100% local 100% open, and is SOTA for the category on SWE-Bench Verified: 46.8% accuracy.","family":"devstral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-08-02","last_updated":"2025-08-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":8192},"cost":{"input":0.06,"output":0.06,"cache_read":0.03}},"mistralai/mistral-nemo-instruct-2407":{"id":"mistralai/mistral-nemo-instruct-2407","name":"Mistral Nemo","description":"12B parameter model with multilingual support.","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.1003,"output":0.1207,"cache_read":0.05015},"canonical_model_id":"mistral/mistral-nemo"},"mistralai/mistral-medium-3.5:thinking":{"id":"mistralai/mistral-medium-3.5:thinking","name":"Mistral Medium 3.5 Thinking","description":"Mistral Medium 3.5 with reasoning enabled by default (reasoning_effort=high), for complex coding, agentic, and multi-step reasoning prompts.","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":32768},"cost":{"input":1.5,"output":7.5,"cache_read":0.75}},"mistralai/mistral-small-3.1-24b-instruct":{"id":"mistralai/mistral-small-3.1-24b-instruct","name":"Mistral Small 3.1 24B (2503)","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-03-17","last_updated":"2025-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":102400},"cost":{"input":0.1,"output":0.3,"cache_read":0.05},"canonical_model_id":"mistral/mistral-small-3.1-24b-instruct"},"mistralai/mixtral-8x22b-instruct-v0.1":{"id":"mistralai/mixtral-8x22b-instruct-v0.1","name":"Mixtral 8x22B","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-01-31","release_date":"2024-04-17","last_updated":"2024-04-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":52428},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"mistral/mixtral-8x22b-instruct"},"mistralai/mistral-small-4-119b-2603:thinking":{"id":"mistralai/mistral-small-4-119b-2603:thinking","name":"Mistral Small 4 119B Thinking","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.4,"output":1.4,"cache_read":0.2},"canonical_model_id":"mistral/mistral-small-2603"},"mistralai/mistral-medium-3.5":{"id":"mistralai/mistral-medium-3.5","name":"Mistral Medium 3.5","description":"Mistral Medium 3.5 is a 128B dense open-weights flagship model for instruction-following, reasoning, coding, long-horizon agentic work, tool use, structured output, and multimodal prompts. It supports a 256k context window and configurable reasoning effort.","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":32768},"cost":{"input":1.5,"output":7.5,"cache_read":0.75}},"mistralai/mistral-medium-3":{"id":"mistralai/mistral-medium-3","name":"Mistral Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.4,"output":2,"cache_read":0.2},"canonical_model_id":"mistral/mistral-medium-3"},"mistralai/devstral-2-123b-instruct-2512":{"id":"mistralai/devstral-2-123b-instruct-2512","name":"Devstral 2 123B","description":"Mistral coding agent model for repository tasks and software engineering workflows","family":"devstral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.4,"output":1.4,"cache_read":0.2},"canonical_model_id":"mistral/devstral-2512"},"mistralai/mistral-small-3.2-24b-instruct":{"id":"mistralai/mistral-small-3.2-24b-instruct","name":"Mistral Small 3.2 24B (2506)","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":0.2,"output":0.4,"cache_read":0.1},"canonical_model_id":"mistral/mistral-small-3.2-24b-instruct"},"mistralai/mistral-saba":{"id":"mistralai/mistral-saba","name":"Mistral Saba","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-02-17","last_updated":"2025-02-17","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"input":32768,"output":26214},"cost":{"input":0.1989,"output":0.595,"cache_read":0.09945},"canonical_model_id":"mistral/mistral-saba"},"mistralai/mistral-large-4":{"id":"mistralai/mistral-large-4","name":"Mistral Large 4","description":"Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"input":524288,"output":262144},"cost":{"input":0.68,"output":2.09,"cache_read":0.07},"canonical_model_id":"mistral/mistral-large-4"},"mistralai/ministral-14b-instruct-2512":{"id":"mistralai/ministral-14b-instruct-2512","name":"Ministral 3 14B","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.05},"canonical_model_id":"mistral/ministral-3-14b-instruct-2512"},"mistralai/mistral-small-4-119b-2603":{"id":"mistralai/mistral-small-4-119b-2603","name":"Mistral Small 4 119B","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.4,"output":1.4,"cache_read":0.2},"canonical_model_id":"mistral/mistral-small-2603"},"mistralai/codestral-2508":{"id":"mistralai/codestral-2508","name":"Codestral 2508","description":"Mistral code model for low-latency completion, fill-in-the-middle, and code generation","family":"codestral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":32768},"cost":{"input":0.3,"output":0.9,"cache_read":0.15},"canonical_model_id":"mistral/codestral-2508"},"mistralai/mistral-small-24b-instruct-2501":{"id":"mistralai/mistral-small-24b-instruct-2501","name":"Mistral Small 24B","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-01-30","last_updated":"2025-01-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":8192},"cost":{"input":0.1155,"output":0.3465},"canonical_model_id":"mistral/mistral-small-24b-instruct-2501"},"mistralai/mistral-large":{"id":"mistralai/mistral-large","name":"Mistral Large 2411","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-11-30","release_date":"2024-02-26","last_updated":"2024-02-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":102400},"cost":{"input":2.006,"output":6.001,"cache_read":0.2},"canonical_model_id":"mistral/mistral-large"},"mistralai/mistral-medium-3.1":{"id":"mistralai/mistral-medium-3.1","name":"Mistral Medium 3.1","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-06-30","release_date":"2025-08-12","last_updated":"2025-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.4,"output":2,"cache_read":0.2},"canonical_model_id":"mistral/mistral-medium-3.1"},"TEE/gpt-oss-120b":{"id":"TEE/gpt-oss-120b","name":"GPT-OSS 120B TEE","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":16384},"cost":{"input":2,"output":2,"cache_read":2},"canonical_model_id":"openai/gpt-oss-120b"},"TEE/kimi-k3":{"id":"TEE/kimi-k3","name":"Kimi K3 TEE","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":65535},"cost":{"input":3,"output":15,"cache_read":1.5},"canonical_model_id":"moonshotai/kimi-k3"},"TEE/glm-5.2":{"id":"TEE/glm-5.2","name":"GLM 5.2 TEE","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.7},"canonical_model_id":"zhipuai/glm-5.2"},"TEE/deepseek-v4.1-flash":{"id":"TEE/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash TEE","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":0.65,"output":1.45,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"TEE/glm-5.2:thinking":{"id":"TEE/glm-5.2:thinking","name":"GLM 5.2 Thinking TEE","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.7},"canonical_model_id":"zhipuai/glm-5.2"},"TEE/qwen2.5-vl-72b-instruct":{"id":"TEE/qwen2.5-vl-72b-instruct","name":"Qwen2.5 VL 72B TEE","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2025-01-26","last_updated":"2025-01-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":8192},"cost":{"input":0.7,"output":0.7,"cache_read":0.35},"canonical_model_id":"alibaba/qwen2-5-vl-72b-instruct"},"TEE/glm-5.3":{"id":"TEE/glm-5.3","name":"GLM 5.3 TEE","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"TEE/qwen3.6-27b":{"id":"TEE/qwen3.6-27b","name":"Qwen3.6 27B TEE","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.32,"output":2.7,"cache_read":0.16},"canonical_model_id":"alibaba/qwen3.6-27b"},"TEE/glm-5.1-thinking":{"id":"TEE/glm-5.1-thinking","name":"GLM 5.1 Thinking TEE","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"input":202752,"output":65535},"cost":{"input":0.7,"output":2.5,"cache_read":0.18},"canonical_model_id":"zhipuai/glm-5.1"},"TEE/glm-5.3-flash":{"id":"TEE/glm-5.3-flash","name":"GLM 5.3 Flash TEE","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"TEE/gemma4-31b:thinking":{"id":"TEE/gemma4-31b:thinking","name":"Gemma 4 31B Thinking TEE","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":131072},"cost":{"input":0.4,"output":1,"cache_read":0.4},"canonical_model_id":"google/gemma-4-31b-it"},"TEE/qwen3.5-397b-a17b":{"id":"TEE/qwen3.5-397b-a17b","name":"Qwen3.5 397B A17B TEE","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.55,"output":3.5,"cache_read":0.275},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"TEE/gemma-4-31b-it":{"id":"TEE/gemma-4-31b-it","name":"Gemma 4 31B IT TEE","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":262144},"cost":{"input":0.15,"output":0.46,"cache_read":0.075},"canonical_model_id":"google/gemma-4-31b-it"},"TEE/kimi-k2.6":{"id":"TEE/kimi-k2.6","name":"Kimi K2.6 TEE","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":1.5,"output":5.25,"cache_read":0.375},"canonical_model_id":"moonshotai/kimi-k2.6"},"TEE/glm-5.1":{"id":"TEE/glm-5.1","name":"GLM 5.1 TEE","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"input":202752,"output":65535},"cost":{"input":0.7,"output":2.5,"cache_read":0.18},"canonical_model_id":"zhipuai/glm-5.1"},"TEE/llama3-3-70b":{"id":"TEE/llama3-3-70b","name":"Llama 3.3 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":1.75,"output":2.75,"cache_read":1.75},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"TEE/muse-glimmer-30b":{"id":"TEE/muse-glimmer-30b","name":"Muse Glimmer 30B TEE","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":131072},"cost":{"input":0.35,"output":1.5,"cache_read":0.04},"canonical_model_id":"meta/muse-glimmer-30b"},"TEE/qwen3.8-27b":{"id":"TEE/qwen3.8-27b","name":"Qwen3.8 27B TEE","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":262144},"cost":{"input":0.4,"output":3,"cache_read":0.15},"canonical_model_id":"alibaba/qwen3.8-27b"},"TEE/nemotron-3.5-lightning":{"id":"TEE/nemotron-3.5-lightning","name":"Nvidia Nemotron 3.5 Lightning TEE","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.08,"output":0.2,"cache_read":0.04},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"TEE/qwen3.5-27b":{"id":"TEE/qwen3.5-27b","name":"Qwen3.5 27B TEE","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.3,"output":2.4,"cache_read":0.15},"canonical_model_id":"alibaba/qwen3.5-27b"},"TEE/gemma-4-26b-a4b-uncensored":{"id":"TEE/gemma-4-26b-a4b-uncensored","name":"Gemma 4 26B A4B Uncensored TEE","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2026-05-23","last_updated":"2026-05-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":65536},"cost":{"input":0.15,"output":0.7,"cache_read":0.075}},"TEE/kimi-k2.7-code":{"id":"TEE/kimi-k2.7-code","name":"Kimi K2.7 Code TEE","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"TEE/gemma4-31b":{"id":"TEE/gemma4-31b","name":"Gemma 4 31B","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":131072},"cost":{"input":0.4,"output":1,"cache_read":0.4},"canonical_model_id":"google/gemma-4-31b-it"},"TEE/deepseek-v3.2":{"id":"TEE/deepseek-v3.2","name":"DeepSeek V3.2 TEE","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":164000,"input":164000,"output":65536},"cost":{"input":0.5,"output":1,"cache_read":0.25},"canonical_model_id":"deepseek/deepseek-v3.2"},"TEE/qwen3.6-35b-a3b":{"id":"TEE/qwen3.6-35b-a3b","name":"Qwen3.6 35B A3B TEE","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":262144},"cost":{"input":0.2,"output":1.27,"cache_read":0.1},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"Salesforce/Llama-xLAM-2-70b-fc-r":{"id":"Salesforce/Llama-xLAM-2-70b-fc-r","name":"Llama-xLAM-2 70B fc-r","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-04-13","last_updated":"2025-04-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":2.5,"output":2.5,"cache_read":1.25}},"shisa-ai/shisa-v2-llama3.3-70b":{"id":"shisa-ai/shisa-v2-llama3.3-70b","name":"Shisa V2 Llama 3.3 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-07-26","last_updated":"2025-07-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":0.5,"output":0.5,"cache_read":0.25}},"shisa-ai/shisa-v2.1-llama3.3-70b":{"id":"shisa-ai/shisa-v2.1-llama3.3-70b","name":"Shisa V2.1 Llama 3.3 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":4096},"cost":{"input":0.5,"output":0.5,"cache_read":0.25}},"perceptron/perceptron-mk1.5":{"id":"perceptron/perceptron-mk1.5","name":"Perceptron Mk1.5","description":"Perceptron Mk1.5 is a multimodal reasoning model for visual analysis and physical agents. It accepts text, images, video, and audio, supports tool calling and structured output, and can return spatial annotations such as points, boxes, polygons, and tracks.","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-25","last_updated":"2026-09-25","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":36864,"input":36864,"output":8192},"cost":{"input":0.15,"output":1.5}},"perceptron/perceptron-mk1":{"id":"perceptron/perceptron-mk1","name":"Perceptron Mk1","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-05-12","last_updated":"2026-05-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"input":32768,"output":8192},"cost":{"input":0.15,"output":1.5,"cache_read":0.075},"canonical_model_id":"perceptron/perceptron-mk1"},"heabsy/cyberheabsy":{"id":"heabsy/cyberheabsy","name":"CyberHeabsy","description":"A low-refusal text model for authorized security research, roleplay, and creative writing. It preserves tool calling after refusal removal, supports optional reasoning, and has a 1M-token context window.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-09-27","last_updated":"2026-09-27","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":1.5,"output":4.5,"cache_read":0.275}},"heabsy/qwen3.8-27b-uncensored-fast":{"id":"heabsy/qwen3.8-27b-uncensored-fast","name":"Qwen 3.8 27B Uncensored Fast by Heabsy","description":"Heabsy's NVFP4 build of Qwen3.8-27B by Alibaba Cloud, with refusal removal based on huihui-ai's Huihui-Qwen3.8-27B-abliterated. Quantized and calibrated by Heabsy, with unpublished weights under the Heabsy Model License. Supports text and image input, tools, and optional reasoning capped at 16,384 tokens within the output budget. This named build is separate from Qwen 3.8 27B Uncensored.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"release_date":"2026-10-16","last_updated":"2026-10-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"input":524288,"output":235929},"cost":{"input":1,"output":3,"cache_read":0.22}},"amazon/nova-2-lite-v1":{"id":"amazon/nova-2-lite-v1","name":"Amazon Nova 2 Lite","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-10","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":65535},"cost":{"input":0.51,"output":4.25,"cache_read":0.255},"canonical_model_id":"amazon/nova-2-lite-v1"},"amazon/nova-pro-v1":{"id":"amazon/nova-pro-v1","name":"Amazon Nova Pro 1.0","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"input":300000,"output":32000},"cost":{"input":0.799,"output":3.196,"cache_read":0.3995},"canonical_model_id":"amazon/nova-pro-v1"},"amazon/nova-lite-v1":{"id":"amazon/nova-lite-v1","name":"Amazon Nova Lite 1.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"input":300000,"output":5120},"cost":{"input":0.0595,"output":0.238,"cache_read":0.02975},"canonical_model_id":"amazon/nova-lite-v1"},"Gryphe/MythoMax-L2-13b":{"id":"Gryphe/MythoMax-L2-13b","name":"MythoMax 13B","description":"Llama 2 merge combining MythoLogic and Huginn for creative writing and roleplay","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2023-08-10","last_updated":"2023-08-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"input":4096,"output":3686},"cost":{"input":0.1003,"output":0.1003,"cache_read":0.05015},"canonical_model_id":"gryphe/mythomax-l2-13b"},"huihui-ai/DeepSeek-R1-Distill-Qwen-32B-abliterated":{"id":"huihui-ai/DeepSeek-R1-Distill-Qwen-32B-abliterated","name":"DeepSeek R1 Qwen Abliterated","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-01-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":1.4,"output":1.4,"cache_read":0.7}},"huihui-ai/Llama-3.3-70B-Instruct-abliterated":{"id":"huihui-ai/Llama-3.3-70B-Instruct-abliterated","name":"Llama 3.3 70B Instruct abliterated","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-08-08","last_updated":"2025-08-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":0.7,"output":0.7,"cache_read":0.35}},"huihui-ai/DeepSeek-R1-Distill-Llama-70B-abliterated":{"id":"huihui-ai/DeepSeek-R1-Distill-Llama-70B-abliterated","name":"DeepSeek R1 Llama 70B Abliterated","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-01-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.7,"output":0.7,"cache_read":0.35}},"huihui-ai/Qwen2.5-32B-Instruct-abliterated":{"id":"huihui-ai/Qwen2.5-32B-Instruct-abliterated","name":"Qwen 2.5 32B Abliterated","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-01-06","last_updated":"2025-01-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":8192},"cost":{"input":0.7,"output":0.7,"cache_read":0.35}},"qwen/qwen3-max":{"id":"qwen/qwen3-max","name":"Qwen3 Max","description":"Flagship Qwen3 model for coding agents, complex reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":32768},"cost":{"input":1.2002,"output":6.001,"cache_read":0.6001},"canonical_model_id":"alibaba/qwen3-max"},"qwen/qwen3-235b-a22b":{"id":"qwen/qwen3-235b-a22b","name":"Qwen 3 235b A22B","description":"Large open Qwen MoE for multilingual reasoning, coding, and tool use","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.0875,"output":0.35,"cache_read":0.0175},"canonical_model_id":"alibaba/qwen3-235b-a22b"},"qwen/qwen3-30b-a3b-instruct-2507":{"id":"qwen/qwen3-30b-a3b-instruct-2507","name":"Qwen3 30B A3B Instruct 2507","description":"Updated compact Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":32768},"cost":{"input":0.2,"output":0.5,"cache_read":0.1},"canonical_model_id":"alibaba/qwen3-30b-a3b-instruct-2507"},"qwen/qwen3.8-flash":{"id":"qwen/qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":991808,"input":991808,"output":131072},"cost":{"input":0.14,"output":0.42,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen/qwen3.6-flash":{"id":"qwen/qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":991808,"input":991808,"output":65536},"cost":{"input":0.19,"output":1.16,"cache_read":0.02,"cache_write":0.24},"canonical_model_id":"alibaba/qwen3.6-flash"},"qwen/qwen3.8-27b-kimiko":{"id":"qwen/qwen3.8-27b-kimiko","name":"Qwen 3.8 27B Kimiko","description":"Qwen 3.8 27B Kimiko is a creative finetune served by Aoru in NVFP4 with a 262,144-token context window. It supports image understanding, tool calling, and optional reasoning.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.6,"cache_read":0.05}},"qwen/qwen-2.5-72b-instruct":{"id":"qwen/qwen-2.5-72b-instruct","name":"Qwen2.5 72B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2025-07-03","last_updated":"2025-07-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":8192},"cost":{"input":0.36,"output":0.4,"cache_read":0.1785}},"qwen/qwen3.5-35b-a3b":{"id":"qwen/qwen3.5-35b-a3b","name":"Qwen3.5 35B A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":260096,"input":260096,"output":65536},"cost":{"input":0.14,"output":1,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"qwen/qwen3.5-plus:thinking":{"id":"qwen/qwen3.5-plus:thinking","name":"Qwen3.5 Plus Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"input":983616,"output":65536},"cost":{"input":0.4,"output":2.4,"cache_read":0.04},"canonical_model_id":"alibaba/qwen3.5-plus"},"qwen/qwen3.8-27b-obliterated":{"id":"qwen/qwen3.8-27b-obliterated","name":"Qwen 3.8 27B Obliterated","description":"Qwen 3.8 27B Obliterated is an open-weight multimodal model LoRA-tuned for fewer refusals across chat, coding, reasoning, tool use, and long-context work.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-07-29","last_updated":"2026-08-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"input":524288,"output":32768},"cost":{"input":0.25,"output":1.75,"cache_read":0.225}},"qwen/qwen3-coder-30b-a3b-instruct":{"id":"qwen/qwen3-coder-30b-a3b-instruct","name":"Qwen3 Coder 30B A3B Instruct","description":"Smaller Qwen coder for efficient local agents and repo-level fixes","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-31","last_updated":"2025-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"qwen/qwen-max":{"id":"qwen/qwen-max","name":"Qwen 2.5 Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-03","last_updated":"2025-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"input":32000,"output":8192},"cost":{"input":1.5997,"output":6.392,"cache_read":0.79985},"canonical_model_id":"alibaba/qwen-max"},"qwen/qwen3.6-27b:thinking":{"id":"qwen/qwen3.6-27b:thinking","name":"Qwen3.6 27B Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.203,"output":2.24,"cache_read":0.1015},"canonical_model_id":"alibaba/qwen3.6-27b"},"qwen/qwen3-8b":{"id":"qwen/qwen3-8b","name":"Qwen 3 8B","description":"Dense 8B Qwen3 model with switchable thinking for chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-04-29","last_updated":"2025-04-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":41000,"input":41000,"output":32768},"cost":{"input":0.47,"output":0.47,"cache_read":0.235},"canonical_model_id":"alibaba/qwen3-8b"},"qwen/qwen3.5-9b":{"id":"qwen/qwen3.5-9b","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.05,"output":0.15,"cache_read":0.025},"canonical_model_id":"alibaba/qwen3.5-9b"},"qwen/qwen3-14b":{"id":"qwen/qwen3-14b","name":"Qwen 3 14b","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":41000,"input":41000,"output":32768},"cost":{"input":0.08,"output":0.24,"cache_read":0.04}},"qwen/qwen2.5-coder-32b-instruct":{"id":"qwen/qwen2.5-coder-32b-instruct","name":"Qwen 2.5 Coder 32b","description":"Open coding-focused Qwen model for code generation, repair, and repository reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2024-11-12","last_updated":"2024-11-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"input":32000,"output":8192},"cost":{"input":0.2006,"output":0.2006,"cache_read":0.1003},"canonical_model_id":"alibaba/qwen2.5-coder-32b-instruct"},"qwen/qwen3.5-397b-a17b:thinking":{"id":"qwen/qwen3.5-397b-a17b:thinking","name":"Qwen3.5 397B A17B Thinking","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.39,"output":2.34,"cache_read":0.3},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"qwen/qwen3-235b-a22b-instruct-2507":{"id":"qwen/qwen3-235b-a22b-instruct-2507","name":"Qwen 3 235b A22B 2507","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.0875,"output":0.35,"cache_read":0.0175},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"qwen/qwen3.8-max":{"id":"qwen/qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":991000,"input":991000,"output":65536},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"qwen/qwen3.6-27b":{"id":"qwen/qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.203,"output":2.24,"cache_read":0.1015},"canonical_model_id":"alibaba/qwen3.6-27b"},"qwen/qwen3-235b-a22b-thinking-2507":{"id":"qwen/qwen3-235b-a22b-thinking-2507","name":"Qwen 3 235b A22B 2507 Thinking","description":"Updated large open Qwen3 MoE thinking model for reasoning, math, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-07-25","last_updated":"2025-07-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":81920},"cost":{"input":0.3,"output":0.5},"canonical_model_id":"alibaba/qwen3-235b-a22b-thinking-2507"},"qwen/qwen3.8-omni-flash":{"id":"qwen/qwen3.8-omni-flash","name":"Qwen3.8 Omni Flash","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":991808,"input":991808,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-omni-flash"},"qwen/qwen3.5-27b:thinking":{"id":"qwen/qwen3.5-27b:thinking","name":"Qwen3.5 27B Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":260096,"input":260096,"output":65536},"cost":{"input":0.25,"output":2,"cache_read":0.135},"canonical_model_id":"alibaba/qwen3.5-27b"},"qwen/qwen3.8-27b-fimi":{"id":"qwen/qwen3.8-27b-fimi","name":"Qwen 3.8 27B Fimi","description":"Qwen 3.8 27B Fimi is a creative finetune served by Aoru in NVFP4 with a 262,144-token context window. It supports image understanding, tool calling, and optional reasoning.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.6,"cache_read":0.05}},"qwen/qwen3.8-27b-antislop":{"id":"qwen/qwen3.8-27b-antislop","name":"Qwen 3.8 27B Antislop","description":"Qwen 3.8 27B Antislop is a creative finetune served by Aoru in NVFP4 with a 262,144-token context window. It supports image understanding, tool calling, and optional reasoning.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.6,"cache_read":0.05}},"qwen/qwen3.8-max-0902":{"id":"qwen/qwen3.8-max-0902","name":"Qwen3.8 Max 0902","description":"2026-09-02 upgraded snapshot of Qwen3.8 Max with stronger coding, collaborative agents, and multimodal document understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":991808,"input":991808,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max-0902"},"qwen/qwen3.5-flash:thinking":{"id":"qwen/qwen3.5-flash:thinking","name":"Qwen3.5 Flash Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":991808,"input":991808,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.5-flash"},"qwen/qwen3.8-27b-obliterated:thinking":{"id":"qwen/qwen3.8-27b-obliterated:thinking","name":"Qwen 3.8 27B Obliterated Thinking","description":"Qwen 3.8 27B Obliterated with thinking enabled for more deliberate creative work, coding, multimodal analysis, tool use, and long-context problem solving.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-07-29","last_updated":"2026-08-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"input":524288,"output":32768},"cost":{"input":0.25,"output":1.75,"cache_read":0.225}},"qwen/qwen3-coder-flash":{"id":"qwen/qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":0.3,"output":1.5,"cache_read":0.15},"canonical_model_id":"alibaba/qwen3-coder-flash"},"qwen/qwen3.7-plus":{"id":"qwen/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":991808,"input":991808,"output":65536},"cost":{"input":0.4,"output":1.6,"cache_read":0.08,"cache_write":0.5},"canonical_model_id":"alibaba/qwen3.7-plus"},"qwen/qwen3.5-122b-a10b:thinking":{"id":"qwen/qwen3.5-122b-a10b:thinking","name":"Qwen3.5 122B A10B Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.26,"output":2.08,"cache_read":0.103788},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"qwen/qwen3.8-max-prime":{"id":"qwen/qwen3.8-max-prime","name":"Qwen3.8 Max Prime","description":"High-throughput edition of Qwen3.8 Max for coding, professional work, multimodal understanding, and long-running agent workflows","family":"qwen3.8-max","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":131072},"cost":{"input":4,"output":12,"cache_read":0.5},"canonical_model_id":"alibaba/qwen3.8-max-prime"},"qwen/qwen3.8-27b-darkidol":{"id":"qwen/qwen3.8-27b-darkidol","name":"Qwen 3.8 27B DarkIdol","description":"Qwen 3.8 27B DarkIdol is a creative finetune served by Aoru in NVFP4 with a 262,144-token context window. It supports image understanding, tool calling, and optional reasoning.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.6,"cache_read":0.05}},"qwen/qwen3.5-397b-a17b":{"id":"qwen/qwen3.5-397b-a17b","name":"Qwen3.5 397B A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.39,"output":2.34,"cache_read":0.3},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"qwen/qwen3.8-27b-synthia":{"id":"qwen/qwen3.8-27b-synthia","name":"Qwen 3.8 27B Synthia","description":"Qwen 3.8 27B Synthia is a text-only roleplay finetune served by Aoru in NVFP4 with a 262,144-token context window.","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.6,"cache_read":0.05}},"qwen/qwen3-next-80b-a3b-instruct":{"id":"qwen/qwen3-next-80b-a3b-instruct","name":"Qwen3 Next 80B A3B (Instruct)","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":1.1,"cache_read":0.07},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"qwen/qwen3.8-27b-kiwen":{"id":"qwen/qwen3.8-27b-kiwen","name":"Qwen 3.8 27B Kiwen","description":"Qwen 3.8 27B Kiwen is a creative finetune served by Aoru in NVFP4 with a 262,144-token context window. It supports image understanding, tool calling, and optional reasoning.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.6,"cache_read":0.05}},"qwen/qwen3-30b-a3b":{"id":"qwen/qwen3-30b-a3b","name":"Qwen3 30B A3B","description":"Sparse MoE Qwen model with 3B active parameters for efficient chat and reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":41000,"input":41000,"output":32768},"cost":{"input":0.1,"output":0.3,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3-30b-a3b"},"qwen/qwen3.5-flash":{"id":"qwen/qwen3.5-flash","name":"Qwen3.5 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":991808,"input":991808,"output":65536},"cost":{"input":0.1,"output":0.4,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.5-flash"},"qwen/qwen3-32b":{"id":"qwen/qwen3-32b","name":"Qwen 3 32b","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":41000,"input":41000,"output":32768},"cost":{"input":0.1,"output":0.3,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3-32b"},"qwen/qwen3.8-27b:thinking":{"id":"qwen/qwen3.8-27b:thinking","name":"Qwen3.8 27B Thinking","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1001536,"input":1001536,"output":32768},"cost":{"input":0.15,"output":0.7,"cache_read":0.04},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3.5-omni-plus":{"id":"qwen/qwen3.5-omni-plus","name":"Qwen3.5 Omni Plus","description":"Qwen3.5 Omni Plus is Qwen's stronger general multimodal model. We verified live support for text prompts, images, audio files, and direct video URLs on Alibaba's chat-completions-compatible API. Alibaba describes Plus as a comprehensive evolution of Qwen3 Omni with support for over 10 hours of audio input.","family":"qwen3.5","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-03-30","last_updated":"2026-03-30","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"input":983616,"output":65536}},"qwen/qwen3-max-2026-01-23":{"id":"qwen/qwen3-max-2026-01-23","name":"Qwen3 Max 2026-01-23","description":"Qwen3 Max is Alibaba's flagship Qwen 3 reasoning model with native tool use (web search, web extractor, code interpreter) and a 256K context window.","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-01-26","last_updated":"2026-01-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"input":256000,"output":32768},"cost":{"input":1.2002,"output":6.001,"cache_read":0.6001}},"qwen/qwen-turbo":{"id":"qwen/qwen-turbo","name":"Qwen Turbo","description":"Efficient Qwen model for fast chat, extraction, and high-volume workloads","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2024-11-01","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":8192},"cost":{"input":0.04998,"output":0.2006,"cache_read":0.02499},"canonical_model_id":"alibaba/qwen-turbo"},"qwen/qwen3.5-omni-flash":{"id":"qwen/qwen3.5-omni-flash","name":"Qwen3.5 Omni Flash","description":"Qwen3.5 Omni Flash is Qwen's fast multimodal model. We verified live support for text prompts, images, audio files, and direct video URLs on Alibaba's chat-completions-compatible API. Alibaba describes Flash as a fully evolved version of Qwen3 Omni with audio input support across 60+ languages.","family":"qwen3.5","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-03-30","last_updated":"2026-03-30","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":49152,"input":49152,"output":16384}},"qwen/qwen3.8-27b-queen":{"id":"qwen/qwen3.8-27b-queen","name":"Qwen 3.8 27B Queen","description":"Qwen 3.8 27B Queen is an open-weight roleplay finetune with image understanding, tool calling, optional reasoning, and a 262,144-token context window.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-09-09","last_updated":"2026-09-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"input":524288,"output":32768},"cost":{"input":0.25,"output":1.5,"cache_read":0.125}},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":65536},"cost":{"input":1.475,"output":4.425,"cache_read":0.295,"cache_write":1.84375},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen3.7-plus:thinking":{"id":"qwen/qwen3.7-plus:thinking","name":"Qwen3.7 Plus Thinking","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"input":983616,"output":65536},"cost":{"input":0.4,"output":1.6,"cache_read":0.08,"cache_write":0.5},"canonical_model_id":"alibaba/qwen3.7-plus"},"qwen/qwen3.8-max:thinking":{"id":"qwen/qwen3.8-max:thinking","name":"Qwen3.8 Max Thinking","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":991000,"input":991000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"qwen/qwen3.7-max:thinking":{"id":"qwen/qwen3.7-max:thinking","name":"Qwen3.7 Max Thinking","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":65536},"cost":{"input":1.475,"output":4.425,"cache_read":0.295,"cache_write":1.84375},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen3.8-27b-uncensored":{"id":"qwen/qwen3.8-27b-uncensored","name":"Qwen 3.8 27B Uncensored","description":"Qwen 3.8 27B Uncensored is an NVFP4 open-weight multimodal model LoRA-tuned for fewer refusals across chat, coding, reasoning, tool use, and long-context work.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-07-29","last_updated":"2026-08-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":32768},"cost":{"input":1,"output":3,"cache_read":0.22}},"qwen/qwen-plus":{"id":"qwen/qwen-plus","name":"Qwen Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":995904,"input":995904,"output":32768},"cost":{"input":0.3995,"output":1.2002,"cache_read":0.19975},"canonical_model_id":"alibaba/qwen-plus"},"qwen/qwen3.5-35b-a3b:thinking":{"id":"qwen/qwen3.5-35b-a3b:thinking","name":"Qwen3.5 35B A3B Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":260096,"input":260096,"output":65536},"cost":{"input":0.14,"output":1,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"qwen/qwen3.8-27b-novelist":{"id":"qwen/qwen3.8-27b-novelist","name":"Qwen 3.8 27B Novelist","description":"Qwen 3.8 27B Novelist is a creative finetune served by Aoru in NVFP4 with a 262,144-token context window. It supports image understanding, tool calling, and optional reasoning.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.6,"cache_read":0.05}},"qwen/qwen3.8-27b-hemmingway":{"id":"qwen/qwen3.8-27b-hemmingway","name":"Qwen 3.8 27B Hemingway","description":"Qwen 3.8 27B Hemingway is an open-weight NVFP4 multimodal creative finetune for long-form prose, character dialogue, storytelling, and roleplay.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.25,"output":1.5,"cache_read":0.125}},"qwen/qwen3.5-122b-a10b":{"id":"qwen/qwen3.5-122b-a10b","name":"Qwen3.5 122B A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.26,"output":2.08,"cache_read":0.103788},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"qwen/qwen3.7-flash":{"id":"qwen/qwen3.7-flash","name":"Qwen3.7 Flash","description":"Lightweight multimodal Qwen model for high-throughput text, image, and video tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":991808,"input":991808,"output":65536},"cost":{"input":0.03,"output":0.13,"cache_read":0.006,"cache_write":0.038},"canonical_model_id":"alibaba/qwen3.7-flash"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1001536,"input":1001536,"output":32768},"cost":{"input":0.15,"output":0.7,"cache_read":0.04},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3.6-plus":{"id":"qwen/qwen3.6-plus","name":"Qwen 3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":991808,"input":991808,"output":65536},"cost":{"input":0.325,"output":1.95,"cache_read":0.0325,"cache_write":0.40625},"canonical_model_id":"alibaba/qwen3.6-plus"},"qwen/qwen3-vl-235b-a22b-instruct":{"id":"qwen/qwen3-vl-235b-a22b-instruct","name":"Qwen3 VL 235B A22B Instruct","description":"Qwen vision-language instruct model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.3,"output":1.9,"cache_read":0.15},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"qwen/qwen3.8-27b-uncensored:thinking":{"id":"qwen/qwen3.8-27b-uncensored:thinking","name":"Qwen 3.8 27B Uncensored Thinking","description":"Qwen 3.8 27B Uncensored with thinking enabled for more deliberate creative work, coding, multimodal analysis, tool use, and long-context problem solving.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-07-29","last_updated":"2026-08-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":32768},"cost":{"input":1,"output":3,"cache_read":0.22}},"qwen/qwen3.5-27b":{"id":"qwen/qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":260096,"input":260096,"output":65536},"cost":{"input":0.25,"output":2,"cache_read":0.135},"canonical_model_id":"alibaba/qwen3.5-27b"},"qwen/qwen3.8-27b-cybersecurity":{"id":"qwen/qwen3.8-27b-cybersecurity","name":"Qwen 3.8 27B Cybersecurity","description":"Qwen 3.8 27B Cybersecurity is a cybersecurity-focused variant based on the uncensored model, with provider moderation for illegal activities. It supports optional reasoning, image understanding, tool calling, and a 262,144-token context window.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-09-19","last_updated":"2026-09-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.6,"cache_read":0.05}},"qwen/qwen3.7-flash:thinking":{"id":"qwen/qwen3.7-flash:thinking","name":"Qwen3.7 Flash Thinking","description":"Lightweight multimodal Qwen model for high-throughput text, image, and video tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"input":983616,"output":65536},"cost":{"input":0.03,"output":0.13,"cache_read":0.006,"cache_write":0.038},"canonical_model_id":"alibaba/qwen3.7-flash"},"qwen/qwen3.6-max-preview":{"id":"qwen/qwen3.6-max-preview","name":"Qwen3.6 Max Preview","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":245760,"input":245760,"output":65536},"cost":{"input":1.04,"output":6.24,"cache_read":0.52},"canonical_model_id":"alibaba/qwen3.6-max-preview"},"qwen/qwen3.8-27b-fable":{"id":"qwen/qwen3.8-27b-fable","name":"Qwen 3.8 27B Fable","description":"Qwen 3.8 27B Fable is an open-weight multimodal creative finetune for expressive dialogue, long-form storytelling, character work, and roleplay.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-07-29","last_updated":"2026-08-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"input":524288,"output":32768},"cost":{"input":0.25,"output":1.5,"cache_read":0.125}},"qwen/qwen3-vl-235b-a22b-thinking":{"id":"qwen/qwen3-vl-235b-a22b-thinking","name":"Qwen3 VL 235B A22B Thinking","description":"Qwen vision-language thinking model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-thinking"},"qwen/qwen3-coder":{"id":"qwen/qwen3-coder","name":"Qwen 3 Coder 480B","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"input":262000,"output":65536},"cost":{"input":0.13,"output":0.5,"cache_read":0.065},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"qwen/qwen-long":{"id":"qwen/qwen-long","name":"Qwen Long 10M","description":"Alibaba's huge context window model. Takes in up to 10 million tokens, which is equivalent to dozens of books.","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-08-01","last_updated":"2024-08-01","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":10000000,"input":10000000,"output":8192},"cost":{"input":0.1003,"output":0.408,"cache_read":0.05015}},"qwen/qwen3-coder-next":{"id":"qwen/qwen3-coder-next","name":"Qwen3 Coder Next","description":"Open-weight Qwen coding model for agents, repository edits, and multi-turn tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.250251,"output":0.80293,"cache_read":0.079764},"canonical_model_id":"alibaba/qwen3-coder-next"},"qwen/qwen3.6-35b-a3b":{"id":"qwen/qwen3.6-35b-a3b","name":"Qwen3.6 35B A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.112,"output":0.8,"cache_read":0.056},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"qwen/qwen3.6-35b-a3b:thinking":{"id":"qwen/qwen3.6-35b-a3b:thinking","name":"Qwen3.6 35B A3B Thinking","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.112,"output":0.8,"cache_read":0.056},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"qwen/qwen3.5-plus":{"id":"qwen/qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":983616,"input":983616,"output":65536},"cost":{"input":0.4,"output":2.4,"cache_read":0.04},"canonical_model_id":"alibaba/qwen3.5-plus"},"qwen/qwen3.8-27b-swift":{"id":"qwen/qwen3.8-27b-swift","name":"Qwen 3.8 27B Swift","description":"Qwen 3.8 27B Swift is a finetune for fast responses, served by Aoru in NVFP4 with a 262,144-token context window. It supports image understanding, tool calling, and optional reasoning.","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.6,"cache_read":0.05}},"qwen/qwen3-next-80b-a3b-thinking":{"id":"qwen/qwen3-next-80b-a3b-thinking","name":"Qwen3 Next 80B A3B (Thinking)","description":"Efficient Qwen thinking model for local reasoning, math, and coding agents","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":32768},"cost":{"input":0.15,"output":0.65,"cache_read":0.075},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-thinking"},"meganova-ai/manta-pro-1.0":{"id":"meganova-ai/manta-pro-1.0","name":"Manta Pro 1.0","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-09-20","last_updated":"2025-12-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"input":65536,"output":32768},"cost":{"input":0.06,"output":0.5,"cache_read":0.03}},"meganova-ai/manta-mini-1.0":{"id":"meganova-ai/manta-mini-1.0","name":"Manta Mini 1.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-09-20","last_updated":"2025-12-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8192,"input":8192,"output":8192},"cost":{"input":0.02,"output":0.16,"cache_read":0.01}},"meganova-ai/manta-flash-1.0":{"id":"meganova-ai/manta-flash-1.0","name":"Manta Flash 1.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-09-20","last_updated":"2025-12-20","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16384,"input":16384,"output":16384},"cost":{"input":0.02,"output":0.16,"cache_read":0.01}},"sakana/fugu-max":{"id":"sakana/fugu-max","name":"Fugu Max","description":"Multi-agent model for routing expert agents across complex analytical tasks","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":128000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"sakana/fugu-max"},"sakana/fugu-ultra":{"id":"sakana/fugu-ultra","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":16384},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"sakana/fugu-ultra"},"sakana/fugu-ultra-v1.1":{"id":"sakana/fugu-ultra-v1.1","name":"Fugu Ultra v1.1","description":"Sakana AI's upgraded Fugu Ultra release with stronger coding, agentic task execution, and advanced reasoning through dynamic orchestration of frontier models.","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":16384},"cost":{"input":5,"output":30,"cache_read":0.5}},"minimax/minimax-m2.7-turbo":{"id":"minimax/minimax-m2.7-turbo","name":"MiniMax M2.7 Turbo","description":"Efficient MiniMax model for quick assistance, coding, and routine automation","family":"minimax-m2.7","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"input":204800,"output":131072},"cost":{"input":0.6,"output":2.4,"cache_read":0.06}},"minimax/minimax-m2.1":{"id":"minimax/minimax-m2.1","name":"MiniMax M2.1","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":131072},"cost":{"input":0.33,"output":1.32,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.1"},"minimax/minimax-m3.1-flash":{"id":"minimax/minimax-m3.1-flash","name":"MiniMax M3.1 Flash","description":"Frontier multimodal coding model with 1M context window and tunable thinking depth","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-19","last_updated":"2026-10-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":524288},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"minimax/MiniMax-M3.1-Flash"},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"input":204800,"output":131072},"cost":{"input":0.27,"output":1.08,"cache_read":0.027},"canonical_model_id":"minimax/MiniMax-M2.5"},"minimax/minimax-m3:thinking":{"id":"minimax/minimax-m3:thinking","name":"MiniMax M3 Thinking","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"input":512000,"output":80000},"cost":{"input":0.23,"output":0.96,"cache_read":0.05},"canonical_model_id":"minimax/MiniMax-M3"},"minimax/minimax-01":{"id":"minimax/minimax-01","name":"MiniMax 01","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-01-15","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000192,"input":1000192,"output":16384},"cost":{"input":0.1394,"output":1.122,"cache_read":0.0697}},"minimax/minimax-m2":{"id":"minimax/minimax-m2","name":"MiniMax M2","description":"Efficient open MiniMax model built for coding agents and tool-heavy workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":131072},"cost":{"input":0.17,"output":1.53,"cache_read":0.085},"canonical_model_id":"minimax/MiniMax-M2"},"minimax/minimax-m2.7":{"id":"minimax/minimax-m2.7","name":"MiniMax M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"input":204800,"output":131072},"cost":{"input":0.21,"output":0.84,"cache_read":0.042},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/minimax-m2-her":{"id":"minimax/minimax-m2-her","name":"MiniMax M2-her","description":"MiniMax M2 variant tuned for conversational and character-driven agent interactions","family":"minimax","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-01-23","last_updated":"2026-01-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":65532,"input":65532,"output":2048},"cost":{"input":0.302,"output":1.207,"cache_read":0.151},"canonical_model_id":"minimax/MiniMax-M2-Her"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"input":512000,"output":80000},"cost":{"input":0.23,"output":0.96,"cache_read":0.05},"canonical_model_id":"minimax/MiniMax-M3"},"minimax/minimax-latest":{"id":"minimax/minimax-latest","name":"MiniMax Latest","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"release_date":"2026-05-03","last_updated":"2026-05-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"input":512000,"output":80000},"cost":{"input":0.23,"output":0.96,"cache_read":0.05}},"liquid/lfm-2.5-2.6b":{"id":"liquid/lfm-2.5-2.6b","name":"LFM2.5 2.6B","description":"Liquid AI's compact 2.6B reasoning model for agent workflows, data extraction, RAG, and long-context processing. It supports tool calling and structured output, but Liquid advises against using it for agentic coding. Warning: prompts and responses may be logged and used for model training or service improvement; do not send sensitive data.","family":"liquid","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":32768},"cost":{"input":0.1,"output":0.2,"cache_read":0.05}},"liquid/lfm-2.5-24b-a2b":{"id":"liquid/lfm-2.5-24b-a2b","name":"LFM2.5 24B A2B","description":"Liquid AI's text-only mixture-of-experts model for reasoning and tool-using agents, with 24B total and 2.45B active parameters. It always thinks before answering and supports structured output. Pair it with retrieval for knowledge-heavy tasks. Open weights use the LFM Open License v1.0, with a $10M annual-revenue commercial threshold; hosted API use is subject to separate service terms that permit retention and use of prompts and responses for model training.","family":"liquid","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-10-14","last_updated":"2026-10-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.05,"output":0.7,"cache_read":0.025}},"moondream/moondream3-preview":{"id":"moondream/moondream3-preview","name":"Moondream 3 Preview","description":"Moondream 3 Preview is the original 9B mixture-of-experts vision-language checkpoint with 2B active parameters, for visual question answering, captioning, OCR, and visual reasoning. It accepts text or one image with optional reasoning, a 32,000-token context, and up to 4,096 output tokens.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"release_date":"2026-10-16","last_updated":"2026-10-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"input":32000,"output":4096},"cost":{"input":0.3,"output":2.5}},"moondream/moondream3.1-9b-a2b":{"id":"moondream/moondream3.1-9b-a2b","name":"Moondream 3.1 9B A2B","description":"Moondream 3.1 is the successor to Moondream 3 Preview: a distinct 9B mixture-of-experts vision-language checkpoint with 2B active parameters, for visual question answering, captioning, OCR, and visual reasoning. It accepts text or one image with optional reasoning, a 32,000-token context, and up to 4,096 output tokens.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"release_date":"2026-10-16","last_updated":"2026-10-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"input":32000,"output":4096},"cost":{"input":0.3,"output":2.5}},"moonshotai/kimi-k2-thinking":{"id":"moonshotai/kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Thinking Kimi model for slower research passes, planning, and hard technical questions","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":98304},"cost":{"input":0.6,"output":2.5,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"moonshotai/kimi-k2.5:thinking":{"id":"moonshotai/kimi-k2.5:thinking","name":"Kimi K2.5 Thinking","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.375,"output":2,"cache_read":0.07},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/kimi-k2-instruct-0711":{"id":"moonshotai/kimi-k2-instruct-0711","name":"Kimi K2 0711","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.4,"output":1.8,"cache_read":0.2},"canonical_model_id":"moonshotai/kimi-k2-instruct"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":943718},"cost":{"input":1.2,"output":5.5,"cache_read":0.2},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/Kimi-K2-Instruct-0905":{"id":"moonshotai/Kimi-K2-Instruct-0905","name":"Kimi K2 0905","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":100352},"cost":{"input":0.4,"output":1.8,"cache_read":0.2},"canonical_model_id":"moonshotai/kimi-k2-0905"},"moonshotai/kimi-k2.5":{"id":"moonshotai/kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.375,"output":2,"cache_read":0.07},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/kimi-latest":{"id":"moonshotai/kimi-latest","name":"Kimi Latest","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-03","last_updated":"2026-05-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":943718},"cost":{"input":1.2,"output":5.5,"cache_read":0.2}},"moonshotai/kimi-k2-instruct":{"id":"moonshotai/kimi-k2-instruct","name":"Kimi K2 Instruct","description":"Non-thinking Kimi K2 MoE instruction model for coding and tool-using agents","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":8192},"cost":{"input":0.4,"output":1.8,"cache_read":0.2},"canonical_model_id":"moonshotai/kimi-k2-instruct"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.45,"output":1.95,"cache_read":0.045},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2.7-code-highspeed":{"id":"moonshotai/kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code High-Speed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":1.9,"output":8,"cache_read":0.32},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"moonshotai/kimi-k2.6:thinking":{"id":"moonshotai/kimi-k2.6:thinking","name":"Kimi K2.6 Thinking","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.45,"output":1.95,"cache_read":0.045},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":65536},"cost":{"input":0.6712,"output":3.35,"cache_read":0.18},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"VongolaChouko/Starcannon-Unleashed-12B-v1.0":{"id":"VongolaChouko/Starcannon-Unleashed-12B-v1.0","name":"Mistral Nemo Starcannon 12b v1","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"nimbz/gemma-4-giftige-blume-31b-v2":{"id":"nimbz/gemma-4-giftige-blume-31b-v2","name":"Gemma 4 Giftige-Blume V2 31B","description":"Nimbz's second Giftige-Blume merge focuses on character roleplay, creative prose, and stricter prompt adherence. It combines storymaxxed, Equinox, Mero-Artemis, Musica, Ortenzya, Gemopus, and Sprinkle. This text-only Gemma 4 31B deployment supports a 65,536-token context window and up to 8,192 output tokens.","family":"gemma","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":false,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":8192},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"nimbz/schattenblume-31b":{"id":"nimbz/schattenblume-31b","name":"Schattenblume 31B","description":"Nimbz's Gemma 4 31B merge for character roleplay, expressive prose, and creative dialogue. It combines Scotoma 2, Giftige-Blume v1, and MeroMero v2. This text-only deployment supports a 65,536-token context window and up to 8,192 output tokens.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":false,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":8192},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"deepseek/deepseek-v4-flash-0423":{"id":"deepseek/deepseek-v4-flash-0423","name":"DeepSeek V4 Flash 0423","description":"Initial DeepSeek V4 Flash snapshot for economical reasoning, coding, and million-token agent workloads","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0423"},"deepseek/deepseek-v4-flash-0423:thinking":{"id":"deepseek/deepseek-v4-flash-0423:thinking","name":"DeepSeek V4 Flash 0423 (Thinking)","description":"Initial DeepSeek V4 Flash snapshot for economical reasoning, coding, and million-token agent workloads","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0423"},"deepseek/deepseek-latest":{"id":"deepseek/deepseek-latest","name":"DeepSeek Latest","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"release_date":"2026-05-03","last_updated":"2026-05-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":0.66,"output":1.98,"cache_read":0.022}},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":384000},"cost":{"input":0.09,"output":0.25,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v3.2:thinking":{"id":"deepseek/deepseek-v3.2:thinking","name":"DeepSeek V3.2 Thinking","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":163000,"input":163000,"output":65536},"cost":{"input":0.2088,"output":0.3096,"cache_read":0.0216},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":0.7,"output":1.4,"cache_read":0.07},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v4-pro-0813:thinking":{"id":"deepseek/deepseek-v4-pro-0813:thinking","name":"DeepSeek V4 Pro 0813 Thinking","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":0.66,"output":1.98,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"deepseek/deepseek-v4-flash:thinking":{"id":"deepseek/deepseek-v4-flash:thinking","name":"DeepSeek V4 Flash (Thinking)","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v4-flash-latest":{"id":"deepseek/deepseek-v4-flash-latest","name":"DeepSeek V4 Flash Latest","description":"Compatibility alias that routes to the newest dated DeepSeek V4 Flash release. Currently routes to DeepSeek V4 Flash 0731. ⚠️ This route goes directly to DeepSeek, so privacy and logging guarantees are limited.","family":"deepseek","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-08-02","last_updated":"2026-08-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":393216},"cost":{"input":0.1,"output":0.6,"cache_read":0.003}},"deepseek/deepseek-v4.1-flash:thinking":{"id":"deepseek/deepseek-v4.1-flash:thinking","name":"DeepSeek V4.1 Flash Thinking","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":384000},"cost":{"input":0.09,"output":0.25,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4.1-flash-1017:thinking":{"id":"deepseek/deepseek-v4.1-flash-1017:thinking","name":"DeepSeek V4.1 Flash 1017 Thinking","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":393216},"cost":{"input":0.1,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek/deepseek-v4-flash-vision-exp":{"id":"deepseek/deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":0.2156,"output":0.6468,"cache_read":0.00686},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"deepseek/deepseek-v4.1-flash-1017":{"id":"deepseek/deepseek-v4.1-flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":393216},"cost":{"input":0.1,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.05,"output":0.16,"cache_read":0.013},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v4-flash-0731:thinking":{"id":"deepseek/deepseek-v4-flash-0731:thinking","name":"DeepSeek V4 Flash 0731 (Thinking)","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.05,"output":0.16,"cache_read":0.013},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v3.2":{"id":"deepseek/deepseek-v3.2","name":"DeepSeek V3.2","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":163000,"input":163000,"output":65536},"cost":{"input":0.2088,"output":0.3096,"cache_read":0.0216},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepseek/deepseek-v4-pro:thinking":{"id":"deepseek/deepseek-v4-pro:thinking","name":"DeepSeek V4 Pro (Thinking)","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":0.7,"output":1.4,"cache_read":0.07},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":384000},"cost":{"input":0.66,"output":1.98,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"aion-labs/aion-3.0":{"id":"aion-labs/aion-3.0","name":"AionLabs: Aion 3.0","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-05-05","last_updated":"2026-05-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":3,"output":6,"cache_read":0.75},"canonical_model_id":"aion-labs/aion-3.0"},"aion-labs/aion-2.0":{"id":"aion-labs/aion-2.0","name":"AionLabs: Aion-2.0","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-21","last_updated":"2025-12-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.8,"output":1.6,"cache_read":0.2},"canonical_model_id":"aion-labs/aion-2.0"},"aion-labs/aion-rp-llama-3.1-8b":{"id":"aion-labs/aion-rp-llama-3.1-8b","name":"Llama 3.1 8b (uncensored)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12-31","release_date":"2025-02-04","last_updated":"2025-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":0.8,"output":1.6,"cache_read":0.4},"canonical_model_id":"aion-labs/aion-rp-llama-3.1-8b"},"aion-labs/aion-3.5-mini":{"id":"aion-labs/aion-3.5-mini","name":"AionLabs: Aion 3.5 Mini","description":"A GLM-family collaborative generation model tuned for immersive roleplay and storytelling, with stronger narrative structure, tension, conflict, and nuanced mature themes.","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.7,"output":1.4,"cache_read":0.18}},"aion-labs/aion-3.0-mini":{"id":"aion-labs/aion-3.0-mini","name":"AionLabs: Aion 3.0 Mini","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-05-14","last_updated":"2026-05-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.7,"output":1.4,"cache_read":0.18},"canonical_model_id":"aion-labs/aion-3.0-mini"},"aion-labs/aion-3.5":{"id":"aion-labs/aion-3.5","name":"AionLabs: Aion 3.5","description":"A GLM-family collaborative generation model tuned for immersive roleplay and storytelling, with stronger narrative structure, tension, conflict, and nuanced mature themes.","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":3,"output":6,"cache_read":0.75}},"nvidia/nemotron-3.5-content-safety":{"id":"nvidia/nemotron-3.5-content-safety","name":"Nemotron 3.5 Content Safety","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.05,"output":0.15,"cache_read":0.025},"canonical_model_id":"nvidia/nemotron-3.5-content-safety"},"nvidia/nemotron-3.5-super-vl":{"id":"nvidia/nemotron-3.5-super-vl","name":"Nvidia Nemotron 3.5 Super VL","description":"NVIDIA’s open-weight 120B model (12B active) for reasoning, coding, tool use, document and GUI understanding, and video understanding. Text, images and video in; text out. Served in NVFP4 with a 262,144-token shared context window. NanoGPT currently limits responses to 16,384 tokens while separate hosted output limits remain unpublished. OpenMDW 1.1 license.","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.15,"output":0.5,"cache_read":0.02},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"nvidia/nemotron-3-super-120b-a12b":{"id":"nvidia/nemotron-3-super-120b-a12b","name":"Nvidia Nemotron 3 Super 120B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.05,"output":0.25,"cache_read":0.025},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"nvidia/nemotron-3-ultra-550b-a55b":{"id":"nvidia/nemotron-3-ultra-550b-a55b","name":"Nvidia Nemotron 3 Ultra 550B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":65536},"cost":{"input":0.5,"output":2.5,"cache_read":0.25},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/nemotron-3-ultra-550b-a55b:thinking":{"id":"nvidia/nemotron-3-ultra-550b-a55b:thinking","name":"Nvidia Nemotron 3 Ultra 550B Thinking","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":65536},"cost":{"input":0.5,"output":2.5,"cache_read":0.25},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/Llama-3.3-Nemotron-Super-49B-v1":{"id":"nvidia/Llama-3.3-Nemotron-Super-49B-v1","name":"Nvidia Nemotron Super 49B","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-03-18","last_updated":"2025-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":16384},"cost":{"input":0.15,"output":0.15,"cache_read":0.075},"canonical_model_id":"nvidia/llama-3.3-nemotron-super-49b-v1"},"nvidia/Llama-3.1-Nemotron-70B-Instruct-HF":{"id":"nvidia/Llama-3.1-Nemotron-70B-Instruct-HF","name":"Nvidia Nemotron 70b","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-04-15","last_updated":"2025-04-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.357,"output":0.408,"cache_read":0.1785},"canonical_model_id":"nvidia/llama-3.1-nemotron-70b-instruct"},"nvidia/nemotron-3.5-lightning:thinking":{"id":"nvidia/nemotron-3.5-lightning:thinking","name":"Nvidia Nemotron 3.5 Lightning Thinking","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-09","release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":65536},"cost":{"input":0.05,"output":0.2,"cache_read":0.01},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/nemotron-3.5-lightning":{"id":"nvidia/nemotron-3.5-lightning","name":"Nvidia Nemotron 3.5 Lightning","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-09","release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":65536},"cost":{"input":0.05,"output":0.2,"cache_read":0.01},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/nemotron-3-nano-30b-a3b":{"id":"nvidia/nemotron-3-nano-30b-a3b","name":"Nvidia Nemotron 3 Nano 30B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-06-25","release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":235929},"cost":{"input":0.17,"output":0.68,"cache_read":0.085},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"nvidia/nemotron-3-super-120b-a12b:thinking":{"id":"nvidia/nemotron-3-super-120b-a12b:thinking","name":"Nvidia Nemotron 3 Super 120B Thinking","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":16384},"cost":{"input":0.05,"output":0.25,"cache_read":0.025},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"inflatebot/MN-12B-Mag-Mell-R1":{"id":"inflatebot/MN-12B-Mag-Mell-R1","name":"Mag Mell R1","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"arcee-ai/trinity-large-thinking":{"id":"arcee-ai/trinity-large-thinking","name":"Trinity Large Thinking","description":"Reasoning-optimized 398B MoE agent model with extended thinking for long-horizon and multi-turn tool use","family":"trinity","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":80000},"cost":{"input":0.25,"output":0.9,"cache_read":0.125},"canonical_model_id":"arcee-ai/trinity-large-thinking"},"microsoft/wizardlm-2-8x22b":{"id":"microsoft/wizardlm-2-8x22b","name":"WizardLM-2 8x22B","description":"Microsoft WizardLM instruction-tuned Mixtral MoE for multilingual dialogue and complex tasks","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2024-04-15","last_updated":"2024-04-15","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":8192},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465},"canonical_model_id":"microsoft/wizardlm-2-8x22b"},"GalrionSoftworks/MN-LooseCannon-12B-v1":{"id":"GalrionSoftworks/MN-LooseCannon-12B-v1","name":"MN-LooseCannon-12B-v1","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-07-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"unbiased/pareto-26.10":{"id":"unbiased/pareto-26.10","name":"Pareto 26.10","description":"Pareto 26.10 is Unbiased AI's multimodal composite model for research, coding, and agentic workflows. It accepts text and images, supports tool calling, and provides a 1M-token context window with up to 131K output tokens. This is the stable release of Pareto 26.10. Tool selection is automatic; forced tool selection, structured output, and adjustable reasoning controls are not supported.","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2026-10-01","last_updated":"2026-10-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.8,"output":3.2,"cache_read":0.03}},"unbiased/pareto-26.9":{"id":"unbiased/pareto-26.9","name":"Pareto 26.9","description":"Pareto 26.9 is an experimental multimodal composite model from Unbiased AI for research, coding, agentic workflows, and general-purpose tasks. It runs several frontier and open models for each request and returns a single selected or synthesized answer. This experimental release supports text and image input, tool calling, a 262K-token context window, and up to 131K output tokens. Its underlying model mix and behavior may change as it is evaluated. Request content may be retained for abuse prevention and security monitoring for up to 30 days, and is not used for model training without explicit consent.","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2026-09-18","last_updated":"2026-09-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"input":262144,"output":131072},"cost":{"input":2.5,"output":7.5,"cache_read":0.25}},"cohere/command-r-plus-08-2024":{"id":"cohere/command-r-plus-08-2024","name":"Cohere: Command R+","description":"Cohere's RAG workhorse for long-context enterprise search and tool use","family":"command-r","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":4096},"cost":{"input":2.856,"output":14.246,"cache_read":1.428},"canonical_model_id":"cohere/command-r-plus-08-2024"},"inference-net/schematron-v2-turbo":{"id":"inference-net/schematron-v2-turbo","name":"Schematron V2 Turbo","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.03,"output":0.15,"cache_read":0.015},"canonical_model_id":"inference-net/schematron-v2-turbo"},"inference-net/schematron-v2-small":{"id":"inference-net/schematron-v2-small","name":"Schematron V2 Small","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":4096},"cost":{"input":0.05,"output":0.23,"cache_read":0.025},"canonical_model_id":"inference-net/schematron-v2-small"},"TheDrummer/Cydonia-24B-v2":{"id":"TheDrummer/Cydonia-24B-v2","name":"The Drummer Cydonia 24B v2","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-02-17","last_updated":"2025-02-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":32768},"cost":{"input":0.1003,"output":0.1207,"cache_read":0.05015}},"TheDrummer/skyfall-31b-v4.2":{"id":"TheDrummer/skyfall-31b-v4.2","name":"TheDrummer Skyfall 31B v4.2","description":"TheDrummer's Skyfall 31B v4.2 is a Magistral Small finetune for creative writing, roleplay, and dialogue. This text-only deployment uses NVFP4 weights and supports a 16K-token context window.","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":4096},"cost":{"input":0.12,"output":0.15,"cache_read":0.06}},"TheDrummer/Cydonia-24B-v4.1":{"id":"TheDrummer/Cydonia-24B-v4.1","name":"The Drummer Cydonia 24B v4.1","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-04-30","release_date":"2025-09-27","last_updated":"2025-09-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":117964},"cost":{"input":0.3,"output":0.5,"cache_read":0.15},"canonical_model_id":"thedrummer/cydonia-24b-v4.1"},"TheDrummer/Anubis-70B-v1.1":{"id":"TheDrummer/Anubis-70B-v1.1","name":"Anubis 70B v1.1","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"input":32000,"output":16384},"cost":{"input":0.31,"output":0.31,"cache_read":0.155}},"TheDrummer/Anubis-70B-v1":{"id":"TheDrummer/Anubis-70B-v1","name":"Anubis 70B v1","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":16384},"cost":{"input":0.31,"output":0.31,"cache_read":0.155}},"TheDrummer/orion-26b-a4b-v1.1":{"id":"TheDrummer/orion-26b-a4b-v1.1","name":"Orion 26B A4B v1.1","description":"TheDrummer's Gemma 4 26B A4B fine-tune for creative writing, roleplay, and expressive dialogue. Supports optional thinking with a 65,536-token context window and up to 8,192 output tokens. Text input only.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":false,"structured_output":false,"release_date":"2026-10-16","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":8192},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"TheDrummer/Magidonia-24B-v4.3":{"id":"TheDrummer/Magidonia-24B-v4.3","name":"The Drummer Magidonia 24B v4.3","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-12-25","last_updated":"2025-12-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":32768},"cost":{"input":0.1003,"output":0.1207,"cache_read":0.05015}},"TheDrummer/skyfall-36b-v2":{"id":"TheDrummer/skyfall-36b-v2","name":"TheDrummer Skyfall 36B V2","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-06-30","release_date":"2025-03-10","last_updated":"2025-03-10","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":29491},"cost":{"input":0.55,"output":0.8,"cache_read":0.25},"canonical_model_id":"thedrummer/skyfall-36b-v2"},"TheDrummer/Rocinante-12B-v1.1":{"id":"TheDrummer/Rocinante-12B-v1.1","name":"Rocinante 12b","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"input":16384,"output":8192},"cost":{"input":0.408,"output":0.595,"cache_read":0.204}},"TheDrummer/Artemis-v1.1":{"id":"TheDrummer/Artemis-v1.1","name":"TheDrummer/Artemis v1.1","description":"TheDrummer's Artemis v1.1 is a Gemma 4 31B fine-tune for creative writing, expressive dialogue, and roleplay, with optional thinking and a 262K context window.","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-09-06","last_updated":"2026-09-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"TheDrummer/UnslopNemo-12B-v4.1":{"id":"TheDrummer/UnslopNemo-12B-v4.1","name":"UnslopNemo 12b v4","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-01-01","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"input":8192,"output":26214},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"TheDrummer/Cydonia-24B-v4":{"id":"TheDrummer/Cydonia-24B-v4","name":"The Drummer Cydonia 24B v4","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":32768},"cost":{"input":0.2006,"output":0.2414,"cache_read":0.1003}},"TheDrummer/Cydonia-24B-v4.3":{"id":"TheDrummer/Cydonia-24B-v4.3","name":"The Drummer Cydonia 24B v4.3","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-12-25","last_updated":"2025-12-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":32768},"cost":{"input":0.12,"output":0.15,"cache_read":0.06}},"nbeerbower/gemma4-gutenberg-31b":{"id":"nbeerbower/gemma4-gutenberg-31b","name":"Gemma 4 Gutenberg 31B","description":"nbeerbower's Gemma 4 31B finetune for literary fiction, character interiority, and controlled narrative pacing. Its text decoder was trained with ORPO on 14,816 Athanorlite-DPO preference pairs. This text-only deployment supports a 65,536-token context window and up to 8,192 output tokens.","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":8192},"cost":{"input":0.1,"output":0.45,"cache_read":0.05}},"meta-llama/llama-3.2-3b-instruct":{"id":"meta-llama/llama-3.2-3b-instruct","name":"Llama 3.2 3b Instruct","description":"Small instruction-tuned Llama model for multilingual dialogue and agentic retrieval","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":8192},"cost":{"input":0.0306,"output":0.0493,"cache_read":0.0153},"canonical_model_id":"meta/llama-3.2-3b-instruct"},"meta-llama/llama-3.3-70b-instruct":{"id":"meta-llama/llama-3.3-70b-instruct","name":"Llama 3.3 70b Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":16384},"cost":{"input":0.05,"output":0.23,"cache_read":0.025},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"meta-llama/llama-4-scout":{"id":"meta-llama/llama-4-scout","name":"Llama 4 Scout","description":"Open multimodal Llama model for long-context analysis and efficient agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":328000,"input":328000,"output":65536},"cost":{"input":0.085,"output":0.46,"cache_read":0.0425},"canonical_model_id":"meta/llama-4-scout-17b-instruct"},"meta-llama/llama-4-maverick":{"id":"meta-llama/llama-4-maverick","name":"Llama 4 Maverick","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.1875,"output":0.6525,"cache_read":0.05},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"meta-llama/llama-3.1-8b-instruct":{"id":"meta-llama/llama-3.1-8b-instruct","name":"Llama 3.1 8b Instruct","description":"Compact open Llama model for lightweight chat, drafting, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":16384},"cost":{"input":0.02,"output":0.04,"cache_read":0.0272},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"aisingapore/Gemma-SEA-LION-v4-27B-IT":{"id":"aisingapore/Gemma-SEA-LION-v4-27B-IT","name":"Gemma SEA-LION v4 27B","description":"Gemma 3 27B tuned by AI Singapore for Southeast Asian languages and instruction following","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":128000},"cost":{"input":0.24,"output":0.48},"canonical_model_id":"aisingapore/gemma-sea-lion-v4-27b-it"},"tencent/hy4-preview":{"id":"tencent/hy4-preview","name":"Tencent Hy4 Preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":64000},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"},"tencent/hy3":{"id":"tencent/hy3","name":"Tencent Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":128000},"cost":{"input":0.066,"output":0.26,"cache_read":0.029},"canonical_model_id":"tencent/hy3"},"MiniMaxAI/MiniMax-M1-80k":{"id":"MiniMaxAI/MiniMax-M1-80k","name":"MiniMax M1 80K","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":131072},"cost":{"input":0.6052,"output":2.4225,"cache_read":0.3026},"canonical_model_id":"minimax/minimax-m1-80k"},"deepseek-ai/DeepSeek-R1-0528":{"id":"deepseek-ai/DeepSeek-R1-0528","name":"DeepSeek R1 0528","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"input":163840,"output":32768},"cost":{"input":0.5,"output":2.15,"cache_read":0.35},"canonical_model_id":"deepseek/deepseek-r1-0528"},"deepseek-ai/DeepSeek-V3.1:thinking":{"id":"deepseek-ai/DeepSeek-V3.1:thinking","name":"DeepSeek V3.1 Thinking","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":0.2,"output":0.7,"cache_read":0.1},"canonical_model_id":"deepseek/deepseek-v3.1"},"deepseek-ai/DeepSeek-V3.1-Terminus:thinking":{"id":"deepseek-ai/DeepSeek-V3.1-Terminus:thinking","name":"DeepSeek V3.1 Terminus (Thinking)","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek-thinking","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2024-01-01","last_updated":"2025-09-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":0.25,"output":0.7,"cache_read":0.125}},"deepseek-ai/deepseek-v3.2-exp-thinking":{"id":"deepseek-ai/deepseek-v3.2-exp-thinking","name":"DeepSeek V3.2 Exp Thinking","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"input":163840,"output":65536},"cost":{"input":0.28,"output":0.42,"cache_read":0.14}},"deepseek-ai/deepseek-v3.2-exp":{"id":"deepseek-ai/deepseek-v3.2-exp","name":"DeepSeek V3.2 Exp","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2025-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"input":163840,"output":65536},"cost":{"input":0.28,"output":0.42,"cache_read":0.14}},"deepseek-ai/DeepSeek-V3.1":{"id":"deepseek-ai/DeepSeek-V3.1","name":"DeepSeek V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":0.2,"output":0.7,"cache_read":0.1},"canonical_model_id":"deepseek/deepseek-v3.1"},"deepseek-ai/DeepSeek-V3.1-Terminus":{"id":"deepseek-ai/DeepSeek-V3.1-Terminus","name":"DeepSeek V3.1 Terminus","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"release_date":"2025-08-02","last_updated":"2025-08-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":0.25,"output":0.7,"cache_read":0.125}},"meta/muse-spark-1.3":{"id":"meta/muse-spark-1.3","name":"Muse Spark 1.3","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":943718},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.3"},"meta/muse-spark-open":{"id":"meta/muse-spark-open","name":"Muse Spark Open","description":"Muse Spark Open is an 816B total / 42B active open-weight multimodal reasoning model from Meta for coding and long-horizon agentic work, with 1M-token context.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-open"},"meta/muse-spark-1.2":{"id":"meta/muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":65536},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"meta/muse-spark-1.2-contributor":{"id":"meta/muse-spark-1.2-contributor","name":"Muse Spark 1.2 Contributor (Data Used for Training)","description":"A much cheaper opt-in version of Muse Spark 1.2 with the same multimodal coding and agentic capabilities. Prompts and outputs sent to this Contributor model may be used by Meta for training and to improve its products; use the standard Muse Spark 1.2 model if you do not want your data used for training.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":65536},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"meta/muse-spark-1.1":{"id":"meta/muse-spark-1.1","name":"Muse Spark 1.1","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":65536},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.1"},"meta/muse-glimmer-30b":{"id":"meta/muse-glimmer-30b","name":"Muse Glimmer 30B","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"input":131072,"output":117964},"cost":{"input":0.35,"output":1.5,"cache_read":0.04},"canonical_model_id":"meta/muse-glimmer-30b"},"meta/muse-spark-1.3-contributor":{"id":"meta/muse-spark-1.3-contributor","name":"Muse Spark 1.3 Contributor","description":"Meta's Muse Spark 1.3 Contributor is a frontier multimodal reasoning model for long-horizon coding and agentic workflows, with strong gains in computer use, browsing, professional tool use, codebase understanding, and million-token retrieval. It accepts text, images, audio, video, and files, supports tool calling and structured output, and always reasons before answering. Prompts and outputs may be used by Meta for training and to improve its products.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":943718},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"stepfun/step-5-preview":{"id":"stepfun/step-5-preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":1000000},"cost":{"input":1,"output":2.7,"cache_read":0.05},"canonical_model_id":"stepfun/step-5-preview"},"stepfun/step-3.7-flash:thinking":{"id":"stepfun/step-3.7-flash:thinking","name":"Step 3.7 Flash Thinking","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":256000},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"Steelskull/L3.3-Electra-R1-70b":{"id":"Steelskull/L3.3-Electra-R1-70b","name":"Steelskull Electra R1 70b","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":0.69989,"output":0.69989,"cache_read":0.349945}},"Steelskull/L3.3-MS-Nevoria-70b":{"id":"Steelskull/L3.3-MS-Nevoria-70b","name":"Steelskull Nevoria 70b","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"Steelskull/L3.3-Cu-Mai-R1-70b":{"id":"Steelskull/L3.3-Cu-Mai-R1-70b","name":"Llama 3.3 70B Cu Mai","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"Steelskull/L3.3-Nevoria-R1-70b":{"id":"Steelskull/L3.3-Nevoria-R1-70b","name":"Steelskull Nevoria R1 70b","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"nothingiisreal/L3.1-70B-Celeste-V0.1-BF16":{"id":"nothingiisreal/L3.1-70B-Celeste-V0.1-BF16","name":"Llama 3.1 70B Celeste v0.1","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"input":32768,"output":16384},"cost":{"input":0.493,"output":0.493,"cache_read":0.2465}},"fireworks/ember-1":{"id":"fireworks/ember-1","name":"Ember 1","description":"Specialized model from Fireworks built on Kimi K3, producing shorter reasoning traces with approximately 40% fewer tokens while maintaining comparable quality","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"fireworks/ember-1"},"z-ai/glm-5-turbo":{"id":"z-ai/glm-5-turbo","name":"GLM 5 Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":202800,"input":202800,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5-turbo"},"z-ai/glm-5.3-flash-uncensored":{"id":"z-ai/glm-5.3-flash-uncensored","name":"GLM 5.3 Flash Uncensored","description":"GLM 5.3 Flash Uncensored is an uncensored fine-tune of the efficient 320B mixture-of-experts reasoning model, built for unrestricted chat, creative writing, coding, agentic work, tool use, and long-context tasks.","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-07-29","last_updated":"2026-08-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":32768},"cost":{"input":0.2,"output":0.8,"cache_read":0.07}},"z-ai/glm-4.5v":{"id":"z-ai/glm-4.5v","name":"GLM 4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":16384},"cost":{"input":0.6,"output":1.8,"cache_read":0.3},"canonical_model_id":"zhipuai/glm-4.5v"},"z-ai/glm-4.7":{"id":"z-ai/glm-4.7","name":"GLM 4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":65535},"cost":{"input":0.4004,"output":1.9292,"cache_read":0.08008},"canonical_model_id":"zhipuai/glm-4.7"},"z-ai/glm-4.7-original":{"id":"z-ai/glm-4.7-original","name":"GLM 4.7 Original","description":"GLM-4.7 is a next-gen GLM series text model with stronger reasoning, long-context chat, and reliable tool use. Routed directly via Z-AI (Zhipu).","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":65535},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.7"},"z-ai/glm-latest":{"id":"z-ai/glm-latest","name":"GLM Latest","description":"Compatibility alias that routes to the newest thinking GLM model. Currently routes to GLM 5.2 Thinking.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"release_date":"2026-05-03","last_updated":"2026-05-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.6,"output":1.1,"cache_read":0.2}},"z-ai/glm-4.6v":{"id":"z-ai/glm-4.6v","name":"GLM 4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":24000},"cost":{"input":0.3,"output":0.9,"cache_read":0.15},"canonical_model_id":"zhipuai/glm-4.6v"},"z-ai/glm-5.3-flash-apex":{"id":"z-ai/glm-5.3-flash-apex","name":"Apex Flash 1","description":"Apex Flash 1 is Cantina Security and Yeta's cybersecurity-focused post-train of GLM 5.3 Flash for code investigation and tool use.","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":32768},"cost":{"input":0.15,"output":0.5,"cache_read":0.075}},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.42,"output":1.32,"cache_read":0.078},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/glm-5v-turbo":{"id":"z-ai/glm-5v-turbo","name":"GLM 5V Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":202800,"input":202800,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5v-turbo"},"z-ai/glm-5.2:thinking":{"id":"z-ai/glm-5.2:thinking","name":"GLM 5.2 Thinking","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.42,"output":1.32,"cache_read":0.078},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/glm-5":{"id":"z-ai/glm-5","name":"GLM 5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":128000},"cost":{"input":0.6,"output":1.9,"cache_read":0.1},"canonical_model_id":"zhipuai/glm-5"},"z-ai/GLM-4.6-turbo:thinking":{"id":"z-ai/GLM-4.6-turbo:thinking","name":"GLM 4.6 Turbo (Thinking)","description":"GLM 4.6 Turbo with thinking mode enabled for enhanced reasoning; shows internal reasoning and supports long context.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"release_date":"2025-10-02","last_updated":"2025-10-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"input":204800,"output":131072},"cost":{"input":1,"output":3,"cache_read":0.5}},"z-ai/glm-4.6:thinking":{"id":"z-ai/glm-4.6:thinking","name":"GLM 4.6 Thinking","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":65535},"cost":{"input":0.5,"output":2,"cache_read":0.1},"canonical_model_id":"zhipuai/glm-4.6"},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.6,"output":1.1,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5.3"},"z-ai/glm-5.3-uncensored":{"id":"z-ai/glm-5.3-uncensored","name":"GLM 5.3 Uncensored","description":"An experimental uncensored version of the full GLM 5.3 reasoning model for chat, creative writing, coding, and tool use. It may show unusual behavior or inconsistent response quality.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-09-26","last_updated":"2026-09-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":1.25,"output":2.25,"cache_read":0.3}},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.1,"output":0.3,"cache_read":0.025},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-4.5v:thinking":{"id":"z-ai/glm-4.5v:thinking","name":"GLM 4.5V Thinking","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":16384},"cost":{"input":0.6,"output":1.8,"cache_read":0.3},"canonical_model_id":"zhipuai/glm-4.5v"},"z-ai/glm-4.7-flash":{"id":"z-ai/glm-4.7-flash","name":"GLM 4.7 Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":128000},"cost":{"input":0.07,"output":0.4,"cache_read":0.01},"canonical_model_id":"zhipuai/glm-4.7-flash"},"z-ai/glm-4.6-original":{"id":"z-ai/glm-4.6-original","name":"GLM 4.6 Original","description":"GLM-4.6, Zhipu's flagship text model with 256K context window and advanced reasoning capabilities. Direct via Z-AI (Zhipu).","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":65535},"cost":{"input":0.5,"output":2,"cache_read":0.1},"canonical_model_id":"zhipuai/glm-4.6"},"z-ai/GLM-4.5:thinking":{"id":"z-ai/GLM-4.5:thinking","name":"GLM 4.5 (Thinking)","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":0.3,"output":1.3,"cache_read":0.15},"canonical_model_id":"zhipuai/glm-4.5"},"z-ai/glm-5-original:thinking":{"id":"z-ai/glm-5-original:thinking","name":"GLM 5 Original Thinking","description":"GLM-5 original with extended thinking capabilities for complex reasoning.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":128000},"cost":{"input":0.6,"output":1.9,"cache_read":0.1},"canonical_model_id":"zhipuai/glm-5"},"z-ai/glm-5.3:thinking":{"id":"z-ai/glm-5.3:thinking","name":"GLM 5.3 Thinking","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"cost":{"input":0.6,"output":1.1,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5.3"},"z-ai/glm-5-original":{"id":"z-ai/glm-5-original","name":"GLM 5 Original","description":"GLM-5 is Zhipu's latest flagship model with advanced reasoning and instruction following. Routed directly via Z-AI (Zhipu).","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":128000},"cost":{"input":0.6,"output":1.9,"cache_read":0.1},"canonical_model_id":"zhipuai/glm-5"},"z-ai/GLM-4.5-Air:thinking":{"id":"z-ai/GLM-4.5-Air:thinking","name":"GLM 4.5 Air (Thinking)","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":98304},"cost":{"input":0.12,"output":0.8,"cache_read":0.06},"canonical_model_id":"zhipuai/glm-4.5-air"},"z-ai/glm-5.1:thinking":{"id":"z-ai/glm-5.1:thinking","name":"GLM 5.1 Thinking","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":131072},"cost":{"input":0.7,"output":2.5,"cache_read":0.18},"canonical_model_id":"zhipuai/glm-5.1"},"z-ai/glm-5.1":{"id":"z-ai/glm-5.1","name":"GLM 5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":131072},"cost":{"input":0.7,"output":2.5,"cache_read":0.18},"canonical_model_id":"zhipuai/glm-5.1"},"z-ai/glm-4.7-original:thinking":{"id":"z-ai/glm-4.7-original:thinking","name":"GLM 4.7 Original Thinking","description":"GLM-4.7 original with extended thinking capabilities for complex reasoning.","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":65535},"cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.7"},"z-ai/glm-5v-turbo:thinking":{"id":"z-ai/glm-5v-turbo:thinking","name":"GLM 5V Turbo Thinking","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":202800,"input":202800,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5v-turbo"},"z-ai/glm-5.3-flash-cybersecurity":{"id":"z-ai/glm-5.3-flash-cybersecurity","name":"GLM 5.3 Flash Cybersecurity","description":"GLM 5.3 Flash Cybersecurity is a cybersecurity-focused variant based on the uncensored model, with provider moderation for illegal activities. It supports always-on reasoning, image understanding, tool calling, and a 1,048,576-token context window.","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-09-19","last_updated":"2026-09-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":32768},"cost":{"input":0.15,"output":0.5,"cache_read":0.075}},"z-ai/glm-4.7:thinking":{"id":"z-ai/glm-4.7:thinking","name":"GLM 4.7 Thinking","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":65535},"cost":{"input":0.4004,"output":1.9292,"cache_read":0.08008},"canonical_model_id":"zhipuai/glm-4.7"},"z-ai/glm-4.6":{"id":"z-ai/glm-4.6","name":"GLM 4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":65535},"cost":{"input":0.5,"output":2,"cache_read":0.1},"canonical_model_id":"zhipuai/glm-4.6"},"z-ai/glm-4.5":{"id":"z-ai/glm-4.5","name":"GLM 4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":65536},"cost":{"input":0.3,"output":1.3,"cache_read":0.15},"canonical_model_id":"zhipuai/glm-4.5"},"z-ai/glm-5:thinking":{"id":"z-ai/glm-5:thinking","name":"GLM 5 Thinking","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":128000},"cost":{"input":0.6,"output":1.9,"cache_read":0.1},"canonical_model_id":"zhipuai/glm-5"},"z-ai/GLM-4.5-Air":{"id":"z-ai/GLM-4.5-Air","name":"GLM 4.5 Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":98304},"cost":{"input":0.12,"output":0.8,"cache_read":0.06},"canonical_model_id":"zhipuai/glm-4.5-air"},"z-ai/GLM-4.6-turbo":{"id":"z-ai/GLM-4.6-turbo","name":"GLM 4.6 Turbo","description":"Fast variant of GLM 4.6 for general chat, coding, and analysis with improved latency and strong reasoning.","family":"glm","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-10-02","last_updated":"2025-10-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"input":204800,"output":131072},"cost":{"input":1,"output":3,"cache_read":0.5}},"z-ai/glm-4.7-flash:thinking":{"id":"z-ai/glm-4.7-flash:thinking","name":"GLM 4.7 Flash Thinking","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"input":200000,"output":128000},"cost":{"input":0.07,"output":0.4,"cache_read":0.01},"canonical_model_id":"zhipuai/glm-4.7-flash"},"z-ai/glm-5.3-flash-apex-abliterated":{"id":"z-ai/glm-5.3-flash-apex-abliterated","name":"Apex Flash 1 Abliterated","description":"Apex Flash 1 Abliterated is an experimental derivative of Cantina Security and Yeta's Apex Flash 1 with modified refusal behavior.","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"release_date":"2026-10-05","last_updated":"2026-10-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":32768},"cost":{"input":0.15,"output":0.5,"cache_read":0.075}},"z-ai/glm-4.6v-original":{"id":"z-ai/glm-4.6v-original","name":"GLM 4.6V Original","description":"GLM-4.6V scales its context window to 128k tokens in training, and achieves SoTA performance in visual understanding among models of similar parameter scales. Integrates native Function Calling capabilities, bridging 'visual perception' and 'executable action' for multimodal agents. Direct via Z-AI (Zhipu).","family":"glm","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":24000},"cost":{"input":0.6,"output":0.9,"cache_read":0.3},"canonical_model_id":"zhipuai/glm-4.6v"},"deepcogito/cogito-v1-preview-qwen-32B":{"id":"deepcogito/cogito-v1-preview-qwen-32B","name":"Cogito v1 Preview Qwen 32B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2025-05-10","last_updated":"2025-05-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":32768},"cost":{"input":1.8,"output":1.8,"cache_read":0.9}},"mlabonne/NeuralDaredevil-8B-abliterated":{"id":"mlabonne/NeuralDaredevil-8B-abliterated","name":"Neural Daredevil 8B abliterated","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"release_date":"2024-01-01","last_updated":"2024-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"input":8192,"output":8192},"cost":{"input":0.44,"output":0.44,"cache_read":0.22}},"NousResearch/hermes-4-405b":{"id":"NousResearch/hermes-4-405b","name":"Hermes 4 Large","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"hermes","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.3,"output":1.2,"cache_read":0.15},"canonical_model_id":"nousresearch/hermes-4-405b"},"NousResearch/hermes-3-llama-3.1-70b":{"id":"NousResearch/hermes-3-llama-3.1-70b","name":"Hermes 3 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"nousresearch","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-18","last_updated":"2024-08-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"input":65536,"output":8192},"cost":{"input":0.408,"output":0.408,"cache_read":0.204},"canonical_model_id":"nousresearch/hermes-3-llama-3.1-70b"},"NousResearch/hermes-4-405b:thinking":{"id":"NousResearch/hermes-4-405b:thinking","name":"Hermes 4 Large (Thinking)","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"hermes","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"input":128000,"output":8192},"cost":{"input":0.3,"output":1.2,"cache_read":0.15},"canonical_model_id":"nousresearch/hermes-4-405b"},"google/gemini-3.5-flash-thinking":{"id":"google/gemini-3.5-flash-thinking","name":"Gemini 3.5 Flash Thinking","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"cache_write":0.083333},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.7-flash"},"google/gemini-pro-latest":{"id":"google/gemini-pro-latest","name":"Gemini Pro Latest","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"release_date":"2026-03-29","last_updated":"2026-03-29","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":0.375}},"google/gemini-3.1-pro-preview-low":{"id":"google/gemini-3.1-pro-preview-low","name":"Gemini 3.1 Pro (Preview Low)","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":0.375},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash (Preview)","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-flash-lite-latest":{"id":"google/gemini-flash-lite-latest","name":"Gemini Flash Lite Latest","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":0.08333},"canonical_model_id":"google/gemini-flash-lite-latest"},"google/gemini-3.1-pro-preview-high":{"id":"google/gemini-3.1-pro-preview-high","name":"Gemini 3.1 Pro (Preview High)","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":0.375},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemma-4-31b-it:thinking":{"id":"google/gemma-4-31b-it:thinking","name":"Gemma 4 31B Thinking","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":131072},"cost":{"input":0.1,"output":0.34,"cache_read":0.1},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemini-4-argon":{"id":"google/gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":0.1875},"canonical_model_id":"google/gemini-4-argon"},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":131072},"cost":{"input":0.14,"output":0.4,"cache_read":0.05},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemma-4-26b-a4b-it":{"id":"google/gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":131072},"cost":{"input":0.0765,"output":0.255,"cache_read":0.0425},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro (Preview)","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":0.375},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3-flash-preview-thinking":{"id":"google/gemini-3-flash-preview-thinking","name":"Gemini 3 Flash Thinking","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.5,"output":3,"cache_read":0.05},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15,"cache_write":0.083333},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemma4-31b-splituntied":{"id":"google/gemma4-31b-splituntied","name":"Gemma 4 31B Split-Untied","description":"Blazed-Forge's Split-Untied is a text-only Gemma 4 31B community finetune with an untied BF16 output head, built for creative writing, roleplay, expressive dialogue, and tool use.","family":"gemma","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1,"output":0.3,"cache_read":0.05}},"google/diffusiongemma":{"id":"google/diffusiongemma","name":"DiffusionGemma","description":"DiffusionGemma is a high-speed diffusion-based version of Gemma 4 26B A4B. It supports optional reasoning and a 262,144-token context window.","family":"gemma","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","xhigh"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-09","last_updated":"2026-07-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.05,"output":0.15,"cache_read":0.025},"canonical_model_id":"google/diffusiongemma-26b-a4b-it"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemma-4-26b-a4b-it:thinking":{"id":"google/gemma-4-26b-a4b-it:thinking","name":"Gemma 4 26B A4B Thinking","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":131072},"cost":{"input":0.0765,"output":0.255,"cache_read":0.0425},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"cache_write":0.08333},"canonical_model_id":"google/gemini-3.1-flash-lite"},"google/gemini-3.1-pro-preview-customtools":{"id":"google/gemini-3.1-pro-preview-customtools","name":"Gemini 3.1 Pro (Preview Custom Tools)","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":0.375},"canonical_model_id":"google/gemini-3.1-pro-preview-customtools"},"google/gemini-flash-latest":{"id":"google/gemini-flash-latest","name":"Gemini Flash Latest","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.041667},"canonical_model_id":"google/gemini-flash-latest"},"google/gemma-4-26b-a4b-it-cybersecurity":{"id":"google/gemma-4-26b-a4b-it-cybersecurity","name":"Gemma 4 26B A4B Cybersecurity","description":"Gemma 4 26B A4B Cybersecurity is a cybersecurity-focused variant based on the uncensored model, with provider moderation for illegal activities. It supports optional reasoning, image understanding, tool calling, and a 262,144-token context window.","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"release_date":"2026-09-19","last_updated":"2026-09-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":262144,"output":32768},"cost":{"input":0.1056,"output":0.3344,"cache_read":0.0528}},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"cache_read":0.075,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.6-flash"}}},"lilac":{"id":"lilac","env":["LILAC_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.getlilac.com/v1","name":"Lilac","doc":"https://docs.getlilac.com/inference/models","models":{"minimaxai/minimax-m3":{"id":"minimaxai/minimax-m3","name":"MiniMax M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"status":"deprecated","cost":{"input":0.28,"output":1.1,"cache_read":0.05},"canonical_model_id":"minimax/MiniMax-M3"},"zai-org/glm-5.2":{"id":"zai-org/glm-5.2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":524288},"status":"deprecated","cost":{"input":0.9,"output":3,"cache_read":0.27},"canonical_model_id":"zhipuai/glm-5.2"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.7,"output":3.5,"cache_read":0.2},"canonical_model_id":"moonshotai/kimi-k2.6"},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262100,"output":262100},"status":"deprecated","cost":{"input":0.11,"output":0.35},"canonical_model_id":"google/gemma-4-31b-it"}}},"inco":{"id":"inco","env":["INCO_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.inco.ai/v1","name":"Inco","doc":"https://platform.inco.ai/docs","models":{"kimi-k3:fast":{"id":"kimi-k3:fast","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":6,"output":30,"cache_read":0.6},"canonical_model_id":"moonshotai/kimi-k3"},"glm-5.3:fast":{"id":"glm-5.3:fast","name":"GLM-5.3 Fast","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":2.8,"output":8.8,"cache_read":0.52},"canonical_model_id":"zhipuai/glm-5.3"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"glm-5.3-flash:fast":{"id":"glm-5.3-flash:fast","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.3,"output":1,"cache_read":0.06},"canonical_model_id":"zhipuai/glm-5.3-flash"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"minimax-m3:fast":{"id":"minimax-m3:fast","name":"MiniMax M3 Fast","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.6,"output":2.4,"cache_read":0.12},"canonical_model_id":"minimax/MiniMax-M3"},"deepseek-v4.1-flash:fast":{"id":"deepseek-v4.1-flash:fast","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.6,"output":2.4,"cache_read":0.012},"canonical_model_id":"deepseek/deepseek-v4.1-flash"}}},"unorouter":{"id":"unorouter","env":["UNOROUTER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.unorouter.com/v1","name":"UnoRouter","doc":"https://unorouter.com/models","models":{"deepseek-v4-flash:free":{"id":"deepseek-v4-flash:free","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-v4-flash"},"nemotron-3-ultra-550b-a55b:free":{"id":"nemotron-3-ultra-550b-a55b:free","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"status":"deprecated","cost":{"input":0.0625,"output":0.125},"canonical_model_id":"deepseek/deepseek-v4-flash"},"minimax-m2.7:free":{"id":"minimax-m2.7:free","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"minimax/MiniMax-M2.7"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":1.6001,"output":5.0288},"canonical_model_id":"zhipuai/glm-5.2"},"gemma-4-31b-it:free":{"id":"gemma-4-31b-it:free","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemma-4-31b-it"},"gpt-5.5:free":{"id":"gpt-5.5:free","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"openai/gpt-5.5"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.8999,"output":1.7999},"canonical_model_id":"deepseek/deepseek-v4-pro"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":1.44,"output":7.2},"canonical_model_id":"anthropic/claude-sonnet-5"},"qwen3.5-397b-a17b:free":{"id":"qwen3.5-397b-a17b:free","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"status":"deprecated","cost":{"input":1.8,"output":10.8},"canonical_model_id":"openai/gpt-5.4"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.2675,"output":5.3368},"canonical_model_id":"moonshotai/kimi-k2.6"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"status":"deprecated","cost":{"input":0.425,"output":2.125},"canonical_model_id":"anthropic/claude-opus-4-8"},"deepseek-v4-pro:free":{"id":"deepseek-v4-pro:free","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-v4-pro"},"glm-4.5-flash:free":{"id":"glm-4.5-flash:free","name":"GLM-4.5-Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":98304},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-4.5-flash"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.1857,"output":1.1142},"canonical_model_id":"google/gemini-3.5-flash"},"minimax-m2.7":{"id":"minimax-m2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","cost":{"input":0.819,"output":3.276},"canonical_model_id":"minimax/MiniMax-M2.7"},"gpt-5.4:free":{"id":"gpt-5.4:free","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"openai/gpt-5.4"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1875,"output":1.125},"canonical_model_id":"openai/gpt-5.5"},"glm-5.2:free":{"id":"glm-5.2:free","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-5.2"},"claude-haiku-4-5-20251001":{"id":"claude-haiku-4-5-20251001","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1.2,"output":6},"canonical_model_id":"anthropic/claude-haiku-4-5-20251001"},"gpt-5.2":{"id":"gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":1.05,"output":8.4},"canonical_model_id":"openai/gpt-5.2"},"step-3.7-flash:free":{"id":"step-3.7-flash:free","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"stepfun/step-3.7-flash"}}},"blueclaw":{"id":"blueclaw","env":["BLUECLAW_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://openai.blueclaw.network/v1","name":"Blue Claw","doc":"https://blueclaw.network","models":{"Qwen3.8-27B":{"id":"Qwen3.8-27B","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"status":"beta","canonical_model_id":"alibaba/qwen3.8-27b"}}},"inference":{"id":"inference","env":["INFERENCE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://inference.net/v1","name":"Inference","doc":"https://inference.net/models","models":{"osmosis/osmosis-structure-0.6b":{"id":"osmosis/osmosis-structure-0.6b","name":"Osmosis Structure 0.6B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","family":"osmosis","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4000,"output":2048},"status":"deprecated","cost":{"input":0.1,"output":0.5}},"mistral/mistral-nemo-12b-instruct":{"id":"mistral/mistral-nemo-12b-instruct","name":"Mistral Nemo 12B Instruct","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16000,"output":4096},"status":"deprecated","cost":{"input":0.038,"output":0.1},"canonical_model_id":"mistral/mistral-nemo"},"qwen/qwen3-embedding-4b":{"id":"qwen/qwen3-embedding-4b","type":"embedding","name":"Qwen 3 Embedding 4B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"knowledge":"2024-12","release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":2048},"status":"deprecated","cost":{"input":0.01,"output":0},"canonical_model_id":"alibaba/qwen3-embedding-4b"},"qwen/qwen-2.5-7b-vision-instruct":{"id":"qwen/qwen-2.5-7b-vision-instruct","name":"Qwen 2.5 7B Vision Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":125000,"output":4096},"status":"deprecated","cost":{"input":0.2,"output":0.2}},"meta/llama-3.2-1b-instruct":{"id":"meta/llama-3.2-1b-instruct","name":"Llama 3.2 1B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16000,"output":4096},"cost":{"input":0.01,"output":0.01},"canonical_model_id":"meta/llama-3.2-1b-instruct"},"meta/llama-3.2-11b-vision-instruct":{"id":"meta/llama-3.2-11b-vision-instruct","name":"Llama 3.2 11B Vision Instruct","description":"Open Llama multimodal model for image understanding and text reasoning","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":16000,"output":4096},"status":"deprecated","cost":{"input":0.055,"output":0.055},"canonical_model_id":"meta/llama-3.2-11b-vision-instruct"},"meta/llama-3.2-3b-instruct":{"id":"meta/llama-3.2-3b-instruct","name":"Llama 3.2 3B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16000,"output":4096},"cost":{"input":0.02,"output":0.02}},"meta/llama-3.1-8b-instruct":{"id":"meta/llama-3.1-8b-instruct","name":"Llama 3.1 8B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16000,"output":4096},"status":"deprecated","cost":{"input":0.025,"output":0.025},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"google/gemma-3":{"id":"google/gemma-3","name":"Google Gemma 3","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2025-01-01","last_updated":"2025-01-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":125000,"output":4096},"cost":{"input":0.15,"output":0.3}}}},"abliteration-ai":{"id":"abliteration-ai","env":["ABLIT_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.abliteration.ai/v1","name":"abliteration.ai","doc":"https://docs.abliteration.ai/models","models":{"abliterated-model-large-v2":{"id":"abliterated-model-large-v2","name":"Abliterated Model Large V2","description":"GLM-5.3 model abliterated and finetuned for cyber, ML red teaming, and agent testing","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-29","last_updated":"2026-08-31","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":999990},"cost":{"input":5,"output":5,"cache_read":0.5}},"abliterated-model":{"id":"abliterated-model","name":"Abliterated Model","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-01-06","last_updated":"2026-07-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":150000,"input":150000,"output":8192},"cost":{"input":3,"output":3,"cache_read":0.3}},"abliterated-model-large":{"id":"abliterated-model-large","name":"Abliterated Model Large","description":"GLM-5.2 model abliterated and finetuned for cyber, ML red teaming, and agent testing","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-25","last_updated":"2026-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":1000000,"output":999990},"cost":{"input":5,"output":5,"cache_read":0.5}}}},"zai-coding-plan":{"id":"zai-coding-plan","env":["ZHIPU_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.z.ai/api/coding/paas/v4","name":"Z.AI Coding Plan","doc":"https://docs.z.ai/devpack/overview","models":{"glm-5.3-highspeed":{"id":"glm-5.3-highspeed","name":"GLM-5.3 Highspeed","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"glm-5-turbo":{"id":"glm-5-turbo","name":"GLM-5-Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5-turbo"},"glm-4.7":{"id":"glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-4.7"},"glm-5.2-highspeed":{"id":"glm-5.2-highspeed","name":"GLM-5.2 Highspeed","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.2"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"zhipuai/glm-5.3-flash"}}},"crusoe":{"id":"crusoe","env":["CRUSOE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.inference.crusoecloud.com/v1","name":"Crusoe","doc":"https://docs.crusoecloud.com/managed-inference/overview","models":{"Qwen/Qwen3-235B-A22B-Instruct-2507":{"id":"Qwen/Qwen3-235B-A22B-Instruct-2507","name":"Qwen3 235B-A22B Instruct 2507","description":"Updated large open Qwen3 MoE instruct model for multilingual chat, coding, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"status":"deprecated","cost":{"input":0.22,"output":0.8,"cache_read":0.11},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.05,"output":0.25,"cache_read":0.05},"canonical_model_id":"openai/gpt-oss-120b"},"zai/GLM-5.1":{"id":"zai/GLM-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"status":"deprecated","cost":{"input":1.2,"output":4.4,"cache_read":0.25},"canonical_model_id":"zhipuai/glm-5.1"},"zai/GLM-5.2":{"id":"zai/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"deprecated","cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.7,"output":3.5,"cache_read":0.35},"canonical_model_id":"moonshotai/kimi-k2.6"},"nvidia/Nemotron-3-Nano-Omni-Reasoning-30B-A3B":{"id":"nvidia/Nemotron-3-Nano-Omni-Reasoning-30B-A3B","name":"Nemotron 3 Nano Omni 30B A3B Reasoning","description":"Open Nemotron omni model combining reasoning with text, vision, and audio","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":true,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0.3,"output":1.83,"cache_read":0.3,"input_audio":0.5},"canonical_model_id":"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning"},"nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B":{"id":"nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B","name":"Nemotron 3 Nano 30B A3B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-06-25","release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.05,"output":0.2,"cache_read":0.03},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"nvidia/NVIDIA-Nemotron-3-Super-120B-A12B":{"id":"nvidia/NVIDIA-Nemotron-3-Super-120B-A12B","name":"Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.3,"output":2.4,"cache_read":0.15},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"meta-llama/Llama-3.3-70B-Instruct":{"id":"meta-llama/Llama-3.3-70B-Instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"status":"deprecated","cost":{"input":0.25,"output":0.75,"cache_read":0.13},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"deepseek-ai/DeepSeek-V3-0324":{"id":"deepseek-ai/DeepSeek-V3-0324","name":"DeepSeek V3 0324","description":"March 2025 checkpoint of DeepSeek-V3 with improved reasoning and coding","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-03-24","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":163840},"status":"deprecated","cost":{"input":0.5,"output":1.5,"cache_read":0.25},"canonical_model_id":"deepseek/deepseek-v3-0324"},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.14,"output":0.4,"cache_read":0.14},"canonical_model_id":"google/gemma-4-31b-it"}}},"opencode-go":{"id":"opencode-go","env":["OPENCODE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://opencode.ai/inference/go/openai/v1","name":"OpenCode Go","doc":"https://opencode.ai/v2/docs/console/go/","models":{"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/go/anthropic/v1"},"cost":{"input":0.15,"output":0.47,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"space-bunny":{"id":"space-bunny","name":"Space Bunny","description":"Anonymous preview reasoning model for coding, agentic tasks, tool use, and multimodal input","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":524288,"output":524288},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.15,"output":0.6,"cache_read":0.03,"cache_write":0}},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"beam-free":{"id":"beam-free","name":"Beam Free","description":"Sparse mixture-of-experts reasoning model with 23B active parameters for coding and agentic workflows","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-06-30","release_date":"2026-10-05","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"reflection/beam-1.0-501b-a23b"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.15,"output":0.6,"cache_read":0.003},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"longcat-2.0":{"id":"longcat-2.0","name":"LongCat-2.0","description":"Meituan LongCat-2.0, a reasoning model with tool calling and a 1M-token context window","family":"longcat","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"meituan/longcat-2.0"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter multimodal flagship for coding, professional work, and long-horizon agentic workflows","family":"qwen3.8-max","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","max":262144}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/go/anthropic/v1"},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro (New)","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.66,"output":1.98,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-pro"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"step-5-preview":{"id":"step-5-preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":65536},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":1,"output":2.7,"cache_read":0.1},"canonical_model_id":"stepfun/step-5-preview"},"grok-4.7":{"id":"grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"mimo-v2.6-flash":{"id":"mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"qwen3.7-plus":{"id":"qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"qwen3.7-plus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","max":262144}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/go/anthropic/v1"},"cost":{"input":0.4,"output":1.6,"cache_read":0.04,"cache_write":0.5,"tiers":[{"input":1.2,"output":4.8,"cache_read":0.12,"cache_write":1.5,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1.2,"output":4.8,"cache_read":0.12,"cache_write":1.5}},"canonical_model_id":"alibaba/qwen3.7-plus"},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/go/anthropic/v1"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"gemini-4-argon-contributor":{"id":"gemini-4-argon-contributor","name":"Gemini 4 Argon Contributor","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://opencode.ai/inference/go/google/v1beta"},"cost":{"input":4,"output":20,"cache_read":0.2,"input_audio":4},"canonical_model_id":"google/gemini-4-argon"},"muse-spark-1.2-contributor":{"id":"muse-spark-1.2-contributor","name":"Muse Spark 1.2 Contributor","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.1,"output":0.2,"cache_read":0.002},"canonical_model_id":"meta/muse-spark-1.2"},"step-5-preview-free":{"id":"step-5-preview-free","name":"Step 5 Preview Free","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":65536},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"stepfun/step-5-preview"},"mimo-v2.6-pro":{"id":"mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.435,"output":0.87,"cache_read":0.003625},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"longcat-2.5-preview-free":{"id":"longcat-2.5-preview-free","name":"LongCat 2.5 Preview Free","description":"Meituan's multimodal reasoning model for coding and agent tasks, with image understanding and a 1M-token context window","family":"longcat","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"release_date":"2026-09-25","last_updated":"2026-09-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"meituan/longcat-2.5-preview"},"mimo-v2.5-pro":{"id":"mimo-v2.5-pro","name":"MiMo V2.5 Pro","description":"MiMo pro model for strong multimodal reasoning and agent execution","family":"mimo-v2.5-pro","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":128000},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.435,"output":0.87,"cache_read":0.003625},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"cat-jam-free":{"id":"cat-jam-free","name":"Cat Jam Free","description":"A text-only reasoning model for coding and agentic workflows, with tool calling and structured JSON outputs.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"hy4-preview":{"id":"hy4-preview","name":"Hy4 preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":64000},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"},"mimo-v2.5":{"id":"mimo-v2.5","name":"MiMo V2.5","description":"MiMo omni model for text, image, video, audio, and agents","family":"mimo-v2.5","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.5"},"hy3":{"id":"hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":192000,"output":128000},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.14,"output":0.58,"cache_read":0.035},"canonical_model_id":"tencent/hy3"},"muse-spark-1.3-contributor":{"id":"muse-spark-1.3-contributor","name":"Muse Spark 1.3 Contributor","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for coding and agentic workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.1,"output":0.2,"cache_read":0.002},"canonical_model_id":"meta/muse-spark-1.3"},"minimax-m2.7":{"id":"minimax-m2.7","name":"MiniMax-M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/go/anthropic/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax-m3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/go/anthropic/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"tiers":[{"input":0.6,"output":2.4,"cache_read":0.12,"tier":{"type":"context","size":512000}}],"context_over_200k":{"input":0.6,"output":2.4,"cache_read":0.12}},"canonical_model_id":"minimax/MiniMax-M3"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"minimax-m3.1-flash-free":{"id":"minimax-m3.1-flash-free","name":"MiniMax M3.1 Flash Free","description":"Frontier multimodal coding model with 1M context window and tunable thinking depth","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-10-19","last_updated":"2026-10-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":512000},"provider":{"api":"https://opencode.ai/inference/go/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"minimax/MiniMax-M3.1-Flash"}}},"kimi-code-plan-global":{"id":"kimi-code-plan-global","env":["KIMI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.kimi.ai/coding/v1","name":"Kimi For Coding (kimi.ai)","doc":"https://www.kimi.ai/code/docs/en/kimi-code/models.html","models":{"k3-256k":{"id":"k3-256k","name":"Kimi K3-256K","description":"256K-context version of Kimi K3, reducing token consumption for shorter coding sessions","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k3"},"k3":{"id":"k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k3"},"kimi-for-coding-highspeed":{"id":"kimi-for-coding-highspeed","name":"Kimi For Coding HighSpeed","description":"Lower-latency Kimi Code variant for interactive edits and coding-agent loops","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.7-code-highspeed"},"kimi-for-coding":{"id":"kimi-for-coding","name":"kimi-for-coding","description":"Kimi coding model with more efficient thinking and up to 1M context, available through Kimi Code","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":32768},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"moonshotai/kimi-k2.8-preview"}}},"aimlapi":{"id":"aimlapi","env":["AIMLAPI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.aimlapi.com/v1","name":"AI/ML API","doc":"https://docs.aimlapi.com","models":{"undi95/remm-slerp-l2-13b":{"id":"undi95/remm-slerp-l2-13b","name":"ReMM SLERP 13B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-06-30","release_date":"2023-07-22","last_updated":"2023-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":6144,"output":4096},"cost":{"input":0.6877,"output":1.03155},"canonical_model_id":"undi95/remm-slerp-l2-13b"},"thinkingmachines/inkling-small":{"id":"thinkingmachines/inkling-small","name":"Inkling Small","description":"Multimodal MoE reasoning model (276B total, 12B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":262144},"cost":{"input":0.797732,"output":1.980576,"cache_read":0.159546},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/inkling":{"id":"thinkingmachines/inkling","name":"Inkling","description":"Multimodal MoE reasoning model (975B total, 41B active) for text, image, and audio","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.3754,"output":5.57037,"cache_read":0.233818},"canonical_model_id":"thinkingmachines/inkling"},"xiaomi/mimo-v2.5-pro":{"id":"xiaomi/mimo-v2.5-pro","name":"MiMo V2.5 Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.598299,"output":1.196598,"cache_read":0.004951},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"xiaomi/mimo-v2.5":{"id":"xiaomi/mimo-v2.5","name":"MiMo V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.192556,"output":0.385112,"cache_read":0.003851},"canonical_model_id":"xiaomi/mimo-v2.5"},"sao10k/l3.1-euryale-70b":{"id":"sao10k/l3.1-euryale-70b","name":"Llama 3.1 Euryale 70B v2.2","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-28","last_updated":"2024-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":1.99488,"output":1.99488},"canonical_model_id":"sao10k/l3.1-euryale-70b"},"sao10k/l3-lunaris-8b":{"id":"sao10k/l3-lunaris-8b","name":"Llama 3 8B Lunaris","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-13","last_updated":"2024-08-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":7372},"cost":{"input":0.06877,"output":0.06877},"canonical_model_id":"sao10k/l3-lunaris-8b"},"sao10k/l3.3-euryale-70b":{"id":"sao10k/l3.3-euryale-70b","name":"Llama 3.3 Euryale 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-12-18","last_updated":"2024-12-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.89401,"output":1.03155},"canonical_model_id":"sao10k/l3.3-euryale-70b"},"zhipu/glm-5.2":{"id":"zhipu/glm-5.2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":1.82,"output":5.72,"cache_read":0.338},"canonical_model_id":"zhipuai/glm-5.2"},"zhipu/glm-5.3":{"id":"zhipu/glm-5.3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":131072},"cost":{"input":1.82,"output":5.72,"cache_read":0.338},"canonical_model_id":"zhipuai/glm-5.3"},"ibm-granite/granite-4.0-h-micro":{"id":"ibm-granite/granite-4.0-h-micro","name":"Granite 4.0 Micro","description":"Compact open-weight hybrid Granite model for lightweight enterprise chat and tool calling","family":"granite","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-02","last_updated":"2025-10-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":131000},"cost":{"input":0.023382,"output":0.154045},"canonical_model_id":"ibm/granite-4-h-micro"},"thedrummer/skyfall-36b-v2":{"id":"thedrummer/skyfall-36b-v2","name":"Skyfall 36B V2","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2025-03-10","last_updated":"2025-03-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.75647,"output":1.10032,"cache_read":0.34385},"canonical_model_id":"thedrummer/skyfall-36b-v2"},"thedrummer/unslopnemo-12b":{"id":"thedrummer/unslopnemo-12b","name":"UnslopNemo 12B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-04-30","release_date":"2024-11-08","last_updated":"2024-11-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.55016,"output":0.55016},"canonical_model_id":"thedrummer/unslopnemo-12b"},"thedrummer/cydonia-24b-v4.1":{"id":"thedrummer/cydonia-24b-v4.1","name":"Cydonia 24B V4.1","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-04-30","release_date":"2025-09-27","last_updated":"2025-09-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.41262,"output":0.6877,"cache_read":0.20631},"canonical_model_id":"thedrummer/cydonia-24b-v4.1"},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude 4.8 Opus","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":6.877,"output":34.385,"cache_read":0.6877,"cache_write":8.59625},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":13,"output":65,"cache_read":1.3,"cache_write":16.25},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":6.5,"output":32.5,"cache_read":0.65,"cache_write":8.125},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-haiku-5.5":{"id":"anthropic/claude-haiku-5.5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.13,"output":0.65,"cache_read":0.013,"cache_write":0.1625},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude 4.6 Sonnet","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":4.1262,"output":20.631,"cache_read":0.41262,"cache_write":5.15775},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.6,"output":13,"cache_read":0.26,"cache_write":3.25},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-opus-5.5":{"id":"anthropic/claude-opus-5.5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.2,"output":26,"cache_read":0.26,"cache_write":6.5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-haiku-4.5":{"id":"anthropic/claude-haiku-4.5","name":"Claude 4.5 Haiku","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1.3754,"output":6.877,"cache_read":0.13754,"cache_write":1.71925},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-sonnet-5.5":{"id":"anthropic/claude-sonnet-5.5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.6,"output":13,"cache_read":0.26,"cache_write":3.25},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-sonnet-4.5":{"id":"anthropic/claude-sonnet-4.5","name":"Claude 4.5 Sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":4.1262,"output":20.631,"cache_read":0.41262,"cache_write":5.15775},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-fable-5.1":{"id":"anthropic/claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":13,"output":65,"cache_read":0.325,"cache_write":16.25},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-opus-4.5":{"id":"anthropic/claude-opus-4.5","name":"Claude 4.5 Opus","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":6.877,"output":34.385,"cache_read":0.6877,"cache_write":8.59625},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude 4.7 Opus","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":6.877,"output":34.385,"cache_read":0.6877,"cache_write":8.59625},"canonical_model_id":"anthropic/claude-opus-4-7"},"bytedance-seed/seed-1.6-flash":{"id":"bytedance-seed/seed-1.6-flash","name":"Seed 1.6 Flash","description":"Low-latency ByteDance Seed model for high-throughput chat, extraction, and lightweight tool use","family":"seed","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-28","last_updated":"2025-08-28","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.103155,"output":0.41262},"canonical_model_id":"bytedance-seed/seed-1-6-flash"},"bytedance-seed/seed-2.0-mini":{"id":"bytedance-seed/seed-2.0-mini","name":"Seed-2.0-Mini","description":"Lightweight ByteDance Seed 2.0 model for low-latency multimodal reasoning and high-volume tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.13754,"output":0.55016},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"bytedance-seed/seed-2.0-code":{"id":"bytedance-seed/seed-2.0-code","name":"Seed-2.0-Code","description":"ByteDance Seed coding model for multimodal software engineering and long-running agents","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.6877,"output":4.1262},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"bytedance-seed/seed-2.0-lite":{"id":"bytedance-seed/seed-2.0-lite","name":"Seed-2.0-Lite","description":"Cost-efficient ByteDance Seed 2.0 model for production chat, analysis, and structured generation","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.34385,"output":2.7508},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"morph/morph-v3-large":{"id":"morph/morph-v3-large","name":"V3 Large","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"morph","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-07-07","last_updated":"2025-07-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":1.23786,"output":2.61326},"canonical_model_id":"morph/morph-v3-large"},"morph/morph-v3-fast":{"id":"morph/morph-v3-fast","name":"V3 Fast","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"morph","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-07-07","last_updated":"2025-07-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":81920,"output":38000},"cost":{"input":1.10032,"output":1.65048},"canonical_model_id":"morph/morph-v3-fast"},"upstage/solar-pro-3":{"id":"upstage/solar-pro-3","name":"Solar Pro 3","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-07","release_date":"2026-01-26","last_updated":"2026-03-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.20631,"output":0.82524,"cache_read":0.020631},"canonical_model_id":"upstage/solar-pro3"},"upstage/solar-pro4":{"id":"upstage/solar-pro4","name":"Solar Pro 4","description":"Upstage's flagship model, specialized for agentic use","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02","release_date":"2026-08-06","last_updated":"2026-08-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":131072},"cost":{"input":0.041262,"output":0.165048,"cache_read":0.008252},"canonical_model_id":"upstage/solar-pro4"},"x-ai/grok-4-fast-non-reasoning":{"id":"x-ai/grok-4-fast-non-reasoning","name":"Grok 4 Fast Non-Reasoning","description":"Fast Grok model for responsive chat, reasoning, and tool-assisted work","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-18","last_updated":"2025-12-18","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":1999000},"cost":{"input":1.625,"output":3.25,"cache_read":0.26},"canonical_model_id":"xai/grok-4-fast-non-reasoning"},"x-ai/grok-4-20-0309-non-reasoning":{"id":"x-ai/grok-4-20-0309-non-reasoning","name":"Grok 4.20 Non-Reasoning","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":1999000},"cost":{"input":1.625,"output":3.25,"cache_read":0.26},"canonical_model_id":"xai/grok-4.20-0309-non-reasoning"},"mancer/weaver":{"id":"mancer/weaver","name":"Weaver (alpha)","description":"General-purpose chat model for instruction following, writing, and analysis","family":"alpha","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-06-30","release_date":"2023-08-02","last_updated":"2023-08-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8000,"output":2000},"cost":{"input":1.03155,"output":1.3754},"canonical_model_id":"mancer/weaver"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.6,"output":13,"cache_read":0.26,"cache_write":3.25},"canonical_model_id":"openai/gpt-6-sol"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.13,"output":0.65,"cache_read":0.013,"cache_write":0.1625},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":117964},"cost":{"input":0.48139,"output":1.30663,"cache_read":0.48139},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.6,"output":13,"cache_read":0.13,"cache_write":3.25},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":4.8139,"output":38.5112,"cache_read":0.48139},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-4":{"id":"openai/gpt-4","name":"GPT-4","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-11","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8000,"output":8192},"cost":{"input":39,"output":78,"cache_read":39},"canonical_model_id":"openai/gpt-4"},"openai/gpt-5-pro":{"id":"openai/gpt-5-pro","name":"GPT-5 Pro","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":272000},"cost":{"input":20.631,"output":165.048},"canonical_model_id":"openai/gpt-5-pro"},"openai/gpt-5-5":{"id":"openai/gpt-5-5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":6.5,"output":39,"cache_read":0.65},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":41.262,"output":247.572},"canonical_model_id":"openai/gpt-5.4-pro"},"openai/gpt-5-1":{"id":"openai/gpt-5-1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.625,"output":13,"cache_read":0.1625},"canonical_model_id":"openai/gpt-5.1"},"openai/o1":{"id":"openai/o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":100000},"cost":{"input":19.5,"output":78,"cache_read":9.75},"canonical_model_id":"openai/o1"},"openai/gpt-4o-2024-05-13":{"id":"openai/gpt-4o-2024-05-13","name":"GPT-4o","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-05-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":6.5,"output":19.5},"canonical_model_id":"openai/gpt-4o-2024-05-13"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2.6,"output":10.4,"cache_read":0.65},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":3.25,"output":13,"cache_read":1.625},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-5.4-image-2":{"id":"openai/gpt-5.4-image-2","type":"image","name":"GPT-5.4 Image 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":false,"structured_output":true,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["image","text","pdf"],"output":["image","text"]},"open_weights":false,"limit":{"context":272000,"output":128000},"cost":{"input":11.0032,"output":20.631,"cache_read":2.7508},"canonical_model_id":"openai/gpt-5.4-image-2"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.26,"output":1.56,"cache_read":0.026,"cache_write":0.325},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.2-pro":{"id":"openai/gpt-5.2-pro","name":"GPT-5.2 Pro","description":"Higher-accuracy GPT-5.2 variant for tougher reasoning and review workflows","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":28.8834,"output":231.0672},"canonical_model_id":"openai/gpt-5.2-pro"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 Mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":2.0631,"output":12.3786,"cache_read":0.20631},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/o1-pro":{"id":"openai/o1-pro","name":"o1-pro","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2025-03-19","last_updated":"2025-03-19","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":206.31,"output":825.24},"canonical_model_id":"openai/o1-pro"},"openai/gpt-4o-2024-08-06":{"id":"openai/gpt-4o-2024-08-06","name":"GPT-4o","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-08-06","last_updated":"2024-08-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":3.25,"output":13,"cache_read":1.625},"canonical_model_id":"openai/gpt-4o-2024-08-06"},"openai/gpt-5.1-codex-max":{"id":"openai/gpt-5.1-codex-max","name":"GPT-5.1-Codex-Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":3.4385,"output":27.508,"cache_read":0.34385},"canonical_model_id":"openai/gpt-5.1-codex-max"},"openai/gpt-oss-safeguard-20b":{"id":"openai/gpt-oss-safeguard-20b","name":"gpt-oss-safeguard-20b","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.103155,"output":0.41262,"cache_read":0.051578},"canonical_model_id":"openai/gpt-oss-safeguard-20b"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5.2,"output":26,"cache_read":0.52,"cache_write":6.5},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 Mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.52,"output":2.08,"cache_read":0.13},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":117964},"cost":{"input":0.103155,"output":0.41262,"cache_read":0.051578},"canonical_model_id":"openai/gpt-oss-20b"},"openai/gpt-4o-2024-11-20":{"id":"openai/gpt-4o-2024-11-20","name":"GPT-4o","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-11-20","last_updated":"2024-11-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":3.25,"output":13,"cache_read":1.625},"canonical_model_id":"openai/gpt-4o-2024-11-20"},"openai/gpt-5.5-pro":{"id":"openai/gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":41.262,"output":247.572},"canonical_model_id":"openai/gpt-5.5-pro"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.325,"output":2.6,"cache_read":0.0325},"canonical_model_id":"openai/gpt-5-mini"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1 Nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.13,"output":0.52,"cache_read":0.0325},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 Nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.27508,"output":1.71925,"cache_read":0.027508},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-4-turbo":{"id":"openai/gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":13,"output":39},"canonical_model_id":"openai/gpt-4-turbo"},"openai/o3-pro":{"id":"openai/o3-pro","name":"o3 Pro","description":"High-effort o3 tier for difficult technical reasoning and careful answers","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-06-10","last_updated":"2025-06-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":27.508,"output":110.032},"canonical_model_id":"openai/o3-pro"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.6,"output":15.6,"cache_read":0.26,"cache_write":3.25},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.625,"output":13,"cache_read":0.1625},"canonical_model_id":"openai/gpt-5"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.065,"output":0.52,"cache_read":0.0065},"canonical_model_id":"openai/gpt-5-nano"},"openai/gpt-3.5-turbo":{"id":"openai/gpt-3.5-turbo","name":"GPT-3.5 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16000,"output":4096},"cost":{"input":0.65,"output":1.95},"canonical_model_id":"openai/gpt-3.5-turbo"},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3 Mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.43,"output":5.72,"cache_read":0.715},"canonical_model_id":"openai/o3-mini"},"openai/gpt-5.6-luna-pro":{"id":"openai/gpt-5.6-luna-pro","name":"GPT-5.6 Luna Pro","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.27508,"output":1.65048,"cache_read":0.027508},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o Mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.195,"output":0.78,"cache_read":0.0975},"canonical_model_id":"openai/gpt-4o-mini"},"openai/gpt-5.6-terra-pro":{"id":"openai/gpt-5.6-terra-pro","name":"GPT-5.6 Terra Pro","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.7508,"output":16.5048,"cache_read":0.27508},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-5-2":{"id":"openai/gpt-5-2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":2.275,"output":18.2,"cache_read":0.2275},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-5.6-sol-pro":{"id":"openai/gpt-5.6-sol-pro","name":"GPT-5.6 Sol Pro","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5.5016,"output":27.508,"cache_read":0.55016},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":13,"output":65,"cache_read":1.3,"cache_write":16.25},"canonical_model_id":"openai/gpt-6-astra"},"openai/gpt-5-4":{"id":"openai/gpt-5-4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":3.25,"output":19.5,"cache_read":0.325},"canonical_model_id":"openai/gpt-5.4"},"inception/mercury-2":{"id":"inception/mercury-2","name":"Mercury 2","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-24","last_updated":"2026-02-24","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":50000},"cost":{"input":0.34385,"output":1.03155,"cache_read":0.034385},"canonical_model_id":"inception/mercury-2"},"inception/mercury-2.5":{"id":"inception/mercury-2.5","name":"Mercury 2.5","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":260000,"output":65536},"cost":{"input":0.27508,"output":1.03155,"cache_read":0.027508},"canonical_model_id":"inception/mercury-2.5"},"perplexity/sonar":{"id":"perplexity/sonar","name":"Sonar","description":"Fast web-grounded Sonar for current answers, citations, and lightweight retrieval","family":"sonar","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":100000},"cost":{"input":1.3,"output":1.3},"canonical_model_id":"perplexity/sonar"},"perplexity/sonar-pro":{"id":"perplexity/sonar-pro","name":"Sonar Pro","description":"Deeper Sonar search model with broader retrieval and stronger synthesis","family":"sonar-pro","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-09-01","release_date":"2024-01-01","last_updated":"2025-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":3.9,"output":19.5},"canonical_model_id":"perplexity/sonar-pro"},"relace/relace-apply-3":{"id":"relace/relace-apply-3","name":"Apply 3","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2025-09-26","last_updated":"2025-09-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":1.16909,"output":1.71925},"canonical_model_id":"relace/relace-apply-3"},"relace/relace-search":{"id":"relace/relace-search","name":"Search","description":"Tool-capable chat model for instruction following and agentic application workflows","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":1.3754,"output":4.1262},"canonical_model_id":"relace/relace-search"},"anthracite-org/magnum-v4-72b":{"id":"anthracite-org/magnum-v4-72b","name":"Magnum v4 72B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":16384},"cost":{"input":4.1262,"output":6.877},"canonical_model_id":"anthracite-org/magnum-v4-72b"},"moonshot/kimi-k3":{"id":"moonshot/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3.9,"output":19.5,"cache_read":0.39},"canonical_model_id":"moonshotai/kimi-k3"},"mistralai/ministral-8b-2512":{"id":"mistralai/ministral-8b-2512","name":"Ministral 3 8B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.41262,"output":0.41262,"cache_read":0.020631},"canonical_model_id":"mistral/ministral-8b-2512"},"mistralai/mistral-nemo":{"id":"mistralai/mistral-nemo","name":"Mistral NeMo","description":"Efficient Mistral-NVIDIA open model for multilingual chat and local deployment","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.20631,"output":0.233818,"cache_read":0.20631},"canonical_model_id":"mistral/mistral-nemo"},"mistralai/ministral-14b-2512":{"id":"mistralai/ministral-14b-2512","name":"Ministral 3 14B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.48139,"output":0.48139,"cache_read":0.027508},"canonical_model_id":"mistral/ministral-14b-2512"},"mistralai/ministral-3b-2512":{"id":"mistralai/ministral-3b-2512","name":"Ministral 3 3B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":104857},"cost":{"input":0.20631,"output":0.20631,"cache_read":0.013754},"canonical_model_id":"mistral/ministral-3b-2512"},"mistralai/voxtral-small-24b-2507":{"id":"mistralai/voxtral-small-24b-2507","name":"Voxtral Small 24B 2507","description":"Open audio-language model for speech transcription, audio understanding, and voice-driven tool use","family":"voxtral","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":32768},"cost":{"input":0.13754,"output":0.41262,"cache_read":0.013754},"canonical_model_id":"mistral/voxtral-small-24b-2507"},"mistralai/mistral-medium-3-5":{"id":"mistralai/mistral-medium-3-5","name":"Medium 3.5","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":209715},"cost":{"input":2.0631,"output":10.3155},"canonical_model_id":"mistral/mistral-medium-3-5"},"mistralai/mistral-small-3.1-24b-instruct":{"id":"mistralai/mistral-small-3.1-24b-instruct","name":"Small 3.1 24B","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-03-17","last_updated":"2025-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0.482765,"output":0.763347},"canonical_model_id":"mistral/mistral-small-3.1-24b-instruct"},"mistralai/mistral-small-2603":{"id":"mistralai/mistral-small-2603","name":"Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":0.257888,"output":1.03155,"cache_read":0.020631},"canonical_model_id":"mistral/mistral-small-2603"},"mistralai/mistral-medium-3":{"id":"mistralai/mistral-medium-3","name":"Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":104857},"cost":{"input":0.55016,"output":2.7508,"cache_read":0.055016},"canonical_model_id":"mistral/mistral-medium-3"},"mistralai/mistral-small-3.2-24b-instruct":{"id":"mistralai/mistral-small-3.2-24b-instruct","name":"Small 3.2 24B","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["image","text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.103155,"output":0.27508},"canonical_model_id":"mistral/mistral-small-3.2-24b-instruct"},"mistralai/mistral-saba":{"id":"mistralai/mistral-saba","name":"Saba","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-02-17","last_updated":"2025-02-17","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":26214},"cost":{"input":0.27508,"output":0.82524,"cache_read":0.027508},"canonical_model_id":"mistral/mistral-saba"},"mistralai/mistral-large-2407":{"id":"mistralai/mistral-large-2407","name":"Large 2407","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-03-31","release_date":"2024-07-24","last_updated":"2024-07-24","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":104857},"cost":{"input":2.7508,"output":8.2524,"cache_read":0.27508},"canonical_model_id":"mistral/mistral-large-2407"},"mistralai/codestral-2508":{"id":"mistralai/codestral-2508","name":"Codestral 2508","description":"Mistral code model for low-latency completion, fill-in-the-middle, and code generation","family":"codestral","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":8192},"cost":{"input":0.41262,"output":1.23786,"cache_read":0.041262},"canonical_model_id":"mistral/codestral-2508"},"mistralai/mistral-small-24b-instruct-2501":{"id":"mistralai/mistral-small-24b-instruct-2501","name":"Small 3","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-01-30","last_updated":"2025-01-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"cost":{"input":0.06877,"output":0.110032},"canonical_model_id":"mistral/mistral-small-24b-instruct-2501"},"mistralai/devstral-2512":{"id":"mistralai/devstral-2512","name":"Devstral 2 2512","description":"Mistral's coding-agent model for repository work, terminal tasks, and software fixes","family":"devstral","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.605176,"output":3.02588,"cache_read":0.060518},"canonical_model_id":"mistral/devstral-2512"},"mistralai/mixtral-8x22b-instruct":{"id":"mistralai/mixtral-8x22b-instruct","name":"Mixtral 8x22B Instruct","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-01-31","release_date":"2024-04-17","last_updated":"2024-04-17","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":52428},"cost":{"input":2.7508,"output":8.2524,"cache_read":0.27508},"canonical_model_id":"mistral/mixtral-8x22b-instruct"},"mistralai/mistral-large":{"id":"mistralai/mistral-large","name":"Large","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11-30","release_date":"2024-02-26","last_updated":"2024-02-26","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":102400},"cost":{"input":2.7508,"output":8.2524,"cache_read":0.27508},"canonical_model_id":"mistral/mistral-large"},"mistralai/mistral-medium-3.1":{"id":"mistralai/mistral-medium-3.1","name":"Medium 3.1","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06-30","release_date":"2025-08-12","last_updated":"2025-08-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":104857},"cost":{"input":0.55016,"output":2.7508,"cache_read":0.055016},"canonical_model_id":"mistral/mistral-medium-3.1"},"alibaba/qwen3.8-flash":{"id":"alibaba/qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.208,"output":0.611,"cache_read":0.0208},"canonical_model_id":"alibaba/qwen3.8-flash"},"alibaba/qwen-max":{"id":"alibaba/qwen-max","name":"Qwen Max","description":"Flagship Qwen model for complex reasoning, coding, and agentic workflows","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-04-03","last_updated":"2025-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":32000,"output":8192},"cost":{"input":2.08,"output":8.32,"cache_read":0.416},"canonical_model_id":"alibaba/qwen-max"},"alibaba/qwen3.8-2.4t-a95b":{"id":"alibaba/qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":52429},"cost":{"input":3.4385,"output":8.59625,"cache_read":0.6877},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"alibaba/qwen3.8-max":{"id":"alibaba/qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2.6,"output":7.8,"cache_read":0.325},"canonical_model_id":"alibaba/qwen3.8-max"},"alibaba/qwen3.8-max-prime":{"id":"alibaba/qwen3.8-max-prime","name":"Qwen3.8 Max Prime","description":"High-throughput edition of Qwen3.8 Max for coding, professional work, multimodal understanding, and long-running agent workflows","family":"qwen3.8-max","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":5.5016,"output":16.5048,"cache_read":0.6877},"canonical_model_id":"alibaba/qwen3.8-max-prime"},"alibaba/qwen3-coder-480b-a35b-instruct":{"id":"alibaba/qwen3-coder-480b-a35b-instruct","name":"Qwen3 Coder","description":"Open Qwen coding heavyweight for repository reasoning and agentic engineering","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":65536},"cost":{"input":1.3754,"output":6.705075,"cache_read":1.3754},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"alibaba/qwen3-next-80b-a3b-instruct":{"id":"alibaba/qwen3-next-80b-a3b-instruct","name":"Qwen3 Next 80B A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":129024,"output":16384},"cost":{"input":0.20631,"output":1.65048},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"alibaba/qwen-plus":{"id":"alibaba/qwen-plus","name":"Qwen Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131000,"output":16384},"cost":{"input":0.52,"output":1.56,"cache_read":0.104},"canonical_model_id":"alibaba/qwen-plus"},"alibaba/qwen3.8-27b":{"id":"alibaba/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.61893,"output":4.40128},"canonical_model_id":"alibaba/qwen3.8-27b"},"amazon/nova-micro-v1":{"id":"amazon/nova-micro-v1","name":"Nova Micro 1.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-micro","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":5120},"cost":{"input":0.048139,"output":0.192556},"canonical_model_id":"amazon/nova-micro-v1"},"amazon/nova-pro-v1":{"id":"amazon/nova-pro-v1","name":"Nova Pro 1.0","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":5120},"cost":{"input":1.10032,"output":4.40128},"canonical_model_id":"amazon/nova-pro-v1"},"amazon/nova-lite-v1":{"id":"amazon/nova-lite-v1","name":"Nova Lite 1.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":5120},"cost":{"input":0.082524,"output":0.330096},"canonical_model_id":"amazon/nova-lite-v1"},"sakana/fugu-max":{"id":"sakana/fugu-max","name":"Fugu Max","description":"Multi-agent model for routing expert agents across complex analytical tasks","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2.7508,"output":8.2524,"cache_read":0.34385},"canonical_model_id":"sakana/fugu-max"},"sakana/fugu-ultra":{"id":"sakana/fugu-ultra","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":6.877,"output":41.262,"cache_read":0.6877},"canonical_model_id":"sakana/fugu-ultra"},"sakana/fugu-ultra-v2":{"id":"sakana/fugu-ultra-v2","name":"Fugu Ultra v2","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-08-28","release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":6.877,"output":41.262,"cache_read":0.6877},"canonical_model_id":"sakana/fugu-ultra-v2"},"rekaai/reka-edge":{"id":"rekaai/reka-edge","name":"Reka Edge","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"reka","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":16384},"cost":{"input":0.13754,"output":0.13754},"canonical_model_id":"rekaai/reka-edge"},"cognitivecomputations/dolphin-mistral-24b-venice-edition":{"id":"cognitivecomputations/dolphin-mistral-24b-venice-edition","name":"Venice Uncensored","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-04-30","release_date":"2025-07-09","last_updated":"2025-07-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.27508,"output":1.23786},"canonical_model_id":"cognitivecomputations/dolphin-mistral-24b-venice-edition"},"moonshotai/kimi-k2-0905":{"id":"moonshotai/kimi-k2-0905","name":"Kimi K2 0905","description":"September 2025 Kimi K2 instruction update with a 256K context and improved agentic coding","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":1.3754,"output":4.1262},"canonical_model_id":"moonshotai/kimi-k2-0905"},"moonshotai/kimi-k2-thinking":{"id":"moonshotai/kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Thinking Kimi model for slower research passes, planning, and hard technical questions","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":0.82524,"output":3.4385,"cache_read":0.20631},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"moonshotai/kimi-k2":{"id":"moonshotai/kimi-k2","name":"Kimi K2 0711","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-12-31","release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.783978,"output":3.16342},"canonical_model_id":"moonshotai/kimi-k2"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.39,"output":1.56,"cache_read":0.0078},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.39,"output":1.56,"cache_read":0.0078},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":1.17,"output":3.51,"cache_read":0.039},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-chat":{"id":"deepseek/deepseek-chat","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.39,"output":1.56,"cache_read":0.0078},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v4-flash-vision-exp":{"id":"deepseek/deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.572,"output":1.716,"cache_read":0.0182},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"deepseek/deepseek-chat-v3-0324":{"id":"deepseek/deepseek-chat-v3-0324","name":"DeepSeek V3","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07-31","release_date":"2025-03-24","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":124000},"cost":{"input":0.398866,"output":1.567956,"cache_read":0.192556},"canonical_model_id":"deepseek/deepseek-chat-v3-0324"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":2.393196,"output":4.786392,"cache_read":0.199433},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"aion-labs/aion-rp-llama-3.1-8b":{"id":"aion-labs/aion-rp-llama-3.1-8b","name":"Aion-RP 1.0 (8B)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12-31","release_date":"2025-02-04","last_updated":"2025-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":1.10032,"output":2.20064},"canonical_model_id":"aion-labs/aion-rp-llama-3.1-8b"},"unbiased/pareto":{"id":"unbiased/pareto","name":"Pareto","description":"Blended multimodal model that runs multiple language models in parallel and returns a synthesized answer","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":3.4385,"output":10.3155,"cache_read":0.34385},"canonical_model_id":"unbiased/pareto"},"cohere/command-r7b-12-2024":{"id":"cohere/command-r7b-12-2024","name":"Command R7B (12-2024)","description":"Cohere retrieval model for long-context chat and enterprise RAG workflows","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-12-13","last_updated":"2024-12-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.051578,"output":0.20631},"canonical_model_id":"cohere/command-r7b-12-2024"},"cohere/command-r-08-2024":{"id":"cohere/command-r-08-2024","name":"Command R (08-2024)","description":"Cohere retrieval model for long-context chat and enterprise RAG workflows","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.20631,"output":0.82524},"canonical_model_id":"cohere/command-r-08-2024"},"cohere/command-a":{"id":"cohere/command-a","name":"Command A","description":"Cohere command model for multilingual enterprise agents, tools, and chat","family":"command-a","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-03-13","last_updated":"2025-03-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":3.4385,"output":13.754},"canonical_model_id":"cohere/command-a"},"cohere/command-r-plus-08-2024":{"id":"cohere/command-r-plus-08-2024","name":"Command R+ (08-2024)","description":"Cohere's RAG workhorse for long-context enterprise search and tool use","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":3.4385,"output":13.754},"canonical_model_id":"cohere/command-r-plus-08-2024"},"inference-net/schematron-v2-turbo":{"id":"inference-net/schematron-v2-turbo","name":"Schematron V2 Turbo","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.041262,"output":0.20631},"canonical_model_id":"inference-net/schematron-v2-turbo"},"inference-net/schematron-v2-small":{"id":"inference-net/schematron-v2-small","name":"Schematron V2 Small","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":0.06877,"output":0.316342},"canonical_model_id":"inference-net/schematron-v2-small"},"meta-llama/Llama-3.3-70B-Instruct-Turbo":{"id":"meta-llama/Llama-3.3-70B-Instruct-Turbo","name":"Llama 3.3 70B Instruct Turbo","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":127000},"cost":{"input":1.352,"output":1.352},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"tencent/hy-mt2-1.8b":{"id":"tencent/hy-mt2-1.8b","name":"Hy-MT2-1.8B","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":4096},"cost":{"input":0.060518,"output":0.243446},"canonical_model_id":"tencent/hy-mt2-1.8b"},"tencent/hy-mt2-30b-a3b":{"id":"tencent/hy-mt2-30b-a3b","name":"Hy-MT2-30B-A3B","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":4096},"cost":{"input":0.10178,"output":0.405743},"canonical_model_id":"tencent/hy-mt2-30b-a3b"},"tencent/hy4-preview":{"id":"tencent/hy4-preview","name":"Hy4 preview","description":"A next-generation productivity model with significantly enhanced Agent and complex task execution capabilities.","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":64000},"cost":{"input":1.147084,"output":3.439875,"cache_read":0.057767},"canonical_model_id":"tencent/hy4-preview"},"tencent/hy-mt2-7b":{"id":"tencent/hy-mt2-7b","name":"Hy-MT2-7B","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":4096},"cost":{"input":0.10178,"output":0.405743},"canonical_model_id":"tencent/hy-mt2-7b"},"tencent/hy3":{"id":"tencent/hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":131072},"cost":{"input":0.27508,"output":1.10032,"cache_read":0.06877},"canonical_model_id":"tencent/hy3"},"meta/muse-spark-1.3":{"id":"meta/muse-spark-1.3","name":"Muse Spark 1.3","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.71925,"output":5.84545,"cache_read":0.20631},"canonical_model_id":"meta/muse-spark-1.3"},"meta/muse-spark-1.2":{"id":"meta/muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.71925,"output":5.84545,"cache_read":0.20631},"canonical_model_id":"meta/muse-spark-1.2"},"meta/muse-spark-1.1":{"id":"meta/muse-spark-1.1","name":"Muse Spark 1.1","description":"Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":1.71925,"output":5.84545,"cache_read":0.20631},"canonical_model_id":"meta/muse-spark-1.1"},"meta/muse-glimmer-30b":{"id":"meta/muse-glimmer-30b","name":"Muse Glimmer 30B","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.48139,"output":2.0631,"cache_read":0.055016},"canonical_model_id":"meta/muse-glimmer-30b"},"stepfun/step-5-preview":{"id":"stepfun/step-5-preview","name":"Step 5 Preview","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":64000},"cost":{"input":1.3754,"output":3.71358,"cache_read":0.06877},"canonical_model_id":"stepfun/step-5-preview"},"nousresearch/hermes-3-llama-3.1-70b":{"id":"nousresearch/hermes-3-llama-3.1-70b","name":"Hermes 3 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"nousresearch","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-18","last_updated":"2024-08-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.96278,"output":0.96278},"canonical_model_id":"nousresearch/hermes-3-llama-3.1-70b"},"nousresearch/hermes-3-llama-3.1-405b":{"id":"nousresearch/hermes-3-llama-3.1-405b","name":"Hermes 3 405B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"nousresearch","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-16","last_updated":"2024-08-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":1.3754,"output":1.3754},"canonical_model_id":"nousresearch/hermes-3-llama-3.1-405b"},"z-ai/glm-5-turbo":{"id":"z-ai/glm-5-turbo","name":"GLM 5 Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":1.56,"output":5.2,"cache_read":0.312},"canonical_model_id":"zhipuai/glm-5-turbo"},"z-ai/glm-4.5v":{"id":"z-ai/glm-4.5v","name":"GLM 4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":16384},"cost":{"input":0.82524,"output":2.47572,"cache_read":0.151294},"canonical_model_id":"zhipuai/glm-4.5v"},"z-ai/glm-4.6v":{"id":"z-ai/glm-4.6v","name":"GLM 4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.41262,"output":1.23786,"cache_read":0.075647},"canonical_model_id":"zhipuai/glm-4.6v"},"z-ai/glm-5v-turbo":{"id":"z-ai/glm-5v-turbo","name":"GLM 5V Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":131072},"cost":{"input":1.56,"output":5.2,"cache_read":0.312},"canonical_model_id":"zhipuai/glm-5v-turbo"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.195,"output":0.65,"cache_read":0.039},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-4.7-flash":{"id":"z-ai/glm-4.7-flash","name":"GLM 4.7 Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":16384},"cost":{"input":0.171925,"output":0.6877,"cache_read":0.013754},"canonical_model_id":"zhipuai/glm-4.7-flash"},"gryphe/mythomax-l2-13b":{"id":"gryphe/mythomax-l2-13b","name":"MythoMax 13B","description":"Llama 2 merge combining MythoLogic and Huginn for creative writing and roleplay","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2023-08-10","last_updated":"2023-08-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":4096},"cost":{"input":2.578875,"output":2.578875,"cache_read":2.578875},"canonical_model_id":"gryphe/mythomax-l2-13b"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.975,"output":4.875,"cache_read":0.0975},"canonical_model_id":"google/gemini-3.7-flash"},"google/gemini-3.1-flash-lite-preview":{"id":"google/gemini-3.1-flash-lite-preview","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.34385,"output":2.0631,"cache_read":0.034385,"cache_write":0.114617},"canonical_model_id":"google/gemini-3.1-flash-lite-preview"},"google/gemma-3-4b-it":{"id":"google/gemma-3-4b-it","name":"Gemma 3 4B","description":"Open multimodal Gemma instruction model for efficient text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":32768},"cost":{"input":0.06877,"output":0.13754,"cache_read":0.055016},"canonical_model_id":"google/gemma-3-4b-it"},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B Instruct","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":1.361646,"output":2.049346,"cache_read":1.361646},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemma-2-27b-it":{"id":"google/gemma-2-27b-it","name":"Gemma 2 27B","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2024-07-13","last_updated":"2024-07-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":2048},"cost":{"input":0.89401,"output":0.89401},"canonical_model_id":"google/gemma-2-27b-it"},"google/gemma-4-26b-a4b-it":{"id":"google/gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":128000},"cost":{"input":0.20631,"output":0.82524,"cache_read":0.20631},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":2.6,"output":15.6,"cache_read":0.65},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.975,"output":4.875,"cache_read":0.0975},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemma-3-27b-it":{"id":"google/gemma-3-27b-it","name":"Gemma 3 27B","description":"Largest open Gemma 3 instruction model for multilingual text generation and visual understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":117964},"cost":{"input":0.20631,"output":0.632684,"cache_read":0.103155},"canonical_model_id":"google/gemma-3-27b-it"},"google/gemma-3-12b-it":{"id":"google/gemma-3-12b-it","name":"Gemma 3 12B","description":"Open multimodal Gemma instruction model for multilingual text generation and image understanding","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":96000},"cost":{"input":0.06877,"output":0.20631,"cache_read":0.055016},"canonical_model_id":"google/gemma-3-12b-it"},"google/gemini-3-8-flash":{"id":"google/gemini-3-8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.975,"output":4.875,"cache_read":0.0975},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-3.1-pro-preview-customtools":{"id":"google/gemini-3.1-pro-preview-customtools","name":"Gemini 3.1 Pro Preview Custom Tools","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048756,"output":65536},"cost":{"input":2.7508,"output":16.5048,"cache_read":0.27508,"cache_write":0.515775},"canonical_model_id":"google/gemini-3.1-pro-preview-customtools"},"google/gemini-flash-latest":{"id":"google/gemini-flash-latest","name":"Gemini Flash Latest","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2.0631,"output":12.3786,"cache_read":0.20631,"cache_write":0.114617},"canonical_model_id":"google/gemini-flash-latest"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.95,"output":9.75,"cache_read":0.195},"canonical_model_id":"google/gemini-3.6-flash"}}},"friendli":{"id":"friendli","env":["FRIENDLI_TOKEN"],"npm":"@ai-sdk/openai-compatible","api":"https://api.friendli.ai/serverless/v1","name":"Friendli","doc":"https://friendli.ai/docs/guides/serverless_endpoints/introduction","models":{"zai-org/GLM-5.3-Flash":{"id":"zai-org/GLM-5.3-Flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"zai-org/GLM-5.1":{"id":"zai-org/GLM-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":202752,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"zai-org/GLM-5.3":{"id":"zai-org/GLM-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":1.26,"output":3.96,"cache_read":0.234},"canonical_model_id":"zhipuai/glm-5.3"},"deepseek-ai/DeepSeek-V3.2":{"id":"deepseek-ai/DeepSeek-V3.2","name":"DeepSeek V3.2","description":"Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":64000},"cost":{"input":0.5,"output":1.5,"cache_read":0.25},"canonical_model_id":"deepseek/deepseek-v3.2"},"google/gemma-4-31B-it":{"id":"google/gemma-4-31B-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.14,"output":0.4},"canonical_model_id":"google/gemma-4-31b-it"}}},"zenmux":{"id":"zenmux","env":["ZENMUX_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://zenmux.ai/api/v1","name":"ZenMux","doc":"https://docs.zenmux.ai","models":{"xiaomi/mimo-v2-flash":{"id":"xiaomi/mimo-v2-flash","name":"MiMo-V2-Flash","description":"MiMo flash model for fast multimodal assistance and agent workflows","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-12-01","release_date":"2025-12-16","last_updated":"2026-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","cost":{"input":0.1,"output":0.3,"cache_read":0.01},"canonical_model_id":"xiaomi/mimo-v2-flash"},"xiaomi/mimo-v2-omni":{"id":"xiaomi/mimo-v2-omni","name":"MiMo V2 Omni","description":"MiMo omni model for text, image, video, audio, and agents","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":265000,"output":265000},"status":"deprecated","cost":{"input":0.4,"output":2,"cache_read":0.08},"canonical_model_id":"xiaomi/mimo-v2-omni"},"xiaomi/mimo-v2-pro":{"id":"xiaomi/mimo-v2-pro","name":"MiMo V2 Pro","description":"Earlier MiMo Pro model for multimodal agents, reasoning, and code tasks","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":256000},"status":"deprecated","cost":{"input":1,"output":3,"cache_read":0.2,"tiers":[{"input":2,"output":6,"cache_read":0.4,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.4}},"canonical_model_id":"xiaomi/mimo-v2-pro"},"xiaomi/mimo-v2.6-pro":{"id":"xiaomi/mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"xiaomi/mimo-v2.5-pro":{"id":"xiaomi/mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":1,"output":3,"cache_read":0.2,"tiers":[{"input":2,"output":6,"cache_read":0.4,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.4}},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"xiaomi/mimo-v2.5":{"id":"xiaomi/mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0.4,"output":2,"cache_read":0.08,"tiers":[{"input":0.8,"output":4,"cache_read":0.16,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.8,"output":4,"cache_read":0.16}},"canonical_model_id":"xiaomi/mimo-v2.5"},"kuaishou/kat-coder-pro-v2":{"id":"kuaishou/kat-coder-pro-v2","name":"KAT-Coder-Pro-V2","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-03-30","last_updated":"2026-03-30","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":80000},"status":"deprecated","cost":{"input":0.3,"output":1.2,"cache_read":0.06}},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude Sonnet 4.6","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-4.6":{"id":"anthropic/claude-opus-4.6","name":"Claude Opus 4.6","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-sonnet-5-free":{"id":"anthropic/claude-sonnet-5-free","name":"Claude Sonnet 5 (Free)","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-opus-5.5":{"id":"anthropic/claude-opus-5.5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-opus-4":{"id":"anthropic/claude-opus-4","name":"Claude Opus 4","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-0"},"anthropic/claude-haiku-4.5":{"id":"anthropic/claude-haiku-4.5","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-opus-4.1":{"id":"anthropic/claude-opus-4.1","name":"Claude Opus 4.1","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1"},"anthropic/claude-3.5-haiku":{"id":"anthropic/claude-3.5-haiku","name":"Claude 3.5 Haiku","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07-31","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":0.8,"output":4,"cache_read":0.08,"cache_write":1},"canonical_model_id":"anthropic/claude-3-5-haiku-20241022"},"anthropic/claude-sonnet-4":{"id":"anthropic/claude-sonnet-4","name":"Claude Sonnet 4","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-0"},"anthropic/claude-sonnet-4.5":{"id":"anthropic/claude-sonnet-4.5","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-fable-5.1":{"id":"anthropic/claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-3.7-sonnet":{"id":"anthropic/claude-3.7-sonnet","name":"Claude 3.7 Sonnet","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-10-31","release_date":"2025-02-19","last_updated":"2025-02-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-3-7-sonnet-20250219"},"anthropic/claude-opus-4.5":{"id":"anthropic/claude-opus-4.5","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude Opus 4.7","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"x-ai/grok-4.2-fast-non-reasoning":{"id":"x-ai/grok-4.2-fast-non-reasoning","name":"Grok 4.2 Fast Non Reasoning","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":2,"output":6,"cache_read":0.2,"tiers":[{"input":4,"output":12,"cache_read":0.2,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"xai/grok-4.20-0309-non-reasoning"},"x-ai/grok-build-0.1":{"id":"x-ai/grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"cost":{"input":1,"output":2,"cache_read":0.2},"canonical_model_id":"xai/grok-build-0.1"},"x-ai/grok-4.3":{"id":"x-ai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":1000000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.3"},"x-ai/grok-4.2-fast":{"id":"x-ai/grok-4.2-fast","name":"Grok 4.2 Fast","description":"Reasoning Grok for document-heavy analysis and long-horizon tool use","family":"grok","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-09","last_updated":"2026-03-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":30000},"cost":{"input":2,"output":6,"cache_read":0.2,"tiers":[{"input":4,"output":12,"cache_read":0.2,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"xai/grok-4.20-0309-reasoning"},"x-ai/grok-voice-tts-1.0":{"id":"x-ai/grok-voice-tts-1.0","type":"speech","name":"Grok Voice TTS 1.0","description":"Convert text into spoken audio with a single API call. The API supports a rich set of expressive voices, inline speech tags for fine-grained delivery control, and output formats from high-fidelity MP3 to telephony-optimized μ-law.","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":15000,"output":15000},"canonical_model_id":"xai/grok-tts"},"x-ai/grok-imagine-image-2.0":{"id":"x-ai/grok-imagine-image-2.0","type":"image","name":"Grok Imagine Image 2.0","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"grok","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-08-07","last_updated":"2026-08-07","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":66000,"output":0},"canonical_model_id":"xai/grok-imagine-image-2.0"},"x-ai/grok-4.6":{"id":"x-ai/grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"x-ai/grok-voice-stt-1.0":{"id":"x-ai/grok-voice-stt-1.0","type":"transcription","name":"Grok Voice STT 1.0","description":"Speech-to-text model with word-level timestamps, speaker diarization, multichannel audio, and streaming","family":"grok","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["audio"],"output":["text"]},"open_weights":false,"limit":{"context":15000,"output":15000},"canonical_model_id":"xai/grok-voice-transcribe-2.0"},"x-ai/grok-4.5":{"id":"x-ai/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.5"},"sapiens-ai/agnes-1.5-pro":{"id":"sapiens-ai/agnes-1.5-pro","name":"Agnes 1.5 Pro","description":"Flagship model for demanding analysis, coding, and production agent workflows","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-21","last_updated":"2026-03-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"status":"deprecated","cost":{"input":0.16,"output":0.8}},"sapiens-ai/agnes-1.5-lite":{"id":"sapiens-ai/agnes-1.5-lite","name":"Agnes 1.5 Lite","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"release_date":"2026-03-26","last_updated":"2026-03-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"status":"deprecated","cost":{"input":0.12,"output":0.6}},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-5-codex":{"id":"openai/gpt-5-codex","name":"GPT-5 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5-codex"},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT-5.4 Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.4-pro"},"openai/gpt-5.1-chat":{"id":"openai/gpt-5.1-chat","name":"GPT-5.1 Chat","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"status":"deprecated","provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":1.25,"output":10,"cache_read":0.12},"canonical_model_id":"openai/gpt-5.1-chat-latest"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.2-pro":{"id":"openai/gpt-5.2-pro","name":"GPT-5.2-Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":21,"output":168},"canonical_model_id":"openai/gpt-5.2-pro"},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-5.5-instant":{"id":"openai/gpt-5.5-instant","name":"GPT-5.5 Instant","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12-01","release_date":"2026-05-05","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5-instant"},"openai/chat-latest":{"id":"openai/chat-latest","name":"Chat Latest (GPT-5.5 Instant)","description":"Compact GPT model for low-latency assistance and high-volume workloads","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12-01","release_date":"2026-05-05","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5},"canonical_model_id":"openai/gpt-5.5-instant"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-5.2-codex":{"id":"openai/gpt-5.2-codex","name":"GPT-5.2-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-codex"},"openai/gpt-5.5-pro":{"id":"openai/gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.5-pro"},"openai/gpt-5.1-codex":{"id":"openai/gpt-5.1-codex","name":"GPT-5.1-Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":12.5,"output":75,"cache_read":1.25},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"openai/gpt-5.1-codex-mini":{"id":"openai/gpt-5.1-codex-mini","name":"GPT-5.1-Codex-Mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":100000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5.1-codex-mini"},"openai/gpt-5.3-chat":{"id":"openai/gpt-5.3-chat","name":"GPT-5.3 Chat","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16380},"status":"deprecated","provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":1.75,"output":14},"canonical_model_id":"openai/gpt-5.3-chat-latest"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://zenmux.ai/api/v1"},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"volcengine/doubao-seed-code":{"id":"volcengine/doubao-seed-code","name":"Doubao-Seed-Code","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-11-11","last_updated":"2025-11-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"status":"deprecated","cost":{"input":0.17,"output":1.12,"cache_read":0.03}},"volcengine/doubao-seed-2.0-code":{"id":"volcengine/doubao-seed-2.0-code","name":"Doubao Seed 2.0 Code","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","family":"seed","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"status":"deprecated","cost":{"input":0.9,"output":4.48},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"volcengine/doubao-seed-2.0-mini":{"id":"volcengine/doubao-seed-2.0-mini","name":"Doubao-Seed-2.0-mini","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-02-14","release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"status":"deprecated","cost":{"input":0.03,"output":0.28,"cache_read":0.01,"cache_write":0.0024},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"volcengine/doubao-seed-1.8":{"id":"volcengine/doubao-seed-1.8","name":"Doubao-Seed-1.8","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-12-28","last_updated":"2025-12-28","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"status":"deprecated","cost":{"input":0.11,"output":0.28,"cache_read":0.02,"cache_write":0.0024},"canonical_model_id":"bytedance-seed/seed-1-8"},"volcengine/doubao-seed-2.0-lite":{"id":"volcengine/doubao-seed-2.0-lite","name":"Doubao-Seed-2.0-lite","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-02-14","release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"status":"deprecated","cost":{"input":0.09,"output":0.51,"cache_read":0.02,"cache_write":0.0024},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"volcengine/doubao-seed-2.0-pro":{"id":"volcengine/doubao-seed-2.0-pro","name":"Doubao-Seed-2.0-pro","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-02-14","release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"status":"deprecated","cost":{"input":0.45,"output":2.24,"cache_read":0.09,"cache_write":0.0024},"canonical_model_id":"bytedance-seed/seed-2.0-pro"},"bytedance/doubao-seed-code":{"id":"bytedance/doubao-seed-code","name":"Doubao-Seed-Code","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2025-11-11","last_updated":"2025-11-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.17,"output":1.12,"cache_read":0.034,"tiers":[{"input":0.2,"output":1.69,"cache_read":0.034,"tier":{"type":"context","size":32000}},{"input":0.39,"output":2.25,"cache_read":0.034,"tier":{"type":"context","size":128000}}]}},"bytedance/doubao-seed-2.0-code":{"id":"bytedance/doubao-seed-2.0-code","name":"Doubao Seed 2.0 Code","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.45,"output":2.24,"cache_read":0.09,"tiers":[{"input":0.67,"output":3.36,"cache_read":0.14,"tier":{"type":"context","size":32000}},{"input":1.34,"output":6.71,"cache_read":0.27,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"bytedance/doubao-seed-2.0-mini":{"id":"bytedance/doubao-seed-2.0-mini","name":"Doubao-Seed-2.0-mini","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.03,"output":0.28,"cache_read":0.01,"tiers":[{"input":0.06,"output":0.56,"cache_read":0.02,"tier":{"type":"context","size":32000}},{"input":0.12,"output":1.12,"cache_read":0.03,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"bytedance/doubao-seed-1.8":{"id":"bytedance/doubao-seed-1.8","name":"Doubao-Seed-1.8","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2025-12-28","last_updated":"2025-12-28","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.11,"output":0.28,"cache_read":0.023,"tiers":[{"input":0.17,"output":2.27,"cache_read":0.023,"tier":{"type":"context","size":32000}},{"input":0.34,"output":3.41,"cache_read":0.023,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-1-8"},"bytedance/doubao-seed-2.0-lite":{"id":"bytedance/doubao-seed-2.0-lite","name":"Doubao-Seed-2.0-lite","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.09,"output":0.51,"cache_read":0.02,"tiers":[{"input":0.13,"output":0.76,"cache_read":0.03,"tier":{"type":"context","size":32000}},{"input":0.25,"output":1.51,"cache_read":0.05,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"bytedance/doubao-seed-2.0-pro":{"id":"bytedance/doubao-seed-2.0-pro","name":"Doubao-Seed-2.0-pro","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"temperature":false,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":32000},"cost":{"input":0.45,"output":2.24,"cache_read":0.09,"tiers":[{"input":0.67,"output":3.36,"cache_read":0.14,"tier":{"type":"context","size":32000}},{"input":1.34,"output":6.71,"cache_read":0.27,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-pro"},"inclusionai/ring-2.6-1t":{"id":"inclusionai/ring-2.6-1t","name":"inclusionAI: Ring-2.6-1T","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-12-31","release_date":"2026-05-07","last_updated":"2026-05-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":65000},"cost":{"input":0.1318155,"output":1.0984625,"cache_read":0.0263631}},"inclusionai/ling-1t":{"id":"inclusionai/ling-1t","name":"Ling-1T","description":"Tool-capable chat model for instruction following and agentic application workflows","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-10-09","last_updated":"2025-10-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"status":"deprecated","cost":{"input":0.56,"output":2.24,"cache_read":0.11}},"inclusionai/ring-1t":{"id":"inclusionai/ring-1t","name":"Ring-1T","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-10-12","last_updated":"2025-10-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"status":"deprecated","cost":{"input":0.56,"output":2.24,"cache_read":0.11}},"qwen/qwen3-max":{"id":"qwen/qwen3-max","name":"Qwen3-Max-Thinking","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"status":"deprecated","cost":{"input":1.2,"output":6},"canonical_model_id":"alibaba/qwen3-max"},"qwen/qwen3-coder-plus":{"id":"qwen/qwen3-coder-plus","name":"Qwen3-Coder-Plus","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-23","last_updated":"2025-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"status":"deprecated","cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"alibaba/qwen3-coder-plus"},"qwen/qwen3.7-plus":{"id":"qwen/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.4,"output":1.6,"cache_read":0.08,"cache_write":0.5,"tiers":[{"input":1.2,"output":4.8,"cache_read":0.24,"cache_write":1.5,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1.2,"output":4.8,"cache_read":0.24,"cache_write":1.5}},"canonical_model_id":"alibaba/qwen3.7-plus"},"qwen/qwen3.5-flash":{"id":"qwen/qwen3.5-flash","name":"Qwen3.5 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1020000,"output":1020000},"cost":{"input":0.1,"output":0.4,"cache_read":0.02,"cache_write":0.125},"canonical_model_id":"alibaba/qwen3.5-flash"},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":1.25,"output":3.75,"cache_read":0.25,"cache_write":1.5625},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen3.6-plus":{"id":"qwen/qwen3.6-plus","name":"Qwen3.6-Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.5,"output":3,"cache_read":0.1,"cache_write":0.625,"tiers":[{"input":2,"output":6,"cache_read":0.4,"cache_write":2.5,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":2,"output":6,"cache_read":0.4,"cache_write":2.5}},"canonical_model_id":"alibaba/qwen3.6-plus"},"qwen/qwen3.5-plus":{"id":"qwen/qwen3.5-plus","name":"Qwen3.5 Plus","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.4,"output":2.4,"cache_read":0.08,"cache_write":0.5,"tiers":[{"input":0.5,"output":3,"cache_read":0.1,"cache_write":0.625,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.5,"output":3,"cache_read":0.1,"cache_write":0.625}},"canonical_model_id":"alibaba/qwen3.5-plus"},"minimax/minimax-m2.1":{"id":"minimax/minimax-m2.1","name":"MiniMax M2.1","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204000,"output":131072},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.1"},"minimax/minimax-m3.1-flash":{"id":"minimax/minimax-m3.1-flash","name":"MiniMax-M3.1-Flash","description":"Frontier multimodal coding model with 1M context window and tunable thinking depth","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-10-19","last_updated":"2026-10-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":512000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"minimax/MiniMax-M3.1-Flash"},"minimax/minimax-m2.5-lightning":{"id":"minimax/minimax-m2.5-lightning","name":"MiniMax M2.5 highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-02-13","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":0.6,"output":2.4,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5-highspeed"},"minimax/minimax-m2.7-highspeed":{"id":"minimax/minimax-m2.7-highspeed","name":"MiniMax M2.7 highspeed","description":"High-speed MiniMax model for low-latency coding and agent workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131070},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":0.611,"output":2.4439,"cache_read":0.0611,"cache_write":0.3819},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.5"},"minimax/minimax-m2":{"id":"minimax/minimax-m2","name":"MiniMax M2","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.03,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2"},"minimax/minimax-m2.7":{"id":"minimax/minimax-m2.7","name":"MiniMax M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131070},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"cache_write":0.375},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":512000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://zenmux.ai/api/anthropic/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.06,"tiers":[{"input":0.6,"output":2.4,"cache_read":0.12,"tier":{"type":"context","size":512000}}],"context_over_200k":{"input":0.6,"output":2.4,"cache_read":0.12}},"canonical_model_id":"minimax/MiniMax-M3"},"baidu/ernie-5.0-thinking-preview":{"id":"baidu/ernie-5.0-thinking-preview","name":"ERNIE 5.0","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-01-22","last_updated":"2026-01-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"cost":{"input":0.84,"output":3.37,"tiers":[{"input":1.41,"output":5.62,"tier":{"type":"context","size":32000}}]}},"moonshotai/kimi-k2-0905":{"id":"moonshotai/kimi-k2-0905","name":"Kimi K2 0905","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":64000},"status":"deprecated","cost":{"input":0.6,"output":2.5,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2-0905"},"moonshotai/kimi-k2-thinking":{"id":"moonshotai/kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Kimi reasoning model for long-horizon research, planning, and tool use","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":64000},"status":"deprecated","cost":{"input":0.6,"output":2.5,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k3-free":{"id":"moonshotai/kimi-k3-free","name":"Kimi K3 (Free)","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2-thinking-turbo":{"id":"moonshotai/kimi-k2-thinking-turbo","name":"Kimi K2 Thinking Turbo","description":"Kimi reasoning model for long-horizon research, planning, and tool use","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":64000},"status":"deprecated","cost":{"input":1.15,"output":8,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2-thinking-turbo"},"moonshotai/kimi-k2.5":{"id":"moonshotai/kimi-k2.5","name":"Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":64000},"status":"deprecated","cost":{"input":0.58,"output":3.02,"cache_read":0.1},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262140,"output":262140},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2.7-code-free":{"id":"moonshotai/kimi-k2.7-code-free","name":"Kimi K2.7 Code (Free)","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"moonshotai/kimi-k2.7-code-highspeed":{"id":"moonshotai/kimi-k2.7-code-highspeed","name":"Kimi K2.7 Code HighSpeed","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.9,"output":8,"cache_read":0.38},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.22,"output":0.66,"cache_read":0.007},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.075,"output":0.3,"cache_read":0.0015},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.66,"output":1.98,"cache_read":0.022},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v3.2-exp":{"id":"deepseek/deepseek-v3.2-exp","name":"DeepSeek-V3.2-Exp","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":163000,"output":64000},"status":"deprecated","cost":{"input":0.22,"output":0.33}},"deepseek/deepseek-chat":{"id":"deepseek/deepseek-chat","name":"DeepSeek-V3.2 (Non-thinking Mode)","description":"DeepSeek chat model for instruction following, coding, and analysis","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":64000},"status":"deprecated","cost":{"input":0.28,"output":0.42,"cache_read":0.03}},"deepseek/deepseek-v3.2":{"id":"deepseek/deepseek-v3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8000},"cost":{"input":0.293,"output":0.4395,"cache_read":0.0293},"canonical_model_id":"deepseek/deepseek-v3.2"},"tencent/hy3-preview":{"id":"tencent/hy3-preview","name":"Hy3 preview","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"status":"deprecated","cost":{"input":0.172,"output":0.572,"cache_read":0.058,"cache_write":0},"canonical_model_id":"tencent/hy3-preview"},"stepfun/step-3":{"id":"stepfun/step-3","name":"Step-3","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2025-07-31","last_updated":"2025-07-31","modalities":{"input":["image","text"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"output":64000},"status":"deprecated","cost":{"input":0.21,"output":0.57}},"stepfun/step-3.5-flash":{"id":"stepfun/step-3.5-flash","name":"Step 3.5 Flash","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","family":"step","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":256000},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"stepfun/step-3.5-flash"},"stepfun/step-3.7-flash":{"id":"stepfun/step-3.7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"stepfun/step-3.7-flash-free":{"id":"stepfun/step-3.7-flash-free","name":"Step 3.7 Flash (Free)","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"stepfun/step-3.7-flash"},"z-ai/glm-4.6v-flash-free":{"id":"z-ai/glm-4.6v-flash-free","name":"GLM 4.6V Flash (Free)","description":"Lightweight GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0,"output":0,"cache_read":0,"tiers":[{"input":0,"output":0,"cache_read":0,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.6v-flash"},"z-ai/glm-5-turbo":{"id":"z-ai/glm-5-turbo","name":"GLM 5 Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":0.73,"output":3.19,"cache_read":0.174,"tiers":[{"input":1.02,"output":3.77,"cache_read":0.261,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-5-turbo"},"z-ai/glm-4.7":{"id":"z-ai/glm-4.7","name":"GLM 4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.2911,"output":1.1645,"cache_read":0.0582,"tiers":[{"input":0.5823,"output":2.3291,"cache_read":0.1165,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.7"},"z-ai/glm-4.6v":{"id":"z-ai/glm-4.6v","name":"GLM 4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.1456,"output":0.4367,"cache_read":0.0291,"tiers":[{"input":0.2911,"output":0.8734,"cache_read":0.0582,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.6v"},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/glm-5v-turbo":{"id":"z-ai/glm-5v-turbo","name":"GLM 5V Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":128000},"cost":{"input":0.726,"output":3.1946,"cache_read":0.1743,"tiers":[{"input":1.0165,"output":3.7754,"cache_read":0.2614,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-5v-turbo"},"z-ai/glm-5":{"id":"z-ai/glm-5","name":"GLM 5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.58,"output":2.6,"cache_read":0.14,"tiers":[{"input":0.87,"output":3.18,"cache_read":0.22,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-5"},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM 5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM 5.3 Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.075,"output":0.25,"cache_read":0.015},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-4.5-air":{"id":"z-ai/glm-4.5-air","name":"GLM 4.5 Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":96000},"cost":{"input":0.1165,"output":0.2911,"cache_read":0.0233,"tiers":[{"input":0.1747,"output":1.1645,"cache_read":0.0349,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.5-air"},"z-ai/glm-4.7-flash-free":{"id":"z-ai/glm-4.7-flash-free","name":"GLM 4.7 Flash (Free)","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-4.7-flash"},"z-ai/glm-5.1":{"id":"z-ai/glm-5.1","name":"GLM 5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.8781,"output":3.5126,"cache_read":0.1903,"tiers":[{"input":1.1709,"output":4.098,"cache_read":0.2927,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-5.1"},"z-ai/glm-4.6":{"id":"z-ai/glm-4.6","name":"GLM 4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.2911,"output":1.1645,"cache_read":0.0582,"tiers":[{"input":0.5823,"output":2.3291,"cache_read":0.1165,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.6"},"z-ai/glm-4.5":{"id":"z-ai/glm-4.5","name":"GLM 4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":96000},"cost":{"input":0.2911,"output":1.1645,"cache_read":0.0582,"tiers":[{"input":0.5823,"output":2.3291,"cache_read":0.1165,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.5"},"z-ai/glm-4.6v-flash":{"id":"z-ai/glm-4.6v-flash","name":"GLM 4.6V FlashX","description":"Lightweight GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.0218,"output":0.2184,"cache_read":0.0044,"tiers":[{"input":0.0437,"output":0.4367,"cache_read":0.0044,"tier":{"type":"context","size":32000}}]},"canonical_model_id":"zhipuai/glm-4.6v-flash"},"z-ai/glm-5.3-flashx":{"id":"z-ai/glm-5.3-flashx","name":"GLM 5.3 FlashX","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.375,"output":1.25,"cache_read":0.075},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-4.7-flashx":{"id":"z-ai/glm-4.7-flashx","name":"GLM 4.7 FlashX","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"cost":{"input":0.0728,"output":0.4367,"cache_read":0.0146},"canonical_model_id":"zhipuai/glm-4.7-flashx"},"z-ai/glm-image":{"id":"z-ai/glm-image","type":"image","name":"GLM-Image","description":"GLM-Image is an image generation model adopts a hybrid autoregressive + diffusion decoder architecture. In general image generation quality, GLM‑Image aligns with mainstream latent diffusion approaches, but it shows significant advantages in text-rendering and knowledge‑intensive generation scenarios. It performs especially well in tasks requiring precise semantic understanding and complex information expression, while maintaining strong capabilities in high‑fidelity and fine‑grained detail generation. In addition to text‑to‑image generation, GLM‑Image also supports a rich set of image‑to‑image tasks including image editing, style transfer, identity‑preserving generation, and multi‑subject consistency.","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-01-14","last_updated":"2026-01-14","modalities":{"input":["text"],"output":["image"]},"open_weights":true,"limit":{"context":10240,"output":0},"provider":{"api":"https://zenmux.ai/api/vertex-ai"},"canonical_model_id":"zhipuai/glm-image"},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens","min":512,"max":24576}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048000,"output":65535},"cost":{"input":0.1,"output":0.4,"cache_read":0.01,"input_audio":0.3},"canonical_model_id":"google/gemini-2.5-flash-lite"},"google/gemini-3.1-flash-lite-preview":{"id":"google/gemini-3.1-flash-lite-preview","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":65530},"status":"deprecated","cost":{"input":0.25,"output":1.5},"canonical_model_id":"google/gemini-3.1-flash-lite-preview"},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048000,"output":65535},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":1,"input_audio":1},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048000,"output":65535},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"input_audio":1},"canonical_model_id":"google/gemini-2.5-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048000,"output":65535},"cost":{"input":1.25,"output":10,"cache_read":0.13,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048000,"output":65535},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"cache_read":0.15},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite"}}},"openrouter":{"id":"openrouter","env":["OPENROUTER_API_KEY"],"npm":"@openrouter/ai-sdk-provider","api":"https://openrouter.ai/api/v1","name":"OpenRouter","doc":"https://openrouter.ai/models","models":{"undi95/remm-slerp-l2-13b":{"id":"undi95/remm-slerp-l2-13b","name":"ReMM SLERP 13B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-06-30","release_date":"2023-07-22","last_updated":"2023-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":6144,"output":5529},"cost":{"input":0.35,"output":0.65},"canonical_model_id":"undi95/remm-slerp-l2-13b"},"thinkingmachines/inkling-small:free":{"id":"thinkingmachines/inkling-small:free","name":"Inkling Small (free)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/inkling-small":{"id":"thinkingmachines/inkling-small","name":"Inkling Small","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-30","last_updated":"2026-07-30","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":262144},"cost":{"input":0.45,"output":1.2,"cache_read":0.1},"canonical_model_id":"thinkingmachines/inkling-small"},"thinkingmachines/inkling":{"id":"thinkingmachines/inkling","name":"Inkling","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":471859},"cost":{"input":1,"output":4.05,"cache_read":0.17},"canonical_model_id":"thinkingmachines/inkling"},"thinkingmachines/inkling:free":{"id":"thinkingmachines/inkling:free","name":"Inkling (free)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"thinkingmachines/inkling"},"~unbiased/pareto-latest":{"id":"~unbiased/pareto-latest","name":"Pareto Latest","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.8,"output":3.2,"cache_read":0.03}},"xiaomi/mimo-v2.6-pro-ultraspeed":{"id":"xiaomi/mimo-v2.6-pro-ultraspeed","name":"MiMo-V2.6-Pro-UltraSpeed","description":"MiMo pro model for strong multimodal reasoning and agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":4.35,"output":8.7,"cache_read":0.036},"canonical_model_id":"xiaomi/mimo-v2.6-pro-ultraspeed"},"xiaomi/mimo-v2.6-flash":{"id":"xiaomi/mimo-v2.6-flash","name":"MiMo-V2.6-Flash","description":"MiMo flash model for fast multimodal assistance and agent workflows","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":131072},"cost":{"input":0.14,"output":0.28,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"xiaomi/mimo-v2.6-pro":{"id":"xiaomi/mimo-v2.6-pro","name":"MiMo-V2.6-Pro","description":"MiMo pro model for strong multimodal reasoning and agent execution","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":131072},"cost":{"input":0.435,"output":0.87,"cache_read":0.0036},"canonical_model_id":"xiaomi/mimo-v2.6-pro"},"xiaomi/mimo-v2.5-pro":{"id":"xiaomi/mimo-v2.5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":945000},"status":"deprecated","cost":{"input":0.3045,"output":0.609,"cache_read":0.0028},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"xiaomi/mimo-v2.5":{"id":"xiaomi/mimo-v2.5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1050000,"output":945000},"status":"deprecated","cost":{"input":0.119,"output":0.238,"cache_read":0.00255},"canonical_model_id":"xiaomi/mimo-v2.5"},"recursive/flint-v1.0:free":{"id":"recursive/flint-v1.0:free","name":"Flint (free)","description":"Free provider route for experiments, demos, and cost-sensitive chat workloads","family":"flint","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-21","last_updated":"2026-10-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0,"output":0}},"meituan/longcat-2.0":{"id":"meituan/longcat-2.0","name":"LongCat-2.0","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"longcat","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048756,"output":262144},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"meituan/longcat-2.0"},"sao10k/l3.1-euryale-70b":{"id":"sao10k/l3.1-euryale-70b","name":"Llama 3.1 Euryale 70B v2.2","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-28","last_updated":"2024-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.85,"output":0.85},"canonical_model_id":"sao10k/l3.1-euryale-70b"},"sao10k/l3-lunaris-8b":{"id":"sao10k/l3-lunaris-8b","name":"Llama 3 8B Lunaris","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-13","last_updated":"2024-08-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":7372},"cost":{"input":0.04,"output":0.05},"canonical_model_id":"sao10k/l3-lunaris-8b"},"elorian/glimpse":{"id":"elorian/glimpse","name":"Glimpse","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":256000},"cost":{"input":0.6,"output":3,"cache_read":0.06}},"reflection/beam-1.0-501b-a23b":{"id":"reflection/beam-1.0-501b-a23b","name":"Beam 1.0 501B A23B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-06-30","release_date":"2026-10-05","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":0.3,"output":1,"cache_read":0.04},"canonical_model_id":"reflection/beam-1.0-501b-a23b"},"ibm-granite/granite-4.0-h-micro":{"id":"ibm-granite/granite-4.0-h-micro","name":"Granite 4.0 Micro","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"granite","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-10-20","last_updated":"2025-10-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":117900},"cost":{"input":0.017,"output":0.112}},"ibm-granite/granite-4.2-8b":{"id":"ibm-granite/granite-4.2-8b","name":"Granite 4.2 8B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"granite","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-25","last_updated":"2026-08-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.06,"output":0.25,"cache_read":0.015},"canonical_model_id":"ibm/granite-4.2-8b"},"thedrummer/skyfall-36b-v2":{"id":"thedrummer/skyfall-36b-v2","name":"Skyfall 36B V2","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2025-03-10","last_updated":"2025-03-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":29491},"cost":{"input":0.55,"output":0.8,"cache_read":0.25},"canonical_model_id":"thedrummer/skyfall-36b-v2"},"thedrummer/unslopnemo-12b":{"id":"thedrummer/unslopnemo-12b","name":"UnslopNemo 12B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-04-30","release_date":"2024-11-08","last_updated":"2024-11-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1024000,"output":819200},"cost":{"input":0.4,"output":0.4},"canonical_model_id":"thedrummer/unslopnemo-12b"},"thedrummer/cydonia-24b-v4.1":{"id":"thedrummer/cydonia-24b-v4.1","name":"Cydonia 24B V4.1","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-04-30","release_date":"2025-09-27","last_updated":"2025-09-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.3,"output":0.5,"cache_read":0.15},"canonical_model_id":"thedrummer/cydonia-24b-v4.1"},"anthropic/claude-opus-4.8":{"id":"anthropic/claude-opus-4.8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"anthropic/claude-fable-5":{"id":"anthropic/claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"anthropic/claude-opus-5":{"id":"anthropic/claude-opus-5","name":"Claude Opus 5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"anthropic/claude-haiku-5.5":{"id":"anthropic/claude-haiku-5.5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"anthropic/claude-sonnet-4.6":{"id":"anthropic/claude-sonnet-4.6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"anthropic/claude-opus-4.6":{"id":"anthropic/claude-opus-4.6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","max"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5}},"canonical_model_id":"anthropic/claude-opus-4-6"},"anthropic/claude-sonnet-5":{"id":"anthropic/claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"anthropic/claude-opus-5.5":{"id":"anthropic/claude-opus-5.5","name":"Claude Opus 5.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"anthropic/claude-haiku-4.5":{"id":"anthropic/claude-haiku-4.5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"anthropic/claude-opus-4.1":{"id":"anthropic/claude-opus-4.1","name":"Claude Opus 4.1 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1"},"anthropic/claude-sonnet-5.5":{"id":"anthropic/claude-sonnet-5.5","name":"Claude Sonnet 5.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"anthropic/claude-sonnet-4.5":{"id":"anthropic/claude-sonnet-4.5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"anthropic/claude-fable-5.1":{"id":"anthropic/claude-fable-5.1","name":"Claude Fable 5.1","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"anthropic/claude-opus-4.5":{"id":"anthropic/claude-opus-4.5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"anthropic/claude-opus-4.7":{"id":"anthropic/claude-opus-4.7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25,"tiers":[{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":10,"output":37.5,"cache_read":1,"cache_write":12.5}},"canonical_model_id":"anthropic/claude-opus-4-7"},"bytedance-seed/seed-1.6-flash":{"id":"bytedance-seed/seed-1.6-flash","name":"Seed 1.6 Flash","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-08-28","last_updated":"2025-08-28","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"status":"deprecated","cost":{"input":0.075,"output":0.3,"tiers":[{"input":0.1,"output":0.8,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-1-6-flash"},"bytedance-seed/seed-2-1-turbo":{"id":"bytedance-seed/seed-2-1-turbo","name":"Seed 2.1 Turbo","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-23","last_updated":"2026-06-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":235929},"cost":{"input":0.5,"output":2.5},"canonical_model_id":"bytedance-seed/seed-2.1-turbo"},"bytedance-seed/seed-1.6":{"id":"bytedance-seed/seed-1.6","name":"Seed 1.6","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"status":"deprecated","cost":{"input":0.25,"output":2,"tiers":[{"input":0.5,"output":4,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-1-6"},"bytedance-seed/seed-2.0-mini":{"id":"bytedance-seed/seed-2.0-mini","name":"Seed 2.0 Mini","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.1,"output":0.4,"tiers":[{"input":0.2,"output":0.8,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-mini"},"bytedance-seed/seed-2.0-code":{"id":"bytedance-seed/seed-2.0-code","name":"Seed 2.0 Code","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"status":"deprecated","cost":{"input":0.5,"output":3,"tiers":[{"input":1,"output":6,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-code"},"bytedance-seed/seed-2.0-lite":{"id":"bytedance-seed/seed-2.0-lite","name":"Seed 2.0 Lite","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"seed","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-14","last_updated":"2026-02-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.25,"output":2,"tiers":[{"input":0.5,"output":4,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"bytedance-seed/seed-2.0-lite"},"morph/morph-v3-large":{"id":"morph/morph-v3-large","name":"Morph V3 Large","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"morph","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-07-07","last_updated":"2025-07-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.9,"output":1.9},"canonical_model_id":"morph/morph-v3-large"},"morph/morph-v3-fast":{"id":"morph/morph-v3-fast","name":"Morph V3 Fast","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"morph","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-07-07","last_updated":"2025-07-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":0.8,"output":1.2},"canonical_model_id":"morph/morph-v3-fast"},"upstage/solar-pro-3":{"id":"upstage/solar-pro-3","name":"Solar Pro 3","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07","release_date":"2026-01-26","last_updated":"2026-03-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":117964},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"upstage/solar-pro3"},"upstage/solar-pro4":{"id":"upstage/solar-pro4","name":"Solar Pro 4","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"solar-pro","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02","release_date":"2026-08-06","last_updated":"2026-08-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":131072},"cost":{"input":0.15,"output":0.6,"cache_read":0.03},"canonical_model_id":"upstage/solar-pro4"},"upstage/solar-mini4":{"id":"upstage/solar-mini4","name":"Solar Mini 4","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"solar-mini","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":131072},"cost":{"input":0.05,"output":0.2,"cache_read":0.005},"canonical_model_id":"upstage/solar-mini4"},"poolside/laguna-s-2.1:free":{"id":"poolside/laguna-s-2.1:free","name":"Laguna S 2.1 (free)","description":"Free provider route for experiments, demos, and cost-sensitive chat workloads","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"poolside/laguna-s-2.1"},"poolside/laguna-xs-2.1":{"id":"poolside/laguna-xs-2.1","name":"Laguna XS 2.1","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-02","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"status":"deprecated","cost":{"input":0.06,"output":0.12,"cache_read":0.03},"canonical_model_id":"poolside/laguna-xs-2.1"},"poolside/laguna-xs-2.1:free":{"id":"poolside/laguna-xs-2.1:free","name":"Laguna XS 2.1 (free)","description":"Free provider route for experiments, demos, and cost-sensitive chat workloads","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-02","last_updated":"2026-07-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"poolside/laguna-xs-2.1"},"poolside/laguna-s-2.1":{"id":"poolside/laguna-s-2.1","name":"Laguna S 2.1","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0.09,"output":0.18,"cache_read":0.009},"canonical_model_id":"poolside/laguna-s-2.1"},"x-ai/grok-build-0.1":{"id":"x-ai/grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":230400},"cost":{"input":1,"output":2,"cache_read":0.2,"tiers":[{"input":2,"output":4,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2,"output":4,"cache_read":0.4}},"canonical_model_id":"xai/grok-build-0.1"},"x-ai/grok-4.3":{"id":"x-ai/grok-4.3","name":"Grok 4.3","description":"xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":900000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}},"canonical_model_id":"xai/grok-4.3"},"x-ai/grok-4.7":{"id":"x-ai/grok-4.7","name":"Grok 4.7","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"x-ai/grok-4.20":{"id":"x-ai/grok-4.20","name":"Grok 4.20","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09-01","release_date":"2026-03-31","last_updated":"2026-03-31","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":1800000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"x-ai/grok-4.6":{"id":"x-ai/grok-4.6","name":"Grok 4.6","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"x-ai/grok-4.20-multi-agent":{"id":"x-ai/grok-4.20-multi-agent","name":"Grok 4.20 Multi-Agent","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-09-01","release_date":"2026-03-31","last_updated":"2026-03-31","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":1800000},"cost":{"input":1.25,"output":2.5,"cache_read":0.2,"tiers":[{"input":2.5,"output":5,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":5,"cache_read":0.4}}},"x-ai/grok-4.5":{"id":"x-ai/grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.3,"tiers":[{"input":4,"output":12,"cache_read":0.6,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":0.6}},"canonical_model_id":"xai/grok-4.5"},"~anthropic/claude-haiku-latest":{"id":"~anthropic/claude-haiku-latest","name":"Claude Haiku Latest","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]}},"~anthropic/claude-sonnet-latest":{"id":"~anthropic/claude-sonnet-latest","name":"Claude Sonnet Latest","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5}},"~anthropic/claude-fable-latest":{"id":"~anthropic/claude-fable-latest","name":"Claude Fable Latest","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5}},"~anthropic/claude-opus-latest":{"id":"~anthropic/claude-opus-latest","name":"Claude Opus Latest","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5}},"mancer/weaver":{"id":"mancer/weaver","name":"Weaver (alpha)","description":"General-purpose chat model for instruction following, writing, and analysis","family":"alpha","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-06-30","release_date":"2023-08-02","last_updated":"2023-08-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8000,"output":6000},"cost":{"input":0.4,"output":0.75},"canonical_model_id":"mancer/weaver"},"openai/gpt-6-sol":{"id":"openai/gpt-6-sol","name":"GPT-6 Sol","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"openai/gpt-6-luna":{"id":"openai/gpt-6-luna","name":"GPT-6 Luna","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-6.1-sol":{"id":"openai/gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"openai/gpt-5.3-codex":{"id":"openai/gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"openai/gpt-4":{"id":"openai/gpt-4","name":"GPT-4","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-11","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":8191,"output":4096},"cost":{"input":30,"output":60},"canonical_model_id":"openai/gpt-4"},"openai/gpt-5-pro":{"id":"openai/gpt-5-pro","name":"GPT-5 Pro","description":"Higher-accuracy GPT-5 tier for tough analysis, coding reviews, and planning","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":15,"output":120},"canonical_model_id":"openai/gpt-5-pro"},"openai/gpt-5.4-pro":{"id":"openai/gpt-5.4-pro","name":"GPT-5.4 Pro","description":"More exact GPT-5.4 tier for demanding professional reasoning and agent tasks","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.4-pro"},"openai/o1":{"id":"openai/o1","name":"o1","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":15,"output":60,"cache_read":7.5},"canonical_model_id":"openai/o1"},"openai/gpt-4o-2024-05-13":{"id":"openai/gpt-4o-2024-05-13","name":"GPT-4o (2024-05-13)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-05-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":5,"output":15},"canonical_model_id":"openai/gpt-4o-2024-05-13"},"openai/gpt-4.1":{"id":"openai/gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/gpt-4.1"},"openai/gpt-6-astra-pro":{"id":"openai/gpt-6-astra-pro","name":"GPT-6 Astra Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}}},"openai/gpt-4o":{"id":"openai/gpt-4o","name":"GPT-4o","description":"Omni-era GPT for multimodal chat, practical coding, and general assistants","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-05-13","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o"},"openai/gpt-5.1":{"id":"openai/gpt-5.1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"openai/gpt-3.5-turbo-16k":{"id":"openai/gpt-3.5-turbo-16k","name":"GPT-3.5 Turbo 16k","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2021-09-30","release_date":"2023-08-28","last_updated":"2023-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"output":4096},"cost":{"input":3,"output":4}},"openai/gpt-5.4-image-2":{"id":"openai/gpt-5.4-image-2","type":"image","name":"GPT-5.4 Image 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":false,"structured_output":true,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["image","text","pdf"],"output":["image","text"]},"open_weights":false,"limit":{"context":272000,"output":128000},"cost":{"input":8,"output":15,"cache_read":2},"canonical_model_id":"openai/gpt-5.4-image-2"},"openai/gpt-chat-latest":{"id":"openai/gpt-chat-latest","name":"GPT Chat Latest","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-05-05","last_updated":"2026-05-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5}},"openai/gpt-5.6-luna":{"id":"openai/gpt-5.6-luna","name":"GPT-5.6 Luna","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-5.2-pro":{"id":"openai/gpt-5.2-pro","name":"GPT-5.2 Pro","description":"Higher-accuracy GPT-5.2 variant for tougher reasoning and review workflows","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":21,"output":168},"canonical_model_id":"openai/gpt-5.2-pro"},"openai/gpt-3.5-turbo-0613":{"id":"openai/gpt-3.5-turbo-0613","name":"GPT-3.5 Turbo (older v0613)","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2021-09-30","release_date":"2024-01-25","last_updated":"2024-01-25","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":4095,"output":3685},"cost":{"input":1,"output":2}},"openai/gpt-5.4":{"id":"openai/gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"openai/gpt-5.4-mini":{"id":"openai/gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"openai/gpt-6-luna-pro":{"id":"openai/gpt-6-luna-pro","name":"GPT-6 Luna Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}}},"openai/o1-pro":{"id":"openai/o1-pro","name":"o1-pro","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":true,"temperature":false,"knowledge":"2023-09","release_date":"2025-03-19","last_updated":"2025-03-19","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":150,"output":600},"canonical_model_id":"openai/o1-pro"},"openai/o3-mini-high":{"id":"openai/o3-mini-high","name":"o3 Mini High","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2023-10-31","release_date":"2025-02-12","last_updated":"2025-02-12","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55}},"openai/gpt-4o-2024-08-06":{"id":"openai/gpt-4o-2024-08-06","name":"GPT-4o (2024-08-06)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-08-06","last_updated":"2024-08-06","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-08-06"},"openai/gpt-5.1-codex-max":{"id":"openai/gpt-5.1-codex-max","name":"GPT-5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex-max"},"openai/gpt-oss-safeguard-20b":{"id":"openai/gpt-oss-safeguard-20b","name":"GPT OSS Safeguard 20B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.075,"output":0.3,"cache_read":0.0375},"canonical_model_id":"openai/gpt-oss-safeguard-20b"},"openai/gpt-audio":{"id":"openai/gpt-audio","type":"chat","name":"GPT-Audio","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-01","release_date":"2025-08-28","last_updated":"2025-08-28","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10},"canonical_model_id":"openai/gpt-audio"},"openai/gpt-5-image-mini":{"id":"openai/gpt-5-image-mini","type":"image","name":"GPT-5 Image Mini","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-10-16","last_updated":"2025-10-16","modalities":{"input":["pdf","image","text"],"output":["image","text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":2.5,"output":2,"cache_read":0.25},"canonical_model_id":"openai/gpt-5-image-mini"},"openai/gpt-5.6-sol":{"id":"openai/gpt-5.6-sol","name":"GPT-5.6 Sol","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-3.5-turbo-instruct":{"id":"openai/gpt-3.5-turbo-instruct","name":"GPT-3.5 Turbo Instruct","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2021-09-30","release_date":"2023-09-28","last_updated":"2023-09-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":4095,"output":3685},"cost":{"input":1.5,"output":2}},"openai/gpt-4.1-mini":{"id":"openai/gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.4,"output":1.6,"cache_read":0.1},"canonical_model_id":"openai/gpt-4.1-mini"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.018,"output":0.09,"cache_read":0.009},"canonical_model_id":"openai/gpt-oss-20b"},"openai/gpt-5.2-codex":{"id":"openai/gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Code-specialist GPT for repository edits, reviews, and long-running software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-codex"},"openai/gpt-4o-2024-11-20":{"id":"openai/gpt-4o-2024-11-20","name":"GPT-4o (2024-11-20)","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-11-20","last_updated":"2024-11-20","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":2.5,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-4o-2024-11-20"},"openai/gpt-5-image":{"id":"openai/gpt-5-image","type":"image","name":"GPT-5 Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-10-01","release_date":"2025-10-14","last_updated":"2025-10-14","modalities":{"input":["image","text","pdf"],"output":["image","text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":10,"output":10,"cache_read":1.25},"canonical_model_id":"openai/gpt-5-image"},"openai/gpt-5.5-pro":{"id":"openai/gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Highest-accuracy GPT-5.5 tier for slower, precision-heavy reasoning and coding","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":30,"output":180,"tiers":[{"input":60,"output":270,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":60,"output":270}},"canonical_model_id":"openai/gpt-5.5-pro"},"openai/gpt-5-mini":{"id":"openai/gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"openai/gpt-4.1-nano":{"id":"openai/gpt-4.1-nano","name":"GPT-4.1 nano","description":"Tiny GPT-4.1 option for classification, routing, and very high-volume tasks","family":"gpt-nano","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"cost":{"input":0.1,"output":0.4,"cache_read":0.025},"canonical_model_id":"openai/gpt-4.1-nano"},"openai/gpt-5.1-codex":{"id":"openai/gpt-5.1-codex","name":"GPT-5.1 Codex","description":"Codex GPT for repository edits, code review, and practical software agents","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.13},"canonical_model_id":"openai/gpt-5.1-codex"},"openai/gpt-5.4-nano":{"id":"openai/gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"openai/gpt-4-turbo":{"id":"openai/gpt-4-turbo","name":"GPT-4 Turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2023-11-06","last_updated":"2024-04-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":10,"output":30},"canonical_model_id":"openai/gpt-4-turbo"},"openai/o3-pro":{"id":"openai/o3-pro","name":"o3-pro","description":"High-effort o3 tier for difficult technical reasoning and careful answers","family":"o-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-06-10","last_updated":"2025-06-10","modalities":{"input":["text","pdf","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":20,"output":80},"canonical_model_id":"openai/o3-pro"},"openai/o3":{"id":"openai/o3","name":"o3","description":"Deliberate o-series reasoner for hard math, coding, and multi-step analysis","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":2,"output":8,"cache_read":0.5},"canonical_model_id":"openai/o3"},"openai/gpt-5.6-terra":{"id":"openai/gpt-5.6-terra","name":"GPT-5.6 Terra","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/gpt-6.1-sol-pro":{"id":"openai/gpt-6.1-sol-pro","name":"GPT-6.1 Sol Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}}},"openai/gpt-5.5":{"id":"openai/gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"openai/gpt-5":{"id":"openai/gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"openai/gpt-audio-mini":{"id":"openai/gpt-audio-mini","type":"chat","name":"GPT-Audio Mini","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-01","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","audio"],"output":["text","audio"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.6,"output":2.4},"canonical_model_id":"openai/gpt-audio-mini"},"openai/gpt-5.2-chat":{"id":"openai/gpt-5.2-chat","name":"GPT-5.2 Chat","description":"Chat-tuned GPT model for conversational assistance, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":32000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-chat-latest"},"openai/gpt-5-nano":{"id":"openai/gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"openai/gpt-3.5-turbo":{"id":"openai/gpt-3.5-turbo","name":"GPT-3.5-turbo","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2021-09-01","release_date":"2023-03-01","last_updated":"2023-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":16385,"output":4096},"cost":{"input":0.5,"output":1.5},"canonical_model_id":"openai/gpt-3.5-turbo"},"openai/o3-mini":{"id":"openai/o3-mini","name":"o3-mini","description":"Smaller o-series reasoner for economical coding, math, and planning tasks","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2024-12-20","last_updated":"2025-01-29","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.55},"canonical_model_id":"openai/o3-mini"},"openai/gpt-5.6-luna-pro":{"id":"openai/gpt-5.6-luna-pro","name":"GPT-5.6 Luna Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"openai/gpt-6-sol-pro":{"id":"openai/gpt-6-sol-pro","name":"GPT-6 Sol Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}}},"openai/gpt-5.1-codex-mini":{"id":"openai/gpt-5.1-codex-mini","name":"GPT-5.1 Codex mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.25,"output":2,"cache_read":0.03},"canonical_model_id":"openai/gpt-5.1-codex-mini"},"openai/gpt-4o-mini":{"id":"openai/gpt-4o-mini","name":"GPT-4o mini","description":"Small omni GPT for cheap multimodal assistance and production-scale traffic","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"openai/gpt-5.6-terra-pro":{"id":"openai/gpt-5.6-terra-pro","name":"GPT-5.6 Terra Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"openai/o4-mini":{"id":"openai/o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.275},"canonical_model_id":"openai/o4-mini"},"openai/gpt-4o-mini-2024-07-18":{"id":"openai/gpt-4o-mini-2024-07-18","name":"GPT-4o-mini (2024-07-18)","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-09","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":16384},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-4o-mini"},"openai/gpt-5.2":{"id":"openai/gpt-5.2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"openai/gpt-5.6-sol-pro":{"id":"openai/gpt-5.6-sol-pro","name":"GPT-5.6 Sol Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"openai/gpt-6-astra":{"id":"openai/gpt-6-astra","name":"GPT-6 Astra","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"openai/o4-mini-high":{"id":"openai/o4-mini-high","name":"o4 Mini High","description":"O-series reasoning model for hard analysis, math, coding, and planning","family":"o","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-06-30","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["image","text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"cost":{"input":1.1,"output":4.4,"cache_read":0.275}},"~deepseek/deepseek-pro-latest":{"id":"~deepseek/deepseek-pro-latest","name":"DeepSeek Pro Latest","description":"Flagship DeepSeek model for coding, reasoning, and agentic work","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-14","last_updated":"2026-09-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":393216},"cost":{"input":0.2235,"output":8,"cache_read":0.22}},"~deepseek/deepseek-v4-flash-latest":{"id":"~deepseek/deepseek-v4-flash-latest","name":"DeepSeek V4 Flash Latest","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-01","last_updated":"2026-08-01","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.0475,"output":0.1568,"cache_read":0.028}},"~deepseek/deepseek-flash-latest":{"id":"~deepseek/deepseek-flash-latest","name":"DeepSeek Flash Latest","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-14","last_updated":"2026-09-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.07,"output":0.5,"cache_read":0.008}},"xingchen-agi/xing4.0-29b-a4b:free":{"id":"xingchen-agi/xing4.0-29b-a4b:free","name":"Xing4.0 29B A4B (free)","description":"Free provider route for experiments, demos, and cost-sensitive chat workloads","family":"agi","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-16","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0,"output":0}},"inception/mercury-2":{"id":"inception/mercury-2","name":"Mercury 2","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-24","last_updated":"2026-02-24","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":50000},"cost":{"input":0.25,"output":0.75,"cache_read":0.025},"canonical_model_id":"inception/mercury-2"},"inception/mercury-3":{"id":"inception/mercury-3","name":"Mercury 3","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-16","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.1,"output":0.35,"cache_read":0.01}},"inception/mercury-2.5":{"id":"inception/mercury-2.5","name":"Mercury 2.5","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"mercury","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":260000,"output":65536},"cost":{"input":0.04,"output":0.15,"cache_read":0.004},"canonical_model_id":"inception/mercury-2.5"},"bytedance/ui-tars-1.5-7b":{"id":"bytedance/ui-tars-1.5-7b","name":"UI-TARS 7B ","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01-31","release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["image","text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":2048},"cost":{"input":0.1,"output":0.2,"cache_read":0.1}},"perplexity/sonar-reasoning-pro":{"id":"perplexity/sonar-reasoning-pro","name":"Sonar Reasoning Pro","description":"Web-grounded reasoning model for multi-step research and cited answers","family":"sonar-reasoning","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-03-07","last_updated":"2025-03-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":115200},"cost":{"input":2,"output":8}},"perplexity/sonar-deep-research":{"id":"perplexity/sonar-deep-research","name":"Sonar Deep Research","description":"Sonar search model for current answers, retrieval, and citation-backed chat","family":"sonar-deep-research","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-03-07","last_updated":"2025-03-07","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":115200},"cost":{"input":2,"output":8,"reasoning":3}},"perplexity/sonar":{"id":"perplexity/sonar","name":"Sonar","description":"Sonar search model for current answers, retrieval, and citation-backed chat","family":"sonar","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-01-27","last_updated":"2025-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":127072,"output":114364},"cost":{"input":1,"output":1}},"perplexity/sonar-pro-search":{"id":"perplexity/sonar-pro-search","name":"Sonar Pro Search","description":"Advanced Sonar search model for deeper research and cited synthesis","family":"sonar-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2025-10-30","last_updated":"2025-10-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8000},"cost":{"input":3,"output":15}},"perplexity/sonar-pro":{"id":"perplexity/sonar-pro","name":"Sonar Pro","description":"Advanced Sonar search model for deeper research and cited synthesis","family":"sonar-pro","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-03-07","last_updated":"2025-03-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8000},"cost":{"input":3,"output":15}},"relace/relace-apply-3":{"id":"relace/relace-apply-3","name":"Relace Apply 3","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2025-09-26","last_updated":"2025-09-26","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":0.85,"output":1.25},"canonical_model_id":"relace/relace-apply-3"},"relace/relace-search":{"id":"relace/relace-search","name":"Relace Search","description":"Tool-capable chat model for instruction following and agentic application workflows","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":128000},"cost":{"input":1,"output":3},"canonical_model_id":"relace/relace-search"},"inclusionai/ling-3.1-flash":{"id":"inclusionai/ling-3.1-flash","name":"Ling 3.1 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.075,"output":0.225,"cache_read":0.015},"canonical_model_id":"inclusionai/ling-3.1-flash"},"inclusionai/ling-3.0-flash-vl":{"id":"inclusionai/ling-3.0-flash-vl","name":"Ling 3.0 Flash VL","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"ling","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.06,"output":0.18,"cache_read":0.012},"canonical_model_id":"inclusionai/ling-3.0-flash-vl"},"inclusionai/ling-3.0-flash":{"id":"inclusionai/ling-3.0-flash","name":"Ling 3.0 Flash","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-23","last_updated":"2026-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.021,"output":0.063,"cache_read":0.0042},"canonical_model_id":"inclusionai/ling-3.0-flash"},"~openai/gpt-mini-latest":{"id":"~openai/gpt-mini-latest","name":"GPT Mini Latest","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"output":128000},"cost":{"input":0.75,"output":4.5,"cache_read":0.075}},"~openai/gpt-terra-latest":{"id":"~openai/gpt-terra-latest","name":"GPT Terra Latest","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}}},"~openai/gpt-luna-latest":{"id":"~openai/gpt-luna-latest","name":"GPT Luna Latest","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}}},"~openai/gpt-astra-latest":{"id":"~openai/gpt-astra-latest","name":"GPT Astra Latest","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}}},"~openai/gpt-sol-latest":{"id":"~openai/gpt-sol-latest","name":"GPT Sol Latest","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["pdf","image","text"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}}},"openrouter/free":{"id":"openrouter/free","name":"Free Models Router","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-01","last_updated":"2026-02-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":200000,"output":8000},"cost":{"input":0,"output":0}},"openrouter/bodybuilder":{"id":"openrouter/bodybuilder","name":"Body Builder (beta)","description":"Preview model for early access evaluation, prototyping, and compatibility testing","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2025-12-05","last_updated":"2025-12-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":128000}},"openrouter/pareto-code":{"id":"openrouter/pareto-code","name":"Pareto Code Router","description":"Coding model for repository understanding, refactors, and agentic engineering tasks","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":2000000,"output":200000}},"openrouter/fusion":{"id":"openrouter/fusion","name":"Fusion","description":"General-purpose chat model for instruction following, writing, and analysis","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000}},"openrouter/auto":{"id":"openrouter/auto","name":"Auto Router","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"auto","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2023-11-08","last_updated":"2023-11-08","modalities":{"input":["text","image","audio","pdf","video"],"output":["text","image"]},"open_weights":false,"limit":{"context":2000000,"output":2000000}},"anthracite-org/magnum-v4-72b":{"id":"anthracite-org/magnum-v4-72b","name":"Magnum v4 72B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":4096},"cost":{"input":2.5,"output":5},"canonical_model_id":"anthracite-org/magnum-v4-72b"},"prism-ml/ternary-bonsai-2-27b":{"id":"prism-ml/ternary-bonsai-2-27b","name":"Ternary Bonsai 2 27B","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-18","last_updated":"2026-09-18","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.075,"output":0.5,"cache_read":0.0375}},"writer/palmyra-x5":{"id":"writer/palmyra-x5","name":"Palmyra X5","description":"General-purpose chat model for instruction following, writing, and analysis","family":"palmyra","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1040000,"output":8192},"cost":{"input":0.6,"output":6},"canonical_model_id":"writer/palmyra-x5"},"~z-ai/glm-latest":{"id":"~z-ai/glm-latest","name":"GLM Latest","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-19","last_updated":"2026-08-19","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.079,"output":1.4,"cache_read":0.078}},"~z-ai/glm-flash-latest":{"id":"~z-ai/glm-flash-latest","name":"GLM Flash Latest","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-27","last_updated":"2026-08-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.018,"output":0.121,"cache_read":0.018}},"mistralai/mistral-large-2512":{"id":"mistralai/mistral-large-2512","name":"Mistral Large 3","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.5,"output":1.5,"cache_read":0.05},"canonical_model_id":"mistral/mistral-large-2512"},"mistralai/ministral-8b-2512":{"id":"mistralai/ministral-8b-2512","name":"Ministral 3 8B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.15,"output":0.15,"cache_read":0.015},"canonical_model_id":"mistral/ministral-8b-2512"},"mistralai/mistral-nemo":{"id":"mistralai/mistral-nemo","name":"Mistral Nemo","description":"Efficient Mistral-NVIDIA open model for multilingual chat and local deployment","family":"mistral-nemo","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2024-07-18","last_updated":"2024-07-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.029,"output":0.03},"canonical_model_id":"mistral/mistral-nemo"},"mistralai/ministral-14b-2512":{"id":"mistralai/ministral-14b-2512","name":"Ministral 3 14B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.2,"output":0.2,"cache_read":0.02},"canonical_model_id":"mistral/ministral-14b-2512"},"mistralai/ministral-3b-2512":{"id":"mistralai/ministral-3b-2512","name":"Ministral 3 3B 2512","description":"Compact Mistral model for edge, latency-sensitive, and cost-efficient workloads","family":"ministral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":104857},"cost":{"input":0.1,"output":0.1,"cache_read":0.01},"canonical_model_id":"mistral/ministral-3b-2512"},"mistralai/voxtral-small-24b-2507":{"id":"mistralai/voxtral-small-24b-2507","name":"Voxtral Small 24B 2507","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"voxtral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-15","last_updated":"2025-07-15","modalities":{"input":["text","audio","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":26214},"cost":{"input":0.1,"output":0.3,"cache_read":0.01},"canonical_model_id":"mistral/voxtral-small-24b-2507"},"mistralai/mistral-medium-3-5":{"id":"mistralai/mistral-medium-3-5","name":"Mistral Medium 3.5","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-30","last_updated":"2026-04-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":209715},"cost":{"input":1.5,"output":7.5},"canonical_model_id":"mistral/mistral-medium-3-5"},"mistralai/mistral-small-3.1-24b-instruct":{"id":"mistralai/mistral-small-3.1-24b-instruct","name":"Mistral Small 3.1 24B","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-03-17","last_updated":"2025-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":102400},"cost":{"input":0.351,"output":0.555},"canonical_model_id":"mistral/mistral-small-3.1-24b-instruct"},"mistralai/mistral-small-2603":{"id":"mistralai/mistral-small-2603","name":"Mistral Small 4","description":"Fast Mistral production model for chat, extraction, and cost-sensitive agents","family":"mistral-small","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.15,"output":0.6,"cache_read":0.015},"canonical_model_id":"mistral/mistral-small-2603"},"mistralai/mistral-medium-3":{"id":"mistralai/mistral-medium-3","name":"Mistral Medium 3","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-07","last_updated":"2025-05-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":104857},"cost":{"input":0.4,"output":2,"cache_read":0.04},"canonical_model_id":"mistral/mistral-medium-3"},"mistralai/mistral-small-3.2-24b-instruct":{"id":"mistralai/mistral-small-3.2-24b-instruct","name":"Mistral Small 3.2 24B","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-06-20","last_updated":"2025-06-20","modalities":{"input":["image","text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":16384},"cost":{"input":0.09375,"output":0.25},"canonical_model_id":"mistral/mistral-small-3.2-24b-instruct"},"mistralai/mistral-saba":{"id":"mistralai/mistral-saba","name":"Saba","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-02-17","last_updated":"2025-02-17","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":26214},"cost":{"input":0.2,"output":0.6,"cache_read":0.02},"canonical_model_id":"mistral/mistral-saba"},"mistralai/mistral-large-2407":{"id":"mistralai/mistral-large-2407","name":"Mistral Large 2407","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-03-31","release_date":"2024-07-24","last_updated":"2024-07-24","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":104857},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"mistral/mistral-large-2407"},"mistralai/mistral-large-4-0":{"id":"mistralai/mistral-large-4-0","name":"Mistral Large 4","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":262144},"cost":{"input":1.36,"output":4.18,"cache_read":0.14},"canonical_model_id":"mistral/mistral-large-4"},"mistralai/codestral-2508":{"id":"mistralai/codestral-2508","name":"Codestral 25.08","description":"Mistral coding model for code completion, generation, and developer workflows","family":"codestral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":204800},"cost":{"input":0.3,"output":0.9,"cache_read":0.03},"canonical_model_id":"mistral/codestral-2508"},"mistralai/mistral-small-24b-instruct-2501":{"id":"mistralai/mistral-small-24b-instruct-2501","name":"Mistral Small 3","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-10-31","release_date":"2025-01-30","last_updated":"2025-01-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"cost":{"input":0.05,"output":0.08},"canonical_model_id":"mistral/mistral-small-24b-instruct-2501"},"mistralai/devstral-2512":{"id":"mistralai/devstral-2512","name":"Devstral 2","description":"Mistral coding agent model for repository tasks and software engineering workflows","family":"devstral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-12","release_date":"2025-12-09","last_updated":"2025-12-09","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":209715},"cost":{"input":0.4,"output":2,"cache_read":0.04},"canonical_model_id":"mistral/devstral-2512"},"mistralai/mixtral-8x22b-instruct":{"id":"mistralai/mixtral-8x22b-instruct","name":"Mixtral 8x22B Instruct","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-01-31","release_date":"2024-04-17","last_updated":"2024-04-17","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":52428},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"mistral/mixtral-8x22b-instruct"},"mistralai/mistral-large":{"id":"mistralai/mistral-large","name":"Mistral Large","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-11-30","release_date":"2024-02-26","last_updated":"2024-02-26","modalities":{"input":["text","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":102400},"cost":{"input":2,"output":6,"cache_read":0.2},"canonical_model_id":"mistral/mistral-large"},"mistralai/mistral-medium-3.1":{"id":"mistralai/mistral-medium-3.1","name":"Mistral Medium 3.1","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral-medium","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06-30","release_date":"2025-08-12","last_updated":"2025-08-12","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":104857},"cost":{"input":0.4,"output":2,"cache_read":0.04},"canonical_model_id":"mistral/mistral-medium-3.1"},"perceptron/perceptron-mk1.5":{"id":"perceptron/perceptron-mk1.5","name":"Perceptron Mk1.5","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-25","last_updated":"2026-09-25","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":36864,"output":8192},"cost":{"input":0.15,"output":1.5}},"perceptron/perceptron-mk1":{"id":"perceptron/perceptron-mk1","name":"Perceptron Mk1","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-05-12","last_updated":"2026-05-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":32768,"output":8192},"cost":{"input":0.15,"output":1.5},"canonical_model_id":"perceptron/perceptron-mk1"},"amazon/nova-micro-v1":{"id":"amazon/nova-micro-v1","name":"Nova Micro 1.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-micro","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":5120},"cost":{"input":0.035,"output":0.14},"canonical_model_id":"amazon/nova-micro-v1"},"amazon/nova-2-lite-v1":{"id":"amazon/nova-2-lite-v1","name":"Nova 2 Lite","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"nova","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-10","release_date":"2025-12-02","last_updated":"2025-12-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65535},"cost":{"input":0.3,"output":2.5},"canonical_model_id":"amazon/nova-2-lite-v1"},"amazon/nova-pro-v1":{"id":"amazon/nova-pro-v1","name":"Nova Pro 1.0","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova-pro","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":5120},"cost":{"input":0.8,"output":3.2},"canonical_model_id":"amazon/nova-pro-v1"},"amazon/nova-lite-v1":{"id":"amazon/nova-lite-v1","name":"Nova Lite 1.0","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"nova-lite","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10-31","release_date":"2024-12-05","last_updated":"2024-12-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":300000,"output":5120},"cost":{"input":0.06,"output":0.24},"canonical_model_id":"amazon/nova-lite-v1"},"amazon/nova-premier-v1":{"id":"amazon/nova-premier-v1","name":"Nova Premier 1.0","description":"Flagship model for demanding analysis, coding, and production agent workflows","family":"nova","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-10","release_date":"2025-04-30","last_updated":"2025-04-30","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32000},"status":"deprecated","cost":{"input":2.5,"output":12.5,"cache_read":0.625},"canonical_model_id":"amazon/nova-premier"},"dots-studio/dots-3-note-preview:free":{"id":"dots-studio/dots-3-note-preview:free","name":"Dots3-Note Preview (free)","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":512000,"output":460800},"status":"deprecated","cost":{"input":0,"output":0}},"qwen/qwen3-vl-8b-instruct":{"id":"qwen/qwen3-vl-8b-instruct","name":"Qwen3 VL 8B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-14","last_updated":"2025-10-14","modalities":{"input":["image","text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.25,"output":0.75,"cache_read":0.12}},"qwen/qwen3-vl-30b-a3b-instruct":{"id":"qwen/qwen3-vl-30b-a3b-instruct","name":"Qwen3 VL 30B A3B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-04","last_updated":"2025-10-04","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"alibaba/qwen3-vl-30b-a3b-instruct"},"qwen/qwen3-vl-30b-a3b-thinking":{"id":"qwen/qwen3-vl-30b-a3b-thinking","name":"Qwen3 VL 30B A3B Thinking","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-10-06","last_updated":"2025-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.29,"output":1}},"qwen/qwen3-30b-a3b-instruct-2507":{"id":"qwen/qwen3-30b-a3b-instruct-2507","name":"Qwen3 30B-A3B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.09,"output":0.3},"canonical_model_id":"alibaba/qwen3-30b-a3b-instruct-2507"},"qwen/qwen3.8-flash":{"id":"qwen/qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-flash"},"qwen/qwen3.6-flash":{"id":"qwen/qwen3.6-flash","name":"Qwen3.6 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.6","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.1875,"output":1.125,"cache_write":0.234375,"tiers":[{"input":0.75,"output":3,"cache_write":0.9375,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.75,"output":3,"cache_write":0.9375}},"canonical_model_id":"alibaba/qwen3.6-flash"},"qwen/qwen-2.5-coder-32b-instruct":{"id":"qwen/qwen-2.5-coder-32b-instruct","name":"Qwen2.5-Coder-32B-Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2024-11-12","last_updated":"2024-11-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":29491},"cost":{"input":0.66,"output":1},"canonical_model_id":"alibaba/qwen2.5-coder-32b-instruct"},"qwen/qwen-2.5-72b-instruct":{"id":"qwen/qwen-2.5-72b-instruct","name":"Qwen2.5 72B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2024-09-19","last_updated":"2024-09-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":16384},"cost":{"input":0.36,"output":0.4}},"qwen/qwen3.5-35b-a3b":{"id":"qwen/qwen3.5-35b-a3b","name":"Qwen3.5 35B-A3B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":81920},"cost":{"input":0.14,"output":1,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.5-35b-a3b"},"qwen/qwen3-coder-30b-a3b-instruct":{"id":"qwen/qwen3-coder-30b-a3b-instruct","name":"Qwen3-Coder 30B-A3B Instruct","description":"Smaller Qwen coder for efficient local agents and repo-level fixes","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-31","last_updated":"2025-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.07,"output":0.28},"canonical_model_id":"alibaba/qwen3-coder-30b-a3b-instruct"},"qwen/qwen3.5-9b":{"id":"qwen/qwen3.5-9b","name":"Qwen3.5 9B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","cost":{"input":0.08,"output":0.13,"cache_read":0.04},"canonical_model_id":"alibaba/qwen3.5-9b"},"qwen/qwen3-14b":{"id":"qwen/qwen3-14b","name":"Qwen3 14B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":16384},"cost":{"input":0.12,"output":0.24}},"qwen/qwen2.5-vl-72b-instruct":{"id":"qwen/qwen2.5-vl-72b-instruct","name":"Qwen2.5-VL 72B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-01-26","last_updated":"2025-01-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":115200},"cost":{"input":0.8,"output":1,"cache_read":0.4},"canonical_model_id":"alibaba/qwen2-5-vl-72b-instruct"},"qwen/qwen3.8-2.4t-a95b":{"id":"qwen/qwen3.8-2.4t-a95b","name":"Qwen3.8 2.4T A95B","description":"Open-weight sparse MoE (2.4T total, 95B active), the open-weight twin of Qwen3.8 Max for coding, research, complex reasoning, and agentic workflows","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":909000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-2.4t-a95b"},"qwen/qwen3.6-27b":{"id":"qwen/qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"alibaba/qwen3.6-27b"},"qwen/qwen-2.5-7b-instruct":{"id":"qwen/qwen-2.5-7b-instruct","name":"Qwen2.5 7B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2024-10-16","last_updated":"2024-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":29491},"cost":{"input":0.1,"output":0.2}},"qwen/qwen3-235b-a22b-thinking-2507":{"id":"qwen/qwen3-235b-a22b-thinking-2507","name":"Qwen3 235B-A22B Thinking 2507","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-07-25","last_updated":"2025-07-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.45,"output":3.5},"canonical_model_id":"alibaba/qwen3-235b-a22b-thinking-2507"},"qwen/qwen3.8-omni-flash":{"id":"qwen/qwen3.8-omni-flash","name":"Qwen3.8 Omni Flash","description":"Qwen omni model for text, vision, audio, and multimodal agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-17","last_updated":"2026-09-17","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.15,"output":0.47,"cache_read":0.016},"canonical_model_id":"alibaba/qwen3.8-omni-flash"},"qwen/qwen3.5-flash-02-23":{"id":"qwen/qwen3.5-flash-02-23","name":"Qwen3.5-Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-25","last_updated":"2026-02-25","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.065,"output":0.26}},"qwen/qwen3.8-max-0902":{"id":"qwen/qwen3.8-max-0902","name":"Qwen3.8 Max 0902","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"alibaba/qwen3.8-max-0902"},"qwen/qwen3.5-plus-20260420":{"id":"qwen/qwen3.5-plus-20260420","name":"Qwen3.5 Plus 2026-04-20","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.5","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.3,"output":1.8,"cache_write":0.375,"tiers":[{"input":0.375,"output":2.25,"cache_write":0.46875,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.375,"output":2.25,"cache_write":0.46875}}},"qwen/qwen3-coder-flash":{"id":"qwen/qwen3-coder-flash","name":"Qwen3 Coder Flash","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.195,"output":0.975,"cache_read":0.039,"cache_write":0.24375,"tiers":[{"input":0.325,"output":1.625,"cache_read":0.065,"cache_write":0.40625,"tier":{"type":"context","size":32000}},{"input":0.52,"output":2.6,"cache_read":0.104,"cache_write":0.65,"tier":{"type":"context","size":128000}}]},"canonical_model_id":"alibaba/qwen3-coder-flash"},"qwen/qwen3.7-plus":{"id":"qwen/qwen3.7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":0.32,"output":1.28,"cache_read":0.064,"cache_write":0.4,"tiers":[{"input":0.96,"output":3.84,"cache_read":0.192,"cache_write":1.2,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.96,"output":3.84,"cache_read":0.192,"cache_write":1.2}},"canonical_model_id":"alibaba/qwen3.7-plus"},"qwen/qwen3.8-max-prime":{"id":"qwen/qwen3.8-max-prime","name":"Qwen 3.8 Max Prime","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen3.8-max","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":4,"output":12,"cache_read":0.5},"canonical_model_id":"alibaba/qwen3.8-max-prime"},"qwen/qwen3.5-397b-a17b":{"id":"qwen/qwen3.5-397b-a17b","name":"Qwen3.5 397B-A17B","description":"Large open Qwen multimodal MoE for visual agents and long technical tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-15","last_updated":"2026-02-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.5,"output":3.6,"cache_read":0.3},"canonical_model_id":"alibaba/qwen3.5-397b-a17b"},"qwen/qwen3-next-80b-a3b-instruct":{"id":"qwen/qwen3-next-80b-a3b-instruct","name":"Qwen3-Next 80B-A3B Instruct","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.09,"output":1.1},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-instruct"},"qwen/qwen3-30b-a3b":{"id":"qwen/qwen3-30b-a3b","name":"Qwen3 30B A3B","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":16384},"cost":{"input":0.12,"output":0.5},"canonical_model_id":"alibaba/qwen3-30b-a3b"},"qwen/qwen3-32b":{"id":"qwen/qwen3-32b","name":"Qwen3 32B","description":"Dense open Qwen model for self-hosted chat, reasoning, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-04-28","last_updated":"2025-04-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.08,"output":0.28},"canonical_model_id":"alibaba/qwen3-32b"},"qwen/qwen3.7-max":{"id":"qwen/qwen3.7-max","name":"Qwen3.7 Max","description":"Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":1.475,"output":4.425,"cache_read":0.295,"cache_write":1.84375},"canonical_model_id":"alibaba/qwen3.7-max"},"qwen/qwen-plus":{"id":"qwen/qwen-plus","name":"Qwen Plus","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2024-01-25","last_updated":"2025-09-11","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":32768},"cost":{"input":0.26,"output":0.78,"cache_read":0.052,"cache_write":0.325,"tiers":[{"input":0.78,"output":2.34,"cache_read":0.156,"cache_write":0.975,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.78,"output":2.34,"cache_read":0.156,"cache_write":0.975}},"canonical_model_id":"alibaba/qwen-plus"},"qwen/qwen3.5-122b-a10b":{"id":"qwen/qwen3.5-122b-a10b","name":"Qwen3.5 122B-A10B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.4,"output":3.2},"canonical_model_id":"alibaba/qwen3.5-122b-a10b"},"qwen/qwen3.7-flash":{"id":"qwen/qwen3.7-flash","name":"Qwen3.7 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-15","last_updated":"2026-07-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"input":991808,"output":65536},"cost":{"input":0.03,"output":0.13,"cache_read":0.006,"cache_write":0.038,"tiers":[{"input":0.1,"output":0.4,"cache_read":0.02,"cache_write":0.125,"tier":{"type":"context","size":32000}},{"input":0.2,"output":0.8,"cache_read":0.04,"cache_write":0.25,"tier":{"type":"context","size":256000}}]},"canonical_model_id":"alibaba/qwen3.7-flash"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":0.04,"output":1.35,"cache_read":0.018},"canonical_model_id":"alibaba/qwen3.8-27b"},"qwen/qwen3.6-plus":{"id":"qwen/qwen3.6-plus","name":"Qwen3.6 Plus","description":"Earlier Qwen multimodal workhorse for million-token agent and document tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.325,"output":1.95,"cache_write":0.40625,"tiers":[{"input":1.3,"output":3.9,"cache_write":1.625,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":1.3,"output":3.9,"cache_write":1.625}},"canonical_model_id":"alibaba/qwen3.6-plus"},"qwen/qwen3-vl-235b-a22b-instruct":{"id":"qwen/qwen3-vl-235b-a22b-instruct","name":"Qwen3 VL 235B A22B Instruct","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-23","last_updated":"2025-09-23","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.21,"output":1.9,"cache_read":0.1},"canonical_model_id":"alibaba/qwen3-vl-235b-a22b-instruct"},"qwen/qwen3.5-27b":{"id":"qwen/qwen3.5-27b","name":"Qwen3.5 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-02-23","last_updated":"2026-02-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.27,"output":2.16,"cache_read":0.27},"canonical_model_id":"alibaba/qwen3.5-27b"},"qwen/qwen3-235b-a22b-2507":{"id":"qwen/qwen3-235b-a22b-2507","name":"Qwen3 235B A22B Instruct 2507","description":"Qwen instruction model for multilingual chat, reasoning, and tool use","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-07-21","last_updated":"2025-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.09,"output":0.55},"canonical_model_id":"alibaba/qwen3-235b-a22b-instruct-2507"},"qwen/qwen3-coder":{"id":"qwen/qwen3-coder","name":"Qwen3 Coder 480B A35B","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.3,"output":1,"cache_read":0.1},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"qwen/qwen3-coder-next":{"id":"qwen/qwen3-coder-next","name":"Qwen3 Coder Next","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-02-03","last_updated":"2026-02-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.12,"output":0.8,"cache_read":0.07},"canonical_model_id":"alibaba/qwen3-coder-next"},"qwen/qwen3.6-35b-a3b":{"id":"qwen/qwen3.6-35b-a3b","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.1,"output":0.95,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"qwen/qwen3.5-plus-02-15":{"id":"qwen/qwen3.5-plus-02-15","name":"Qwen3.5 Plus 2026-02-15","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":65536},"cost":{"input":0.26,"output":1.56,"tiers":[{"input":0.325,"output":1.95,"tier":{"type":"context","size":256000}}],"context_over_200k":{"input":0.325,"output":1.95}}},"qwen/qwen3-next-80b-a3b-thinking":{"id":"qwen/qwen3-next-80b-a3b-thinking","name":"Qwen3-Next 80B-A3B (Thinking)","description":"Efficient Qwen thinking model for local reasoning, math, and coding agents","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09","last_updated":"2025-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.15,"output":1.2},"canonical_model_id":"alibaba/qwen3-next-80b-a3b-thinking"},"sakana/fugu-max":{"id":"sakana/fugu-max","name":"Fugu Max","description":"Multi-agent model for routing expert agents across complex analytical tasks","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":2,"output":6,"cache_read":0.25},"canonical_model_id":"sakana/fugu-max"},"sakana/fugu-ultra":{"id":"sakana/fugu-ultra","name":"Fugu Ultra","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-06-15","last_updated":"2026-06-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"sakana/fugu-ultra"},"sakana/fugu-ultra-v2":{"id":"sakana/fugu-ultra-v2","name":"Fugu Ultra v2","description":"Quality-first multi-agent model for hard research, analysis, and competitions","family":"fugu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-08-28","release_date":"2026-09-11","last_updated":"2026-09-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"sakana/fugu-ultra-v2"},"sakana/sakana-namazu":{"id":"sakana/sakana-namazu","name":"Sakana Namazu","description":"Multi-agent model for routing expert agents across complex analytical tasks","family":"sakana-namazu","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0.95,"output":4,"cache_read":0.15},"canonical_model_id":"sakana/sakana-namazu"},"rekaai/reka-edge":{"id":"rekaai/reka-edge","name":"Reka Edge","description":"Multimodal model for analyzing text, images, documents, and rich media","family":"reka","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":14745},"cost":{"input":0.1,"output":0.1},"canonical_model_id":"rekaai/reka-edge"},"rekaai/reka-flash-3":{"id":"rekaai/reka-flash-3","name":"Reka Flash 3","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"reka","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01-31","release_date":"2025-03-10","last_updated":"2025-03-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":58982},"cost":{"input":0.1,"output":0.2},"canonical_model_id":"rekaai/reka-flash-3"},"minimax/minimax-m2.1":{"id":"minimax/minimax-m2.1","name":"MiniMax-M2.1","description":"Earlier MiniMax agent model for practical coding and productivity tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":false,"temperature":true,"release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.1"},"minimax/minimax-m2.5":{"id":"minimax/minimax-m2.5","name":"MiniMax-M2.5","description":"Prior MiniMax coding model for agent workflows, office edits, and automation","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":32768},"cost":{"input":0.27,"output":0.95,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2.5"},"minimax/minimax-01":{"id":"minimax/minimax-01","name":"MiniMax-01","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-03-31","release_date":"2025-01-15","last_updated":"2025-01-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000192,"output":40000},"cost":{"input":0.2,"output":1.1}},"minimax/minimax-m2":{"id":"minimax/minimax-m2","name":"MiniMax-M2","description":"Efficient open MiniMax model built for coding agents and tool-heavy workflows","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"release_date":"2025-10-27","last_updated":"2025-10-27","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.255,"output":1.02},"canonical_model_id":"minimax/MiniMax-M2"},"minimax/minimax-m2.7":{"id":"minimax/minimax-m2.7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7"},"minimax/minimax-m2-her":{"id":"minimax/minimax-m2-her","name":"MiniMax-M2 Her","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-01-23","last_updated":"2026-01-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":65536,"output":2048},"cost":{"input":0.3,"output":1.2,"cache_read":0.03},"canonical_model_id":"minimax/MiniMax-M2-Her"},"minimax/minimax-m3":{"id":"minimax/minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"minimax/minimax-m1":{"id":"minimax/minimax-m1","name":"MiniMax M1","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-06-30","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":40000},"cost":{"input":0.55,"output":2.2}},"minimax/minimax-m3.1-flash:free":{"id":"minimax/minimax-m3.1-flash:free","name":"MiniMax M3.1 Flash (free)","description":"MiniMax multimodal coding model for long-context reasoning and agent tasks","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-19","last_updated":"2026-10-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":524288},"cost":{"input":0,"output":0},"canonical_model_id":"minimax/MiniMax-M3.1-Flash"},"cognitivecomputations/dolphin-mistral-24b-venice-edition":{"id":"cognitivecomputations/dolphin-mistral-24b-venice-edition","name":"Uncensored","description":"Mistral model for multilingual chat, reasoning, and tool-assisted workflows","family":"mistral","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-04-30","release_date":"2025-07-09","last_updated":"2025-07-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.2,"output":0.9},"canonical_model_id":"cognitivecomputations/dolphin-mistral-24b-venice-edition"},"liquid/lfm-2.5-2.6b:free":{"id":"liquid/lfm-2.5-2.6b:free","name":"LFM2.5-2.6B (free)","description":"Free provider route for experiments, demos, and cost-sensitive chat workloads","family":"liquid","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":8192},"cost":{"input":0,"output":0}},"liquid/lfm-2.5-24b-a2b":{"id":"liquid/lfm-2.5-24b-a2b","name":"LFM2.5-24B-A2B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"liquid","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0.05,"output":0.7,"cache_read":0.025}},"moondream/moondream3-preview":{"id":"moondream/moondream3-preview","name":"Moondream 3 Preview","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":4096},"cost":{"input":0.3,"output":2.5}},"moondream/moondream3.1-9b-a2b":{"id":"moondream/moondream3.1-9b-a2b","name":"Moondream 3.1","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":4096},"cost":{"input":0.3,"output":2.5}},"moonshotai/kimi-k2-0905":{"id":"moonshotai/kimi-k2-0905","name":"Kimi K2 Instruct 0905","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":0.6,"output":2.5},"canonical_model_id":"moonshotai/kimi-k2-0905"},"moonshotai/kimi-k2-thinking":{"id":"moonshotai/kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Thinking Kimi model for slower research passes, planning, and hard technical questions","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":98304},"cost":{"input":0.6,"output":2.5,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"moonshotai/kimi-k3":{"id":"moonshotai/kimi-k3","name":"Kimi K3","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":0.239,"output":11.936,"cache_read":0.21},"canonical_model_id":"moonshotai/kimi-k3"},"moonshotai/kimi-k2.5":{"id":"moonshotai/kimi-k2.5","name":"Kimi K2.5","description":"Earlier Kimi frontier model for long-context agents, coding, and multimodal work","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.5,"output":2.5,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2.5"},"moonshotai/kimi-k2.6":{"id":"moonshotai/kimi-k2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.65,"output":3.41,"cache_read":0.15},"canonical_model_id":"moonshotai/kimi-k2.6"},"moonshotai/kimi-k2":{"id":"moonshotai/kimi-k2","name":"Kimi K2 0711","description":"Kimi model for long-context chat, coding, and agentic reasoning","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-12-31","release_date":"2025-07-11","last_updated":"2025-07-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.57,"output":2.3},"canonical_model_id":"moonshotai/kimi-k2"},"moonshotai/kimi-k2.7-code":{"id":"moonshotai/kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.6712,"output":3.35,"cache_read":0.18},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"deepseek/deepseek-v4-flash":{"id":"deepseek/deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943717},"cost":{"input":0.091,"output":0.182,"cache_read":0.0182},"canonical_model_id":"deepseek/deepseek-v4-flash"},"deepseek/deepseek-v4.1-flash":{"id":"deepseek/deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"deepseek/deepseek-v4-pro":{"id":"deepseek/deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":384000},"cost":{"input":0.95526,"output":1.91052,"cache_read":0.079605},"canonical_model_id":"deepseek/deepseek-v4-pro"},"deepseek/deepseek-v3.1-terminus":{"id":"deepseek/deepseek-v3.1-terminus","name":"DeepSeek V3.1 Terminus","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-09-22","last_updated":"2025-09-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":147456},"cost":{"input":0.27,"output":1}},"deepseek/deepseek-v3.2-exp":{"id":"deepseek/deepseek-v3.2-exp","name":"DeepSeek V3.2 Exp","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":147456},"cost":{"input":0.27,"output":0.41}},"deepseek/deepseek-chat-v3.1":{"id":"deepseek/deepseek-chat-v3.1","name":"DeepSeek V3.1","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-21","last_updated":"2025-08-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":32768},"cost":{"input":0.25,"output":0.95,"cache_read":0.13},"canonical_model_id":"deepseek/deepseek-chat-v3.1"},"deepseek/deepseek-chat":{"id":"deepseek/deepseek-chat","name":"DeepSeek Chat","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2025-12-01","last_updated":"2026-02-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":16000},"cost":{"input":0.2574,"output":1.0287},"canonical_model_id":"deepseek/deepseek-chat"},"deepseek/deepseek-v4-flash-vision-exp":{"id":"deepseek/deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":262144},"cost":{"input":0.2156,"output":0.6468,"cache_read":0.00686},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"deepseek/deepseek-r1-0528":{"id":"deepseek/deepseek-r1-0528","name":"DeepSeek R1 0528","description":"DeepSeek reasoning model for multi-step analysis, math, coding, and tools","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-05-28","last_updated":"2025-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":32768},"cost":{"input":0.5,"output":2.15,"cache_read":0.35},"canonical_model_id":"deepseek/deepseek-r1-0528"},"deepseek/deepseek-v4.1-flash-1017":{"id":"deepseek/deepseek-v4.1-flash-1017","name":"DeepSeek V4.1 Flash 1017","description":"Fast DeepSeek model for efficient chat, coding help, and agent loops","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-10-17","last_updated":"2026-10-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash-1017"},"deepseek/deepseek-chat-v3-0324":{"id":"deepseek/deepseek-chat-v3-0324","name":"DeepSeek V3 0324","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07-31","release_date":"2025-03-24","last_updated":"2025-03-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":115200},"cost":{"input":0.29,"output":1.14,"cache_read":0.11},"canonical_model_id":"deepseek/deepseek-chat-v3-0324"},"deepseek/deepseek-v4-flash-0731":{"id":"deepseek/deepseek-v4-flash-0731","name":"DeepSeek V4 Flash 0731","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.44,"output":1.32,"cache_read":0.014},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek/deepseek-v3.2":{"id":"deepseek/deepseek-v3.2","name":"DeepSeek V3.2","description":"DeepSeek chat model for instruction following, coding, and analysis","family":"deepseek","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-07","release_date":"2025-12-01","last_updated":"2025-12-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":65536},"cost":{"input":0.28,"output":0.42,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v3.2"},"deepseek/deepseek-v4-pro-0813":{"id":"deepseek/deepseek-v4-pro-0813","name":"DeepSeek V4 Pro 0813","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":393216},"cost":{"input":1.32,"output":3.96,"cache_read":0.044},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"},"aion-labs/aion-3.0":{"id":"aion-labs/aion-3.0","name":"Aion-3.0","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-05-05","last_updated":"2026-05-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":3,"output":6,"cache_read":0.75},"canonical_model_id":"aion-labs/aion-3.0"},"aion-labs/aion-2.0":{"id":"aion-labs/aion-2.0","name":"Aion-2.0","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-12-21","last_updated":"2025-12-21","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.8,"output":1.6,"cache_read":0.2},"canonical_model_id":"aion-labs/aion-2.0"},"aion-labs/aion-rp-llama-3.1-8b":{"id":"aion-labs/aion-rp-llama-3.1-8b","name":"Aion-RP 1.0 (8B)","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12-31","release_date":"2025-02-04","last_updated":"2025-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":29491},"cost":{"input":0.8,"output":1.6},"canonical_model_id":"aion-labs/aion-rp-llama-3.1-8b"},"aion-labs/aion-3.5-mini":{"id":"aion-labs/aion-3.5-mini","name":"Aion 3.5 Mini","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":0.7,"output":1.4,"cache_read":0.18}},"aion-labs/aion-3.0-mini":{"id":"aion-labs/aion-3.0-mini","name":"Aion-3.0-Mini","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-05-14","last_updated":"2026-05-14","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.7,"output":1.4,"cache_read":0.18},"canonical_model_id":"aion-labs/aion-3.0-mini"},"aion-labs/aion-3.5":{"id":"aion-labs/aion-3.5","name":"Aion 3.5","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"cost":{"input":3,"output":6,"cache_read":0.75}},"nvidia/nemotron-3-ultra-550b-a55b:free":{"id":"nvidia/nemotron-3-ultra-550b-a55b:free","name":"Nemotron 3 Ultra (free)","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/nemotron-3.5-content-safety:free":{"id":"nvidia/nemotron-3.5-content-safety:free","name":"Nemotron 3.5 Content Safety (free)","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":8192},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-content-safety"},"nvidia/nemotron-3.5-content-safety":{"id":"nvidia/nemotron-3.5-content-safety","name":"Nemotron 3.5 Content Safety","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.2,"output":0.2},"canonical_model_id":"nvidia/nemotron-3.5-content-safety"},"nvidia/nemotron-3.5-super-vl":{"id":"nvidia/nemotron-3.5-super-vl","name":"Nemotron 3.5 Super VL","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":235929},"cost":{"input":0.15,"output":0.5,"cache_read":0.02},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"nvidia/nemotron-3-super-120b-a12b":{"id":"nvidia/nemotron-3-super-120b-a12b","name":"Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.3,"output":2.4,"cache_read":0.15},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"nvidia/nemotron-3-ultra-550b-a55b":{"id":"nvidia/nemotron-3-ultra-550b-a55b","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":182520},"cost":{"input":0.6,"output":2.4,"cache_read":0.12},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"nvidia/nemotron-3-super-120b-a12b:free":{"id":"nvidia/nemotron-3-super-120b-a12b:free","name":"Nemotron 3 Super (free)","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"nvidia/nemotron-3.5-super-vl:free":{"id":"nvidia/nemotron-3.5-super-vl:free","name":"Nemotron 3.5 Super VL (free)","description":"Nemotron multimodal model for visual reasoning and agentic AI workflows","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"nvidia/nemotron-3.5-lightning":{"id":"nvidia/nemotron-3.5-lightning","name":"Nemotron 3.5 Lightning 30B A3B","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.07,"output":0.2,"cache_read":0.04},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/nemotron-3.5-lightning:free":{"id":"nvidia/nemotron-3.5-lightning:free","name":"Nemotron 3.5 Lightning (free)","description":"Nemotron model for efficient reasoning, coding, and specialized AI agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-09","release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning:free":{"id":"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning:free","name":"Nemotron 3 Nano Omni (free)","description":"Open Nemotron omni model combining reasoning with text, vision, and audio","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-28","last_updated":"2026-04-28","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-nano-omni-30b-a3b-reasoning"},"nvidia/nemotron-3-nano-30b-a3b":{"id":"nvidia/nemotron-3-nano-30b-a3b","name":"Nemotron 3 Nano 30B A3B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-06-25","release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.06,"output":0.24},"canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"arcee-ai/trinity-large-thinking":{"id":"arcee-ai/trinity-large-thinking","name":"Trinity Large Thinking","description":"Reasoning-optimized 398B MoE agent model with extended thinking for long-horizon and multi-turn tool use","family":"trinity","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":80000},"cost":{"input":0.25,"output":0.8,"cache_read":0.06},"canonical_model_id":"arcee-ai/trinity-large-thinking"},"microsoft/phi-4":{"id":"microsoft/phi-4","name":"Phi 4","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","family":"phi","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2025-01-10","last_updated":"2025-01-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":16384,"output":14745},"cost":{"input":0.07,"output":0.14}},"unbiased/pareto-26.10":{"id":"unbiased/pareto-26.10","name":"Pareto 26.10","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.8,"output":3.2,"cache_read":0.03}},"unbiased/pareto-26.9":{"id":"unbiased/pareto-26.9","name":"Pareto 26.9","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"cost":{"input":2.5,"output":7.5,"cache_read":0.25}},"cohere/command-r7b-12-2024":{"id":"cohere/command-r7b-12-2024","name":"Command R7B","description":"Cohere retrieval model for long-context chat and enterprise RAG workflows","family":"command-r","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-12-13","last_updated":"2024-12-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.0375,"output":0.15},"canonical_model_id":"cohere/command-r7b-12-2024"},"cohere/command-r-08-2024":{"id":"cohere/command-r-08-2024","name":"Command R","description":"Cohere retrieval model for long-context chat and enterprise RAG workflows","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"cohere/command-r-08-2024"},"cohere/command-a":{"id":"cohere/command-a","name":"Command A","description":"Cohere command model for multilingual enterprise agents, tools, and chat","family":"command-a","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-03-13","last_updated":"2025-03-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":8192},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-a"},"cohere/command-a-plus":{"id":"cohere/command-a-plus","name":"Command A+","description":"Cohere command model for multilingual enterprise agents, tools, and chat","family":"command-a","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04-01","release_date":"2026-05-20","last_updated":"2026-06-09","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":192000,"output":64000},"cost":{"input":0.3,"output":1.5,"cache_read":0.15},"canonical_model_id":"cohere/command-a-plus-05-2026"},"cohere/command-r-plus-08-2024":{"id":"cohere/command-r-plus-08-2024","name":"Command R+","description":"Cohere's RAG workhorse for long-context enterprise search and tool use","family":"command-r","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06-01","release_date":"2024-08-30","last_updated":"2024-08-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4000},"cost":{"input":2.5,"output":10},"canonical_model_id":"cohere/command-r-plus-08-2024"},"cohere/north-mini-code:free":{"id":"cohere/north-mini-code:free","name":"North Mini Code (free)","description":"Cohere coding model for practical software engineering and agentic edits","family":"north","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-09-23","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"cost":{"input":0,"output":0},"canonical_model_id":"cohere/north-mini-code-1-0"},"inference-net/schematron-v2-turbo":{"id":"inference-net/schematron-v2-turbo","name":"Schematron V2 Turbo","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":8192},"cost":{"input":0.03,"output":0.15,"cache_read":0.03},"canonical_model_id":"inference-net/schematron-v2-turbo"},"inference-net/schematron-v2-small":{"id":"inference-net/schematron-v2-small","name":"Schematron V2 Small","description":"Efficient model for low-latency assistance, extraction, and routine automation","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"output":4096},"cost":{"input":0.05,"output":0.23,"cache_read":0.05},"canonical_model_id":"inference-net/schematron-v2-small"},"~moonshotai/kimi-latest":{"id":"~moonshotai/kimi-latest","name":"Kimi Latest","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.238,"output":24,"cache_read":0.228}},"meta-llama/llama-3.2-1b-instruct":{"id":"meta-llama/llama-3.2-1b-instruct","name":"Llama 3.2 1B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":60000,"output":54000},"cost":{"input":0.027,"output":0.201},"canonical_model_id":"meta/llama-3.2-1b-instruct"},"meta-llama/llama-3.2-3b-instruct":{"id":"meta-llama/llama-3.2-3b-instruct","name":"Llama 3.2 3B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-09-25","last_updated":"2024-09-25","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":72000},"cost":{"input":0.0509,"output":0.335},"canonical_model_id":"meta/llama-3.2-3b-instruct"},"meta-llama/llama-3.3-70b-instruct":{"id":"meta-llama/llama-3.3-70b-instruct","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.1,"output":0.32},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"meta-llama/llama-4-scout":{"id":"meta-llama/llama-4-scout","name":"Llama 4 Scout","description":"Open multimodal Llama model for long-context analysis and efficient agents","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1310720,"output":16384},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"meta/llama-4-scout-17b-instruct"},"meta-llama/llama-guard-4-12b":{"id":"meta-llama/llama-guard-4-12b","name":"Llama Guard 4 12B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"llama","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2025-04-29","last_updated":"2025-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":163840,"output":16384},"cost":{"input":0.18,"output":0.18},"canonical_model_id":"meta/llama-guard-4-12b"},"meta-llama/llama-4-maverick":{"id":"meta-llama/llama-4-maverick","name":"Llama 4 Maverick","description":"Open multimodal Llama model for strong reasoning and fast responses","family":"llama","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-04-05","last_updated":"2025-04-05","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":16384},"cost":{"input":0.1875,"output":0.6525,"cache_read":0.05},"canonical_model_id":"meta/llama-4-maverick-17b-instruct"},"meta-llama/llama-3.1-8b-instruct":{"id":"meta-llama/llama-3.1-8b-instruct","name":"Llama-3.1-8B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.05,"output":0.08,"cache_read":0.025},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"meta-llama/llama-3.1-70b-instruct":{"id":"meta-llama/llama-3.1-70b-instruct","name":"Llama-3.1-70B-Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.4,"output":0.4},"canonical_model_id":"meta/llama-3.1-70b-instruct"},"scaledown/summarize":{"id":"scaledown/summarize","name":"Summarize","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":4000},"cost":{"input":0.04,"output":0}},"scaledown/extract":{"id":"scaledown/extract","name":"Extract","description":"Multimodal model for analyzing text, images, documents, and rich media","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":false,"release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":900000},"cost":{"input":0.04,"output":0}},"tencent/hy-mt2-1.8b":{"id":"tencent/hy-mt2-1.8b","name":"Hy-MT2-1.8B","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":4096},"cost":{"input":0.044,"output":0.177},"canonical_model_id":"tencent/hy-mt2-1.8b"},"tencent/hy-mt2-30b-a3b":{"id":"tencent/hy-mt2-30b-a3b","name":"Hy-MT2-30B-A3B","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":4096},"cost":{"input":0.074,"output":0.295},"canonical_model_id":"tencent/hy-mt2-30b-a3b"},"tencent/hy4-preview":{"id":"tencent/hy4-preview","name":"Hy4 preview","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-28","last_updated":"2026-08-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":64000},"cost":{"input":0.834,"output":2.501,"cache_read":0.042},"canonical_model_id":"tencent/hy4-preview"},"tencent/hy-mt2-7b":{"id":"tencent/hy-mt2-7b","name":"Hy-MT2-7B","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-05-21","last_updated":"2026-05-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":4096},"cost":{"input":0.074,"output":0.295},"canonical_model_id":"tencent/hy-mt2-7b"},"tencent/hy3":{"id":"tencent/hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":192000,"output":128000},"cost":{"input":0.132,"output":0.528,"cache_read":0.033},"canonical_model_id":"tencent/hy3"},"tencent/hunyuan-a13b-instruct":{"id":"tencent/hunyuan-a13b-instruct","name":"Hunyuan A13B Instruct","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"hunyuan","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-07-08","last_updated":"2025-07-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.14,"output":0.57}},"tencent/hy3-preview":{"id":"tencent/hy3-preview","name":"Hy3 preview","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.18,"output":0.6,"cache_read":0.06},"canonical_model_id":"tencent/hy3-preview"},"meta/muse-spark-1.3":{"id":"meta/muse-spark-1.3","name":"Muse Spark 1.3","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.3"},"meta/muse-spark-open":{"id":"meta/muse-spark-open","name":"Muse Spark Open","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-open"},"meta/muse-wonder":{"id":"meta/muse-wonder","name":"Muse Wonder","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":4,"output":20,"cache_read":0.2}},"meta/muse-spark-1.2":{"id":"meta/muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"meta/muse-spark-1.2-contributor":{"id":"meta/muse-spark-1.2-contributor","name":"Muse Spark 1.2 Contributor","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-08-21","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"meta/muse-spark-1.1":{"id":"meta/muse-spark-1.1","name":"Muse Spark 1.1","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-08","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.1"},"meta/muse-glimmer-30b":{"id":"meta/muse-glimmer-30b","name":"Muse Glimmer 30B","description":"Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-01-04","release_date":"2026-08-10","last_updated":"2026-08-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.3,"output":1.2,"cache_read":0.04},"canonical_model_id":"meta/muse-glimmer-30b"},"meta/muse-spark-1.3-contributor":{"id":"meta/muse-spark-1.3-contributor","name":"Muse Spark 1.3 Contributor","description":"Open Llama multimodal model for image understanding and text reasoning","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":0.1,"output":0.2,"cache_read":0.002}},"stepfun/step-3.5-flash":{"id":"stepfun/step-3.5-flash","name":"Step 3.5 Flash","description":"StepFun flash lane for quick multimodal reasoning and coding assistance","family":"step","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-01-29","last_updated":"2026-02-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.1,"output":0.3},"canonical_model_id":"stepfun/step-3.5-flash"},"stepfun/step-5-preview":{"id":"stepfun/step-5-preview","name":"Step 5 Preview","description":"StepFun flash model for efficient multimodal reasoning, coding, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1000000,"output":64000},"cost":{"input":1,"output":2.7,"cache_read":0.1},"canonical_model_id":"stepfun/step-5-preview"},"stepfun/step-3.7-flash":{"id":"stepfun/step-3.7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"input":256000,"output":230400},"cost":{"input":0.2,"output":1.15,"cache_read":0.04},"canonical_model_id":"stepfun/step-3.7-flash"},"nousresearch/hermes-4-405b":{"id":"nousresearch/hermes-4-405b","name":"Hermes 4 405B","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"hermes","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08-31","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":1,"output":3},"canonical_model_id":"nousresearch/hermes-4-405b"},"nousresearch/hermes-3-llama-3.1-70b":{"id":"nousresearch/hermes-3-llama-3.1-70b","name":"Hermes 3 70B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"nousresearch","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-18","last_updated":"2024-08-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"status":"deprecated","cost":{"input":0.7,"output":0.7},"canonical_model_id":"nousresearch/hermes-3-llama-3.1-70b"},"nousresearch/hermes-3-llama-3.1-405b":{"id":"nousresearch/hermes-3-llama-3.1-405b","name":"Hermes 3 405B Instruct","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"nousresearch","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2023-12-31","release_date":"2024-08-16","last_updated":"2024-08-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"status":"deprecated","cost":{"input":1,"output":1},"canonical_model_id":"nousresearch/hermes-3-llama-3.1-405b"},"fireworks/ember-1":{"id":"fireworks/ember-1","name":"Ember-1","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"fireworks/ember-1"},"~google/gemini-pro-latest":{"id":"~google/gemini-pro-latest","name":"Gemini Pro Latest","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["audio","pdf","image","text","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":2,"output":10,"reasoning":10,"cache_read":0.1,"cache_write":0.1875,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}}},"~google/gemini-flash-latest":{"id":"~google/gemini-flash-latest","name":"Gemini Flash Latest","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01-01","release_date":"2026-04-27","last_updated":"2026-04-27","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"reasoning":3.75,"cache_read":0.075,"cache_write":0.041667}},"~x-ai/grok-latest":{"id":"~x-ai/grok-latest","name":"Grok Latest","description":"Grok model for agentic tool use, reasoning, coding, and live assistance","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":450000},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}}},"z-ai/glm-5-turbo":{"id":"z-ai/glm-5-turbo","name":"GLM-5-Turbo","description":"Faster GLM-5 lane for coding agents that need lower latency","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"release_date":"2026-03-16","last_updated":"2026-03-16","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5-turbo"},"z-ai/glm-4.5v":{"id":"z-ai/glm-4.5v","name":"GLM-4.5V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-08-11","last_updated":"2025-08-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":16384},"cost":{"input":0.6,"output":1.8,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5v"},"z-ai/glm-4.7":{"id":"z-ai/glm-4.7","name":"GLM-4.7","description":"Mature GLM model for dependable coding, reasoning, and structured agent tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.54,"output":1.98,"cache_read":0.099},"canonical_model_id":"zhipuai/glm-4.7"},"z-ai/glm-4.6v":{"id":"z-ai/glm-4.6v","name":"GLM-4.6V","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-12-08","last_updated":"2025-12-08","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.3,"output":0.9,"cache_read":0.055},"canonical_model_id":"zhipuai/glm-4.6v"},"z-ai/glm-5.2":{"id":"z-ai/glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":0.0341,"output":7,"cache_read":0.033},"canonical_model_id":"zhipuai/glm-5.2"},"z-ai/glm-5v-turbo":{"id":"z-ai/glm-5v-turbo","name":"GLM-5V-Turbo","description":"Fast GLM vision model for screenshots, documents, and multimodal agent tasks","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-01","last_updated":"2026-04-01","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":false,"limit":{"context":202752,"output":131072},"cost":{"input":1.2,"output":4,"cache_read":0.24},"canonical_model_id":"zhipuai/glm-5v-turbo"},"z-ai/glm-5":{"id":"z-ai/glm-5","name":"GLM-5","description":"General GLM flagship for coding, analysis, and tool-heavy engineering workflows","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"z-ai/glm-5.3":{"id":"z-ai/glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":943718},"cost":{"input":0.079,"output":1.4,"cache_read":0.078},"canonical_model_id":"zhipuai/glm-5.3"},"z-ai/glm-5.3-flash":{"id":"z-ai/glm-5.3-flash","name":"GLM-5.3-Flash","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.018,"output":0.121,"cache_read":0.018},"canonical_model_id":"zhipuai/glm-5.3-flash"},"z-ai/glm-4.7-flash":{"id":"z-ai/glm-4.7-flash","name":"GLM-4.7-Flash","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":117964},"cost":{"input":0.0605,"output":0.4},"canonical_model_id":"zhipuai/glm-4.7-flash"},"z-ai/glm-4.5-air":{"id":"z-ai/glm-4.5-air","name":"GLM-4.5-Air","description":"Lighter GLM-4.5 variant for fast coding assistance and cheaper agents","family":"glm-air","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"cost":{"input":0.13,"output":0.85,"cache_read":0.025},"canonical_model_id":"zhipuai/glm-4.5-air"},"z-ai/glm-5.1":{"id":"z-ai/glm-5.1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"z-ai/glm-4.6":{"id":"z-ai/glm-4.6","name":"GLM-4.6","description":"Late GLM-4 workhorse for coding agents, reasoning, and structured tasks","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.55,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.6"},"z-ai/glm-4.5":{"id":"z-ai/glm-4.5","name":"GLM-4.5","description":"Hybrid-reasoning GLM release that made the 4.5 line broadly useful","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-28","last_updated":"2025-07-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":98304},"status":"deprecated","cost":{"input":0.6,"output":2.2,"cache_read":0.11},"canonical_model_id":"zhipuai/glm-4.5"},"z-ai/glm-5.3-prime":{"id":"z-ai/glm-5.3-prime","name":"GLM 5.3 Prime","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2.8,"output":8.8,"cache_read":0.56}},"z-ai/glm-5.3-flashx":{"id":"z-ai/glm-5.3-flashx","name":"GLM 5.3 FlashX","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-18","last_updated":"2026-09-18","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"cost":{"input":0.37,"output":1.25,"cache_read":0.09}},"gryphe/mythomax-l2-13b":{"id":"gryphe/mythomax-l2-13b","name":"MythoMax L2 13B","description":"Open-weight instruction model for adaptable chat and self-hosted production workloads","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2023-08-10","last_updated":"2023-08-10","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":3686},"cost":{"input":0.08,"output":0.11},"canonical_model_id":"gryphe/mythomax-l2-13b"},"google/gemma-4-26b-a4b-it:free":{"id":"google/gemma-4-26b-a4b-it:free","name":"Gemma 4 26B A4B (free)","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemini-2.5-flash-lite":{"id":"google/gemini-2.5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"status":"deprecated","cost":{"input":0.1,"output":0.4,"reasoning":0.4,"cache_read":0.01,"cache_write":0.083333},"canonical_model_id":"google/gemini-2.5-flash-lite"},"google/gemini-3.7-flash":{"id":"google/gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"reasoning":3.75,"cache_read":0.075,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.7-flash"},"google/lyria-3-pro-preview":{"id":"google/lyria-3-pro-preview","name":"Lyria 3 Pro Preview","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"lyria","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-03-25","last_updated":"2026-03-25","modalities":{"input":["text","image"],"output":["text","audio"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"google/lyria-3-pro-preview"},"google/gemini-3-pro-image":{"id":"google/gemini-3-pro-image","type":"image","name":"Nano Banana Pro","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":2,"output":12,"reasoning":12,"cache_read":0.2,"cache_write":0.375},"canonical_model_id":"google/gemini-3-pro-image"},"google/gemini-3.1-flash-lite-preview":{"id":"google/gemini-3.1-flash-lite-preview","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"reasoning":1.5,"cache_read":0.025,"cache_write":0.083333},"canonical_model_id":"google/gemini-3.1-flash-lite-preview"},"google/gemini-3.1-flash-image":{"id":"google/gemini-3.1-flash-image","type":"image","name":"Nano Banana 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["image","text"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3.1-flash-image"},"google/gemini-3-flash-preview":{"id":"google/gemini-3-flash-preview","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.5,"output":3,"reasoning":3,"cache_read":0.05,"cache_write":0.083333},"canonical_model_id":"google/gemini-3-flash-preview"},"google/gemma-4-31b-it:free":{"id":"google/gemma-4-31b-it:free","name":"Gemma 4 31B (free)","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0,"output":0},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemini-2.5-flash":{"id":"google/gemini-2.5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65535},"status":"deprecated","cost":{"input":0.3,"output":2.5,"reasoning":2.5,"cache_read":0.03,"cache_write":0.083333},"canonical_model_id":"google/gemini-2.5-flash"},"google/gemini-2.5-pro":{"id":"google/gemini-2.5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":1.25,"output":10,"reasoning":10,"cache_read":0.125,"cache_write":0.375,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro"},"google/gemini-2.5-flash-image":{"id":"google/gemini-2.5-flash-image","type":"image","name":"Nano Banana","description":"Nano Banana image model for fast generation, edits, and character-consistent assets","family":"gemini-flash","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-26","last_updated":"2025-08-26","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":32768,"output":8192},"cost":{"input":0.3,"output":2.5,"cache_read":0.03,"cache_write":0.083333},"canonical_model_id":"google/gemini-2.5-flash-image"},"google/gemma-3-4b-it":{"id":"google/gemma-3-4b-it","name":"Gemma 3 4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.04,"output":0.05,"cache_read":0.02},"canonical_model_id":"google/gemma-3-4b-it"},"google/gemini-4-argon":{"id":"google/gemini-4-argon","name":"Gemini 4 Argon","description":"Gemini multimodal model for text, image, audio, video, and document tasks","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":943718},"cost":{"input":2,"output":10,"reasoning":10,"cache_read":0.1,"cache_write":0.1875},"canonical_model_id":"google/gemini-4-argon"},"google/gemma-4-31b-it":{"id":"google/gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":16384},"cost":{"input":0.2,"output":0.4},"canonical_model_id":"google/gemma-4-31b-it"},"google/gemini-3.5-flash-lite":{"id":"google/gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.3,"output":2.5,"reasoning":2.5,"cache_read":0.03,"cache_write":0.083333},"canonical_model_id":"google/gemini-3.5-flash-lite"},"google/gemma-2-27b-it":{"id":"google/gemma-2-27b-it","name":"Gemma 2 27B","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":false,"reasoning":false,"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2024-06-30","release_date":"2024-07-13","last_updated":"2024-07-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":8192,"output":2048},"cost":{"input":0.65,"output":0.65},"canonical_model_id":"google/gemma-2-27b-it"},"google/lyria-3-clip-preview":{"id":"google/lyria-3-clip-preview","name":"Lyria 3 Clip Preview","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"lyria","attachment":true,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2026-03-25","last_updated":"2026-03-25","modalities":{"input":["text","image"],"output":["text","audio"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0},"canonical_model_id":"google/lyria-3-clip-preview"},"google/gemini-3-pro-image-preview":{"id":"google/gemini-3-pro-image-preview","type":"image","name":"Nano Banana Pro Preview","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-20","last_updated":"2025-11-20","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"cost":{"input":2,"output":12,"reasoning":12,"cache_read":0.2,"cache_write":0.375},"canonical_model_id":"google/gemini-3-pro-image-preview"},"google/gemma-4-26b-a4b-it":{"id":"google/gemma-4-26b-a4b-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["image","text","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.0765,"output":0.255,"cache_read":0.0425},"canonical_model_id":"google/gemma-4-26b-a4b-it"},"google/gemini-3.1-flash-lite-image":{"id":"google/gemini-3.1-flash-lite-image","type":"image","name":"Nano Banana 2 Lite","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","high"]}],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":58982},"cost":{"input":0.25,"output":1.5},"canonical_model_id":"google/gemini-3.1-flash-lite-image"},"google/gemini-3.1-pro-preview":{"id":"google/gemini-3.1-pro-preview","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"reasoning":12,"cache_read":0.2,"cache_write":0.375,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"google/gemini-3.5-flash":{"id":"google/gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.5,"output":9,"reasoning":9,"cache_read":0.15,"cache_write":0.083333},"canonical_model_id":"google/gemini-3.5-flash"},"google/gemini-2.5-pro-preview":{"id":"google/gemini-2.5-pro-preview","name":"Gemini 2.5 Pro Preview 06-05","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01-31","release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["pdf","image","text","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.25,"output":10,"reasoning":10,"cache_read":0.125,"cache_write":0.375,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro-preview"},"google/gemini-3.8-flash":{"id":"google/gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.825,"output":4.125,"reasoning":4.125,"cache_read":0.0825,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.8-flash"},"google/gemini-3.1-flash-lite":{"id":"google/gemini-3.1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.25,"output":1.5,"reasoning":1.5,"cache_read":0.025,"cache_write":0.083333},"canonical_model_id":"google/gemini-3.1-flash-lite"},"google/gemma-3-27b-it":{"id":"google/gemma-3-27b-it","name":"Gemma 3 27B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":117964},"cost":{"input":0.08,"output":0.35,"cache_read":0.04},"canonical_model_id":"google/gemma-3-27b-it"},"google/gemini-3.1-flash-image-preview":{"id":"google/gemini-3.1-flash-image-preview","type":"image","name":"Nano Banana 2 Preview","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-26","last_updated":"2026-02-26","modalities":{"input":["image","text"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":58982},"cost":{"input":0.5,"output":3},"canonical_model_id":"google/gemini-3.1-flash-image-preview"},"google/gemma-3-12b-it":{"id":"google/gemma-3-12b-it","name":"Gemma 3 12B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-08","release_date":"2025-03-12","last_updated":"2025-03-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"cost":{"input":0.05,"output":0.15},"canonical_model_id":"google/gemma-3-12b-it"},"google/gemini-nano-banana-2.1":{"id":"google/gemini-nano-banana-2.1","type":"image","name":"Nano Banana 2.1","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["image","text"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":58982},"cost":{"input":1.5,"output":7.5},"canonical_model_id":"google/gemini-nano-banana-2.1"},"google/gemini-3.1-pro-preview-customtools":{"id":"google/gemini-3.1-pro-preview-customtools","name":"Gemini 3.1 Pro Preview Custom Tools","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_details"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":2,"output":12,"reasoning":12,"cache_read":0.2,"cache_write":0.375,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview-customtools"},"google/gemini-3.6-flash":{"id":"google/gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.75,"output":3.75,"reasoning":3.75,"cache_read":0.075,"cache_write":0.041667},"canonical_model_id":"google/gemini-3.6-flash"},"nex-agi/nex-n2.5-pro":{"id":"nex-agi/nex-n2.5-pro","name":"Nex-N2.5-Pro","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"agi","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.075,"output":0.25,"cache_read":0.015}},"nex-agi/nex-n2.5-mini":{"id":"nex-agi/nex-n2.5-mini","name":"Nex-N2.5-Mini","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"agi","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","medium","high"]}],"tool_call":false,"structured_output":true,"temperature":true,"release_date":"2026-09-08","last_updated":"2026-09-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":235929},"cost":{"input":0.025,"output":0.1,"cache_read":0.0025}}}},"agentrouter":{"id":"agentrouter","env":["AGENTROUTER_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://agentrouter.org/v1","name":"AgentRouter","doc":"https://agentrouter.org/docs/opencode.html","models":{"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"canonical_model_id":"deepseek/deepseek-v4-flash"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://agentrouter.org/v1"},"canonical_model_id":"anthropic/claude-opus-5"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"canonical_model_id":"zhipuai/glm-5.3"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://agentrouter.org/v1"},"canonical_model_id":"anthropic/claude-opus-4-8"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"canonical_model_id":"openai/gpt-5.6-sol"}}},"opencode":{"id":"opencode","env":["OPENCODE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://opencode.ai/inference/openai/v1","name":"OpenCode","doc":"https://opencode.ai/v2/docs/console/models/","models":{"hy3-free":{"id":"hy3-free","name":"Hy3 Free","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":190000,"input":192000,"output":64000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"tencent/hy3"},"ll-alpha-free":{"id":"ll-alpha-free","name":"LL Alpha Free","description":"Best in class local model","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-06","release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"claude-sonnet-4-5":{"id":"claude-sonnet-4-5","name":"Claude Sonnet 4.5","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"gpt-6-sol":{"id":"gpt-6-sol","name":"GPT-6 Sol","description":"OpenAI model for complex coding and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-20","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-6-sol"},"gpt-6-luna":{"id":"gpt-6-luna","name":"GPT-6 Luna","description":"OpenAI's most efficient model for focused, high-volume tasks","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-05-18","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.2,"output":0.75,"cache_read":0.02,"cache_write":0.25}},"canonical_model_id":"openai/gpt-6-luna"},"muse-spark-1.3":{"id":"muse-spark-1.3","name":"Muse Spark 1.3","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.3"},"nemotron-3-super-free":{"id":"nemotron-3-super-free","name":"Nemotron 3 Super Free","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":128000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"kimi-k2-thinking":{"id":"kimi-k2-thinking","name":"Kimi K2 Thinking","description":"Legacy model retained for compatibility with older integrations","family":"kimi-thinking","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-08","release_date":"2025-11-06","last_updated":"2025-11-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.4,"output":2.5,"cache_read":0.4},"canonical_model_id":"moonshotai/kimi-k2-thinking"},"gpt-6.1-sol":{"id":"gpt-6.1-sol","name":"GPT-6.1 Sol","description":"Near-Astra performance for complex coding, computer use, and professional work at a lower cost.","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":2,"output":10,"cache_read":0.1,"cache_write":2.5,"tiers":[{"input":4,"output":15,"cache_read":0.2,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":15,"cache_read":0.2,"cache_write":5}},"canonical_model_id":"openai/gpt-6.1-sol"},"nemotron-3-ultra-free":{"id":"nemotron-3-ultra-free","name":"Nemotron 3 Ultra Free","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"minimax-m2.1":{"id":"minimax-m2.1","name":"MiniMax-M2.1","description":"Legacy model retained for compatibility with older integrations","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.1},"canonical_model_id":"minimax/MiniMax-M2.1"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"qwen3.6-plus-free":{"id":"qwen3.6-plus-free","name":"Qwen3.6 Plus Free","description":"Legacy model retained for compatibility with older integrations","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"alibaba/qwen3.6-plus"},"gpt-5.3-codex":{"id":"gpt-5.3-codex","name":"GPT-5.3 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex"},"claude-opus-4-6":{"id":"claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"gemini-3.7-flash":{"id":"gemini-3.7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://opencode.ai/inference/google/v1beta"},"cost":{"input":1.5,"output":7.5,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.7-flash"},"qwen3.8-flash":{"id":"qwen3.8-flash","name":"Qwen3.8 Flash","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":0.15,"output":0.47,"cache_read":0.016,"cache_write":0.2},"canonical_model_id":"alibaba/qwen3.8-flash"},"gpt-5-codex":{"id":"gpt-5-codex","name":"GPT-5 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-09-15","last_updated":"2025-09-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.07,"output":8.5,"cache_read":0.107},"canonical_model_id":"openai/gpt-5-codex"},"ling-3.0-flash-free":{"id":"ling-3.0-flash-free","name":"Ling-3.0-flash Free","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-23","last_updated":"2026-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"inclusionai/ling-3.0-flash"},"grok-build-0.1":{"id":"grok-build-0.1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1,"output":2,"cache_read":0.2},"canonical_model_id":"xai/grok-build-0.1"},"glm-4.7":{"id":"glm-4.7","name":"GLM-4.7","description":"Legacy model retained for compatibility with older integrations","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.6,"output":2.2,"cache_read":0.1},"canonical_model_id":"zhipuai/glm-4.7"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"mimo-v2.6-flash-free":{"id":"mimo-v2.6-flash-free","name":"MiMo-V2.6-Flash Free","description":"MiMo Flash model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.6-flash"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":3,"output":15,"cache_read":0.3},"canonical_model_id":"moonshotai/kimi-k3"},"big-pickle":{"id":"big-pickle","name":"Big Pickle","description":"Reasoning model for deliberate analysis, multi-step problem solving, and tool use","family":"big-pickle","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-10-17","last_updated":"2025-10-17","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"input":160000,"output":32000},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5"},"gpt-5.4-pro":{"id":"gpt-5.4-pro","name":"GPT-5.4 Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":30,"output":180,"cache_read":30},"canonical_model_id":"openai/gpt-5.4-pro"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-5"},"mimo-v2-flash-free":{"id":"mimo-v2-flash-free","name":"MiMo V2 Flash Free","description":"Legacy model retained for compatibility with older integrations","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12-01","release_date":"2025-12-16","last_updated":"2026-02-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2-flash"},"laguna-s-2.1-free":{"id":"laguna-s-2.1-free","name":"Laguna S 2.1 Free","description":"Agentic coding model from Poolside in the XS size class for local deployment","family":"laguna","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":32000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"poolside/laguna-s-2.1"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"beam-free":{"id":"beam-free","name":"Beam Free","description":"Sparse mixture-of-experts reasoning model with 23B active parameters for coding and agentic workflows","family":"beam","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-06-30","release_date":"2026-10-05","last_updated":"2026-10-16","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"reflection/beam-1.0-501b-a23b"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.006},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"kimi-k2.5-free":{"id":"kimi-k2.5-free","name":"Kimi K2.5 Free","description":"Legacy model retained for compatibility with older integrations","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"moonshotai/kimi-k2.5"},"glm-5":{"id":"glm-5","name":"GLM-5","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1,"output":3.2,"cache_read":0.2},"canonical_model_id":"zhipuai/glm-5"},"north-mini-code-free":{"id":"north-mini-code-free","name":"North Mini Code Free","description":"Cohere coding model for practical software engineering and agentic edits","family":"north","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":false,"temperature":true,"knowledge":"2025-09-23","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0},"canonical_model_id":"cohere/north-mini-code-1-0"},"gemini-3.1-pro":{"id":"gemini-3.1-pro","name":"Gemini 3.1 Pro Preview","description":"Advanced Gemini model for complex reasoning, coding, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://opencode.ai/inference/google/v1beta"},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"glm-5.3":{"id":"glm-5.3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"glm-5-free":{"id":"glm-5-free","name":"GLM-5 Free","description":"Legacy model retained for compatibility with older integrations","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-5"},"qwen3.8-max":{"id":"qwen3.8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":2,"output":6,"cache_read":0.25,"cache_write":2.5},"canonical_model_id":"alibaba/qwen3.8-max"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.74,"output":3.48,"cache_read":0.145},"canonical_model_id":"deepseek/deepseek-v4-pro"},"claude-opus-5-5":{"id":"claude-opus-5-5","name":"Claude Opus 5.5","description":"Claude model for long-running agentic coding and knowledge work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-22","last_updated":"2026-09-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":4,"output":20,"cache_read":0.2,"cache_write":5},"canonical_model_id":"anthropic/claude-opus-5-5"},"gpt-5.1":{"id":"gpt-5.1","name":"GPT-5.1","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.07,"output":8.5,"cache_read":0.107},"canonical_model_id":"openai/gpt-5.1"},"claude-haiku-4-5":{"id":"claude-haiku-4-5","name":"Claude Haiku 4.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"fledge-alpha-free":{"id":"fledge-alpha-free","name":"Fledge Alpha Free","description":"Free-tier preview reasoning model with text and image input and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"temperature":true,"release_date":"2026-10-01","last_updated":"2026-10-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0}},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5"},"gpt-5.3-codex-spark":{"id":"gpt-5.3-codex-spark","name":"GPT-5.3 Codex Spark","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex-spark","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2026-02-05","last_updated":"2026-02-05","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":128000,"input":128000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.3-codex-spark"},"trinity-large-preview-free":{"id":"trinity-large-preview-free","name":"Trinity Large Preview","description":"Legacy model retained for compatibility with older integrations","family":"trinity","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-01-27","last_updated":"2026-05-28","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0},"canonical_model_id":"arcee-ai/trinity-large-preview"},"gemini-3-flash":{"id":"gemini-3-flash","name":"Gemini 3 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://opencode.ai/inference/google/v1beta"},"cost":{"input":0.5,"output":3,"cache_read":0.05},"canonical_model_id":"google/gemini-3-flash-preview"},"muse-spark-1.2":{"id":"muse-spark-1.2","name":"Muse Spark 1.2","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.25,"output":4.25,"cache_read":0.15},"canonical_model_id":"meta/muse-spark-1.2"},"ling-3.0-flash-fin-free":{"id":"ling-3.0-flash-fin-free","name":"Ling 3.0 Flash Fin Free","description":"Finance-enhanced model for financial research, multi-step investment workflows, and long-horizon planning and execution","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-27","last_updated":"2026-09-03","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"inclusionai/ling-3.0-flash-fin"},"glm-5.3-flash":{"id":"glm-5.3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"mimo-v2-omni-free":{"id":"mimo-v2-omni-free","name":"MiMo V2 Omni Free","description":"Legacy model retained for compatibility with older integrations","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text","image","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":64000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2-omni"},"grok-4.7":{"id":"grok-4.7","name":"Grok 4.7","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-05","release_date":"2026-09-21","last_updated":"2026-09-21","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.7"},"gpt-5.6-luna":{"id":"gpt-5.6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"},"deepseek-v4-flash-free":{"id":"deepseek-v4-flash-free","name":"DeepSeek V4 Flash Free","description":"Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-07-31","last_updated":"2026-07-31","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":128000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4-flash-0731"},"deepseek-v4.1-flash-free":{"id":"deepseek-v4.1-flash-free","name":"DeepSeek V4.1 Flash Free","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"ling-3.1-flash-free":{"id":"ling-3.1-flash-free","name":"Ling 3.1 Flash Free","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-09-29","last_updated":"2026-09-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"inclusionai/ling-3.1-flash"},"ling-3.0-tiny-free":{"id":"ling-3.0-tiny-free","name":"Ling-3.0-tiny Free","description":"Compact MoE model for responsive agents, instruction following, and multi-turn conversations","family":"ling","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2026-08-06","last_updated":"2026-08-06","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":32768},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0}},"flint-40b-free":{"id":"flint-40b-free","name":"Flint 40B Free","description":"Open-weight mixture-of-experts model with about 2.5B active parameters for local coding agents","family":"flint","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-06","release_date":"2026-10-21","last_updated":"2026-10-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"recursive/flint"},"kimi-k2.5":{"id":"kimi-k2.5","name":"Kimi K2.5","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"knowledge":"2025-01","release_date":"2026-01-27","last_updated":"2026-01-27","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.6,"output":3,"cache_read":0.1},"canonical_model_id":"moonshotai/kimi-k2.5"},"claude-haiku-5-5":{"id":"claude-haiku-5-5","name":"Claude Haiku 5.5","description":"Fast Claude model for responsive assistance, classification, and lightweight agents","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-10-07","last_updated":"2026-10-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":0.1,"output":0.5,"cache_read":0.01,"cache_write":0.125,"tiers":[{"input":0.5,"output":2.5,"cache_read":0.05,"cache_write":0.625,"tier":{"type":"context","size":100000}}]},"canonical_model_id":"anthropic/claude-haiku-5-5"},"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"hy3-preview-free":{"id":"hy3-preview-free","name":"Hy3 preview Free","description":"Legacy model retained for compatibility with older integrations","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"output":64000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"tencent/hy3-preview"},"minimax-m2.5":{"id":"minimax-m2.5","name":"MiniMax-M2.5","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.5"},"nemotron-3.5-super-vl-free":{"id":"nemotron-3.5-super-vl-free","name":"Nemotron 3.5 Super VL Free","description":"NVIDIA vision-language reasoning model for text, image, and video understanding and agentic tool use","family":"nemotron","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-10-15","last_updated":"2026-10-15","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"input":1048576,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"nvidia/nemotron-3.5-super-vl-120b-a12b"},"gemini-4-argon":{"id":"gemini-4-argon","name":"Gemini 4 Argon","description":"Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents","family":"gemini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-03","release_date":"2026-10-13","last_updated":"2026-10-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://opencode.ai/inference/google/v1beta"},"cost":{"input":2,"output":10,"cache_read":0.1,"input_audio":2},"canonical_model_id":"google/gemini-4-argon"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 Mini","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"glm-4.7-free":{"id":"glm-4.7-free","name":"GLM-4.7 Free","description":"Legacy model retained for compatibility with older integrations","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2025-12-22","last_updated":"2025-12-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-4.7"},"gemini-3.5-flash-lite":{"id":"gemini-3.5-flash-lite","name":"Gemini 3.5 Flash Lite","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://opencode.ai/inference/google/v1beta"},"cost":{"input":0.3,"output":2.5,"cache_read":0.03},"canonical_model_id":"google/gemini-3.5-flash-lite"},"nemotron-3.5-lightning-free":{"id":"nemotron-3.5-lightning-free","name":"Nemotron 3.5 Lightning Free","description":"Fast NVIDIA Nemotron MoE for reliable agentic tasks across enterprise workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-08-11","last_updated":"2026-08-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"nvidia/nemotron-3.5-lightning"},"claude-fable-5-1":{"id":"claude-fable-5-1","name":"Claude Fable 5.1","description":"Claude model for demanding reasoning and long-horizon agentic work","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-01","last_updated":"2026-09-01","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":10,"output":50,"cache_read":0.25,"cache_write":12.5},"canonical_model_id":"anthropic/claude-fable-5-1"},"muse-spark-1.2-contributor-free":{"id":"muse-spark-1.2-contributor-free","name":"Muse Spark 1.2 Free","description":"Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-05","last_updated":"2026-08-05","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"status":"deprecated","provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"meta/muse-spark-1.2"},"exo-free":{"id":"exo-free","name":"Exo Free","description":"Free-tier preview reasoning model with text and image input and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["high"]}],"tool_call":true,"temperature":false,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0}},"gpt-5.1-codex-max":{"id":"gpt-5.1-codex-max","name":"GPT-5.1 Codex Max","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1-codex-max"},"kimi-k2.6":{"id":"kimi-k2.6","name":"Kimi K2.6","description":"Kimi multimodal agent model for visual understanding, coding, and planning","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.95,"output":4,"cache_read":0.16},"canonical_model_id":"moonshotai/kimi-k2.6"},"step-5-preview-free":{"id":"step-5-preview-free","name":"Step 5 Preview Free","description":"StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-09-16","last_updated":"2026-09-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"input":1000000,"output":65536},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"stepfun/step-5-preview"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-8"},"glm-5.1":{"id":"glm-5.1","name":"GLM-5.1","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-04","release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.1"},"gpt-5.6-sol":{"id":"gpt-5.6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"minimax-m3-free":{"id":"minimax-m3-free","name":"MiniMax-M3 Free","description":"Legacy model retained for compatibility with older integrations","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"minimax/MiniMax-M3"},"longcat-2.5-preview-free":{"id":"longcat-2.5-preview-free","name":"LongCat 2.5 Preview Free","description":"Meituan's multimodal reasoning model for coding and agent tasks, with image understanding and a 1M-token context window","family":"longcat","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":false,"release_date":"2026-09-25","last_updated":"2026-09-25","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"meituan/longcat-2.5-preview"},"cat-jam-free":{"id":"cat-jam-free","name":"Cat Jam Free","description":"A text-only reasoning model for coding and agentic workflows, with tool calling and structured JSON outputs.","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"gpt-5.2-codex":{"id":"gpt-5.2-codex","name":"GPT-5.2 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2-codex"},"glm-4.6":{"id":"glm-4.6","name":"GLM-4.6","description":"Legacy model retained for compatibility with older integrations","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-09-30","last_updated":"2025-09-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.6,"output":2.2,"cache_read":0.1},"canonical_model_id":"zhipuai/glm-4.6"},"longcat-2.0-free":{"id":"longcat-2.0-free","name":"LongCat-2.0 Free","description":"Meituan LongCat-2.0, a reasoning model with tool calling and a 1M-token context window","family":"longcat","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"meituan/longcat-2.0"},"mistral-large-4":{"id":"mistral-large-4","name":"Mistral Large 4","description":"Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work","family":"mistral-large","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-06","last_updated":"2026-10-06","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":524288,"output":262144},"provider":{"npm":"@ai-sdk/mistral","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.68,"output":2.09,"cache_read":0.07},"canonical_model_id":"mistral/mistral-large-4"},"claude-3-5-haiku":{"id":"claude-3-5-haiku","name":"Claude Haiku 3.5","description":"Legacy model retained for compatibility with older integrations","family":"claude-haiku","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-07-31","release_date":"2024-10-22","last_updated":"2024-10-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":8192},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":0.8,"output":4,"cache_read":0.08,"cache_write":1},"canonical_model_id":"anthropic/claude-3-5-haiku-20241022"},"gpt-5.5-pro":{"id":"gpt-5.5-pro","name":"GPT-5.5 Pro","description":"Frontier GPT model for professional reasoning, coding, and multimodal work","family":"gpt-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["medium","high","xhigh"]}],"tool_call":true,"structured_output":false,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":30,"output":180,"cache_read":30},"canonical_model_id":"openai/gpt-5.5-pro"},"grok-4.6":{"id":"grok-4.6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":2,"output":6,"cache_read":0.5,"tiers":[{"input":4,"output":12,"cache_read":1,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":1}},"canonical_model_id":"xai/grok-4.6"},"claude-sonnet-4":{"id":"claude-sonnet-4","name":"Claude Sonnet 4","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75,"tiers":[{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":6,"output":22.5,"cache_read":0.6,"cache_write":7.5}},"canonical_model_id":"anthropic/claude-sonnet-4-0"},"gemini-3-pro":{"id":"gemini-3-pro","name":"Gemini 3 Pro","description":"Legacy model retained for compatibility with older integrations","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","provider":{"npm":"@ai-sdk/google","api":"https://opencode.ai/inference/google/v1beta"},"cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3-pro-preview"},"gemini-3.5-flash":{"id":"gemini-3.5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://opencode.ai/inference/google/v1beta"},"cost":{"input":1.5,"output":9,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.5-flash"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"interleaved":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"x-preview-f-free":{"id":"x-preview-f-free","name":"Ox Alpha Free (Unlimited)","description":"Stealth reasoning model for coding, agentic tasks, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-08-21","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0}},"grok-code":{"id":"grok-code","name":"Grok Code Fast 1","description":"Legacy model retained for compatibility with older integrations","family":"grok","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2025-09-02","last_updated":"2025-09-02","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0},"canonical_model_id":"xai/grok-code-fast-1"},"minimax-m2.7":{"id":"minimax-m2.7","name":"MiniMax-M2.7","description":"MiniMax model for chat, coding, office work, and agentic tasks","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-01","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M2.7"},"gpt-5.1-codex":{"id":"gpt-5.1-codex","name":"GPT-5.1 Codex","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.07,"output":8.5,"cache_read":0.107},"canonical_model_id":"openai/gpt-5.1-codex"},"space-bunny-free":{"id":"space-bunny-free","name":"Space Bunny Free","description":"Anonymous preview reasoning model for coding, agentic tasks, tool use, and multimodal input","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"release_date":"2026-09-23","last_updated":"2026-09-23","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"input":524288,"output":524288},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0,"cache_write":0}},"muse-spark-1.3-contributor-free":{"id":"muse-spark-1.3-contributor-free","name":"Muse Spark 1.3 Free","description":"Muse Spark 1.3 is a multimodal reasoning model from Meta for coding and agentic workflows.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"status":"deprecated","provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"meta/muse-spark-1.3"},"kimi-k2":{"id":"kimi-k2","name":"Kimi K2","description":"Legacy model retained for compatibility with older integrations","family":"kimi-k2","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-10","release_date":"2025-09-05","last_updated":"2025-09-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.4,"output":2.5,"cache_read":0.4},"canonical_model_id":"moonshotai/kimi-k2-0905"},"gemini-3.8-flash":{"id":"gemini-3.8-flash","name":"Gemini 3.8 Flash","description":"Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-09-02","last_updated":"2026-09-02","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://opencode.ai/inference/google/v1beta"},"cost":{"input":1.5,"output":7.5,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.8-flash"},"grok-4.5":{"id":"grok-4.5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":2,"output":6,"cache_read":0.3,"tiers":[{"input":4,"output":12,"cache_read":0.6,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":12,"cache_read":0.6}},"canonical_model_id":"xai/grok-4.5"},"qwen3.6-plus":{"id":"qwen3.6-plus","name":"Qwen3.6 Plus","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":0.5,"output":3,"cache_read":0.05,"cache_write":0.625},"canonical_model_id":"alibaba/qwen3.6-plus"},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"minimax-m2.1-free":{"id":"minimax-m2.1-free","name":"MiniMax-M2.1 Free","description":"Legacy model retained for compatibility with older integrations","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-23","last_updated":"2025-12-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"minimax/MiniMax-M2.1"},"deepseek-v4-flash-vision-exp":{"id":"deepseek-v4-flash-vision-exp","name":"DeepSeek V4 Flash Vision Exp","description":"Experimental multimodal DeepSeek V4 Flash model for image understanding, coding, and agentic work","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-21","last_updated":"2026-09-01","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.14,"output":0.28,"cache_read":0.028},"canonical_model_id":"deepseek/deepseek-v4-flash-vision-exp"},"gpt-5.6-terra":{"id":"gpt-5.6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"gpt-5":{"id":"gpt-5","name":"GPT-5","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.07,"output":8.5,"cache_read":0.107},"canonical_model_id":"openai/gpt-5"},"claude-sonnet-5-5":{"id":"claude-sonnet-5-5","name":"Claude Sonnet 5.5","description":"Fast Claude model for everyday coding, agents, and knowledge work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-06","release_date":"2026-09-28","last_updated":"2026-09-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":2,"output":10,"cache_read":0.2,"cache_write":2.5},"canonical_model_id":"anthropic/claude-sonnet-5-5"},"muse-wonder-1.0":{"id":"muse-wonder-1.0","name":"Muse Wonder","description":"Muse Wonder is a frontier multimodal reasoning model from Meta for personal and professional agents, long-horizon coding, and computer use. It combines Active Memory, which carries relevant context across conversations, with Active Focus, which keeps it working through blockers toward a goal.","family":"muse","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-10-12","last_updated":"2026-10-12","modalities":{"input":["text","image","video","pdf","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":131072},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":4,"output":20,"cache_read":0.2},"canonical_model_id":"meta/muse-wonder-1.0"},"glm-5.3-flash-free":{"id":"glm-5.3-flash-free","name":"GLM-5.3-Flash Free","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-5.3-flash"},"gpt-5-nano":{"id":"gpt-5-nano","name":"GPT-5 Nano","description":"Compact GPT model for low-latency assistance and high-volume workloads","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":512000,"output":128000},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.3,"output":1.2,"cache_read":0.06},"canonical_model_id":"minimax/MiniMax-M3"},"kimi-k2.7-code":{"id":"kimi-k2.7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"gpt-5.1-codex-mini":{"id":"gpt-5.1-codex-mini","name":"GPT-5.1 Codex Mini","description":"Coding-optimized GPT model for repository edits, reviews, and agentic software work","family":"gpt-codex","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5.1-codex-mini"},"mimo-v2.5-free":{"id":"mimo-v2.5-free","name":"MiMo V2.5 Free","description":"MiMo omni model for text, image, video, audio, and agents","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":32000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2.5"},"claude-opus-4-1":{"id":"claude-opus-4-1","name":"Claude Opus 4.1","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1"},"qwen3-coder":{"id":"qwen3-coder","name":"Qwen3 Coder","description":"Legacy model retained for compatibility with older integrations","family":"qwen","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2025-07-22","last_updated":"2025-07-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0.45,"output":1.8},"canonical_model_id":"alibaba/qwen3-coder-480b-a35b-instruct"},"claude-opus-4-5":{"id":"claude-opus-4-5","name":"Claude Opus 4.5","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]},{"type":"budget_tokens","min":1024}],"tool_call":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"minimax-m2.5-free":{"id":"minimax-m2.5-free","name":"MiniMax-M2.5 Free","description":"Legacy model retained for compatibility with older integrations","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-12","last_updated":"2026-02-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"status":"deprecated","provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"minimax/MiniMax-M2.5"},"ring-2.6-1t-free":{"id":"ring-2.6-1t-free","name":"Ring 2.6 1T Free","description":"Legacy model retained for compatibility with older integrations","family":"ring-1t-free","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2025-06","release_date":"2026-05-08","last_updated":"2026-05-08","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262000,"output":66000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0}},"minimax-m3.1-flash-free":{"id":"minimax-m3.1-flash-free","name":"MiniMax M3.1 Flash Free","description":"Frontier multimodal coding model with 1M context window and tunable thinking depth","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"release_date":"2026-10-19","last_updated":"2026-10-19","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":512000},"provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"minimax/MiniMax-M3.1-Flash"},"qwen3.5-plus":{"id":"qwen3.5-plus","name":"Qwen3.5 Plus","description":"Multimodal reasoning model for visual analysis, planning, and tool use","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"budget_tokens"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-02-16","last_updated":"2026-02-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"provider":{"npm":"@ai-sdk/anthropic","api":"https://opencode.ai/inference/anthropic/v1"},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25},"canonical_model_id":"alibaba/qwen3.5-plus"},"ling-2.6-flash-free":{"id":"ling-2.6-flash-free","name":"Ling 2.6 Flash Free","description":"Legacy model retained for compatibility with older integrations","family":"ling-flash-free","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262100,"output":32800},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0}},"gpt-5.2":{"id":"gpt-5.2","name":"GPT-5.2","description":"GPT model for general reasoning, writing, coding, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"gpt-6-astra":{"id":"gpt-6-astra","name":"GPT-6 Astra","description":"GPT-6 Astra is OpenAI's most capable model for complex reasoning, coding, computer use, research, and document creation.","family":"gpt-astra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-04-30","release_date":"2026-09-04","last_updated":"2026-09-04","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"provider":{"npm":"@ai-sdk/openai","api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":10,"output":50,"cache_read":1,"cache_write":12.5,"tiers":[{"input":20,"output":75,"cache_read":2,"cache_write":25,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":20,"output":75,"cache_read":2,"cache_write":25}},"canonical_model_id":"openai/gpt-6-astra"},"gemini-3.6-flash":{"id":"gemini-3.6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"provider":{"npm":"@ai-sdk/google","api":"https://opencode.ai/inference/google/v1beta"},"cost":{"input":1.5,"output":7.5,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.6-flash"},"mimo-v2-pro-free":{"id":"mimo-v2-pro-free","name":"MiMo V2 Pro Free","description":"Legacy model retained for compatibility with older integrations","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"interleaved":{"field":"reasoning_content"},"temperature":true,"knowledge":"2024-12","release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":64000},"status":"deprecated","provider":{"api":"https://opencode.ai/inference/openai/v1"},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"xiaomi/mimo-v2-pro"}}},"databricks":{"id":"databricks","env":["DATABRICKS_HOST","DATABRICKS_TOKEN"],"npm":"@ai-sdk/openai-compatible","api":"https://${DATABRICKS_HOST}/ai-gateway/mlflow/v1","name":"Databricks","doc":"https://docs.databricks.com/aws/en/machine-learning/foundation-models/","models":{"databricks-gpt-5-1":{"id":"databricks-gpt-5-1","name":"GPT-5.1","description":"Sharper GPT-5 generation for coding, product work, and tool-assisted tasks","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-09-30","release_date":"2025-11-13","last_updated":"2025-11-13","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":2.5,"output":20,"cache_read":0.25},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5.1"},"databricks-gemini-3-pro":{"id":"databricks-gemini-3-pro","name":"Gemini 3 Pro Preview","description":"Preview Gemini flagship for complex reasoning, coding, and rich multimodal prompts","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-11-18","last_updated":"2025-11-18","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":2,"output":12,"cache_read":0.2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3-pro-preview"},"databricks-claude-opus-4-7":{"id":"databricks-claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-7"},"databricks-gpt-oss-120b":{"id":"databricks-gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":25000},"cost":{"input":0.15,"output":0.6},"canonical_model_id":"openai/gpt-oss-120b"},"databricks-gemini-3-5-flash":{"id":"databricks-gemini-3-5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"experimental":{"modes":{"fast":{"cost":{"input":2.7,"output":16.2,"cache_read":0.27,"input_audio":2.7},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":1.5,"output":9,"cache_read":0.15,"input_audio":1.5},"canonical_model_id":"google/gemini-3.5-flash"},"databricks-gemini-3-flash":{"id":"databricks-gemini-3-flash","name":"Gemini 3 Flash Preview","description":"New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-12-17","last_updated":"2025-12-17","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"experimental":{"modes":{"fast":{"cost":{"input":0.9,"output":5.4,"cache_read":0.09,"input_audio":1.8},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.5,"output":3,"cache_read":0.05,"input_audio":1},"canonical_model_id":"google/gemini-3-flash-preview"},"databricks-claude-sonnet-4":{"id":"databricks-claude-sonnet-4","name":"Claude Sonnet 4","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-05-22","last_updated":"2025-05-22","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"status":"deprecated","cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-20250514"},"databricks-gpt-5-5":{"id":"databricks-gpt-5-5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":12.5,"output":75,"cache_read":1.25},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":5,"output":30,"cache_read":0.5,"tiers":[{"input":10,"output":45,"cache_read":1,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":10,"output":45,"cache_read":1}},"canonical_model_id":"openai/gpt-5.5"},"databricks-gpt-5-4-nano":{"id":"databricks-gpt-5-4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.2,"output":1.25,"cache_read":0.02},"canonical_model_id":"openai/gpt-5.4-nano"},"databricks-gpt-5-4-mini":{"id":"databricks-gpt-5-4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":1.5,"output":9,"cache_read":0.15},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.75,"output":4.5,"cache_read":0.075},"canonical_model_id":"openai/gpt-5.4-mini"},"databricks-claude-opus-4-5":{"id":"databricks-claude-opus-4-5","name":"Claude Opus 4.5 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2025-11-24","last_updated":"2025-11-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-5"},"databricks-claude-sonnet-4-6":{"id":"databricks-claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"databricks-gpt-5":{"id":"databricks-gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":2.5,"output":20,"cache_read":0.25},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":1.25,"output":10,"cache_read":0.125},"canonical_model_id":"openai/gpt-5"},"databricks-gpt-5-nano":{"id":"databricks-gpt-5-nano","name":"GPT-5 Nano","description":"Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"cost":{"input":0.05,"output":0.4,"cache_read":0.005},"canonical_model_id":"openai/gpt-5-nano"},"databricks-claude-opus-4-1":{"id":"databricks-claude-opus-4-1","name":"Claude Opus 4.1 (latest)","description":"Flagship Claude model for deep reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-03-31","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":32000},"cost":{"input":15,"output":75,"cache_read":1.5,"cache_write":18.75},"canonical_model_id":"anthropic/claude-opus-4-1"},"databricks-kimi-k2-7-code":{"id":"databricks-kimi-k2-7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0.95,"output":4,"cache_read":0.19},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"databricks-gemini-3-1-pro":{"id":"databricks-gemini-3-1-pro","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"experimental":{"modes":{"fast":{"cost":{"input":3.6,"output":21.6,"cache_read":0.36,"input_audio":3.6},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2,"output":12,"cache_read":0.2,"input_audio":2,"tiers":[{"input":4,"output":18,"cache_read":0.4,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4}},"canonical_model_id":"google/gemini-3.1-pro-preview"},"databricks-gemini-2-5-pro":{"id":"databricks-gemini-2-5-pro","name":"Gemini 2.5 Pro","description":"Google's proven reasoning model for coding, math, and multimodal analysis","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":128,"max":32768}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":1.25,"output":10,"cache_read":0.125,"tiers":[{"input":2.5,"output":15,"cache_read":0.25,"tier":{"type":"context","size":200000}}],"context_over_200k":{"input":2.5,"output":15,"cache_read":0.25}},"canonical_model_id":"google/gemini-2.5-pro"},"databricks-gpt-5-mini":{"id":"databricks-gpt-5-mini","name":"GPT-5 Mini","description":"Small GPT-5 for responsive agents, coding help, and everyday automation","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":0.45,"output":3.6,"cache_read":0.045},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.25,"output":2,"cache_read":0.025},"canonical_model_id":"openai/gpt-5-mini"},"databricks-gpt-oss-20b":{"id":"databricks-gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":25000},"cost":{"input":0.07,"output":0.3},"canonical_model_id":"openai/gpt-oss-20b"},"databricks-gpt-5-6-terra":{"id":"databricks-gpt-5-6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":4,"output":24,"cache_read":0.4,"cache_write":5},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2,"output":12,"cache_read":0.2,"cache_write":2.5,"tiers":[{"input":4,"output":18,"cache_read":0.4,"cache_write":5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":4,"output":18,"cache_read":0.4,"cache_write":5}},"canonical_model_id":"openai/gpt-5.6-terra"},"databricks-gpt-5-6-sol":{"id":"databricks-gpt-5-6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":8,"output":40,"cache_read":0.8,"cache_write":10},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":4,"output":20,"cache_read":0.4,"cache_write":5,"tiers":[{"input":8,"output":30,"cache_read":0.8,"cache_write":10,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":8,"output":30,"cache_read":0.8,"cache_write":10}},"canonical_model_id":"openai/gpt-5.6-sol"},"databricks-gemini-3-1-flash-lite":{"id":"databricks-gemini-3-1-flash-lite","name":"Gemini 3.1 Flash Lite Preview","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-03-03","last_updated":"2026-03-03","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"experimental":{"modes":{"fast":{"cost":{"input":0.45,"output":2.7,"cache_read":0.045,"input_audio":0.9},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.25,"output":1.5,"cache_read":0.025,"input_audio":0.5},"canonical_model_id":"google/gemini-3.1-flash-lite-preview"},"databricks-glm-5-2":{"id":"databricks-glm-5-2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"experimental":{"modes":{"fast":{"cost":{"input":2.45,"output":7.7,"cache_read":0.455},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"databricks-gpt-5-2":{"id":"databricks-gpt-5-2","name":"GPT-5.2","description":"Reliable GPT generation for broad coding, writing, and tool-assisted product work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2025-12-11","last_updated":"2025-12-11","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":3.5,"output":28,"cache_read":0.35},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":1.75,"output":14,"cache_read":0.175},"canonical_model_id":"openai/gpt-5.2"},"databricks-claude-sonnet-4-5":{"id":"databricks-claude-sonnet-4-5","name":"Claude Sonnet 4.5 (latest)","description":"Balanced Claude model for coding, analysis, agent workflows, and cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-07-31","release_date":"2025-09-29","last_updated":"2025-09-29","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":3,"output":15,"cache_read":0.3,"cache_write":3.75},"canonical_model_id":"anthropic/claude-sonnet-4-5"},"databricks-claude-haiku-4-5":{"id":"databricks-claude-haiku-4-5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"cost":{"input":1,"output":5,"cache_read":0.1,"cache_write":1.25},"canonical_model_id":"anthropic/claude-haiku-4-5"},"databricks-claude-opus-4-6":{"id":"databricks-claude-opus-4-6","name":"Claude Opus 4.6","description":"High-end Claude for difficult coding, planning, and slower expert reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":1024}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05-31","release_date":"2026-02-05","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5,"output":25,"cache_read":0.5,"cache_write":6.25},"canonical_model_id":"anthropic/claude-opus-4-6"},"databricks-gpt-5-4":{"id":"databricks-gpt-5-4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":5,"output":30,"cache_read":0.5},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":2.5,"output":15,"cache_read":0.25,"tiers":[{"input":5,"output":22.5,"cache_read":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":5,"output":22.5,"cache_read":0.5}},"canonical_model_id":"openai/gpt-5.4"},"databricks-gemini-2-5-flash":{"id":"databricks-gemini-2-5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens","min":0,"max":24576}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":0.3,"output":2.5,"cache_read":0.03,"input_audio":1},"canonical_model_id":"google/gemini-2.5-flash"},"databricks-gpt-5-6-luna":{"id":"databricks-gpt-5-6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"experimental":{"modes":{"fast":{"cost":{"input":0.4,"output":2.4,"cache_read":0.04,"cache_write":0.5},"provider":{"body":{"service_tier":"priority"}}}}},"cost":{"input":0.2,"output":1.2,"cache_read":0.02,"cache_write":0.25,"tiers":[{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5,"tier":{"type":"context","size":272000}}],"context_over_200k":{"input":0.4,"output":1.8,"cache_read":0.04,"cache_write":0.5}},"canonical_model_id":"openai/gpt-5.6-luna"}}},"groq":{"id":"groq","env":["GROQ_API_KEY"],"npm":"@ai-sdk/groq","name":"Groq","doc":"https://console.groq.com/docs/models","models":{"whisper-large-v3-turbo":{"id":"whisper-large-v3-turbo","type":"transcription","name":"Whisper Large V3 Turbo","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"whisper","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-10-01","last_updated":"2024-10-01","modalities":{"input":["audio"],"output":["text"]},"open_weights":true,"limit":{"context":448,"output":448},"canonical_model_id":"openai/whisper-large-v3-turbo"},"allam-2-7b":{"id":"allam-2-7b","name":"ALLaM-2-7b","description":"ALLaM-2-7b instruction tuned model by SDAIA","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-01-23","last_updated":"2025-01-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":4096,"output":4096},"cost":{"input":0,"output":0},"canonical_model_id":"sdaia/allam-2-7b"},"llama-3.3-70b-versatile":{"id":"llama-3.3-70b-versatile","name":"Llama 3.3 70B","description":"Open Llama instruction model for multilingual chat, reasoning, and coding","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"status":"deprecated","cost":{"input":0.59,"output":0.79},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"whisper-large-v3":{"id":"whisper-large-v3","type":"transcription","name":"Whisper","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"whisper","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2023-11-06","last_updated":"2023-11-06","modalities":{"input":["audio"],"output":["text"]},"open_weights":true,"limit":{"context":448,"output":448},"canonical_model_id":"openai/whisper-large-v3"},"llama-3.1-8b-instant":{"id":"llama-3.1-8b-instant","name":"Llama 3.1 8B","description":"Compact Llama instruction model for fast chat and local deployment","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-07-23","last_updated":"2024-07-23","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"status":"deprecated","cost":{"input":0.05,"output":0.08},"canonical_model_id":"meta/llama-3.1-8b-instruct"},"canopylabs/orpheus-v1-english":{"id":"canopylabs/orpheus-v1-english","type":"speech","name":"Canopy Labs Orpheus V1 English","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"canopylabs","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-19","last_updated":"2025-12-19","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":4000,"output":50000},"status":"beta","provider":{"npm":"@ai-sdk/openai","api":"https://api.groq.com/openai/v1"},"canonical_model_id":"canopylabs/orpheus-v1-english"},"canopylabs/orpheus-arabic-saudi":{"id":"canopylabs/orpheus-arabic-saudi","type":"speech","name":"Canopy Labs Orpheus Arabic Saudi","description":"Speech generation model for controllable voice, narration, and audio delivery","family":"canopylabs","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-12-16","last_updated":"2025-12-16","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":4000,"output":50000},"status":"beta","provider":{"npm":"@ai-sdk/openai","api":"https://api.groq.com/openai/v1"},"canonical_model_id":"canopylabs/orpheus-arabic-saudi"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.15,"output":0.6,"cache_read":0.075},"canonical_model_id":"openai/gpt-oss-120b"},"openai/gpt-oss-safeguard-20b":{"id":"openai/gpt-oss-safeguard-20b","name":"Safety GPT OSS 20B","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2025-10-29","last_updated":"2025-10-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"status":"beta","cost":{"input":0.075,"output":0.3,"cache_read":0.0375},"canonical_model_id":"openai/gpt-oss-safeguard-20b"},"openai/gpt-oss-20b":{"id":"openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":65536},"cost":{"input":0.075,"output":0.3,"cache_read":0.0375},"canonical_model_id":"openai/gpt-oss-20b"},"groq/compound":{"id":"groq/compound","name":"Compound","description":"General-purpose chat model for instruction following, writing, and analysis","family":"groq","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-09-04","last_updated":"2025-09-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"status":"deprecated"},"groq/compound-mini":{"id":"groq/compound-mini","name":"Compound Mini","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"groq","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2025-09-04","last_updated":"2025-09-04","modalities":{"input":["text"],"output":["text"]},"open_weights":false,"limit":{"context":131072,"output":8192},"status":"deprecated"},"qwen/qwen3.6-27b":{"id":"qwen/qwen3.6-27b","name":"Qwen3.6 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","default"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"status":"deprecated","cost":{"input":0.6,"output":3,"cache_read":0.3},"canonical_model_id":"alibaba/qwen3.6-27b"},"qwen/qwen3.8-27b":{"id":"qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","default","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":16384},"status":"beta","cost":{"input":0.8,"output":4},"canonical_model_id":"alibaba/qwen3.8-27b"},"meta-llama/llama-prompt-guard-2-22m":{"id":"meta-llama/llama-prompt-guard-2-22m","name":"Llama Prompt Guard 2 22M","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-04-29","last_updated":"2025-04-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512,"output":512},"status":"beta","cost":{"input":0.03,"output":0.03},"canonical_model_id":"meta/llama-prompt-guard-2-22m"},"meta-llama/llama-prompt-guard-2-86m":{"id":"meta-llama/llama-prompt-guard-2-86m","name":"Prompt Guard 2 86M","description":"Safety model for policy screening, moderation, and risk-aware routing workflows","family":"llama","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-04-29","last_updated":"2025-04-29","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512,"output":512},"status":"beta","cost":{"input":0.04,"output":0.04},"canonical_model_id":"meta/llama-prompt-guard-2-86m"}}},"kenari":{"id":"kenari","env":["KENARI_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://kenari.id/v1","name":"Kenari","doc":"https://kenari.id/docs","models":{"gpt-image-2":{"id":"gpt-image-2","type":"image","name":"GPT-Image-2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gpt-image","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-04-21","last_updated":"2026-04-21","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":272000,"output":16384},"canonical_model_id":"openai/gpt-image-2"},"kimi-k2-7-code":{"id":"kimi-k2-7-code","name":"Kimi K2.7 Code","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.57142857,"output":2.85714286,"cache_read":0.11428571},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"deepseek-v4-flash:free":{"id":"deepseek-v4-flash:free","name":"DeepSeek V4 Flash (Free)","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"deepseek/deepseek-v4-flash"},"gpt-oss-120b":{"id":"gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.036,"output":0.2,"cache_read":0.0036},"canonical_model_id":"openai/gpt-oss-120b"},"gemini-3-1-pro":{"id":"gemini-3-1-pro","name":"Gemini 3.1 Pro Preview","description":"Reasoning-first Gemini preview for agentic coding and complex problem solving","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-02-19","last_updated":"2026-02-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":1.2,"output":7.14285714,"cache_read":0.12,"cache_write":0.22285714},"canonical_model_id":"google/gemini-3.1-pro-preview"},"claude-opus-4-7":{"id":"claude-opus-4-7","name":"Claude Opus 4.7","description":"Stronger Opus tier for advanced software work and high-stakes reasoning","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.71428571,"output":29.71428571,"cache_read":0.57142857,"cache_write":7.42857143},"canonical_model_id":"anthropic/claude-opus-4-7"},"gemini-2-5-flash-lite":{"id":"gemini-2-5-flash-lite","name":"Gemini 2.5 Flash-Lite","description":"Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","canonical_model_id":"google/gemini-2.5-flash-lite"},"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15714286,"output":0.31428571,"cache_read":0.00371429},"canonical_model_id":"deepseek/deepseek-v4-flash"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"cost":{"input":0.85714286,"output":8.57142857,"cache_read":0.11428571},"canonical_model_id":"moonshotai/kimi-k3"},"qwen3-8-max":{"id":"qwen3-8-max","name":"Qwen3.8 Max","description":"2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"temperature":true,"release_date":"2026-08-03","last_updated":"2026-08-03","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":131072},"cost":{"input":2.4,"output":6.85714286,"cache_read":0.29714286,"cache_write":2.97142857},"canonical_model_id":"alibaba/qwen3.8-max"},"gpt-5-5":{"id":"gpt-5-5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"cost":{"input":5.71428571,"output":36,"cache_read":0.57142857},"canonical_model_id":"openai/gpt-5.5"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":12,"output":57.14285714,"cache_read":1.2,"cache_write":14.85714286},"canonical_model_id":"anthropic/claude-fable-5"},"claude-opus-5":{"id":"claude-opus-5","name":"Claude Opus 5","description":"Strongest Claude Opus model for coding, agents, and professional work","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-05","release_date":"2026-07-24","last_updated":"2026-07-24","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.71428571,"output":28.57142857,"cache_read":2.28571429,"cache_write":5.71428571},"canonical_model_id":"anthropic/claude-opus-5"},"gpt-5-6-terra":{"id":"gpt-5-6-terra","name":"GPT-5.6 Terra","description":"Balanced GPT-5.6 model for capable, cost-efficient everyday work","family":"gpt-terra","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"status":"deprecated","cost":{"input":2.4,"output":14.28571429},"canonical_model_id":"openai/gpt-5.6-terra"},"mistral-medium-3-5:free":{"id":"mistral-medium-3-5:free","name":"Mistral Medium 3.5 (Free)","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"mistral/mistral-medium-2604"},"glm-4-7-flash:free":{"id":"glm-4-7-flash:free","name":"GLM-4.7-Flash (Free)","description":"Budget GLM lane for fast coding help, routing, and everyday automation","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"cost":{"input":0,"output":0},"canonical_model_id":"zhipuai/glm-4.7-flash"},"gemini-3-1-flash-lite":{"id":"gemini-3-1-flash-lite","name":"Gemini 3.1 Flash Lite","description":"Low-latency Gemini model for high-volume multimodal and agent workloads","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-07","last_updated":"2026-05-07","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"cost":{"input":0.28571429,"output":1.71428571,"cache_read":0.02857143,"cache_write":0.08571429},"canonical_model_id":"google/gemini-3.1-flash-lite"},"grok-imagine-image-2-0":{"id":"grok-imagine-image-2-0","type":"image","name":"Grok Imagine Image 2.0","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"grok","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-08-07","last_updated":"2026-08-07","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":64000,"output":0},"canonical_model_id":"xai/grok-imagine-image-2.0"},"mistral-large:free":{"id":"mistral-large:free","name":"Mistral Large (Free)","description":"Flagship Mistral model for advanced reasoning, coding, and multilingual work","family":"mistral-large","attachment":true,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2024-11","release_date":"2024-11-01","last_updated":"2025-12-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"mistral/mistral-large-latest"},"gemini-3-5-flash":{"id":"gemini-3-5-flash","name":"Gemini 3.5 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-19","last_updated":"2026-05-19","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","canonical_model_id":"google/gemini-3.5-flash"},"whisper-large-v3-turbo":{"id":"whisper-large-v3-turbo","type":"transcription","name":"Whisper Large v3 Turbo","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"whisper","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-10-01","last_updated":"2024-10-01","modalities":{"input":["audio"],"output":["text"]},"open_weights":true,"limit":{"context":448,"output":448},"provider":{"npm":"@ai-sdk/openai"},"canonical_model_id":"openai/whisper-large-v3-turbo"},"kimi-k2-6":{"id":"kimi-k2-6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.57142857,"output":2.85714286,"cache_read":0.28571429},"canonical_model_id":"moonshotai/kimi-k2.6"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.57142857,"output":1.14285714,"cache_read":0.00571429},"canonical_model_id":"deepseek/deepseek-v4-pro"},"gemini-3-7-flash":{"id":"gemini-3-7-flash","name":"Gemini 3.7 Flash","description":"High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-08-13","last_updated":"2026-08-13","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":0.34285714,"output":1.71428571,"cache_read":0.03428571,"cache_write":0.01714286},"canonical_model_id":"google/gemini-3.7-flash"},"gemini-3-1-flash-tts":{"id":"gemini-3-1-flash-tts","type":"speech","name":"Gemini 3.1 Flash TTS Preview","description":"Low-latency speech generation with steerable prompts and expressive audio tags","family":"gemini-flash","attachment":false,"reasoning":false,"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-15","last_updated":"2026-04-15","modalities":{"input":["text"],"output":["audio"]},"open_weights":false,"limit":{"context":8192,"output":16384},"provider":{"npm":"@ai-sdk/openai"},"canonical_model_id":"google/gemini-3.1-flash-tts-preview"},"minimax-m2-7":{"id":"minimax-m2-7","name":"MiniMax-M2.7","description":"Open MiniMax flagship for coding agents, office automation, and complex environments","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.36,"output":1.42857143,"cache_read":0.06857143},"canonical_model_id":"minimax/MiniMax-M2.7"},"mimo-v2-5":{"id":"mimo-v2-5","name":"MiMo-V2.5","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0.16571429,"output":0.33142857},"canonical_model_id":"xiaomi/mimo-v2.5"},"gpt-5-6-sol":{"id":"gpt-5-6-sol","name":"GPT-5.6 Sol","description":"Frontier GPT-5.6 model for complex professional work, coding, and agentic workflows","family":"gpt-sol","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":2.97142857,"output":17.71428571,"cache_read":1.18857143,"cache_write":3.71428571},"canonical_model_id":"openai/gpt-5.6-sol"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":1.42857143,"output":7.14285714,"cache_read":0.57142857,"cache_write":1.71428571},"canonical_model_id":"anthropic/claude-sonnet-5"},"step-3-7-flash":{"id":"step-3-7-flash","name":"Step 3.7 Flash","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"cost":{"input":0.24,"output":1.37142857,"cache_read":0.048},"canonical_model_id":"stepfun/step-3.7-flash"},"glm-5-3-flash":{"id":"glm-5-3-flash","name":"GLM-5.3-Flash","description":"Native multimodal GLM model for efficient coding and long-horizon agent tasks","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image","video","pdf"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.11428571,"output":0.34285714,"cache_read":0.02285714},"canonical_model_id":"zhipuai/glm-5.3-flash"},"nano-banana-2":{"id":"nano-banana-2","type":"image","name":"Nano Banana 2","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","video","pdf"],"output":["text","image"]},"open_weights":false,"limit":{"context":131072,"output":32768},"canonical_model_id":"google/gemini-3.1-flash-image"},"grok-imagine-image":{"id":"grok-imagine-image","type":"image","name":"Grok Imagine Image","description":"Image model for prompt-driven generation, editing, and visual design workflows","family":"grok","attachment":true,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2026-01-28","last_updated":"2026-01-28","modalities":{"input":["text","image"],"output":["image"]},"open_weights":false,"limit":{"context":16000,"output":0},"canonical_model_id":"xai/grok-imagine-image"},"gemini-3-6-flash":{"id":"gemini-3-6-flash","name":"Gemini 3.6 Flash","description":"Fast Gemini model balancing multimodal reasoning, tool use, and cost","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-03","release_date":"2026-07-21","last_updated":"2026-07-21","modalities":{"input":["text","image","video","audio","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","cost":{"input":0.34285714,"output":1.71428571,"cache_read":0.03428571,"cache_write":0.01714286},"canonical_model_id":"google/gemini-3.6-flash"},"gemma-4-31b-it":{"id":"gemma-4-31b-it","name":"Gemma 4 31B IT","description":"Largest Gemma 4 instruction model for open, self-hosted chat and reasoning","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.10285714,"output":0.40571429,"cache_read":0.04114286},"canonical_model_id":"google/gemma-4-31b-it"},"nemotron-3-super-120b-a12b":{"id":"nemotron-3-super-120b-a12b","name":"Nemotron 3 Super 120B A12B","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium"]}],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.09714286,"output":0.48,"cache_read":0.00971429},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"hy3:free":{"id":"hy3:free","name":"Hy3 (Free)","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":192000,"output":128000},"cost":{"input":0,"output":0},"canonical_model_id":"tencent/hy3"},"nemotron-3-ultra-550b-a55b":{"id":"nemotron-3-ultra-550b-a55b","name":"Nemotron 3 Ultra 550B A55B","description":"Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"temperature":true,"knowledge":"2025-09","release_date":"2026-06-04","last_updated":"2026-06-04","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":128000},"cost":{"input":0.68571429,"output":4.28571429,"cache_read":0.06857143},"canonical_model_id":"nvidia/nemotron-3-ultra-550b-a55b"},"gpt-5-6-luna":{"id":"gpt-5-6-luna","name":"GPT-5.6 Luna","description":"Cost-efficient GPT-5.6 model for fast, high-volume workloads","family":"gpt-luna","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2026-02-16","release_date":"2026-07-09","last_updated":"2026-07-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"output":128000},"cost":{"input":0.2,"output":1.14285714,"cache_read":0.02,"cache_write":0.25714286},"canonical_model_id":"openai/gpt-5.6-luna"},"claude-opus-4-8":{"id":"claude-opus-4-8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"cost":{"input":5.71428571,"output":29.71428571,"cache_read":0.57142857,"cache_write":7.42857143},"canonical_model_id":"anthropic/claude-opus-4-8"},"grok-build-0-1":{"id":"grok-build-0-1","name":"Grok Build 0.1","description":"Fast Grok coding model tuned for agentic engineering and iterative edits","family":"grok-build","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-16","last_updated":"2026-04-16","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":256000},"status":"deprecated","canonical_model_id":"xai/grok-build-0.1"},"nemotron-3-super-120b-a12b:free":{"id":"nemotron-3-super-120b-a12b:free","name":"Nemotron 3 Super 120B A12B (Free)","description":"Nemotron middle tier for collaborative agents and high-volume reasoning workloads","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium"]}],"tool_call":true,"temperature":true,"knowledge":"2025-06","release_date":"2026-03-11","last_updated":"2026-03-11","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0,"output":0},"canonical_model_id":"nvidia/nemotron-3-super-120b-a12b"},"kimi-k2-6:free":{"id":"kimi-k2-6:free","name":"Kimi K2.6 (Free)","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"moonshotai/kimi-k2.6"},"gpt-oss-20b":{"id":"gpt-oss-20b","name":"GPT OSS 20B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":32768},"cost":{"input":0.036,"output":0.15428571,"cache_read":0.00371429},"canonical_model_id":"openai/gpt-oss-20b"},"grok-4-6":{"id":"grok-4-6","name":"Grok 4.6","description":"xAI's frontier model for long-running agents, coding, knowledge work, and visual projects","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2026-02-01","release_date":"2026-08-12","last_updated":"2026-08-12","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2.28571429,"output":6.85714286,"cache_read":0.34285714},"canonical_model_id":"xai/grok-4.6"},"glm-5-1":{"id":"glm-5-1","name":"GLM-5.1","description":"Strong GLM coding model for agentic engineering, terminals, and repository generation","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-07","last_updated":"2026-04-07","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":200000,"output":131072},"status":"deprecated","canonical_model_id":"zhipuai/glm-5.1"},"claude-sonnet-4-6":{"id":"claude-sonnet-4-6","name":"Claude Sonnet 4.6","description":"Claude workhorse for coding agents, careful analysis, and production cost control","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-02-17","last_updated":"2026-03-13","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":3.6,"output":17.71428571,"cache_read":0.36,"cache_write":4.45714286},"canonical_model_id":"anthropic/claude-sonnet-4-6"},"hy3":{"id":"hy3","name":"Hy3","description":"Tencent Hy reasoning model for coding, instruction following, and agent tasks","family":"Hy","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high"]}],"tool_call":true,"temperature":true,"release_date":"2026-07-06","last_updated":"2026-07-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":192000,"output":128000},"cost":{"input":0.15428571,"output":0.62857143,"cache_read":0.01542857},"canonical_model_id":"tencent/hy3"},"mimo-v2-5:free":{"id":"mimo-v2-5:free","name":"MiMo-V2.5 (Free)","description":"Open MiMo model for multimodal coding agents and long-context automation","family":"mimo","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"xiaomi/mimo-v2.5"},"mimo-v2-5-pro":{"id":"mimo-v2-5-pro","name":"MiMo-V2.5-Pro","description":"Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution","family":"mimo","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2024-12","release_date":"2026-04-22","last_updated":"2026-04-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":131072},"status":"deprecated","cost":{"input":0.52,"output":1.02857143},"canonical_model_id":"xiaomi/mimo-v2.5-pro"},"glm-5-2":{"id":"glm-5-2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.28571429,"output":3.42857143,"cache_read":0.05314286},"canonical_model_id":"zhipuai/glm-5.2"},"step-3-7-flash:free":{"id":"step-3-7-flash:free","name":"Step 3.7 Flash (Free)","description":"Newer StepFun flash model for faster agents, coding, and multimodal prompts","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2026-03-01","release_date":"2026-05-29","last_updated":"2026-05-29","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":256000,"input":256000,"output":256000},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"stepfun/step-3.7-flash"},"minimax-m3":{"id":"minimax-m3","name":"MiniMax-M3","description":"MiniMax multimodal model for long-context coding, perception, and agent planning","family":"minimax","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-06-01","last_updated":"2026-06-01","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":512000},"cost":{"input":0.36,"output":1.42857143,"cache_read":0.06857143},"canonical_model_id":"minimax/MiniMax-M3"},"minimax-m2-7-highspeed":{"id":"minimax-m2-7-highspeed","name":"MiniMax-M2.7-highspeed","description":"Low-latency M2.7 variant for interactive coding plans and agent loops","family":"minimax","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"release_date":"2026-03-18","last_updated":"2026-03-18","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":204800,"output":131072},"cost":{"input":0.59428571,"output":2.4,"cache_read":0.11428571},"canonical_model_id":"minimax/MiniMax-M2.7-highspeed"},"gpt-5-4-mini":{"id":"gpt-5-4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"status":"deprecated","cost":{"input":0.85714286,"output":5.37142857},"canonical_model_id":"openai/gpt-5.4-mini"},"deepseek-v4-1-flash":{"id":"deepseek-v4-1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash model for reasoning and agentic coding","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"cost":{"input":0.15714286,"output":0.31428571,"cache_read":0.00371429},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"gemini-2-5-flash":{"id":"gemini-2-5-flash","name":"Gemini 2.5 Flash","description":"Fast Gemini workhorse for multimodal apps where latency and price matter","family":"gemini-flash","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2025-06-17","last_updated":"2025-06-17","modalities":{"input":["text","image","audio","video","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1048576,"output":65536},"status":"deprecated","canonical_model_id":"google/gemini-2.5-flash"},"nano-banana-pro":{"id":"nano-banana-pro","type":"image","name":"Nano Banana Pro","description":"Nano Banana Pro for higher-fidelity image generation and design-heavy edits","family":"gemini-pro","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high"]}],"tool_call":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":32768},"canonical_model_id":"google/gemini-3-pro-image"},"kimi-k2-7-code:free":{"id":"kimi-k2-7-code:free","name":"Kimi K2.7 Code (Free)","description":"Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-01","release_date":"2026-06-12","last_updated":"2026-06-12","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","cost":{"input":0,"output":0},"canonical_model_id":"moonshotai/kimi-k2.7-code"},"nemotron-3-nano-30b-a3b":{"id":"nemotron-3-nano-30b-a3b","name":"Nemotron 3 Nano 30B A3B","description":"Small Nemotron 3 MoE for efficient coding, math, and long-context agents","family":"nemotron","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-06-25","release_date":"2025-12-15","last_updated":"2025-12-15","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"status":"deprecated","canonical_model_id":"nvidia/nemotron-3-nano-30b-a3b"},"grok-4-5":{"id":"grok-4-5","name":"Grok 4.5","description":"xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk","family":"grok","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-07-08","last_updated":"2026-07-08","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":500000,"output":500000},"cost":{"input":2.28571429,"output":6.85714286,"cache_read":0.34285714},"canonical_model_id":"xai/grok-4.5"},"qwen3-7-plus":{"id":"qwen3-7-plus","name":"Qwen3.7 Plus","description":"Multimodal Qwen workhorse for long-context agents, visual inputs, and coding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-06-02","last_updated":"2026-06-02","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":64000},"cost":{"input":0.38285714,"output":1.48571429,"cache_read":0.07428571,"cache_write":0.48},"canonical_model_id":"alibaba/qwen3.7-plus"},"glm-5-3":{"id":"glm-5-3","name":"GLM-5.3","description":"Flagship GLM model for long-horizon coding, agents, and complex project delivery","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0.28571429,"output":3.42857143,"cache_read":0.05314286},"canonical_model_id":"zhipuai/glm-5.3"},"nano-banana-2-lite":{"id":"nano-banana-2-lite","type":"image","name":"Nano Banana 2 Lite","description":"Fastest, most cost-efficient Gemini image model for high-volume 1K generation and editing","family":"gemini-flash-lite","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","high"]}],"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2025-01","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image"],"output":["text","image"]},"open_weights":false,"limit":{"context":65536,"output":4096},"canonical_model_id":"google/gemini-3.1-flash-lite-image"}}},"evroc":{"id":"evroc","env":["EVROC_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://models.think.evroc.com/v1","name":"evroc","doc":"https://docs.evroc.com/products/think/overview.html","models":{"Qwen/Qwen3-Reranker-4B":{"id":"Qwen/Qwen3-Reranker-4B","type":"reranking","name":"Qwen3 Reranker 4B","description":"Reranking model for improving retrieval quality in search and recommendation systems","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2025-07-30","last_updated":"2025-07-30","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":4096},"cost":{"input":0.0575,"output":0}},"Qwen/Qwen3.8-27B":{"id":"Qwen/Qwen3.8-27B","name":"Qwen3.8-27B","description":"Dense 27B vision-language model for coding, agent tasks, and image and video understanding","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.87,"output":3.5},"canonical_model_id":"alibaba/qwen3.8-27b"},"Qwen/Qwen3-Embedding-8B":{"id":"Qwen/Qwen3-Embedding-8B","type":"embedding","name":"Qwen3 Embedding 8B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"temperature":false,"release_date":"2025-06-05","last_updated":"2025-06-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":40960,"output":4096},"cost":{"input":0.115,"output":0.115},"canonical_model_id":"alibaba/qwen3-embedding-8b"},"Qwen/Qwen3.6-35B-A3B":{"id":"Qwen/Qwen3.6-35B-A3B","name":"Qwen3.6 35B-A3B","description":"Open multimodal Qwen MoE for local agents that need vision, audio, and code","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-17","last_updated":"2026-04-17","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":65536},"cost":{"input":0.345,"output":1.38},"canonical_model_id":"alibaba/qwen3.6-35b-a3b"},"openai/gpt-oss-120b":{"id":"openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":65536,"output":65536},"cost":{"input":0.23,"output":0.92},"canonical_model_id":"openai/gpt-oss-120b"},"openai/whisper-large-v3-turbo":{"id":"openai/whisper-large-v3-turbo","type":"transcription","name":"Whisper Large v3 Turbo","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"whisper","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2024-10-01","last_updated":"2024-10-01","modalities":{"input":["audio"],"output":["text"]},"open_weights":true,"limit":{"context":448,"output":448},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":0.0023,"output":0.0023,"output_audio":2.3},"canonical_model_id":"openai/whisper-large-v3-turbo"},"openai/whisper-large-v3":{"id":"openai/whisper-large-v3","type":"transcription","name":"Whisper 3 Large","description":"Open Whisper checkpoint for robust multilingual transcription and captioning","family":"whisper","attachment":true,"reasoning":false,"tool_call":false,"temperature":true,"release_date":"2023-11-06","last_updated":"2023-11-06","modalities":{"input":["audio"],"output":["text"]},"open_weights":true,"limit":{"context":448,"output":4096},"provider":{"npm":"@ai-sdk/openai"},"cost":{"input":0.0023,"output":0.0023,"output_audio":2.3},"canonical_model_id":"openai/whisper-large-v3"},"KBLab/kb-whisper-large":{"id":"KBLab/kb-whisper-large","type":"transcription","name":"KB Whisper","description":"Speech transcription model for accurate audio-to-text and captioning workflows","family":"whisper","attachment":true,"reasoning":false,"tool_call":false,"release_date":"2024-10-01","last_updated":"2024-10-01","modalities":{"input":["audio"],"output":["text"]},"open_weights":true,"limit":{"context":448,"output":448},"provider":{"npm":"@ai-sdk/openai"}},"evroc/roc":{"id":"evroc/roc","name":"roc","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2026-01","release_date":"2026-06-06","last_updated":"2026-06-06","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":262144},"cost":{"input":2.875,"output":11.516}},"zai-org/GLM-5.2":{"id":"zai-org/GLM-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":524288,"output":131072},"cost":{"input":1.4375,"output":5.75},"canonical_model_id":"zhipuai/glm-5.2"},"mistralai/Mistral-Medium-3.5-128B":{"id":"mistralai/Mistral-Medium-3.5-128B","name":"Mistral Medium 3.5","description":"Balanced Mistral model for enterprise assistants, multilingual work, and tools","family":"mistral-medium","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-29","last_updated":"2026-04-29","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.725,"output":6.9},"canonical_model_id":"mistral/mistral-medium-2604"},"mistralai/Voxtral-Small-24B-2507":{"id":"mistralai/Voxtral-Small-24B-2507","type":"transcription","name":"Voxtral Small 24B","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"voxtral","attachment":true,"reasoning":false,"tool_call":false,"release_date":"2025-03-01","last_updated":"2025-03-01","modalities":{"input":["audio","text"],"output":["text"]},"open_weights":true,"limit":{"context":32000,"output":32000},"provider":{"npm":"@ai-sdk/openai"}},"moonshotai/Kimi-K2.6":{"id":"moonshotai/Kimi-K2.6","name":"Kimi K2.6","description":"Multimodal Kimi workhorse for agent loops, coding tasks, and visual context","family":"kimi-k2","attachment":true,"reasoning":true,"reasoning_options":[{"type":"budget_tokens"}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-01","release_date":"2026-04-20","last_updated":"2026-04-20","modalities":{"input":["text","image","video"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":1.4375,"output":5.75},"canonical_model_id":"moonshotai/kimi-k2.6"},"nvidia/Llama-3.3-70B-Instruct-FP8":{"id":"nvidia/Llama-3.3-70B-Instruct-FP8","name":"Llama-3.3-70B-Instruct","description":"Popular open Llama workhorse for multilingual chat, coding, and self-hosting","family":"llama","attachment":false,"reasoning":false,"tool_call":true,"temperature":true,"knowledge":"2023-12","release_date":"2024-12-06","last_updated":"2024-12-06","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":4096},"cost":{"input":1.15,"output":1.15},"canonical_model_id":"meta/llama-3.3-70b-instruct"},"intfloat/multilingual-e5-large-instruct":{"id":"intfloat/multilingual-e5-large-instruct","type":"embedding","name":"E5 Multi-Lingual Large Embeddings 0.6B","description":"Embedding model for semantic search, retrieval, clustering, and ranking pipelines","family":"text-embedding","attachment":false,"reasoning":false,"tool_call":false,"release_date":"2024-06-01","last_updated":"2024-06-01","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":512,"output":512},"cost":{"input":0.114,"output":0.114}},"google/gemma-4-26B-A4B-it":{"id":"google/gemma-4-26B-A4B-it","name":"Gemma 4 26B A4B IT","description":"Open Gemma instruction model for efficient chat and self-hosted deployments","family":"gemma","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-04-02","last_updated":"2026-04-02","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":32768},"cost":{"input":0.144,"output":0.575},"canonical_model_id":"google/gemma-4-26b-a4b-it"}}},"model-oracle-ai":{"id":"model-oracle-ai","env":["MODEL_ORACLE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.modeloracle.com/api/v1","name":"Model Oracle AI","doc":"https://modeloracle.com/setup/","models":{"claude-opus-4.8":{"id":"claude-opus-4.8","name":"Claude Opus 4.8","description":"Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents","family":"claude-opus","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01","release_date":"2026-05-28","last_updated":"2026-05-28","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"canonical_model_id":"anthropic/claude-opus-4-8"},"claude-fable-5":{"id":"claude-fable-5","name":"Claude Fable 5","description":"Claude model for creative writing, analysis, and controlled agent workflows","family":"claude-fable","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-09","last_updated":"2026-06-09","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"canonical_model_id":"anthropic/claude-fable-5"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","xhigh"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"canonical_model_id":"zhipuai/glm-5.2"},"gpt-4.1":{"id":"gpt-4.1","name":"GPT-4.1","description":"Long-lived GPT workhorse for coding, instruction following, and production apps","family":"gpt","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"canonical_model_id":"openai/gpt-4.1"},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"Open MoE flagship with million-token context for coding and long agent runs","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":384000},"canonical_model_id":"deepseek/deepseek-v4-pro"},"claude-sonnet-5":{"id":"claude-sonnet-5","name":"Claude Sonnet 5","description":"Everyday Claude agent model for coding, planning, browsing, and general work","family":"claude-sonnet","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":false,"knowledge":"2026-01-31","release_date":"2026-06-30","last_updated":"2026-06-30","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000},"canonical_model_id":"anthropic/claude-sonnet-5"},"gpt-5.4":{"id":"gpt-5.4","name":"GPT-5.4","description":"Agent-ready GPT for coding and computer-use workflows at a lower cost","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-05","last_updated":"2026-03-05","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"canonical_model_id":"openai/gpt-5.4"},"gpt-5.4-mini":{"id":"gpt-5.4-mini","name":"GPT-5.4 mini","description":"Strong small GPT for coding subagents, quick tool use, and high-volume work","family":"gpt-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"canonical_model_id":"openai/gpt-5.4-mini"},"claude-haiku-4.5":{"id":"claude-haiku-4.5","name":"Claude Haiku 4.5 (latest)","description":"Fast Claude lane for lightweight agents, office tasks, and responsive chat","family":"claude-haiku","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high","xhigh","max"]}],"tool_call":true,"temperature":true,"knowledge":"2025-02-28","release_date":"2025-10-15","last_updated":"2025-10-15","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":64000},"canonical_model_id":"anthropic/claude-haiku-4-5"},"gpt-4.1-mini":{"id":"gpt-4.1-mini","name":"GPT-4.1 mini","description":"Affordable GPT-4.1 lane for fast coding help and structured extraction","family":"gpt-mini","attachment":true,"reasoning":false,"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-04","release_date":"2025-04-14","last_updated":"2025-04-14","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1047576,"output":32768},"canonical_model_id":"openai/gpt-4.1-mini"},"gpt-5.4-nano":{"id":"gpt-5.4-nano","name":"GPT-5.4 nano","description":"Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation","family":"gpt-nano","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2025-08-31","release_date":"2026-03-17","last_updated":"2026-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"canonical_model_id":"openai/gpt-5.4-nano"},"gpt-5.5":{"id":"gpt-5.5","name":"GPT-5.5","description":"Default frontier GPT for coding, computer use, research, and knowledge work","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2025-12-01","release_date":"2026-04-23","last_updated":"2026-04-23","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1050000,"input":922000,"output":128000},"canonical_model_id":"openai/gpt-5.5"},"gpt-5":{"id":"gpt-5","name":"GPT-5","description":"Original GPT-5 workhorse for reasoning, coding, writing, and tool workflows","family":"gpt","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["minimal","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-09-30","release_date":"2025-08-07","last_updated":"2025-08-07","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":400000,"input":272000,"output":128000},"canonical_model_id":"openai/gpt-5"},"auto":{"id":"auto","name":"Auto","description":"Model Oracle AI decision engine that selects and routes among configured coding-agent models","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","minimal","low","medium","high","xhigh","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-29","last_updated":"2026-07-07","modalities":{"input":["text","image","pdf"],"output":["text"]},"open_weights":false,"limit":{"context":1000000,"output":128000}},"o4-mini":{"id":"o4-mini","name":"o4-mini","description":"Fast o-series model for compact reasoning, coding, and tool use","family":"o-mini","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":false,"knowledge":"2024-05","release_date":"2025-04-16","last_updated":"2025-04-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":200000,"output":100000},"canonical_model_id":"openai/o4-mini"}}},"claudinio":{"id":"claudinio","env":["CLAUDINIO_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.claudin.io/v1","name":"Claudinio","doc":"https://claudin.io","models":{"claudinio":{"id":"claudinio","name":"Claudinio","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"knowledge":"2026-05","release_date":"2026-05-12","last_updated":"2026-06-02","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":0.5,"output":2,"cache_read":0.15}},"claudius":{"id":"claudius","name":"Claudius","description":"Multimodal reasoning model for visual analysis, planning, and tool use","attachment":true,"reasoning":true,"reasoning_options":[],"tool_call":true,"knowledge":"2026-05","release_date":"2026-05-12","last_updated":"2026-05-12","modalities":{"input":["text","image","audio","video"],"output":["text"]},"open_weights":false,"limit":{"context":256000,"output":64000},"cost":{"input":3,"output":8,"cache_read":0.9}}}},"sensenova":{"id":"sensenova","env":["SENSENOVA_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://token.sensenova.cn/v1","name":"SenseNova (China)","doc":"https://platform.sensenova.cn/docs","models":{"deepseek-v4-flash":{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","description":"Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work","family":"deepseek-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-04-24","last_updated":"2026-04-24","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":65536},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4-flash"},"kimi-k3":{"id":"kimi-k3","name":"Kimi K3","description":"Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work","family":"kimi-k3","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":false,"release_date":"2026-07-16","last_updated":"2026-07-16","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"moonshotai/kimi-k3"},"glm-5.2":{"id":"glm-5.2","name":"GLM-5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1000000,"output":131072},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"zhipuai/glm-5.2"},"deepseek-v4.1-flash":{"id":"deepseek-v4.1-flash","name":"DeepSeek V4.1 Flash","description":"DeepSeek V4.1 Flash is a high-performance conversational model by DeepSeek, supporting thinking/non-thinking modes, 1M context window, and tool calling.","family":"deepseek-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-05","release_date":"2026-09-10","last_updated":"2026-09-10","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4.1-flash"},"sensenova-6.8-flash-lite":{"id":"sensenova-6.8-flash-lite","name":"SenseNova 6.8 Flash Lite","description":"SenseNova lightweight multimodal agent model for real-world complex tasks, data analysis, and complex information presentation","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-11","last_updated":"2026-08-28","modalities":{"input":["text","image"],"output":["text"]},"open_weights":false,"limit":{"context":262144,"output":65536},"cost":{"input":0,"output":0,"cache_read":0}},"deepseek-v4-pro":{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","description":"DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes","family":"deepseek-thinking","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["high","max"]}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"release_date":"2026-08-13","last_updated":"2026-08-22","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":65536},"cost":{"input":0,"output":0,"cache_read":0},"canonical_model_id":"deepseek/deepseek-v4-pro-0813"}}},"cloudflare-workers-ai":{"id":"cloudflare-workers-ai","env":["CLOUDFLARE_ACCOUNT_ID","CLOUDFLARE_API_KEY"],"npm":"@ai-sdk/openai-compatible","api":"https://api.cloudflare.com/client/v4/accounts/${CLOUDFLARE_ACCOUNT_ID}/ai/v1","name":"Cloudflare Workers AI","doc":"https://developers.cloudflare.com/workers-ai/models/","models":{"@cf/ibm-granite/granite-4.0-h-micro":{"id":"@cf/ibm-granite/granite-4.0-h-micro","name":"Granite 4.0 H Micro","description":"Efficient model for low-latency assistance, extraction, and routine automation","family":"granite","attachment":false,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"release_date":"2025-10-02","last_updated":"2025-10-02","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131000,"output":131000},"cost":{"input":0.017,"output":0.112},"canonical_model_id":"ibm/granite-4-h-micro"},"@cf/openai/gpt-oss-120b":{"id":"@cf/openai/gpt-oss-120b","name":"GPT OSS 120B","description":"Open GPT reasoning model for self-hosted agents and controllable deployments","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.35,"output":0.75},"canonical_model_id":"openai/gpt-oss-120b"},"@cf/openai/gpt-oss-20b":{"id":"@cf/openai/gpt-oss-20b","name":"GPT OSS 20B","description":"Open-weight GPT model for self-hosted reasoning and instruction-following workloads","family":"gpt-oss","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","medium","high"]}],"tool_call":true,"structured_output":true,"temperature":true,"knowledge":"2024-06","release_date":"2025-08-05","last_updated":"2025-08-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":16384},"cost":{"input":0.2,"output":0.3},"canonical_model_id":"openai/gpt-oss-20b"},"@cf/zai-org/glm-5.2":{"id":"@cf/zai-org/glm-5.2","name":"Glm 5.2","description":"Open flagship GLM for long-horizon coding agents and million-token context work","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["none","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-06-13","last_updated":"2026-06-13","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":256000},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.2"},"@cf/zai-org/glm-5.3":{"id":"@cf/zai-org/glm-5.3","name":"Glm 5.3","description":"Flagship GLM model for hybrid reasoning, coding, and agentic engineering","family":"glm","attachment":false,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":1.4,"output":4.4,"cache_read":0.26},"canonical_model_id":"zhipuai/glm-5.3"},"@cf/zai-org/glm-5.3-flash":{"id":"@cf/zai-org/glm-5.3-flash","name":"Glm 5.3 Flash","description":"GLM vision model for visual reasoning, documents, and multimodal agents","family":"glm-flash","attachment":true,"reasoning":true,"reasoning_options":[{"type":"effort","values":["low","high","max"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-26","last_updated":"2026-08-26","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":1048576,"output":1048576},"cost":{"input":0.15,"output":0.5,"cache_read":0.03},"canonical_model_id":"zhipuai/glm-5.3-flash"},"@cf/zai-org/glm-4.7-flash":{"id":"@cf/zai-org/glm-4.7-flash","name":"GLM-4.7-Flash","description":"Efficient GLM model for fast reasoning, coding, and agent workflows","family":"glm-flash","attachment":false,"reasoning":true,"reasoning_options":[{"type":"toggle"}],"tool_call":true,"interleaved":{"field":"reasoning_content"},"structured_output":true,"temperature":true,"knowledge":"2025-04","release_date":"2026-01-19","last_updated":"2026-01-19","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":131072,"output":131072},"cost":{"input":0.0605,"output":0.4},"canonical_model_id":"zhipuai/glm-4.7-flash"},"@cf/mistralai/mistral-small-3.1-24b-instruct":{"id":"@cf/mistralai/mistral-small-3.1-24b-instruct","name":"Mistral Small 3.1 24B Instruct","description":"Efficient Mistral model for fast chat, extraction, and production assistants","family":"mistral-small","attachment":true,"reasoning":false,"tool_call":true,"structured_output":false,"temperature":true,"knowledge":"2024-06","release_date":"2025-03-17","last_updated":"2025-03-17","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":128000,"output":128000},"cost":{"input":0.351,"output":0.555},"canonical_model_id":"mistral/mistral-small-3-1-24b-instruct-2503"},"@cf/qwen/qwq-32b":{"id":"@cf/qwen/qwq-32b","name":"Qwq 32B","description":"Qwen reasoning model for deliberate problem solving, math, and coding","family":"qwen","attachment":false,"reasoning":true,"reasoning_options":[],"tool_call":false,"structured_output":false,"temperature":true,"knowledge":"2024-04","release_date":"2025-03-05","last_updated":"2025-03-05","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":24000,"output":24000},"cost":{"input":0.66,"output":1},"canonical_model_id":"alibaba/qwq-32b"},"@cf/qwen/qwen2.5-coder-32b-instruct":{"id":"@cf/qwen/qwen2.5-coder-32b-instruct","name":"Qwen2.5 Coder 32B Instruct","description":"Qwen coding model for software agents, repository edits, and code reasoning","family":"qwen","attachment":false,"reasoning":false,"tool_call":false,"structured_output":false,"temperature":true,"release_date":"2024-11-12","last_updated":"2024-11-12","modalities":{"input":["text"],"output":["text"]},"open_weights":true,"limit":{"context":32768,"output":32768},"cost":{"input":0.66,"output":1},"canonical_model_id":"alibaba/qwen2.5-coder-32b-instruct"},"@cf/qwen/qwen3.8-27b":{"id":"@cf/qwen/qwen3.8-27b","name":"Qwen3.8 27B","description":"Qwen vision-language model for visual reasoning, documents, and agent tasks","family":"qwen","attachment":true,"reasoning":true,"reasoning_options":[{"type":"toggle"},{"type":"effort","values":["low","medium","xhigh"]}],"tool_call":true,"structured_output":true,"temperature":true,"release_date":"2026-08-14","last_updated":"2026-08-14","modalities":{"input":["text","image"],"output":["text"]},"open_weights":true,"limit":{"context":262144,"output":262144},"cost":{"input":0.45,"output":3.2,"cache_read":0.05},"canonical_model_id":"alibaba/qwen3.8-27b"},"@cf/qwen/q